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Sample records for regression survival analyses

  1. Survival analysis II: Cox regression

    NARCIS (Netherlands)

    Stel, Vianda S.; Dekker, Friedo W.; Tripepi, Giovanni; Zoccali, Carmine; Jager, Kitty J.

    2011-01-01

    In contrast to the Kaplan-Meier method, Cox proportional hazards regression can provide an effect estimate by quantifying the difference in survival between patient groups and can adjust for confounding effects of other variables. The purpose of this article is to explain the basic concepts of the

  2. Statistical power analyses using G*Power 3.1: tests for correlation and regression analyses.

    Science.gov (United States)

    Faul, Franz; Erdfelder, Edgar; Buchner, Axel; Lang, Albert-Georg

    2009-11-01

    G*Power is a free power analysis program for a variety of statistical tests. We present extensions and improvements of the version introduced by Faul, Erdfelder, Lang, and Buchner (2007) in the domain of correlation and regression analyses. In the new version, we have added procedures to analyze the power of tests based on (1) single-sample tetrachoric correlations, (2) comparisons of dependent correlations, (3) bivariate linear regression, (4) multiple linear regression based on the random predictor model, (5) logistic regression, and (6) Poisson regression. We describe these new features and provide a brief introduction to their scope and handling.

  3. Applications of MIDAS regression in analysing trends in water quality

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    Penev, Spiridon; Leonte, Daniela; Lazarov, Zdravetz; Mann, Rob A.

    2014-04-01

    We discuss novel statistical methods in analysing trends in water quality. Such analysis uses complex data sets of different classes of variables, including water quality, hydrological and meteorological. We analyse the effect of rainfall and flow on trends in water quality utilising a flexible model called Mixed Data Sampling (MIDAS). This model arises because of the mixed frequency in the data collection. Typically, water quality variables are sampled fortnightly, whereas the rain data is sampled daily. The advantage of using MIDAS regression is in the flexible and parsimonious modelling of the influence of the rain and flow on trends in water quality variables. We discuss the model and its implementation on a data set from the Shoalhaven Supply System and Catchments in the state of New South Wales, Australia. Information criteria indicate that MIDAS modelling improves upon simplistic approaches that do not utilise the mixed data sampling nature of the data.

  4. Quantifying Fire Cycle from Dendroecological Records Using Survival Analyses

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    Dominic Cyr

    2016-06-01

    Full Text Available Quantifying fire regimes in the boreal forest ecosystem is crucial for understanding the past and present dynamics, as well as for predicting its future dynamics. Survival analyses have often been used to estimate the fire cycle in eastern Canada because they make it possible to take into account the censored information that is made prevalent by the typically long fire return intervals and the limited scope of the dendroecological methods that are used to quantify them. Here, we assess how the true length of the fire cycle, the short-term temporal variations in fire activity, and the sampling effort affect the accuracy and precision of estimates obtained from two types of parametric survival models, the Weibull and the exponential models, and one non-parametric model obtained with the Cox regression. Then, we apply those results in a case area located in eastern Canada. Our simulation experiment confirms some documented concerns regarding the detrimental effects of temporal variations in fire activity on parametric estimation of the fire cycle. Cox regressions appear to provide the most accurate and robust estimator, being by far the least affected by temporal variations in fire activity. The Cox-based estimate of the fire cycle for the last 300 years in the case study area is 229 years (CI95: 162–407, compared with the likely overestimated 319 years obtained with the commonly used exponential model.

  5. Predicting and Modelling of Survival Data when Cox's Regression Model does not hold

    DEFF Research Database (Denmark)

    Scheike, Thomas H.; Zhang, Mei-Jie

    2002-01-01

    Aalen model; additive risk model; counting processes; competing risk; Cox regression; flexible modeling; goodness of fit; prediction of survival; survival analysis; time-varying effects......Aalen model; additive risk model; counting processes; competing risk; Cox regression; flexible modeling; goodness of fit; prediction of survival; survival analysis; time-varying effects...

  6. A generalized additive regression model for survival times

    DEFF Research Database (Denmark)

    Scheike, Thomas H.

    2001-01-01

    Additive Aalen model; counting process; disability model; illness-death model; generalized additive models; multiple time-scales; non-parametric estimation; survival data; varying-coefficient models......Additive Aalen model; counting process; disability model; illness-death model; generalized additive models; multiple time-scales; non-parametric estimation; survival data; varying-coefficient models...

  7. Multicollinearity in Regression Analyses Conducted in Epidemiologic Studies.

    Science.gov (United States)

    Vatcheva, Kristina P; Lee, MinJae; McCormick, Joseph B; Rahbar, Mohammad H

    2016-04-01

    The adverse impact of ignoring multicollinearity on findings and data interpretation in regression analysis is very well documented in the statistical literature. The failure to identify and report multicollinearity could result in misleading interpretations of the results. A review of epidemiological literature in PubMed from January 2004 to December 2013, illustrated the need for a greater attention to identifying and minimizing the effect of multicollinearity in analysis of data from epidemiologic studies. We used simulated datasets and real life data from the Cameron County Hispanic Cohort to demonstrate the adverse effects of multicollinearity in the regression analysis and encourage researchers to consider the diagnostic for multicollinearity as one of the steps in regression analysis.

  8. Statistical and regression analyses of detected extrasolar systems

    Czech Academy of Sciences Publication Activity Database

    Pintr, Pavel; Peřinová, V.; Lukš, A.; Pathak, A.

    2013-01-01

    Roč. 75, č. 1 (2013), s. 37-45 ISSN 0032-0633 Institutional support: RVO:61389021 Keywords : Exoplanets * Kepler candidates * Regression analysis Subject RIV: BN - Astronomy, Celestial Mechanics, Astrophysics Impact factor: 1.630, year: 2013 http://www.sciencedirect.com/science/article/pii/S0032063312003066

  9. Multicollinearity in Regression Analyses Conducted in Epidemiologic Studies

    OpenAIRE

    Vatcheva, Kristina P.; Lee, MinJae; McCormick, Joseph B.; Rahbar, Mohammad H.

    2016-01-01

    The adverse impact of ignoring multicollinearity on findings and data interpretation in regression analysis is very well documented in the statistical literature. The failure to identify and report multicollinearity could result in misleading interpretations of the results. A review of epidemiological literature in PubMed from January 2004 to December 2013, illustrated the need for a greater attention to identifying and minimizing the effect of multicollinearity in analysis of data from epide...

  10. Analysing inequalities in Germany a structured additive distributional regression approach

    CERN Document Server

    Silbersdorff, Alexander

    2017-01-01

    This book seeks new perspectives on the growing inequalities that our societies face, putting forward Structured Additive Distributional Regression as a means of statistical analysis that circumvents the common problem of analytical reduction to simple point estimators. This new approach allows the observed discrepancy between the individuals’ realities and the abstract representation of those realities to be explicitly taken into consideration using the arithmetic mean alone. In turn, the method is applied to the question of economic inequality in Germany.

  11. The analysis of survival data in nephrology: basic concepts and methods of Cox regression

    NARCIS (Netherlands)

    van Dijk, Paul C.; Jager, Kitty J.; Zwinderman, Aeilko H.; Zoccali, Carmine; Dekker, Friedo W.

    2008-01-01

    How much does the survival of one group differ from the survival of another group? How do differences in age in these two groups affect such a comparison? To obtain a quantity to compare the survival of different patient groups and to account for confounding effects, a multiple regression technique

  12. Regression models for interval censored survival data: Application to HIV infection in Danish homosexual men

    DEFF Research Database (Denmark)

    Carstensen, Bendix

    1996-01-01

    This paper shows how to fit excess and relative risk regression models to interval censored survival data, and how to implement the models in standard statistical software. The methods developed are used for the analysis of HIV infection rates in a cohort of Danish homosexual men.......This paper shows how to fit excess and relative risk regression models to interval censored survival data, and how to implement the models in standard statistical software. The methods developed are used for the analysis of HIV infection rates in a cohort of Danish homosexual men....

  13. How to deal with continuous and dichotomic outcomes in epidemiological research: linear and logistic regression analyses

    NARCIS (Netherlands)

    Tripepi, Giovanni; Jager, Kitty J.; Stel, Vianda S.; Dekker, Friedo W.; Zoccali, Carmine

    2011-01-01

    Because of some limitations of stratification methods, epidemiologists frequently use multiple linear and logistic regression analyses to address specific epidemiological questions. If the dependent variable is a continuous one (for example, systolic pressure and serum creatinine), the researcher

  14. Support vector methods for survival analysis: a comparison between ranking and regression approaches.

    Science.gov (United States)

    Van Belle, Vanya; Pelckmans, Kristiaan; Van Huffel, Sabine; Suykens, Johan A K

    2011-10-01

    To compare and evaluate ranking, regression and combined machine learning approaches for the analysis of survival data. The literature describes two approaches based on support vector machines to deal with censored observations. In the first approach the key idea is to rephrase the task as a ranking problem via the concordance index, a problem which can be solved efficiently in a context of structural risk minimization and convex optimization techniques. In a second approach, one uses a regression approach, dealing with censoring by means of inequality constraints. The goal of this paper is then twofold: (i) introducing a new model combining the ranking and regression strategy, which retains the link with existing survival models such as the proportional hazards model via transformation models; and (ii) comparison of the three techniques on 6 clinical and 3 high-dimensional datasets and discussing the relevance of these techniques over classical approaches fur survival data. We compare svm-based survival models based on ranking constraints, based on regression constraints and models based on both ranking and regression constraints. The performance of the models is compared by means of three different measures: (i) the concordance index, measuring the model's discriminating ability; (ii) the logrank test statistic, indicating whether patients with a prognostic index lower than the median prognostic index have a significant different survival than patients with a prognostic index higher than the median; and (iii) the hazard ratio after normalization to restrict the prognostic index between 0 and 1. Our results indicate a significantly better performance for models including regression constraints above models only based on ranking constraints. This work gives empirical evidence that svm-based models using regression constraints perform significantly better than svm-based models based on ranking constraints. Our experiments show a comparable performance for methods

  15. Determining factors influencing survival of breast cancer by fuzzy logistic regression model.

    Science.gov (United States)

    Nikbakht, Roya; Bahrampour, Abbas

    2017-01-01

    Fuzzy logistic regression model can be used for determining influential factors of disease. This study explores the important factors of actual predictive survival factors of breast cancer's patients. We used breast cancer data which collected by cancer registry of Kerman University of Medical Sciences during the period of 2000-2007. The variables such as morphology, grade, age, and treatments (surgery, radiotherapy, and chemotherapy) were applied in the fuzzy logistic regression model. Performance of model was determined in terms of mean degree of membership (MDM). The study results showed that almost 41% of patients were in neoplasm and malignant group and more than two-third of them were still alive after 5-year follow-up. Based on the fuzzy logistic model, the most important factors influencing survival were chemotherapy, morphology, and radiotherapy, respectively. Furthermore, the MDM criteria show that the fuzzy logistic regression have a good fit on the data (MDM = 0.86). Fuzzy logistic regression model showed that chemotherapy is more important than radiotherapy in survival of patients with breast cancer. In addition, another ability of this model is calculating possibilistic odds of survival in cancer patients. The results of this study can be applied in clinical research. Furthermore, there are few studies which applied the fuzzy logistic models. Furthermore, we recommend using this model in various research areas.

  16. Association between response rates and survival outcomes in patients with newly diagnosed multiple myeloma. A systematic review and meta-regression analysis.

    Science.gov (United States)

    Mainou, Maria; Madenidou, Anastasia-Vasiliki; Liakos, Aris; Paschos, Paschalis; Karagiannis, Thomas; Bekiari, Eleni; Vlachaki, Efthymia; Wang, Zhen; Murad, Mohammad Hassan; Kumar, Shaji; Tsapas, Apostolos

    2017-06-01

    We performed a systematic review and meta-regression analysis of randomized control trials to investigate the association between response to initial treatment and survival outcomes in patients with newly diagnosed multiple myeloma (MM). Response outcomes included complete response (CR) and the combined outcome of CR or very good partial response (VGPR), while survival outcomes were overall survival (OS) and progression-free survival (PFS). We used random-effect meta-regression models and conducted sensitivity analyses based on definition of CR and study quality. Seventy-two trials were included in the systematic review, 63 of which contributed data in meta-regression analyses. There was no association between OS and CR in patients without autologous stem cell transplant (ASCT) (regression coefficient: .02, 95% confidence interval [CI] -0.06, 0.10), in patients undergoing ASCT (-.11, 95% CI -0.44, 0.22) and in trials comparing ASCT with non-ASCT patients (.04, 95% CI -0.29, 0.38). Similarly, OS did not correlate with the combined metric of CR or VGPR, and no association was evident between response outcomes and PFS. Sensitivity analyses yielded similar results. This meta-regression analysis suggests that there is no association between conventional response outcomes and survival in patients with newly diagnosed MM. © 2017 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

  17. USE OF THE SIMPLE LINEAR REGRESSION MODEL IN MACRO-ECONOMICAL ANALYSES

    Directory of Open Access Journals (Sweden)

    Constantin ANGHELACHE

    2011-10-01

    Full Text Available The article presents the fundamental aspects of the linear regression, as a toolbox which can be used in macroeconomic analyses. The article describes the estimation of the parameters, the statistical tests used, the homoscesasticity and heteroskedasticity. The use of econometrics instrument in macroeconomics is an important factor that guarantees the quality of the models, analyses, results and possible interpretation that can be drawn at this level.

  18. Meta-regression analysis of commensal and pathogenic Escherichia coli survival in soil and water.

    Science.gov (United States)

    Franz, Eelco; Schijven, Jack; de Roda Husman, Ana Maria; Blaak, Hetty

    2014-06-17

    The extent to which pathogenic and commensal E. coli (respectively PEC and CEC) can survive, and which factors predominantly determine the rate of decline, are crucial issues from a public health point of view. The goal of this study was to provide a quantitative summary of the variability in E. coli survival in soil and water over a broad range of individual studies and to identify the most important sources of variability. To that end, a meta-regression analysis on available literature data was conducted. The considerable variation in reported decline rates indicated that the persistence of E. coli is not easily predictable. The meta-analysis demonstrated that for soil and water, the type of experiment (laboratory or field), the matrix subtype (type of water and soil), and temperature were the main factors included in the regression analysis. A higher average decline rate in soil of PEC compared with CEC was observed. The regression models explained at best 57% of the variation in decline rate in soil and 41% of the variation in decline rate in water. This indicates that additional factors, not included in the current meta-regression analysis, are of importance but rarely reported. More complete reporting of experimental conditions may allow future inference on the global effects of these variables on the decline rate of E. coli.

  19. Prediction of survival to discharge following cardiopulmonary resuscitation using classification and regression trees.

    Science.gov (United States)

    Ebell, Mark H; Afonso, Anna M; Geocadin, Romergryko G

    2013-12-01

    To predict the likelihood that an inpatient who experiences cardiopulmonary arrest and undergoes cardiopulmonary resuscitation survives to discharge with good neurologic function or with mild deficits (Cerebral Performance Category score = 1). Classification and Regression Trees were used to develop branching algorithms that optimize the ability of a series of tests to correctly classify patients into two or more groups. Data from 2007 to 2008 (n = 38,092) were used to develop candidate Classification and Regression Trees models to predict the outcome of inpatient cardiopulmonary resuscitation episodes and data from 2009 (n = 14,435) to evaluate the accuracy of the models and judge the degree of over fitting. Both supervised and unsupervised approaches to model development were used. 366 hospitals participating in the Get With the Guidelines-Resuscitation registry. Adult inpatients experiencing an index episode of cardiopulmonary arrest and undergoing cardiopulmonary resuscitation in the hospital. The five candidate models had between 8 and 21 nodes and an area under the receiver operating characteristic curve from 0.718 to 0.766 in the derivation group and from 0.683 to 0.746 in the validation group. One of the supervised models had 14 nodes and classified 27.9% of patients as very unlikely to survive neurologically intact or with mild deficits (Tree models that predict survival to discharge with good neurologic function or with mild deficits following in-hospital cardiopulmonary arrest. Models like this can assist physicians and patients who are considering do-not-resuscitate orders.

  20. Survival Prediction and Feature Selection in Patients with Breast Cancer Using Support Vector Regression

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    Shahrbanoo Goli

    2016-01-01

    Full Text Available The Support Vector Regression (SVR model has been broadly used for response prediction. However, few researchers have used SVR for survival analysis. In this study, a new SVR model is proposed and SVR with different kernels and the traditional Cox model are trained. The models are compared based on different performance measures. We also select the best subset of features using three feature selection methods: combination of SVR and statistical tests, univariate feature selection based on concordance index, and recursive feature elimination. The evaluations are performed using available medical datasets and also a Breast Cancer (BC dataset consisting of 573 patients who visited the Oncology Clinic of Hamadan province in Iran. Results show that, for the BC dataset, survival time can be predicted more accurately by linear SVR than nonlinear SVR. Based on the three feature selection methods, metastasis status, progesterone receptor status, and human epidermal growth factor receptor 2 status are the best features associated to survival. Also, according to the obtained results, performance of linear and nonlinear kernels is comparable. The proposed SVR model performs similar to or slightly better than other models. Also, SVR performs similar to or better than Cox when all features are included in model.

  1. Bayesian linear regression with skew-symmetric error distributions with applications to survival analysis

    KAUST Repository

    Rubio, Francisco J.

    2016-02-09

    We study Bayesian linear regression models with skew-symmetric scale mixtures of normal error distributions. These kinds of models can be used to capture departures from the usual assumption of normality of the errors in terms of heavy tails and asymmetry. We propose a general noninformative prior structure for these regression models and show that the corresponding posterior distribution is proper under mild conditions. We extend these propriety results to cases where the response variables are censored. The latter scenario is of interest in the context of accelerated failure time models, which are relevant in survival analysis. We present a simulation study that demonstrates good frequentist properties of the posterior credible intervals associated with the proposed priors. This study also sheds some light on the trade-off between increased model flexibility and the risk of over-fitting. We illustrate the performance of the proposed models with real data. Although we focus on models with univariate response variables, we also present some extensions to the multivariate case in the Supporting Information.

  2. Genetic analyses of partial egg production in Japanese quail using multi-trait random regression models.

    Science.gov (United States)

    Karami, K; Zerehdaran, S; Barzanooni, B; Lotfi, E

    2017-12-01

    1. The aim of the present study was to estimate genetic parameters for average egg weight (EW) and egg number (EN) at different ages in Japanese quail using multi-trait random regression (MTRR) models. 2. A total of 8534 records from 900 quail, hatched between 2014 and 2015, were used in the study. Average weekly egg weights and egg numbers were measured from second until sixth week of egg production. 3. Nine random regression models were compared to identify the best order of the Legendre polynomials (LP). The most optimal model was identified by the Bayesian Information Criterion. A model with second order of LP for fixed effects, second order of LP for additive genetic effects and third order of LP for permanent environmental effects (MTRR23) was found to be the best. 4. According to the MTRR23 model, direct heritability for EW increased from 0.26 in the second week to 0.53 in the sixth week of egg production, whereas the ratio of permanent environment to phenotypic variance decreased from 0.48 to 0.1. Direct heritability for EN was low, whereas the ratio of permanent environment to phenotypic variance decreased from 0.57 to 0.15 during the production period. 5. For each trait, estimated genetic correlations among weeks of egg production were high (from 0.85 to 0.98). Genetic correlations between EW and EN were low and negative for the first two weeks, but they were low and positive for the rest of the egg production period. 6. In conclusion, random regression models can be used effectively for analysing egg production traits in Japanese quail. Response to selection for increased egg weight would be higher at older ages because of its higher heritability and such a breeding program would have no negative genetic impact on egg production.

  3. Reducing Inter-Laboratory Differences between Semen Analyses Using Z Score and Regression Transformations

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    Esther Leushuis

    2016-12-01

    Full Text Available Background: Standardization of the semen analysis may improve reproducibility. We assessed variability between laboratories in semen analyses and evaluated whether a transformation using Z scores and regression statistics was able to reduce this variability. Materials and Methods: We performed a retrospective cohort study. We calculated between-laboratory coefficients of variation (CVB for sperm concentration and for morphology. Subsequently, we standardized the semen analysis results by calculating laboratory specific Z scores, and by using regression. We used analysis of variance for four semen parameters to assess systematic differences between laboratories before and after the transformations, both in the circulation samples and in the samples obtained in the prospective cohort study in the Netherlands between January 2002 and February 2004. Results: The mean CVB was 7% for sperm concentration (range 3 to 13% and 32% for sperm morphology (range 18 to 51%. The differences between the laboratories were statistically significant for all semen parameters (all P<0.001. Standardization using Z scores did not reduce the differences in semen analysis results between the laboratories (all P<0.001. Conclusion: There exists large between-laboratory variability for sperm morphology and small, but statistically significant, between-laboratory variation for sperm concentration. Standardization using Z scores does not eliminate between-laboratory variability.

  4. Exponential Decay Nonlinear Regression Analysis of Patient Survival Curves: Preliminary Assessment in Non-Small Cell Lung Cancer

    Science.gov (United States)

    Stewart, David J.; Behrens, Carmen; Roth, Jack; Wistuba, Ignacio I.

    2010-01-01

    Background For processes that follow first order kinetics, exponential decay nonlinear regression analysis (EDNRA) may delineate curve characteristics and suggest processes affecting curve shape. We conducted a preliminary feasibility assessment of EDNRA of patient survival curves. Methods EDNRA was performed on Kaplan-Meier overall survival (OS) and time-to-relapse (TTR) curves for 323 patients with resected NSCLC and on OS and progression-free survival (PFS) curves from selected publications. Results and Conclusions In our resected patients, TTR curves were triphasic with a “cured” fraction of 60.7% (half-life [t1/2] >100,000 months), a rapidly-relapsing group (7.4%, t1/2=5.9 months) and a slowly-relapsing group (31.9%, t1/2=23.6 months). OS was uniphasic (t1/2=74.3 months), suggesting an impact of co-morbidities; hence, tumor molecular characteristics would more likely predict TTR than OS. Of 172 published curves analyzed, 72 (42%) were uniphasic, 92 (53%) were biphasic, 8 (5%) were triphasic. With first-line chemotherapy in advanced NSCLC, 87.5% of curves from 2-3 drug regimens were uniphasic vs only 20% of those with best supportive care or 1 drug (p<0.001). 54% of curves from 2-3 drug regimens had convex rapid-decay phases vs 0% with fewer agents (p<0.001). Curve convexities suggest that discontinuing chemotherapy after 3-6 cycles “synchronizes” patient progression and death. With postoperative adjuvant chemotherapy, the PFS rapid-decay phase accounted for a smaller proportion of the population than in controls (p=0.02) with no significant difference in rapid-decay t1/2, suggesting adjuvant chemotherapy may move a subpopulation of patients with sensitive tumors from the relapsing group to the cured group, with minimal impact on time to relapse for a larger group of patients with resistant tumors. In untreated patients, the proportion of patients in the rapid-decay phase increased (p=0.04) while rapid-decay t1/2 decreased (p=0.0004) with increasing

  5. Modelling lecturer performance index of private university in Tulungagung by using survival analysis with multivariate adaptive regression spline

    Science.gov (United States)

    Hasyim, M.; Prastyo, D. D.

    2018-03-01

    Survival analysis performs relationship between independent variables and survival time as dependent variable. In fact, not all survival data can be recorded completely by any reasons. In such situation, the data is called censored data. Moreover, several model for survival analysis requires assumptions. One of the approaches in survival analysis is nonparametric that gives more relax assumption. In this research, the nonparametric approach that is employed is Multivariate Regression Adaptive Spline (MARS). This study is aimed to measure the performance of private university’s lecturer. The survival time in this study is duration needed by lecturer to obtain their professional certificate. The results show that research activities is a significant factor along with developing courses material, good publication in international or national journal, and activities in research collaboration.

  6. 77 FR 6548 - Notice of Availability of Ballistic Survivability, Lethality and Vulnerability Analyses

    Science.gov (United States)

    2012-02-08

    ... DEPARTMENT OF DEFENSE Department of the Army Notice of Availability of Ballistic Survivability, Lethality and Vulnerability Analyses AGENCY: Department of the Army, DoD. ACTION: Notice of availability. SUMMARY: The US Army Research Laboratory's (ARL's), Survivability, Lethality Analysis Directorate (SLAD...

  7. Logistic regression and multiple classification analyses to explore risk factors of under-5 mortality in bangladesh

    International Nuclear Information System (INIS)

    Bhowmik, K.R.; Islam, S.

    2016-01-01

    Logistic regression (LR) analysis is the most common statistical methodology to find out the determinants of childhood mortality. However, the significant predictors cannot be ranked according to their influence on the response variable. Multiple classification (MC) analysis can be applied to identify the significant predictors with a priority index which helps to rank the predictors. The main objective of the study is to find the socio-demographic determinants of childhood mortality at neonatal, post-neonatal, and post-infant period by fitting LR model as well as to rank those through MC analysis. The study is conducted using the data of Bangladesh Demographic and Health Survey 2007 where birth and death information of children were collected from their mothers. Three dichotomous response variables are constructed from children age at death to fit the LR and MC models. Socio-economic and demographic variables significantly associated with the response variables separately are considered in LR and MC analyses. Both the LR and MC models identified the same significant predictors for specific childhood mortality. For both the neonatal and child mortality, biological factors of children, regional settings, and parents socio-economic status are found as 1st, 2nd, and 3rd significant groups of predictors respectively. Mother education and household environment are detected as major significant predictors of post-neonatal mortality. This study shows that MC analysis with or without LR analysis can be applied to detect determinants with rank which help the policy makers taking initiatives on a priority basis. (author)

  8. The number of subjects per variable required in linear regression analyses

    NARCIS (Netherlands)

    P.C. Austin (Peter); E.W. Steyerberg (Ewout)

    2015-01-01

    textabstractObjectives To determine the number of independent variables that can be included in a linear regression model. Study Design and Setting We used a series of Monte Carlo simulations to examine the impact of the number of subjects per variable (SPV) on the accuracy of estimated regression

  9. The number of subjects per variable required in linear regression analyses.

    Science.gov (United States)

    Austin, Peter C; Steyerberg, Ewout W

    2015-06-01

    To determine the number of independent variables that can be included in a linear regression model. We used a series of Monte Carlo simulations to examine the impact of the number of subjects per variable (SPV) on the accuracy of estimated regression coefficients and standard errors, on the empirical coverage of estimated confidence intervals, and on the accuracy of the estimated R(2) of the fitted model. A minimum of approximately two SPV tended to result in estimation of regression coefficients with relative bias of less than 10%. Furthermore, with this minimum number of SPV, the standard errors of the regression coefficients were accurately estimated and estimated confidence intervals had approximately the advertised coverage rates. A much higher number of SPV were necessary to minimize bias in estimating the model R(2), although adjusted R(2) estimates behaved well. The bias in estimating the model R(2) statistic was inversely proportional to the magnitude of the proportion of variation explained by the population regression model. Linear regression models require only two SPV for adequate estimation of regression coefficients, standard errors, and confidence intervals. Copyright © 2015 The Authors. Published by Elsevier Inc. All rights reserved.

  10. Development of a likelihood of survival scoring system for hospitalized equine neonates using generalized boosted regression modeling.

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    Katarzyna A Dembek

    Full Text Available BACKGROUND: Medical management of critically ill equine neonates (foals can be expensive and labor intensive. Predicting the odds of foal survival using clinical information could facilitate the decision-making process for owners and clinicians. Numerous prognostic indicators and mathematical models to predict outcome in foals have been published; however, a validated scoring method to predict survival in sick foals has not been reported. The goal of this study was to develop and validate a scoring system that can be used by clinicians to predict likelihood of survival of equine neonates based on clinical data obtained on admission. METHODS AND RESULTS: Data from 339 hospitalized foals of less than four days of age admitted to three equine hospitals were included to develop the model. Thirty seven variables including historical information, physical examination and laboratory findings were analyzed by generalized boosted regression modeling (GBM to determine which ones would be included in the survival score. Of these, six variables were retained in the final model. The weight for each variable was calculated using a generalized linear model and the probability of survival for each total score was determined. The highest (7 and the lowest (0 scores represented 97% and 3% probability of survival, respectively. Accuracy of this survival score was validated in a prospective study on data from 283 hospitalized foals from the same three hospitals. Sensitivity, specificity, positive and negative predictive values for the survival score in the prospective population were 96%, 71%, 91%, and 85%, respectively. CONCLUSIONS: The survival score developed in our study was validated in a large number of foals with a wide range of diseases and can be easily implemented using data available in most equine hospitals. GBM was a useful tool to develop the survival score. Further evaluations of this scoring system in field conditions are needed.

  11. Bayesian linear regression with skew-symmetric error distributions with applications to survival analysis

    KAUST Repository

    Rubio, Francisco J.; Genton, Marc G.

    2016-01-01

    are censored. The latter scenario is of interest in the context of accelerated failure time models, which are relevant in survival analysis. We present a simulation study that demonstrates good frequentist properties of the posterior credible intervals

  12. Correcting for multivariate measurement error by regression calibration in meta-analyses of epidemiological studies.

    NARCIS (Netherlands)

    Kromhout, D.

    2009-01-01

    Within-person variability in measured values of multiple risk factors can bias their associations with disease. The multivariate regression calibration (RC) approach can correct for such measurement error and has been applied to studies in which true values or independent repeat measurements of the

  13. Testing Mediation Using Multiple Regression and Structural Equation Modeling Analyses in Secondary Data

    Science.gov (United States)

    Li, Spencer D.

    2011-01-01

    Mediation analysis in child and adolescent development research is possible using large secondary data sets. This article provides an overview of two statistical methods commonly used to test mediated effects in secondary analysis: multiple regression and structural equation modeling (SEM). Two empirical studies are presented to illustrate the…

  14. Regression Analyses on the Butterfly Ballot Effect: A Statistical Perspective of the US 2000 Election

    Science.gov (United States)

    Wu, Dane W.

    2002-01-01

    The year 2000 US presidential election between Al Gore and George Bush has been the most intriguing and controversial one in American history. The state of Florida was the trigger for the controversy, mainly, due to the use of the misleading "butterfly ballot". Using prediction (or confidence) intervals for least squares regression lines…

  15. Alpins and thibos vectorial astigmatism analyses: proposal of a linear regression model between methods

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    Giuliano de Oliveira Freitas

    2013-10-01

    Full Text Available PURPOSE: To determine linear regression models between Alpins descriptive indices and Thibos astigmatic power vectors (APV, assessing the validity and strength of such correlations. METHODS: This case series prospectively assessed 62 eyes of 31 consecutive cataract patients with preoperative corneal astigmatism between 0.75 and 2.50 diopters in both eyes. Patients were randomly assorted among two phacoemulsification groups: one assigned to receive AcrySof®Toric intraocular lens (IOL in both eyes and another assigned to have AcrySof Natural IOL associated with limbal relaxing incisions, also in both eyes. All patients were reevaluated postoperatively at 6 months, when refractive astigmatism analysis was performed using both Alpins and Thibos methods. The ratio between Thibos postoperative APV and preoperative APV (APVratio and its linear regression to Alpins percentage of success of astigmatic surgery, percentage of astigmatism corrected and percentage of astigmatism reduction at the intended axis were assessed. RESULTS: Significant negative correlation between the ratio of post- and preoperative Thibos APVratio and Alpins percentage of success (%Success was found (Spearman's ρ=-0.93; linear regression is given by the following equation: %Success = (-APVratio + 1.00x100. CONCLUSION: The linear regression we found between APVratio and %Success permits a validated mathematical inference concerning the overall success of astigmatic surgery.

  16. Check-all-that-apply data analysed by Partial Least Squares regression

    DEFF Research Database (Denmark)

    Rinnan, Åsmund; Giacalone, Davide; Frøst, Michael Bom

    2015-01-01

    are analysed by multivariate techniques. CATA data can be analysed both by setting the CATA as the X and the Y. The former is the PLS-Discriminant Analysis (PLS-DA) version, while the latter is the ANOVA-PLS (A-PLS) version. We investigated the difference between these two approaches, concluding...

  17. Differential item functioning (DIF) analyses of health-related quality of life instruments using logistic regression

    DEFF Research Database (Denmark)

    Scott, Neil W; Fayers, Peter M; Aaronson, Neil K

    2010-01-01

    Differential item functioning (DIF) methods can be used to determine whether different subgroups respond differently to particular items within a health-related quality of life (HRQoL) subscale, after allowing for overall subgroup differences in that scale. This article reviews issues that arise ...... when testing for DIF in HRQoL instruments. We focus on logistic regression methods, which are often used because of their efficiency, simplicity and ease of application....

  18. Analyses of Developmental Rate Isomorphy in Ectotherms: Introducing the Dirichlet Regression.

    Directory of Open Access Journals (Sweden)

    David S Boukal

    Full Text Available Temperature drives development in insects and other ectotherms because their metabolic rate and growth depends directly on thermal conditions. However, relative durations of successive ontogenetic stages often remain nearly constant across a substantial range of temperatures. This pattern, termed 'developmental rate isomorphy' (DRI in insects, appears to be widespread and reported departures from DRI are generally very small. We show that these conclusions may be due to the caveats hidden in the statistical methods currently used to study DRI. Because the DRI concept is inherently based on proportional data, we propose that Dirichlet regression applied to individual-level data is an appropriate statistical method to critically assess DRI. As a case study we analyze data on five aquatic and four terrestrial insect species. We find that results obtained by Dirichlet regression are consistent with DRI violation in at least eight of the studied species, although standard analysis detects significant departure from DRI in only four of them. Moreover, the departures from DRI detected by Dirichlet regression are consistently much larger than previously reported. The proposed framework can also be used to infer whether observed departures from DRI reflect life history adaptations to size- or stage-dependent effects of varying temperature. Our results indicate that the concept of DRI in insects and other ectotherms should be critically re-evaluated and put in a wider context, including the concept of 'equiproportional development' developed for copepods.

  19. Correlation and regression analyses of genetic effects for different types of cells in mammals under radiation and chemical treatment

    International Nuclear Information System (INIS)

    Slutskaya, N.G.; Mosseh, I.B.

    2006-01-01

    Data about genetic mutations under radiation and chemical treatment for different types of cells have been analyzed with correlation and regression analyses. Linear correlation between different genetic effects in sex cells and somatic cells have found. The results may be extrapolated on sex cells of human and mammals. (authors)

  20. Correcting for multivariate measurement error by regression calibration in meta-analyses of epidemiological studies

    DEFF Research Database (Denmark)

    Tybjærg-Hansen, Anne

    2009-01-01

    Within-person variability in measured values of multiple risk factors can bias their associations with disease. The multivariate regression calibration (RC) approach can correct for such measurement error and has been applied to studies in which true values or independent repeat measurements...... of the risk factors are observed on a subsample. We extend the multivariate RC techniques to a meta-analysis framework where multiple studies provide independent repeat measurements and information on disease outcome. We consider the cases where some or all studies have repeat measurements, and compare study......-specific, averaged and empirical Bayes estimates of RC parameters. Additionally, we allow for binary covariates (e.g. smoking status) and for uncertainty and time trends in the measurement error corrections. Our methods are illustrated using a subset of individual participant data from prospective long-term studies...

  1. Correlation, Regression and Path Analyses of Seed Yield Components in Crambe abyssinica, a Promising Industrial Oil Crop

    OpenAIRE

    Huang, Banglian; Yang, Yiming; Luo, Tingting; Wu, S.; Du, Xuezhu; Cai, Detian; Loo, van, E.N.; Huang Bangquan

    2013-01-01

    In the present study correlation, regression and path analyses were carried out to decide correlations among the agro- nomic traits and their contributions to seed yield per plant in Crambe abyssinica. Partial correlation analysis indicated that plant height (X1) was significantly correlated with branching height and the number of first branches (P <0.01); Branching height (X2) was significantly correlated with pod number of primary inflorescence (P <0.01) and number of secondary branch...

  2. New insights into survival trend analyses in cancer population-based studies: the SUDCAN methodology.

    Science.gov (United States)

    Uhry, Zoé; Bossard, Nadine; Remontet, Laurent; Iwaz, Jean; Roche, Laurent

    2017-01-01

    The main objective of the SUDCAN study was to compare, for 15 cancer sites, the trends in net survival and excess mortality rates from cancer 5 years after diagnosis between six European Latin countries (Belgium, France, Italy, Portugal, Spain and Switzerland). The data were extracted from the EUROCARE-5 database. The study period ranged from 6 (Portugal, 2000-2005) to 18 years (Switzerland, 1989-2007). Trend analyses were carried out separately for each country and cancer site; the number of cases ranged from 1500 to 104 000 cases. We developed an original flexible excess rate modelling strategy that accounts for the continuous effects of age, year of diagnosis, time since diagnosis and their interactions. Nineteen models were constructed; they differed in the modelling of the effect of the year of diagnosis in terms of linearity, proportionality and interaction with age. The final model was chosen according to the Akaike Information Criterion. The fit was assessed graphically by comparing model estimates versus nonparametric (Pohar-Perme) net survival estimates. Out of the 90 analyses carried out, the effect of the year of diagnosis on the excess mortality rate depended on age in 61 and was nonproportional in 64; it was nonlinear in 27 out of the 75 analyses where this effect was considered. The model fit was overall satisfactory. We analysed successfully 15 cancer sites in six countries. The refined methodology proved necessary for detailed trend analyses. It is hoped that three-dimensional parametric modelling will be used more widely in net survival trend studies as it has major advantages over stratified analyses.

  3. A chip-level modeling approach for rail span collapse and survivability analyses

    International Nuclear Information System (INIS)

    Marvis, D.G.; Alexander, D.R.; Dinger, G.L.

    1989-01-01

    A general semiautomated analysis technique has been developed for analyzing rail span collapse and survivability of VLSI microcircuits in high ionizing dose rate radiation environments. Hierarchical macrocell modeling permits analyses at the chip level and interactive graphical postprocessing provides a rapid visualization of voltage, current and power distributions over an entire VLSIC. The technique is demonstrated for a 16k C MOS/SOI SRAM and a CMOS/SOS 8-bit multiplier. The authors also present an efficient method to treat memory arrays as well as a three-dimensional integration technique to compute sapphire photoconduction from the design layout

  4. Analyses of non-fatal accidents in an opencast mine by logistic regression model - a case study.

    Science.gov (United States)

    Onder, Seyhan; Mutlu, Mert

    2017-09-01

    Accidents cause major damage for both workers and enterprises in the mining industry. To reduce the number of occupational accidents, these incidents should be properly registered and carefully analysed. This study efficiently examines the Aegean Lignite Enterprise (ELI) of Turkish Coal Enterprises (TKI) in Soma between 2006 and 2011, and opencast coal mine occupational accident records were used for statistical analyses. A total of 231 occupational accidents were analysed for this study. The accident records were categorized into seven groups: area, reason, occupation, part of body, age, shift hour and lost days. The SPSS package program was used in this study for logistic regression analyses, which predicted the probability of accidents resulting in greater or less than 3 lost workdays for non-fatal injuries. Social facilities-area of surface installations, workshops and opencast mining areas are the areas with the highest probability for accidents with greater than 3 lost workdays for non-fatal injuries, while the reasons with the highest probability for these types of accidents are transporting and manual handling. Additionally, the model was tested for such reported accidents that occurred in 2012 for the ELI in Soma and estimated the probability of exposure to accidents with lost workdays correctly by 70%.

  5. Improved Dietary Guidelines for Vitamin D: Application of Individual Participant Data (IPD-Level Meta-Regression Analyses

    Directory of Open Access Journals (Sweden)

    Kevin D. Cashman

    2017-05-01

    Full Text Available Dietary Reference Values (DRVs for vitamin D have a key role in the prevention of vitamin D deficiency. However, despite adopting similar risk assessment protocols, estimates from authoritative agencies over the last 6 years have been diverse. This may have arisen from diverse approaches to data analysis. Modelling strategies for pooling of individual subject data from cognate vitamin D randomized controlled trials (RCTs are likely to provide the most appropriate DRV estimates. Thus, the objective of the present work was to undertake the first-ever individual participant data (IPD-level meta-regression, which is increasingly recognized as best practice, from seven winter-based RCTs (with 882 participants ranging in age from 4 to 90 years of the vitamin D intake–serum 25-hydroxyvitamin D (25(OHD dose-response. Our IPD-derived estimates of vitamin D intakes required to maintain 97.5% of 25(OHD concentrations >25, 30, and 50 nmol/L across the population are 10, 13, and 26 µg/day, respectively. In contrast, standard meta-regression analyses with aggregate data (as used by several agencies in recent years from the same RCTs estimated that a vitamin D intake requirement of 14 µg/day would maintain 97.5% of 25(OHD >50 nmol/L. These first IPD-derived estimates offer improved dietary recommendations for vitamin D because the underpinning modeling captures the between-person variability in response of serum 25(OHD to vitamin D intake.

  6. Improved Dietary Guidelines for Vitamin D: Application of Individual Participant Data (IPD)-Level Meta-Regression Analyses

    Science.gov (United States)

    Cashman, Kevin D.; Ritz, Christian; Kiely, Mairead

    2017-01-01

    Dietary Reference Values (DRVs) for vitamin D have a key role in the prevention of vitamin D deficiency. However, despite adopting similar risk assessment protocols, estimates from authoritative agencies over the last 6 years have been diverse. This may have arisen from diverse approaches to data analysis. Modelling strategies for pooling of individual subject data from cognate vitamin D randomized controlled trials (RCTs) are likely to provide the most appropriate DRV estimates. Thus, the objective of the present work was to undertake the first-ever individual participant data (IPD)-level meta-regression, which is increasingly recognized as best practice, from seven winter-based RCTs (with 882 participants ranging in age from 4 to 90 years) of the vitamin D intake–serum 25-hydroxyvitamin D (25(OH)D) dose-response. Our IPD-derived estimates of vitamin D intakes required to maintain 97.5% of 25(OH)D concentrations >25, 30, and 50 nmol/L across the population are 10, 13, and 26 µg/day, respectively. In contrast, standard meta-regression analyses with aggregate data (as used by several agencies in recent years) from the same RCTs estimated that a vitamin D intake requirement of 14 µg/day would maintain 97.5% of 25(OH)D >50 nmol/L. These first IPD-derived estimates offer improved dietary recommendations for vitamin D because the underpinning modeling captures the between-person variability in response of serum 25(OH)D to vitamin D intake. PMID:28481259

  7. Longitudinal changes in telomere length and associated genetic parameters in dairy cattle analysed using random regression models.

    Directory of Open Access Journals (Sweden)

    Luise A Seeker

    Full Text Available Telomeres cap the ends of linear chromosomes and shorten with age in many organisms. In humans short telomeres have been linked to morbidity and mortality. With the accumulation of longitudinal datasets the focus shifts from investigating telomere length (TL to exploring TL change within individuals over time. Some studies indicate that the speed of telomere attrition is predictive of future disease. The objectives of the present study were to 1 characterize the change in bovine relative leukocyte TL (RLTL across the lifetime in Holstein Friesian dairy cattle, 2 estimate genetic parameters of RLTL over time and 3 investigate the association of differences in individual RLTL profiles with productive lifespan. RLTL measurements were analysed using Legendre polynomials in a random regression model to describe TL profiles and genetic variance over age. The analyses were based on 1,328 repeated RLTL measurements of 308 female Holstein Friesian dairy cattle. A quadratic Legendre polynomial was fitted to the fixed effect of age in months and to the random effect of the animal identity. Changes in RLTL, heritability and within-trait genetic correlation along the age trajectory were calculated and illustrated. At a population level, the relationship between RLTL and age was described by a positive quadratic function. Individuals varied significantly regarding the direction and amount of RLTL change over life. The heritability of RLTL ranged from 0.36 to 0.47 (SE = 0.05-0.08 and remained statistically unchanged over time. The genetic correlation of RLTL at birth with measurements later in life decreased with the time interval between samplings from near unity to 0.69, indicating that TL later in life might be regulated by different genes than TL early in life. Even though animals differed in their RLTL profiles significantly, those differences were not correlated with productive lifespan (p = 0.954.

  8. Vitamin K2 regression aortic calcification induced by warfarin via Gas6/Axl survival pathway in rats.

    Science.gov (United States)

    Jiang, Xiaoyu; Tao, Huiren; Qiu, Cuiting; Ma, Xiaolei; Li, Shan; Guo, Xian; Lv, Anlin; Li, Huan

    2016-09-05

    The aim of this study was to investigate the effect of vitamin K2 on aortic calcification induced by warfarin via Gas6/Axl survival pathway in rats. A calcification model was established by administering 3mg/g warfarin to rats. Rats were divided into 9 groups: control group (0W, 4W, 6W and 12W groups), 4W calcification group, 6W calcification group, 12W calcification group, 6W calcification+6W normal group and 6W calcification+6W vitamin K2 group. Alizarin red S staining measured aortic calcium depositions; alkaline phosphatase activity in serum was measured by a kit; apoptosis was evaluated by TUNEL assay; protein expression levels of Gas6, Axl, phosphorylated Akt (p-Akt), and Bcl-2 were determined by western blotting. The calcium content, calcium depositions, ALP activity and apoptosis were significantly higher in the calcification groups than control group. Gas6, Axl, p-Akt and Bcl-2 expression was lower in the calcification group than control group. 100μg/g vitamin K2 treatment decreased calcium depositions, ALP activity and apoptosis significantly, but increased Gas6, Axl, p-Akt and Bcl-2 expression. 100μg/g vitamin K2 reversed 44% calcification. Pearson correlation analysis showed a positive correlation between formation calcification and apoptosis (R(2)=0.8853, PK2 can inhibit warfarin-induced aortic calcification and apoptosis. The regression of aortic calcification by vitamin K2 involved the Gas6/Axl axis. This data may provide a theoretical basis for future clinical treatments for aortic calcification. Copyright © 2016 Elsevier B.V. All rights reserved.

  9. SPECIFICS OF THE APPLICATIONS OF MULTIPLE REGRESSION MODEL IN THE ANALYSES OF THE EFFECTS OF GLOBAL FINANCIAL CRISES

    Directory of Open Access Journals (Sweden)

    Željko V. Račić

    2010-12-01

    Full Text Available This paper aims to present the specifics of the application of multiple linear regression model. The economic (financial crisis is analyzed in terms of gross domestic product which is in a function of the foreign trade balance (on one hand and the credit cards, i.e. indebtedness of the population on this basis (on the other hand, in the USA (from 1999. to 2008. We used the extended application model which shows how the analyst should run the whole development process of regression model. This process began with simple statistical features and the application of regression procedures, and ended with residual analysis, intended for the study of compatibility of data and model settings. This paper also analyzes the values of some standard statistics used in the selection of appropriate regression model. Testing of the model is carried out with the use of the Statistics PASW 17 program.

  10. Surrogacy of progression free survival for overall survival in metastatic breast cancer studies: Meta-analyses of published studies.

    Science.gov (United States)

    Kundu, Madan G; Acharyya, Suddhasatta

    2017-02-01

    PFS is often used as a surrogate endpoint for OS in metastatic breast cancer studies. We have evaluated the association of treatment effect on PFS with significant HR OS (and how this association is affected by other factors) in published prospective metastatic breast cancer studies. A systematic literature search in PubMed identified prospective metastatic breast cancer studies. Treatment effects on PFS were determined using hazard ratio (HR PFS ), increase in median PFS (ΔMED PFS ) and % increase in median PFS (%ΔMED PFS ). Diagnostic accuracy of PFS measures (HR PFS , ΔMED PFS and %ΔMED PFS ) in predicting significant HR OS was assessed using receiver operating characteristic (ROC) curves and classification tree approach (CART). Seventy-four cases (i.e., treatment to control comparisons) from 65 individual publications were identified for the analyses. Of these, 16 cases reported significant treatment effect on HR OS at 5% level of significance. Median number of deaths reported in these cases were 153. Area under the ROC curve (AUC) for diagnostic measures as HR PFS , ΔMED PFS and %ΔMED PFS were 0.69, 0.70 and 0.75, respectively. Classification tree results identified %ΔMED PFS and number of deaths as diagnostic measure for significant HR OS . Only 7.9% (3/39) cases with ΔMED PFS shorter than 48.27% reported significant HR OS . There were 7 cases with ΔMED PFS of 48.27% or more and number of deaths reported as 227 or more - of these 5 cases reported significant HR OS . %ΔMED PFS was found to be a better diagnostic measure for predicting significant HR OS . Our analysis results also suggest that consideration of total number of deaths may further improve its diagnostic performance. Based on our study results, the studies with 50% improvement in median PFS are more likely to produce significant HR OS if the total number of OS events at the time of analysis is 227 or more. Copyright © 2016 Elsevier Inc. All rights reserved.

  11. Using synthetic data to evaluate multiple regression and principal component analyses for statistical modeling of daily building energy consumption

    Energy Technology Data Exchange (ETDEWEB)

    Reddy, T.A. (Energy Systems Lab., Texas A and M Univ., College Station, TX (United States)); Claridge, D.E. (Energy Systems Lab., Texas A and M Univ., College Station, TX (United States))

    1994-01-01

    Multiple regression modeling of monitored building energy use data is often faulted as a reliable means of predicting energy use on the grounds that multicollinearity between the regressor variables can lead both to improper interpretation of the relative importance of the various physical regressor parameters and to a model with unstable regressor coefficients. Principal component analysis (PCA) has the potential to overcome such drawbacks. While a few case studies have already attempted to apply this technique to building energy data, the objectives of this study were to make a broader evaluation of PCA and multiple regression analysis (MRA) and to establish guidelines under which one approach is preferable to the other. Four geographic locations in the US with different climatic conditions were selected and synthetic data sequence representative of daily energy use in large institutional buildings were generated in each location using a linear model with outdoor temperature, outdoor specific humidity and solar radiation as the three regression variables. MRA and PCA approaches were then applied to these data sets and their relative performances were compared. Conditions under which PCA seems to perform better than MRA were identified and preliminary recommendations on the use of either modeling approach formulated. (orig.)

  12. Enhanced left ventricular mass regression after aortic valve replacement in patients with aortic stenosis is associated with improved long-term survival.

    Science.gov (United States)

    Ali, Ayyaz; Patel, Amit; Ali, Ziad; Abu-Omar, Yasir; Saeed, Amber; Athanasiou, Thanos; Pepper, John

    2011-08-01

    Aortic valve replacement in patients with aortic stenosis is usually followed by regression of left ventricular hypertrophy. More complete resolution of left ventricular hypertrophy is suggested to be associated with superior clinical outcomes; however, its translational impact on long-term survival after aortic valve replacement has not been investigated. Demographic, operative, and clinical data were obtained retrospectively through case note review. Transthoracic echocardiography was used to measure left ventricular mass preoperatively and at annual follow-up visits. Patients were classified according to their reduction in left ventricular mass at 1 year after the operation: group 1, less than 25 g; group 2, 25 to 150 g; and group 3, more than 150 g. Kaplan-Meier and multivariable Cox regression were used. A total of 147 patients were discharged from the hospital after aortic valve replacement for aortic stenosis between 1991 and 2001. Preoperative left ventricular mass was 279 ± 98 g in group 1 (n = 47), 347 ± 104 g in group 2 (n = 62), and 491 ± 183 g in group 3 (n = 38) (P regression such as ischemic heart disease or hypertension, valve type, or valve size used. Ten-year actuarial survival was not statistically different in patients with enhanced left ventricular mass regression when compared with the log-rank test (group 1, 51% ± 9%; group 2, 54% ± 8%; and group 3, 72% ± 10%) (P = .26). After adjustment, left ventricular mass reduction of more than 150 g was demonstrated as an independent predictor of improved long-term survival on multivariate analysis (P = .02). Our study is the first to suggest that enhanced postoperative left ventricular mass regression, specifically in patients undergoing aortic valve replacement for aortic stenosis, may be associated with improved long-term survival. In view of these findings, strategies purported to be associated with superior left ventricular mass regression should be considered when undertaking

  13. Survival prediction of non-small cell lung cancer patients using radiomics analyses of cone-beam CT images

    DEFF Research Database (Denmark)

    van Timmeren, Janna E; Leijenaar, Ralph T H; van Elmpt, Wouter

    2017-01-01

    was validated. MATERIAL AND METHODS: One training dataset of 132 and two validation datasets of 62 and 94stage I-IV NSCLC patients were included. Interchangeability was assessed by performing a linear regression on CT and CBCT extracted features. A two-step correction was applied prior to model validation...... different between groups with high and low prognostic value for both modalities. Harrell's concordance index was 0.69 for CT and 0.66 for CBCT models for dataset 1. Conclusions The results show that a subset of radiomic features extracted from CT and CBCT images are interchangeable using simple linear...... regression. Moreover, a previously developed radiomics signature has prognostic value for overall survival in three CBCT cohorts, showing the potential of CBCT radiomics to be used as prognostic imaging biomarker....

  14. The N400 as a snapshot of interactive processing: evidence from regression analyses of orthographic neighbor and lexical associate effects

    Science.gov (United States)

    Laszlo, Sarah; Federmeier, Kara D.

    2010-01-01

    Linking print with meaning tends to be divided into subprocesses, such as recognition of an input's lexical entry and subsequent access of semantics. However, recent results suggest that the set of semantic features activated by an input is broader than implied by a view wherein access serially follows recognition. EEG was collected from participants who viewed items varying in number and frequency of both orthographic neighbors and lexical associates. Regression analysis of single item ERPs replicated past findings, showing that N400 amplitudes are greater for items with more neighbors, and further revealed that N400 amplitudes increase for items with more lexical associates and with higher frequency neighbors or associates. Together, the data suggest that in the N400 time window semantic features of items broadly related to inputs are active, consistent with models in which semantic access takes place in parallel with stimulus recognition. PMID:20624252

  15. Treatment algorithm based on the multivariate survival analyses in patients with advanced hepatocellular carcinoma treated with trans-arterial chemoembolization.

    Directory of Open Access Journals (Sweden)

    Hasmukh J Prajapati

    Full Text Available To develop the treatment algorithm from multivariate survival analyses (MVA in patients with Barcelona clinic liver cancer (BCLC C (advanced Hepatocellular carcinoma (HCC patients treated with Trans-arterial Chemoembolization (TACE.Consecutive unresectable and non-tranplantable patients with advanced HCC, who received DEB TACE were studied. A total of 238 patients (mean age, 62.4yrs was included in the study. Survivals were analyzed according to different parameters from the time of the 1st DEB TACE. Kaplan Meier and Cox Proportional Hazard model were used for survival analysis. The SS was constructed from MVA and named BCLC C HCC Prognostic (BCHP staging system (SS.Overall median survival (OS was 16.2 months. In HCC patients with venous thrombosis (VT of large vein [main portal vein (PV, right or left PV, hepatic vein, inferior vena cava] (22.7% versus small vein (segmental/subsegmental PV (9.7% versus no VT had OSs of 6.4 months versus 20 months versus 22.8 months respectively (p<0.001. On MVA, the significant independent prognostic factors (PFs of survival were CP class, eastern cooperative oncology group (ECOG performance status (PS, single HCC<5 cm, site of VT, metastases, serum creatinine and serum alpha-feto protein. Based on these PFs, the BCHP staging system was constructed. The OSs of stages I, II and III were 28.4 months, 11.8 months and 2.4 months accordingly (p<0.001. The treatment plan was proposed according to the different stages.On MVA of patients with advanced HCC treated with TACE, significant independent prognostic factors (PFs of survival were CP class, ECOG PS, single HCC<5 cm or others, site of VT, metastases, serum creatinine and serum alpha-feto protein. New BCHP SS was proposed based on MVA data to identify the suitable advanced HCC patients for TACE treatments.

  16. Modeling the potential risk factors of bovine viral diarrhea prevalence in Egypt using univariable and multivariable logistic regression analyses

    Directory of Open Access Journals (Sweden)

    Abdelfattah M. Selim

    2018-03-01

    Full Text Available Aim: The present cross-sectional study was conducted to determine the seroprevalence and potential risk factors associated with Bovine viral diarrhea virus (BVDV disease in cattle and buffaloes in Egypt, to model the potential risk factors associated with the disease using logistic regression (LR models, and to fit the best predictive model for the current data. Materials and Methods: A total of 740 blood samples were collected within November 2012-March 2013 from animals aged between 6 months and 3 years. The potential risk factors studied were species, age, sex, and herd location. All serum samples were examined with indirect ELIZA test for antibody detection. Data were analyzed with different statistical approaches such as Chi-square test, odds ratios (OR, univariable, and multivariable LR models. Results: Results revealed a non-significant association between being seropositive with BVDV and all risk factors, except for species of animal. Seroprevalence percentages were 40% and 23% for cattle and buffaloes, respectively. OR for all categories were close to one with the highest OR for cattle relative to buffaloes, which was 2.237. Likelihood ratio tests showed a significant drop of the -2LL from univariable LR to multivariable LR models. Conclusion: There was an evidence of high seroprevalence of BVDV among cattle as compared with buffaloes with the possibility of infection in different age groups of animals. In addition, multivariable LR model was proved to provide more information for association and prediction purposes relative to univariable LR models and Chi-square tests if we have more than one predictor.

  17. Structural vascular disease in Africans: performance of ethnic-specific waist circumference cut points using logistic regression and neural network analyses: the SABPA study

    OpenAIRE

    Botha, J.; De Ridder, J.H.; Potgieter, J.C.; Steyn, H.S.; Malan, L.

    2013-01-01

    A recently proposed model for waist circumference cut points (RPWC), driven by increased blood pressure, was demonstrated in an African population. We therefore aimed to validate the RPWC by comparing the RPWC and the Joint Statement Consensus (JSC) models via Logistic Regression (LR) and Neural Networks (NN) analyses. Urban African gender groups (N=171) were stratified according to the JSC and RPWC cut point models. Ultrasound carotid intima media thickness (CIMT), blood pressure (BP) and fa...

  18. Comparative analyses of longevity and senescence reveal variable survival benefits of living in zoos across mammals.

    Science.gov (United States)

    Tidière, Morgane; Gaillard, Jean-Michel; Berger, Vérane; Müller, Dennis W H; Bingaman Lackey, Laurie; Gimenez, Olivier; Clauss, Marcus; Lemaître, Jean-François

    2016-11-07

    While it is commonly believed that animals live longer in zoos than in the wild, this assumption has rarely been tested. We compared four survival metrics (longevity, baseline mortality, onset of senescence and rate of senescence) between both sexes of free-ranging and zoo populations of more than 50 mammal species. We found that mammals from zoo populations generally lived longer than their wild counterparts (84% of species). The effect was most notable in species with a faster pace of life (i.e. a short life span, high reproductive rate and high mortality in the wild) because zoos evidently offer protection against a number of relevant conditions like predation, intraspecific competition and diseases. Species with a slower pace of life (i.e. a long life span, low reproduction rate and low mortality in the wild) benefit less from captivity in terms of longevity; in such species, there is probably less potential for a reduction in mortality. These findings provide a first general explanation about the different magnitude of zoo environment benefits among mammalian species, and thereby highlight the effort that is needed to improve captive conditions for slow-living species that are particularly susceptible to extinction in the wild.

  19. Improving validation methods for molecular diagnostics: application of Bland-Altman, Deming and simple linear regression analyses in assay comparison and evaluation for next-generation sequencing.

    Science.gov (United States)

    Misyura, Maksym; Sukhai, Mahadeo A; Kulasignam, Vathany; Zhang, Tong; Kamel-Reid, Suzanne; Stockley, Tracy L

    2018-02-01

    A standard approach in test evaluation is to compare results of the assay in validation to results from previously validated methods. For quantitative molecular diagnostic assays, comparison of test values is often performed using simple linear regression and the coefficient of determination (R 2 ), using R 2 as the primary metric of assay agreement. However, the use of R 2 alone does not adequately quantify constant or proportional errors required for optimal test evaluation. More extensive statistical approaches, such as Bland-Altman and expanded interpretation of linear regression methods, can be used to more thoroughly compare data from quantitative molecular assays. We present the application of Bland-Altman and linear regression statistical methods to evaluate quantitative outputs from next-generation sequencing assays (NGS). NGS-derived data sets from assay validation experiments were used to demonstrate the utility of the statistical methods. Both Bland-Altman and linear regression were able to detect the presence and magnitude of constant and proportional error in quantitative values of NGS data. Deming linear regression was used in the context of assay comparison studies, while simple linear regression was used to analyse serial dilution data. Bland-Altman statistical approach was also adapted to quantify assay accuracy, including constant and proportional errors, and precision where theoretical and empirical values were known. The complementary application of the statistical methods described in this manuscript enables more extensive evaluation of performance characteristics of quantitative molecular assays, prior to implementation in the clinical molecular laboratory. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2018. All rights reserved. No commercial use is permitted unless otherwise expressly granted.

  20. Exposure-survival analyses of pazopanib in renal cell carcinoma and soft tissue sarcoma patients: opportunities for dose optimization.

    Science.gov (United States)

    Verheijen, R B; Swart, L E; Beijnen, J H; Schellens, J H M; Huitema, A D R; Steeghs, N

    2017-12-01

    Pazopanib is an angiogenesis inhibitor approved for the treatment of renal cell carcinoma and soft tissue sarcoma. Post hoc analysis of a clinical trial demonstrated a relationship between pazopanib trough concentrations (C min ) and treatment efficacy. The aim of this study was to explore the pharmacokinetics and exposure-survival relationships of pazopanib in a real-world patient cohort. Renal cell cancer and soft tissue sarcoma patients who had at least one pazopanib plasma concentration available were included. Using calculated C min values and a threshold of > 20 mg/L, univariate and multivariate exposure-survival analyses were performed. Sixty-one patients were included, of which 16.4% were underexposed (mean C min   20 mg/L was related to longer progression free survival in renal cell cancer patients (34.1 vs. 12.5 weeks, n = 35, p = 0.027) and the overall population (25.0 vs. 8.8 weeks, n = 61, p = 0.012), but not in the sarcoma subgroup (18.7 vs. 8.8 weeks, n = 26, p = 0.142). In multivariate analysis C min  > 20 mg/L was associated with hazard ratios of 0.25 (p = 0.021) in renal cancer, 0.12 (p = 0.011) in sarcoma and 0.38 (p = 0.017) in a pooled analysis. This study confirms that pazopanib C min  > 20 mg/L relates to better progression free survival in renal cancer and points towards a similar trend in sarcoma patients. C min monitoring of pazopanib can help identify patients with low C min for whom individualized treatment at a higher dose may be appropriate.

  1. Comparison of Adjuvant Radiation Therapy Alone and Chemotherapy Alone in Surgically Resected Low-Grade Gliomas: Survival Analyses of 2253 Cases from the National Cancer Data Base.

    Science.gov (United States)

    Wu, Jing; Neale, Natalie; Huang, Yuqian; Bai, Harrison X; Li, Xuejun; Zhang, Zishu; Karakousis, Giorgos; Huang, Raymond; Zhang, Paul J; Tang, Lei; Xiao, Bo; Yang, Li

    2018-04-01

    It is becoming increasingly common to incorporate chemotherapy (CT) with radiotherapy (RT) in the treatment of low-grade gliomas (LGGs) after surgical resection. However, there is a lack of literature comparing survival of patients who underwent RT or CT alone. The U.S. National Cancer Data Base was used to identify patients with histologically confirmed, World Health Organization grade 2 gliomas who received either RT alone or CT alone after surgery from 2004 to 2013. Overall survival (OS) was evaluated by Kaplan-Meier analysis, multivariable Cox proportional hazard regression, and propensity-score-matched analysis. In total, 2253 patients with World Health Organization grade 2 gliomas were included, of whom 1466 (65.1%) received RT alone and 787 (34.9%) CT alone. The median OS was 98.9 months for the RT alone group and 125.8 months for the CT alone group. On multivariable analysis, CT alone was associated with a significant OS benefit compared with RT alone (hazard ratio [HR], 0.405; 95% confidence interval, 0.277-0.592; P < 0.001). On subgroup analyses, the survival advantage of CT alone over RT alone persisted across all age groups, and for the subtotal resection and biopsy groups, but not in the gross total resection group. In propensity-score-matched analysis, CT alone still showed significantly improved OS compared with RT alone (HR, 0.612; 95% confidence interval, 0.506-0.741; P < 0.001). Our results suggest that CT alone was independently associated with longer OS compared with RT alone in patients with LGGs who underwent surgery. Copyright © 2018 Elsevier Inc. All rights reserved.

  2. Classification and regression tree (CART) analyses of genomic signatures reveal sets of tetramers that discriminate temperature optima of archaea and bacteria

    Science.gov (United States)

    Dyer, Betsey D.; Kahn, Michael J.; LeBlanc, Mark D.

    2008-01-01

    Classification and regression tree (CART) analysis was applied to genome-wide tetranucleotide frequencies (genomic signatures) of 195 archaea and bacteria. Although genomic signatures have typically been used to classify evolutionary divergence, in this study, convergent evolution was the focus. Temperature optima for most of the organisms examined could be distinguished by CART analyses of tetranucleotide frequencies. This suggests that pervasive (nonlinear) qualities of genomes may reflect certain environmental conditions (such as temperature) in which those genomes evolved. The predominant use of GAGA and AGGA as the discriminating tetramers in CART models suggests that purine-loading and codon biases of thermophiles may explain some of the results. PMID:19054742

  3. Assessing the suitability of summary data for two-sample Mendelian randomization analyses using MR-Egger regression: the role of the I2 statistic.

    Science.gov (United States)

    Bowden, Jack; Del Greco M, Fabiola; Minelli, Cosetta; Davey Smith, George; Sheehan, Nuala A; Thompson, John R

    2016-12-01

    : MR-Egger regression has recently been proposed as a method for Mendelian randomization (MR) analyses incorporating summary data estimates of causal effect from multiple individual variants, which is robust to invalid instruments. It can be used to test for directional pleiotropy and provides an estimate of the causal effect adjusted for its presence. MR-Egger regression provides a useful additional sensitivity analysis to the standard inverse variance weighted (IVW) approach that assumes all variants are valid instruments. Both methods use weights that consider the single nucleotide polymorphism (SNP)-exposure associations to be known, rather than estimated. We call this the `NO Measurement Error' (NOME) assumption. Causal effect estimates from the IVW approach exhibit weak instrument bias whenever the genetic variants utilized violate the NOME assumption, which can be reliably measured using the F-statistic. The effect of NOME violation on MR-Egger regression has yet to be studied. An adaptation of the I2 statistic from the field of meta-analysis is proposed to quantify the strength of NOME violation for MR-Egger. It lies between 0 and 1, and indicates the expected relative bias (or dilution) of the MR-Egger causal estimate in the two-sample MR context. We call it IGX2 . The method of simulation extrapolation is also explored to counteract the dilution. Their joint utility is evaluated using simulated data and applied to a real MR example. In simulated two-sample MR analyses we show that, when a causal effect exists, the MR-Egger estimate of causal effect is biased towards the null when NOME is violated, and the stronger the violation (as indicated by lower values of IGX2 ), the stronger the dilution. When additionally all genetic variants are valid instruments, the type I error rate of the MR-Egger test for pleiotropy is inflated and the causal effect underestimated. Simulation extrapolation is shown to substantially mitigate these adverse effects. We

  4. The more total cognitive load is reduced by cues, the better retention and transfer of multimedia learning: A meta-analysis and two meta-regression analyses.

    Science.gov (United States)

    Xie, Heping; Wang, Fuxing; Hao, Yanbin; Chen, Jiaxue; An, Jing; Wang, Yuxin; Liu, Huashan

    2017-01-01

    Cueing facilitates retention and transfer of multimedia learning. From the perspective of cognitive load theory (CLT), cueing has a positive effect on learning outcomes because of the reduction in total cognitive load and avoidance of cognitive overload. However, this has not been systematically evaluated. Moreover, what remains ambiguous is the direct relationship between the cue-related cognitive load and learning outcomes. A meta-analysis and two subsequent meta-regression analyses were conducted to explore these issues. Subjective total cognitive load (SCL) and scores on a retention test and transfer test were selected as dependent variables. Through a systematic literature search, 32 eligible articles encompassing 3,597 participants were included in the SCL-related meta-analysis. Among them, 25 articles containing 2,910 participants were included in the retention-related meta-analysis and the following retention-related meta-regression, while there were 29 articles containing 3,204 participants included in the transfer-related meta-analysis and the transfer-related meta-regression. The meta-analysis revealed a statistically significant cueing effect on subjective ratings of cognitive load (d = -0.11, 95% CI = [-0.19, -0.02], p < 0.05), retention performance (d = 0.27, 95% CI = [0.08, 0.46], p < 0.01), and transfer performance (d = 0.34, 95% CI = [0.12, 0.56], p < 0.01). The subsequent meta-regression analyses showed that dSCL for cueing significantly predicted dretention for cueing (β = -0.70, 95% CI = [-1.02, -0.38], p < 0.001), as well as dtransfer for cueing (β = -0.60, 95% CI = [-0.92, -0.28], p < 0.001). Thus in line with CLT, adding cues in multimedia materials can indeed reduce SCL and promote learning outcomes, and the more SCL is reduced by cues, the better retention and transfer of multimedia learning.

  5. Extended mitogenomic phylogenetic analyses yield new insight into crocodylian evolution and their survival of the Cretaceous-Tertiary boundary.

    Science.gov (United States)

    Roos, Jonas; Aggarwal, Ramesh K; Janke, Axel

    2007-11-01

    The mitochondrial genomes of the dwarf crocodile, Osteolaemus tetraspis, and two species of dwarf caimans, the smooth-fronted caiman, Paleosuchus trigonatus, and Cuvier's dwarf caiman, Paleosuchus palpebrosus, were sequenced and included in a mitogenomic phylogenetic study. The phylogenetic analyses, which included a total of ten crocodylian species, yielded strong support to a basal split between Crocodylidae and Alligatoridae. Osteolaemus fell within the Crocodylidae as the sister group to Crocodylus. Gavialis and Tomistoma, which joined on a common branch, constituted a sister group to Crocodylus/Osteolaemus. This suggests that extant crocodylians are organized in two families: Alligatoridae and Crocodylidae. Within the Alligatoridae there was a basal split between Alligator and a branch that contained Paleosuchus and Caiman. The analyses also provided molecular estimates of various divergences applying recently established crocodylian and outgroup fossil calibration points. Molecular estimates based on amino acid data placed the divergence between Crocodylidae and Alligatoridae at 97-103 million years ago and that between Alligator and Caiman/Paleosuchus at 65-72 million years ago. Other crocodilian divergences were placed after the Cretaceous-Tertiary boundary. Thus, according to the molecular estimates, three extant crocodylian lineages have their roots in the Cretaceous. Considering the crocodylian diversification in the Cretaceous the molecular datings suggest that the extinction of the dinosaurs was also to some extent paralleled in the crocodylian evolution. However, for whatever reason, some crocodylian lineages survived into the Tertiary.

  6. Predictors of success of external cephalic version and cephalic presentation at birth among 1253 women with non-cephalic presentation using logistic regression and classification tree analyses.

    Science.gov (United States)

    Hutton, Eileen K; Simioni, Julia C; Thabane, Lehana

    2017-08-01

    Among women with a fetus with a non-cephalic presentation, external cephalic version (ECV) has been shown to reduce the rate of breech presentation at birth and cesarean birth. Compared with ECV at term, beginning ECV prior to 37 weeks' gestation decreases the number of infants in a non-cephalic presentation at birth. The purpose of this secondary analysis was to investigate factors associated with a successful ECV procedure and to present this in a clinically useful format. Data were collected as part of the Early ECV Pilot and Early ECV2 Trials, which randomized 1776 women with a fetus in breech presentation to either early ECV (34-36 weeks' gestation) or delayed ECV (at or after 37 weeks). The outcome of interest was successful ECV, defined as the fetus being in a cephalic presentation immediately following the procedure, as well as at the time of birth. The importance of several factors in predicting successful ECV was investigated using two statistical methods: logistic regression and classification and regression tree (CART) analyses. Among nulliparas, non-engagement of the presenting part and an easily palpable fetal head were independently associated with success. Among multiparas, non-engagement of the presenting part, gestation less than 37 weeks and an easily palpable fetal head were found to be independent predictors of success. These findings were consistent with results of the CART analyses. Regardless of parity, descent of the presenting part was the most discriminating factor in predicting successful ECV and cephalic presentation at birth. © 2017 Nordic Federation of Societies of Obstetrics and Gynecology.

  7. Adjuvant Sunitinib for High-risk Renal Cell Carcinoma After Nephrectomy: Subgroup Analyses and Updated Overall Survival Results.

    Science.gov (United States)

    Motzer, Robert J; Ravaud, Alain; Patard, Jean-Jacques; Pandha, Hardev S; George, Daniel J; Patel, Anup; Chang, Yen-Hwa; Escudier, Bernard; Donskov, Frede; Magheli, Ahmed; Carteni, Giacomo; Laguerre, Brigitte; Tomczak, Piotr; Breza, Jan; Gerletti, Paola; Lechuga, Mariajose; Lin, Xun; Casey, Michelle; Serfass, Lucile; Pantuck, Allan J; Staehler, Michael

    2018-01-01

    Adjuvant sunitinib significantly improved disease-free survival (DFS) versus placebo in patients with locoregional renal cell carcinoma (RCC) at high risk of recurrence after nephrectomy (hazard ratio [HR] 0.76, 95% confidence interval [CI] 0.59-0.98; p=0.03). To report the relationship between baseline factors and DFS, pattern of recurrence, and updated overall survival (OS). Data for 615 patients randomized to sunitinib (n=309) or placebo (n=306) in the S-TRAC trial. Subgroup DFS analyses by baseline risk factors were conducted using a Cox proportional hazards model. Baseline risk factors included: modified University of California Los Angeles integrated staging system criteria, age, gender, Eastern Cooperative Oncology Group performance status (ECOG PS), weight, neutrophil-to-lymphocyte ratio (NLR), and Fuhrman grade. Of 615 patients, 97 and 122 in the sunitinib and placebo arms developed metastatic disease, with the most common sites of distant recurrence being lung (40 and 49), lymph node (21 and 26), and liver (11 and 14), respectively. A benefit of adjuvant sunitinib over placebo was observed across subgroups, including: higher risk (T3, no or undetermined nodal involvement, Fuhrman grade ≥2, ECOG PS ≥1, T4 and/or nodal involvement; hazard ratio [HR] 0.74, 95% confidence interval [CI] 0.55-0.99; p=0.04), NLR ≤3 (HR 0.72, 95% CI 0.54-0.95; p=0.02), and Fuhrman grade 3/4 (HR 0.73, 95% CI 0.55-0.98; p=0.04). All subgroup analyses were exploratory, and no adjustments for multiplicity were made. Median OS was not reached in either arm (HR 0.92, 95% CI 0.66-1.28; p=0.6); 67 and 74 patients died in the sunitinib and placebo arms, respectively. A benefit of adjuvant sunitinib over placebo was observed across subgroups. The results are consistent with the primary analysis, which showed a benefit for adjuvant sunitinib in patients at high risk of recurrent RCC after nephrectomy. Most subgroups of patients at high risk of recurrent renal cell carcinoma after

  8. Using threshold regression to analyze survival data from complex surveys: With application to mortality linked NHANES III Phase II genetic data.

    Science.gov (United States)

    Li, Yan; Xiao, Tao; Liao, Dandan; Lee, Mei-Ling Ting

    2018-03-30

    The Cox proportional hazards (PH) model is a common statistical technique used for analyzing time-to-event data. The assumption of PH, however, is not always appropriate in real applications. In cases where the assumption is not tenable, threshold regression (TR) and other survival methods, which do not require the PH assumption, are available and widely used. These alternative methods generally assume that the study data constitute simple random samples. In particular, TR has not been studied in the setting of complex surveys that involve (1) differential selection probabilities of study subjects and (2) intracluster correlations induced by multistage cluster sampling. In this paper, we extend TR procedures to account for complex sampling designs. The pseudo-maximum likelihood estimation technique is applied to estimate the TR model parameters. Computationally efficient Taylor linearization variance estimators that consider both the intracluster correlation and the differential selection probabilities are developed. The proposed methods are evaluated by using simulation experiments with various complex designs and illustrated empirically by using mortality-linked Third National Health and Nutrition Examination Survey Phase II genetic data. Copyright © 2017 John Wiley & Sons, Ltd.

  9. Adjuvant Sunitinib for High-risk Renal Cell Carcinoma After Nephrectomy: Subgroup Analyses and Updated Overall Survival Results

    DEFF Research Database (Denmark)

    Motzer, Robert J; Ravaud, Alain; Patard, Jean-Jacques

    2018-01-01

    BACKGROUND: Adjuvant sunitinib significantly improved disease-free survival (DFS) versus placebo in patients with locoregional renal cell carcinoma (RCC) at high risk of recurrence after nephrectomy (hazard ratio [HR] 0.76, 95% confidence interval [CI] 0.59-0.98; p=0.03). OBJECTIVE: To report...... sunitinib over placebo was observed across subgroups, including: higher risk (T3, no or undetermined nodal involvement, Fuhrman grade ≥2, ECOG PS ≥1, T4 and/or nodal involvement; hazard ratio [HR] 0.74, 95% confidence interval [CI] 0.55-0.99; p=0.04), NLR ≤3 (HR 0.72, 95% CI 0.54-0.95; p=0.02), and Fuhrman...... grade 3/4 (HR 0.73, 95% CI 0.55-0.98; p=0.04). All subgroup analyses were exploratory, and no adjustments for multiplicity were made. Median OS was not reached in either arm (HR 0.92, 95% CI 0.66-1.28; p=0.6); 67 and 74 patients died in the sunitinib and placebo arms, respectively. CONCLUSIONS...

  10. Analyses of polycyclic aromatic hydrocarbon (PAH) and chiral-PAH analogues-methyl-β-cyclodextrin guest-host inclusion complexes by fluorescence spectrophotometry and multivariate regression analysis.

    Science.gov (United States)

    Greene, LaVana; Elzey, Brianda; Franklin, Mariah; Fakayode, Sayo O

    2017-03-05

    The negative health impact of polycyclic aromatic hydrocarbons (PAHs) and differences in pharmacological activity of enantiomers of chiral molecules in humans highlights the need for analysis of PAHs and their chiral analogue molecules in humans. Herein, the first use of cyclodextrin guest-host inclusion complexation, fluorescence spectrophotometry, and chemometric approach to PAH (anthracene) and chiral-PAH analogue derivatives (1-(9-anthryl)-2,2,2-triflouroethanol (TFE)) analyses are reported. The binding constants (K b ), stoichiometry (n), and thermodynamic properties (Gibbs free energy (ΔG), enthalpy (ΔH), and entropy (ΔS)) of anthracene and enantiomers of TFE-methyl-β-cyclodextrin (Me-β-CD) guest-host complexes were also determined. Chemometric partial-least-square (PLS) regression analysis of emission spectra data of Me-β-CD-guest-host inclusion complexes was used for the determination of anthracene and TFE enantiomer concentrations in Me-β-CD-guest-host inclusion complex samples. The values of calculated K b and negative ΔG suggest the thermodynamic favorability of anthracene-Me-β-CD and enantiomeric of TFE-Me-β-CD inclusion complexation reactions. However, anthracene-Me-β-CD and enantiomer TFE-Me-β-CD inclusion complexations showed notable differences in the binding affinity behaviors and thermodynamic properties. The PLS regression analysis resulted in square-correlation-coefficients of 0.997530 or better and a low LOD of 3.81×10 -7 M for anthracene and 3.48×10 -8 M for TFE enantiomers at physiological conditions. Most importantly, PLS regression accurately determined the anthracene and TFE enantiomer concentrations with an average low error of 2.31% for anthracene, 4.44% for R-TFE and 3.60% for S-TFE. The results of the study are highly significant because of its high sensitivity and accuracy for analysis of PAH and chiral PAH analogue derivatives without the need of an expensive chiral column, enantiomeric resolution, or use of a polarized

  11. Bisphenol-A exposures and behavioural aberrations: median and linear spline and meta-regression analyses of 12 toxicity studies in rodents.

    Science.gov (United States)

    Peluso, Marco E M; Munnia, Armelle; Ceppi, Marcello

    2014-11-05

    Exposures to bisphenol-A, a weak estrogenic chemical, largely used for the production of plastic containers, can affect the rodent behaviour. Thus, we examined the relationships between bisphenol-A and the anxiety-like behaviour, spatial skills, and aggressiveness, in 12 toxicity studies of rodent offspring from females orally exposed to bisphenol-A, while pregnant and/or lactating, by median and linear splines analyses. Subsequently, the meta-regression analysis was applied to quantify the behavioural changes. U-shaped, inverted U-shaped and J-shaped dose-response curves were found to describe the relationships between bisphenol-A with the behavioural outcomes. The occurrence of anxiogenic-like effects and spatial skill changes displayed U-shaped and inverted U-shaped curves, respectively, providing examples of effects that are observed at low-doses. Conversely, a J-dose-response relationship was observed for aggressiveness. When the proportion of rodents expressing certain traits or the time that they employed to manifest an attitude was analysed, the meta-regression indicated that a borderline significant increment of anxiogenic-like effects was present at low-doses regardless of sexes (β)=-0.8%, 95% C.I. -1.7/0.1, P=0.076, at ≤120 μg bisphenol-A. Whereas, only bisphenol-A-males exhibited a significant inhibition of spatial skills (β)=0.7%, 95% C.I. 0.2/1.2, P=0.004, at ≤100 μg/day. A significant increment of aggressiveness was observed in both the sexes (β)=67.9,C.I. 3.4, 172.5, P=0.038, at >4.0 μg. Then, bisphenol-A treatments significantly abrogated spatial learning and ability in males (Pbisphenol-A, e.g. ≤120 μg/day, were associated to behavioural aberrations in offspring. Copyright © 2014. Published by Elsevier Ireland Ltd.

  12. Exploring reasons for the observed inconsistent trial reports on intra-articular injections with hyaluronic acid in the treatment of osteoarthritis: Meta-regression analyses of randomized trials.

    Science.gov (United States)

    Johansen, Mette; Bahrt, Henriette; Altman, Roy D; Bartels, Else M; Juhl, Carsten B; Bliddal, Henning; Lund, Hans; Christensen, Robin

    2016-08-01

    The aim was to identify factors explaining inconsistent observations concerning the efficacy of intra-articular hyaluronic acid compared to intra-articular sham/control, or non-intervention control, in patients with symptomatic osteoarthritis, based on randomized clinical trials (RCTs). A systematic review and meta-regression analyses of available randomized trials were conducted. The outcome, pain, was assessed according to a pre-specified hierarchy of potentially available outcomes. Hedges׳s standardized mean difference [SMD (95% CI)] served as effect size. REstricted Maximum Likelihood (REML) mixed-effects models were used to combine study results, and heterogeneity was calculated and interpreted as Tau-squared and I-squared, respectively. Overall, 99 studies (14,804 patients) met the inclusion criteria: Of these, only 71 studies (72%), including 85 comparisons (11,216 patients), had adequate data available for inclusion in the primary meta-analysis. Overall, compared with placebo, intra-articular hyaluronic acid reduced pain with an effect size of -0.39 [-0.47 to -0.31; P hyaluronic acid. Based on available trial data, intra-articular hyaluronic acid showed a better effect than intra-articular saline on pain reduction in osteoarthritis. Publication bias and the risk of selective outcome reporting suggest only small clinical effect compared to saline. Copyright © 2016 Elsevier Inc. All rights reserved.

  13. Item Response Theory Modeling and Categorical Regression Analyses of the Five-Factor Model Rating Form: A Study on Italian Community-Dwelling Adolescent Participants and Adult Participants.

    Science.gov (United States)

    Fossati, Andrea; Widiger, Thomas A; Borroni, Serena; Maffei, Cesare; Somma, Antonella

    2017-06-01

    To extend the evidence on the reliability and construct validity of the Five-Factor Model Rating Form (FFMRF) in its self-report version, two independent samples of Italian participants, which were composed of 510 adolescent high school students and 457 community-dwelling adults, respectively, were administered the FFMRF in its Italian translation. Adolescent participants were also administered the Italian translation of the Borderline Personality Features Scale for Children-11 (BPFSC-11), whereas adult participants were administered the Italian translation of the Triarchic Psychopathy Measure (TriPM). Cronbach α values were consistent with previous findings; in both samples, average interitem r values indicated acceptable internal consistency for all FFMRF scales. A multidimensional graded item response theory model indicated that the majority of FFMRF items had adequate discrimination parameters; information indices supported the reliability of the FFMRF scales. Both categorical (i.e., item-level) and scale-level regression analyses suggested that the FFMRF scores may predict a nonnegligible amount of variance in the BPFSC-11 total score in adolescent participants, and in the TriPM scale scores in adult participants.

  14. Effective behaviour change techniques for physical activity and healthy eating in overweight and obese adults; systematic review and meta-regression analyses.

    Science.gov (United States)

    Samdal, Gro Beate; Eide, Geir Egil; Barth, Tom; Williams, Geoffrey; Meland, Eivind

    2017-03-28

    This systematic review aims to explain the heterogeneity in results of interventions to promote physical activity and healthy eating for overweight and obese adults, by exploring the differential effects of behaviour change techniques (BCTs) and other intervention characteristics. The inclusion criteria specified RCTs with ≥ 12 weeks' duration, from January 2007 to October 2014, for adults (mean age ≥ 40 years, mean BMI ≥ 30). Primary outcomes were measures of healthy diet or physical activity. Two reviewers rated study quality, coded the BCTs, and collected outcome results at short (≤6 months) and long term (≥12 months). Meta-analyses and meta-regressions were used to estimate effect sizes (ES), heterogeneity indices (I 2 ) and regression coefficients. We included 48 studies containing a total of 82 outcome reports. The 32 long term reports had an overall ES = 0.24 with 95% confidence interval (CI): 0.15 to 0.33 and I 2  = 59.4%. The 50 short term reports had an ES = 0.37 with 95% CI: 0.26 to 0.48, and I 2  = 71.3%. The number of BCTs unique to the intervention group, and the BCTs goal setting and self-monitoring of behaviour predicted the effect at short and long term. The total number of BCTs in both intervention arms and using the BCTs goal setting of outcome, feedback on outcome of behaviour, implementing graded tasks, and adding objects to the environment, e.g. using a step counter, significantly predicted the effect at long term. Setting a goal for change; and the presence of reporting bias independently explained 58.8% of inter-study variation at short term. Autonomy supportive and person-centred methods as in Motivational Interviewing, the BCTs goal setting of behaviour, and receiving feedback on the outcome of behaviour, explained all of the between study variations in effects at long term. There are similarities, but also differences in effective BCTs promoting change in healthy eating and physical activity and

  15. Dual Regression

    OpenAIRE

    Spady, Richard; Stouli, Sami

    2012-01-01

    We propose dual regression as an alternative to the quantile regression process for the global estimation of conditional distribution functions under minimal assumptions. Dual regression provides all the interpretational power of the quantile regression process while avoiding the need for repairing the intersecting conditional quantile surfaces that quantile regression often produces in practice. Our approach introduces a mathematical programming characterization of conditional distribution f...

  16. Personal, social, and game-related correlates of active and non-active gaming among dutch gaming adolescents: survey-based multivariable, multilevel logistic regression analyses.

    Science.gov (United States)

    Simons, Monique; de Vet, Emely; Chinapaw, Mai Jm; de Boer, Michiel; Seidell, Jacob C; Brug, Johannes

    2014-04-04

    Playing video games contributes substantially to sedentary behavior in youth. A new generation of video games-active games-seems to be a promising alternative to sedentary games to promote physical activity and reduce sedentary behavior. At this time, little is known about correlates of active and non-active gaming among adolescents. The objective of this study was to examine potential personal, social, and game-related correlates of both active and non-active gaming in adolescents. A survey assessing game behavior and potential personal, social, and game-related correlates was conducted among adolescents (12-16 years, N=353) recruited via schools. Multivariable, multilevel logistic regression analyses, adjusted for demographics (age, sex and educational level of adolescents), were conducted to examine personal, social, and game-related correlates of active gaming ≥1 hour per week (h/wk) and non-active gaming >7 h/wk. Active gaming ≥1 h/wk was significantly associated with a more positive attitude toward active gaming (OR 5.3, CI 2.4-11.8; Pgames (OR 0.30, CI 0.1-0.6; P=.002), a higher score on habit strength regarding gaming (OR 1.9, CI 1.2-3.2; P=.008) and having brothers/sisters (OR 6.7, CI 2.6-17.1; Pgame engagement (OR 0.95, CI 0.91-0.997; P=.04). Non-active gaming >7 h/wk was significantly associated with a more positive attitude toward non-active gaming (OR 2.6, CI 1.1-6.3; P=.035), a stronger habit regarding gaming (OR 3.0, CI 1.7-5.3; P7 h/wk. Active gaming is most strongly (negatively) associated with attitude with respect to non-active games, followed by observed active game behavior of brothers and sisters and attitude with respect to active gaming (positive associations). On the other hand, non-active gaming is most strongly associated with observed non-active game behavior of friends, habit strength regarding gaming and attitude toward non-active gaming (positive associations). Habit strength was a correlate of both active and non-active gaming

  17. Personal, Social, and Game-Related Correlates of Active and Non-Active Gaming Among Dutch Gaming Adolescents: Survey-Based Multivariable, Multilevel Logistic Regression Analyses

    Science.gov (United States)

    de Vet, Emely; Chinapaw, Mai JM; de Boer, Michiel; Seidell, Jacob C; Brug, Johannes

    2014-01-01

    Background Playing video games contributes substantially to sedentary behavior in youth. A new generation of video games—active games—seems to be a promising alternative to sedentary games to promote physical activity and reduce sedentary behavior. At this time, little is known about correlates of active and non-active gaming among adolescents. Objective The objective of this study was to examine potential personal, social, and game-related correlates of both active and non-active gaming in adolescents. Methods A survey assessing game behavior and potential personal, social, and game-related correlates was conducted among adolescents (12-16 years, N=353) recruited via schools. Multivariable, multilevel logistic regression analyses, adjusted for demographics (age, sex and educational level of adolescents), were conducted to examine personal, social, and game-related correlates of active gaming ≥1 hour per week (h/wk) and non-active gaming >7 h/wk. Results Active gaming ≥1 h/wk was significantly associated with a more positive attitude toward active gaming (OR 5.3, CI 2.4-11.8; Pgames (OR 0.30, CI 0.1-0.6; P=.002), a higher score on habit strength regarding gaming (OR 1.9, CI 1.2-3.2; P=.008) and having brothers/sisters (OR 6.7, CI 2.6-17.1; Pgame engagement (OR 0.95, CI 0.91-0.997; P=.04). Non-active gaming >7 h/wk was significantly associated with a more positive attitude toward non-active gaming (OR 2.6, CI 1.1-6.3; P=.035), a stronger habit regarding gaming (OR 3.0, CI 1.7-5.3; P7 h/wk. Active gaming is most strongly (negatively) associated with attitude with respect to non-active games, followed by observed active game behavior of brothers and sisters and attitude with respect to active gaming (positive associations). On the other hand, non-active gaming is most strongly associated with observed non-active game behavior of friends, habit strength regarding gaming and attitude toward non-active gaming (positive associations). Habit strength was a

  18. Consequences of kriging and land use regression for PM2.5 predictions in epidemiologic analyses: insights into spatial variability using high-resolution satellite data.

    Science.gov (United States)

    Alexeeff, Stacey E; Schwartz, Joel; Kloog, Itai; Chudnovsky, Alexandra; Koutrakis, Petros; Coull, Brent A

    2015-01-01

    Many epidemiological studies use predicted air pollution exposures as surrogates for true air pollution levels. These predicted exposures contain exposure measurement error, yet simulation studies have typically found negligible bias in resulting health effect estimates. However, previous studies typically assumed a statistical spatial model for air pollution exposure, which may be oversimplified. We address this shortcoming by assuming a realistic, complex exposure surface derived from fine-scale (1 km × 1 km) remote-sensing satellite data. Using simulation, we evaluate the accuracy of epidemiological health effect estimates in linear and logistic regression when using spatial air pollution predictions from kriging and land use regression models. We examined chronic (long-term) and acute (short-term) exposure to air pollution. Results varied substantially across different scenarios. Exposure models with low out-of-sample R(2) yielded severe biases in the health effect estimates of some models, ranging from 60% upward bias to 70% downward bias. One land use regression exposure model with >0.9 out-of-sample R(2) yielded upward biases up to 13% for acute health effect estimates. Almost all models drastically underestimated the SEs. Land use regression models performed better in chronic effect simulations. These results can help researchers when interpreting health effect estimates in these types of studies.

  19. Analyses of potential factors affecting survival of juvenile salmonids volitionally passing through turbines at McNary and John Day Dams, Columbia River

    Science.gov (United States)

    Beeman, John; Hansel, Hal; Perry, Russell; Hockersmith, Eric; Sandford, Ben

    2011-01-01

    This report describes analyses of data from radio- or acoustic-tagged juvenile salmonids passing through hydro-dam turbines to determine factors affecting fish survival. The data were collected during a series of studies designed to estimate passage and survival probabilities at McNary (2002-09) and John Day (2002-03) Dams on the Columbia River during controlled experiments of structures or operations at spillways. Relatively few tagged fish passed turbines in any single study, but sample sizes generally were adequate for our analyses when data were combined from studies using common methods over a series of years. We used information-theoretic methods to evaluate biological, operational, and group covariates by creating models fitting linear (all covariates) or curvilinear (operational covariates only) functions to the data. Biological covariates included tag burden, weight, and water temperature; operational covariates included spill percentage, total discharge, hydraulic head, and turbine unit discharge; and group covariates included year, treatment, and photoperiod. Several interactions between the variables also were considered. Support of covariates by the data was assessed by comparing the Akaike Information Criterion of competing models. The analyses were conducted because there was a lack of information about factors affecting survival of fish passing turbines volitionally and the data were available from past studies. The depth of acclimation, tag size relative to fish size (tag burden), turbine unit discharge, and area of entry into the turbine intake have been shown to affect turbine passage survival of juvenile salmonids in other studies. This study indicates that turbine passage survival of the study fish was primarily affected by biological covariates rather than operational covariates. A negative effect of tag burden was strongly supported in data from yearling Chinook salmon at John Day and McNary dams, but not for subyearling Chinook salmon or

  20. Regression Phalanxes

    OpenAIRE

    Zhang, Hongyang; Welch, William J.; Zamar, Ruben H.

    2017-01-01

    Tomal et al. (2015) introduced the notion of "phalanxes" in the context of rare-class detection in two-class classification problems. A phalanx is a subset of features that work well for classification tasks. In this paper, we propose a different class of phalanxes for application in regression settings. We define a "Regression Phalanx" - a subset of features that work well together for prediction. We propose a novel algorithm which automatically chooses Regression Phalanxes from high-dimensi...

  1. Univariate and multiple linear regression analyses for 23 single nucleotide polymorphisms in 14 genes predisposing to chronic glomerular diseases and IgA nephropathy in Han Chinese.

    Science.gov (United States)

    Wang, Hui; Sui, Weiguo; Xue, Wen; Wu, Junyong; Chen, Jiejing; Dai, Yong

    2014-09-01

    Immunoglobulin A nephropathy (IgAN) is a complex trait regulated by the interaction among multiple physiologic regulatory systems and probably involving numerous genes, which leads to inconsistent findings in genetic studies. One possibility of failure to replicate some single-locus results is that the underlying genetics of IgAN nephropathy is based on multiple genes with minor effects. To learn the association between 23 single nucleotide polymorphisms (SNPs) in 14 genes predisposing to chronic glomerular diseases and IgAN in Han males, the 23 SNPs genotypes of 21 Han males were detected and analyzed with a BaiO gene chip, and their associations were analyzed with univariate analysis and multiple linear regression analysis. Analysis showed that CTLA4 rs231726 and CR2 rs1048971 revealed a significant association with IgAN. These findings support the multi-gene nature of the etiology of IgAN and propose a potential gene-gene interactive model for future studies.

  2. Meta-regression analyses to explain statistical heterogeneity in a systematic review of strategies for guideline implementation in primary health care.

    Directory of Open Access Journals (Sweden)

    Susanne Unverzagt

    Full Text Available This study is an in-depth-analysis to explain statistical heterogeneity in a systematic review of implementation strategies to improve guideline adherence of primary care physicians in the treatment of patients with cardiovascular diseases. The systematic review included randomized controlled trials from a systematic search in MEDLINE, EMBASE, CENTRAL, conference proceedings and registers of ongoing studies. Implementation strategies were shown to be effective with substantial heterogeneity of treatment effects across all investigated strategies. Primary aim of this study was to explain different effects of eligible trials and to identify methodological and clinical effect modifiers. Random effects meta-regression models were used to simultaneously assess the influence of multimodal implementation strategies and effect modifiers on physician adherence. Effect modifiers included the staff responsible for implementation, level of prevention and definition pf the primary outcome, unit of randomization, duration of follow-up and risk of bias. Six clinical and methodological factors were investigated as potential effect modifiers of the efficacy of different implementation strategies on guideline adherence in primary care practices on the basis of information from 75 eligible trials. Five effect modifiers were able to explain a substantial amount of statistical heterogeneity. Physician adherence was improved by 62% (95% confidence interval (95% CI 29 to 104% or 29% (95% CI 5 to 60% in trials where other non-medical professionals or nurses were included in the implementation process. Improvement of physician adherence was more successful in primary and secondary prevention of cardiovascular diseases by around 30% (30%; 95% CI -2 to 71% and 31%; 95% CI 9 to 57%, respectively compared to tertiary prevention. This study aimed to identify effect modifiers of implementation strategies on physician adherence. Especially the cooperation of different health

  3. Basic Diagnosis and Prediction of Persistent Contrail Occurrence using High-resolution Numerical Weather Analyses/Forecasts and Logistic Regression. Part II: Evaluation of Sample Models

    Science.gov (United States)

    Duda, David P.; Minnis, Patrick

    2009-01-01

    Previous studies have shown that probabilistic forecasting may be a useful method for predicting persistent contrail formation. A probabilistic forecast to accurately predict contrail formation over the contiguous United States (CONUS) is created by using meteorological data based on hourly meteorological analyses from the Advanced Regional Prediction System (ARPS) and from the Rapid Update Cycle (RUC) as well as GOES water vapor channel measurements, combined with surface and satellite observations of contrails. Two groups of logistic models were created. The first group of models (SURFACE models) is based on surface-based contrail observations supplemented with satellite observations of contrail occurrence. The second group of models (OUTBREAK models) is derived from a selected subgroup of satellite-based observations of widespread persistent contrails. The mean accuracies for both the SURFACE and OUTBREAK models typically exceeded 75 percent when based on the RUC or ARPS analysis data, but decreased when the logistic models were derived from ARPS forecast data.

  4. Propensity-score matching in economic analyses: comparison with regression models, instrumental variables, residual inclusion, differences-in-differences, and decomposition methods.

    Science.gov (United States)

    Crown, William H

    2014-02-01

    This paper examines the use of propensity score matching in economic analyses of observational data. Several excellent papers have previously reviewed practical aspects of propensity score estimation and other aspects of the propensity score literature. The purpose of this paper is to compare the conceptual foundation of propensity score models with alternative estimators of treatment effects. References are provided to empirical comparisons among methods that have appeared in the literature. These comparisons are available for a subset of the methods considered in this paper. However, in some cases, no pairwise comparisons of particular methods are yet available, and there are no examples of comparisons across all of the methods surveyed here. Irrespective of the availability of empirical comparisons, the goal of this paper is to provide some intuition about the relative merits of alternative estimators in health economic evaluations where nonlinearity, sample size, availability of pre/post data, heterogeneity, and missing variables can have important implications for choice of methodology. Also considered is the potential combination of propensity score matching with alternative methods such as differences-in-differences and decomposition methods that have not yet appeared in the empirical literature.

  5. Basic Diagnosis and Prediction of Persistent Contrail Occurrence using High-resolution Numerical Weather Analyses/Forecasts and Logistic Regression. Part I: Effects of Random Error

    Science.gov (United States)

    Duda, David P.; Minnis, Patrick

    2009-01-01

    Straightforward application of the Schmidt-Appleman contrail formation criteria to diagnose persistent contrail occurrence from numerical weather prediction data is hindered by significant bias errors in the upper tropospheric humidity. Logistic models of contrail occurrence have been proposed to overcome this problem, but basic questions remain about how random measurement error may affect their accuracy. A set of 5000 synthetic contrail observations is created to study the effects of random error in these probabilistic models. The simulated observations are based on distributions of temperature, humidity, and vertical velocity derived from Advanced Regional Prediction System (ARPS) weather analyses. The logistic models created from the simulated observations were evaluated using two common statistical measures of model accuracy, the percent correct (PC) and the Hanssen-Kuipers discriminant (HKD). To convert the probabilistic results of the logistic models into a dichotomous yes/no choice suitable for the statistical measures, two critical probability thresholds are considered. The HKD scores are higher when the climatological frequency of contrail occurrence is used as the critical threshold, while the PC scores are higher when the critical probability threshold is 0.5. For both thresholds, typical random errors in temperature, relative humidity, and vertical velocity are found to be small enough to allow for accurate logistic models of contrail occurrence. The accuracy of the models developed from synthetic data is over 85 percent for both the prediction of contrail occurrence and non-occurrence, although in practice, larger errors would be anticipated.

  6. Analyses of germline variants associated with ovarian cancer survival identify functional candidates at the 1q22 and 19p12 outcome loci

    DEFF Research Database (Denmark)

    Glubb, Dylan M; Johnatty, Sharon E; Quinn, Michael C J

    2017-01-01

    We previously identified associations with ovarian cancer outcome at five genetic loci. To identify putatively causal genetic variants and target genes, we prioritized two ovarian outcome loci (1q22 and 19p12) for further study. Bioinformatic and functional genetic analyses indicated that MEF2D...... and ZNF100 are targets of candidate outcome variants at 1q22 and 19p12, respectively. At 19p12, the chromatin interaction of a putative regulatory element with the ZNF100 promoter region correlated with candidate outcome variants. At 1q22, putative regulatory elements enhanced MEF2D promoter activity...... and haplotypes containing candidate outcome variants modulated these effects. In a public dataset, MEF2D and ZNF100 expression were both associated with ovarian cancer progression-free or overall survival time. In an extended set of 6,162 epithelial ovarian cancer patients, we found that functional candidates...

  7. Comparative Analyses of Nonpathogenic, Opportunistic, and Totally Pathogenic Mycobacteria Reveal Genomic and Biochemical Variabilities and Highlight the Survival Attributes of Mycobacterium tuberculosis

    Science.gov (United States)

    Singh, Yadvir; Kohli, Sakshi; Ahmad, Javeed; Ehtesham, Nasreen Z.; Tyagi, Anil K.

    2014-01-01

    ABSTRACT Mycobacterial evolution involves various processes, such as genome reduction, gene cooption, and critical gene acquisition. Our comparative genome size analysis of 44 mycobacterial genomes revealed that the nonpathogenic (NP) genomes were bigger than those of opportunistic (OP) or totally pathogenic (TP) mycobacteria, with the TP genomes being smaller yet variable in size—their genomic plasticity reflected their ability to evolve and survive under various environmental conditions. From the 44 mycobacterial species, 13 species, representing TP, OP, and NP, were selected for genomic-relatedness analyses. Analysis of homologous protein-coding genes shared between Mycobacterium indicus pranii (NP), Mycobacterium intracellulare ATCC 13950 (OP), and Mycobacterium tuberculosis H37Rv (TP) revealed that 4,995 (i.e., ~95%) M. indicaus pranii proteins have homology with M. intracellulare, whereas the homologies among M. indicus pranii, M. intracellulare ATCC 13950, and M. tuberculosis H37Rv were significantly lower. A total of 4,153 (~79%) M. indicus pranii proteins and 4,093 (~79%) M. intracellulare ATCC 13950 proteins exhibited homology with the M. tuberculosis H37Rv proteome, while 3,301 (~82%) and 3,295 (~82%) M. tuberculosis H37Rv proteins showed homology with M. indicus pranii and M. intracellulare ATCC 13950 proteomes, respectively. Comparative metabolic pathway analyses of TP/OP/NP mycobacteria showed enzymatic plasticity between M. indicus pranii (NP) and M. intracellulare ATCC 13950 (OP), Mycobacterium avium 104 (OP), and M. tuberculosis H37Rv (TP). Mycobacterium tuberculosis seems to have acquired novel alternate pathways with possible roles in metabolism, host-pathogen interactions, virulence, and intracellular survival, and by implication some of these could be potential drug targets. PMID:25370496

  8. Autistic Regression

    Science.gov (United States)

    Matson, Johnny L.; Kozlowski, Alison M.

    2010-01-01

    Autistic regression is one of the many mysteries in the developmental course of autism and pervasive developmental disorders not otherwise specified (PDD-NOS). Various definitions of this phenomenon have been used, further clouding the study of the topic. Despite this problem, some efforts at establishing prevalence have been made. The purpose of…

  9. Regression Analysis

    CERN Document Server

    Freund, Rudolf J; Sa, Ping

    2006-01-01

    The book provides complete coverage of the classical methods of statistical analysis. It is designed to give students an understanding of the purpose of statistical analyses, to allow the student to determine, at least to some degree, the correct type of statistical analyses to be performed in a given situation, and have some appreciation of what constitutes good experimental design

  10. riskRegression

    DEFF Research Database (Denmark)

    Ozenne, Brice; Sørensen, Anne Lyngholm; Scheike, Thomas

    2017-01-01

    In the presence of competing risks a prediction of the time-dynamic absolute risk of an event can be based on cause-specific Cox regression models for the event and the competing risks (Benichou and Gail, 1990). We present computationally fast and memory optimized C++ functions with an R interface......-product we obtain fast access to the baseline hazards (compared to survival::basehaz()) and predictions of survival probabilities, their confidence intervals and confidence bands. Confidence intervals and confidence bands are based on point-wise asymptotic expansions of the corresponding statistical...

  11. Linear regression

    CERN Document Server

    Olive, David J

    2017-01-01

    This text covers both multiple linear regression and some experimental design models. The text uses the response plot to visualize the model and to detect outliers, does not assume that the error distribution has a known parametric distribution, develops prediction intervals that work when the error distribution is unknown, suggests bootstrap hypothesis tests that may be useful for inference after variable selection, and develops prediction regions and large sample theory for the multivariate linear regression model that has m response variables. A relationship between multivariate prediction regions and confidence regions provides a simple way to bootstrap confidence regions. These confidence regions often provide a practical method for testing hypotheses. There is also a chapter on generalized linear models and generalized additive models. There are many R functions to produce response and residual plots, to simulate prediction intervals and hypothesis tests, to detect outliers, and to choose response trans...

  12. Treatment factors influencing survival in pancreatic carcinoma; Der Einfluss der Therapie auf das Ueberleben von Patienten mit Pankreaskarzinom. Eine Analyse von Einzelfaktoren

    Energy Technology Data Exchange (ETDEWEB)

    Warszawski, N.; Warszawski, A.; Schneider, B.M.; Roettinger, E.M. [Ulm Univ. (Germany). Abt. Radiologie 2 (Strahlentherapie); Link, K.H.; Gansauge, F. [Ulm Univ. (Germany). Abt. fuer Allgemeinchirurgie; Lutz, M.P. [Ulm Univ. (Germany). Abt. Innere Medizin 1

    1999-07-01

    Purpose: To identify the impact of treatment factors on overall survival in patients with pancreatic carcinoma. Patients and methods: We performed a follow-up study on 38 patients with adenocarcinoma of the pancreas treated from 1984 to 1998. 18/38 patients were resected. Irradiated volume included the primary tumor (or tumor bed) and regional lymph nodes. Thirty-seven patients received in addition chemotherapy consisting of mitoxantrone, 5-fluorouracil and cis-platin, either i.v. (14/38) or i.a. (23/38). The influence of treatment related factors on the overall survival was tested. Biologically effective dose was calculated by the linear-quadratic model ({alpha}/{beta}=25 Gy) and by losing 0.85 Gy per day starting accelerated repopulation at day 28. Results: Treatment factors influencing overall survival were resection (p=0.02), overall treatment time (p=0.03) and biologically effective dose (p<0.002). Total dose and kind of chemotherapy had no significant influence. Treatment volume had a negative correlation (r=-0.5, p=0.06) with overall survival, without any correlation between tumor size, tumor stage, and treatment volume. In multivariate analysis only biologically effective dose remained significant (p=0.02). Conclusions: Among with surgery, biologically effective dose strongly influences overall survival in patients treated for pancreatic carcinoma. Treatment volume should be kept as small as possible and all efforts should be made to avoid treatments splits in radiation therapy. (orig.) [Deutsch] Ziel: Behandlungsfaktoren zu identifizieren, die einen Einfluss auf das Ueberleben von Patienten mit Pankreaskarzinom haben. Patienten und Methode: In einer nichtrandomisierten Studie wurden 38 Patienten ausgewertet, die von 1984 bis 1998 wegen eines Adenokarzinoms des Pankreas behandelt worden waren. Bei 18/38 Patienten war eine Resektion vorgenommen worden. Das Bestrahlungsvolumen beinhaltete den Primaertumor bzw. das Tumorbett und die regionaeren Lymphknoten

  13. Clinical impact of tumor location on the colon cancer survival and recurrence: analyses of pooled data from three large phase III randomized clinical trials.

    Science.gov (United States)

    Aoyama, Toru; Kashiwabara, Kosuke; Oba, Koji; Honda, Michitaka; Sadahiro, Sotaro; Hamada, Chikuma; Maeda, Hiromichi; Mayanagi, Shuhei; Kanda, Mitsuro; Sakamoto, Junichi; Saji, Shigetoyo; Yoshikawa, Takaki

    2017-11-01

    The aim of the present study was to determine whether or not the overall survival (OS) and disease-free survival (DFS) were affected by the tumor location in patients who underwent curative resection for colon cancer in a pooled analysis of three large phase III studies performed in Japan. In total, 4029 patients were included in the present study. Patients were classified as having right-side colon cancer (RC) if the primary tumor was located in the cecum, ascending colon, hepatic flexure or transverse colon, and left-side colon cancer (LCC) if the tumor site was within the splenic flexure, descending colon, sigmoid colon or recto sigmoid junction. The risk factors for the OS and DFS were analyzed. In the present study, 1449 patients were RC, and 2580 were LCC. The OS rates at 3 and 5 years after surgery were 87.6% and 81.6% in the RC group and 91.5% and 84.5% in the LCC group, respectively. Uni- and multivariate analyses showed that RRC increased the risk of death by 19.7% (adjusted hazard ratio = 1.197; 95% confidence interval, 1.020-1.408; P = 0.0272). In contrast, the DFS was similar between the two locations. The present study confirmed that the tumor location was a risk factor for the OS in patients who underwent curative treatment for colon cancer. Tumor location may, therefore, need to be considered a stratification factor in future phase III trials of colon cancer. © 2017 The Authors. Cancer Medicine published by John Wiley & Sons Ltd.

  14. Denosumab and Bone Metastasis–Free Survival in Men With Nonmetastatic Castration-Resistant Prostate Cancer: Exploratory Analyses by Baseline Prostate-Specific Antigen Doubling Time

    Science.gov (United States)

    Smith, Matthew R.; Saad, Fred; Oudard, Stephane; Shore, Neal; Fizazi, Karim; Sieber, Paul; Tombal, Bertrand; Damiao, Ronaldo; Marx, Gavin; Miller, Kurt; Van Veldhuizen, Peter; Morote, Juan; Ye, Zhishen; Dansey, Roger; Goessl, Carsten

    2013-01-01

    Purpose Denosumab, an anti–RANK ligand monoclonal antibody, significantly increases bone metastasis–free survival (BMFS; hazard ratio [HR], 0.85; P = .028) and delays time to first bone metastasis in men with nonmetastatic castration-resistant prostate cancer (CRPC) and baseline prostate-specific antigen (PSA) ≥ 8.0 ng/mL and/or PSA doubling time (PSADT) ≤ 10.0 months. To identify men at greatest risk for bone metastasis or death, we evaluated relationships between PSA and PSADT with BMFS in the placebo group and the efficacy and safety of denosumab in men with PSADT ≤ 10, ≤ 6, and ≤ 4 months. Patients and Methods A total of 1,432 men with nonmetastatic CRPC were randomly assigned 1:1 to monthly subcutaneous denosumab 120 mg or placebo. Enrollment began February 2006; primary analysis cutoff was July 2010, when approximately 660 men were anticipated to have developed bone metastases or died. Results In the placebo group, shorter BMFS was observed as PSADT decreased below 8 months. In analyses by shorter baseline PSADT, denosumab consistently increased BMFS by a median of 6.0, 7.2, and 7.5 months among men with PSADT ≤ 10 (HR, 0.84; P = .042), ≤ 6 (HR, 0.77; P = .006), and ≤ 4 months (HR, 0.71; P = .004), respectively. Denosumab also consistently increased time to bone metastasis by PSADT subset. No difference in survival was observed between treatment groups for the overall study population or PSADT subsets. Conclusion Patients with shorter PSADT are at greater risk for bone metastasis or death. Denosumab consistently improves BMFS in men with shorter PSADT and seems to have the greatest treatment effects in men at high risk for progression. PMID:24043751

  15. Denosumab and bone metastasis-free survival in men with nonmetastatic castration-resistant prostate cancer: exploratory analyses by baseline prostate-specific antigen doubling time.

    Science.gov (United States)

    Smith, Matthew R; Saad, Fred; Oudard, Stephane; Shore, Neal; Fizazi, Karim; Sieber, Paul; Tombal, Bertrand; Damiao, Ronaldo; Marx, Gavin; Miller, Kurt; Van Veldhuizen, Peter; Morote, Juan; Ye, Zhishen; Dansey, Roger; Goessl, Carsten

    2013-10-20

    Denosumab, an anti-RANK ligand monoclonal antibody, significantly increases bone metastasis-free survival (BMFS; hazard ratio [HR], 0.85; P = .028) and delays time to first bone metastasis in men with nonmetastatic castration-resistant prostate cancer (CRPC) and baseline prostate-specific antigen (PSA) ≥ 8.0 ng/mL and/or PSA doubling time (PSADT) ≤ 10.0 months. To identify men at greatest risk for bone metastasis or death, we evaluated relationships between PSA and PSADT with BMFS in the placebo group and the efficacy and safety of denosumab in men with PSADT ≤ 10, ≤ 6, and ≤ 4 months. A total of 1,432 men with nonmetastatic CRPC were randomly assigned 1:1 to monthly subcutaneous denosumab 120 mg or placebo. Enrollment began February 2006; primary analysis cutoff was July 2010, when approximately 660 men were anticipated to have developed bone metastases or died. In the placebo group, shorter BMFS was observed as PSADT decreased below 8 months. In analyses by shorter baseline PSADT, denosumab consistently increased BMFS by a median of 6.0, 7.2, and 7.5 months among men with PSADT ≤ 10 (HR, 0.84; P = .042), ≤ 6 (HR, 0.77; P = .006), and ≤ 4 months (HR, 0.71; P = .004), respectively. Denosumab also consistently increased time to bone metastasis by PSADT subset. No difference in survival was observed between treatment groups for the overall study population or PSADT subsets. Patients with shorter PSADT are at greater risk for bone metastasis or death. Denosumab consistently improves BMFS in men with shorter PSADT and seems to have the greatest treatment effects in men at high risk for progression.

  16. Area under the curve predictions of dalbavancin, a new lipoglycopeptide agent, using the end of intravenous infusion concentration data point by regression analyses such as linear, log-linear and power models.

    Science.gov (United States)

    Bhamidipati, Ravi Kanth; Syed, Muzeeb; Mullangi, Ramesh; Srinivas, Nuggehally

    2018-02-01

    1. Dalbavancin, a lipoglycopeptide, is approved for treating gram-positive bacterial infections. Area under plasma concentration versus time curve (AUC inf ) of dalbavancin is a key parameter and AUC inf /MIC ratio is a critical pharmacodynamic marker. 2. Using end of intravenous infusion concentration (i.e. C max ) C max versus AUC inf relationship for dalbavancin was established by regression analyses (i.e. linear, log-log, log-linear and power models) using 21 pairs of subject data. 3. The predictions of the AUC inf were performed using published C max data by application of regression equations. The quotient of observed/predicted values rendered fold difference. The mean absolute error (MAE)/root mean square error (RMSE) and correlation coefficient (r) were used in the assessment. 4. MAE and RMSE values for the various models were comparable. The C max versus AUC inf exhibited excellent correlation (r > 0.9488). The internal data evaluation showed narrow confinement (0.84-1.14-fold difference) with a RMSE models predicted AUC inf with a RMSE of 3.02-27.46% with fold difference largely contained within 0.64-1.48. 5. Regardless of the regression models, a single time point strategy of using C max (i.e. end of 30-min infusion) is amenable as a prospective tool for predicting AUC inf of dalbavancin in patients.

  17. Classification and Regression Tree Analysis of Clinical Patterns that Predict Survival in 127 Chinese Patients with Advanced Non-small Cell Lung Cancer Treated by Gefitinib Who Failed to Previous Chemotherapy

    Directory of Open Access Journals (Sweden)

    Ziping WANG

    2011-09-01

    Full Text Available Background and objective It has been proven that gefitinib produces only 10%-20% tumor regression in heavily pretreated, unselected non-small cell lung cancer (NSCLC patients as the second- and third-line setting. Asian, female, nonsmokers and adenocarcinoma are favorable factors; however, it is difficult to find a patient satisfying all the above clinical characteristics. The aim of this study is to identify novel predicting factors, and to explore the interactions between clinical variables and their impact on the survival of Chinese patients with advanced NSCLC who were heavily treated with gefitinib in the second- or third-line setting. Methods The clinical and follow-up data of 127 advanced NSCLC patients referred to the Cancer Hospital & Institute, Chinese Academy of Medical Sciences from March 2005 to March 2010 were analyzed. Multivariate analysis of progression-free survival (PFS was performed using recursive partitioning, which is referred to as the classification and regression tree (CART analysis. Results The median PFS of 127 eligible consecutive advanced NSCLC patients was 8.0 months (95%CI: 5.8-10.2. CART was performed with an initial split on first-line chemotherapy outcomes and a second split on patients’ age. Three terminal subgroups were formed. The median PFS of the three subsets ranged from 1.0 month (95%CI: 0.8-1.2 for those with progressive disease outcome after the first-line chemotherapy subgroup, 10 months (95%CI: 7.0-13.0 in patients with a partial response or stable disease in first-line chemotherapy and age <70, and 22.0 months for patients obtaining a partial response or stable disease in first-line chemotherapy at age 70-81 (95%CI: 3.8-40.1. Conclusion Partial response, stable disease in first-line chemotherapy and age ≥ 70 are closely correlated with long-term survival treated by gefitinib as a second- or third-line setting in advanced NSCLC. CART can be used to identify previously unappreciated patient

  18. An Additive-Multiplicative Cox-Aalen Regression Model

    DEFF Research Database (Denmark)

    Scheike, Thomas H.; Zhang, Mei-Jie

    2002-01-01

    Aalen model; additive risk model; counting processes; Cox regression; survival analysis; time-varying effects......Aalen model; additive risk model; counting processes; Cox regression; survival analysis; time-varying effects...

  19. Multivariate analyses to assess the effects of surgeon and hospital volume on cancer survival rates: a nationwide population-based study in Taiwan.

    Directory of Open Access Journals (Sweden)

    Chun-Ming Chang

    Full Text Available BACKGROUND: Positive results between caseloads and outcomes have been validated in several procedures and cancer treatments. However, there is limited information available on the combined effects of surgeon and hospital caseloads. We used nationwide population-based data to explore the association between surgeon and hospital caseloads and survival rates for major cancers. METHODOLOGY: A total of 11,677 patients with incident cancer diagnosed in 2002 were identified from the Taiwan National Health Insurance Research Database. Survival analysis, the Cox proportional hazards model, and propensity scores were used to assess the relationship between 5-year survival rates and different caseload combinations. RESULTS: Based on the Cox proportional hazard model, cancer patients treated by low-volume surgeons in low-volume hospitals had poorer survival rates, and hazard ratios ranged from 1.3 in head and neck cancer to 1.8 in lung cancer after adjusting for patients' demographic variables, co-morbidities, and treatment modality. When analyzed using the propensity scores, the adjusted 5-year survival rates were poorer for patients treated by low-volume surgeons in low-volume hospitals, compared to those treated by high-volume surgeons in high-volume hospitals (P<0.005. CONCLUSIONS: After adjusting for differences in the case mix, cancer patients treated by low-volume surgeons in low-volume hospitals had poorer 5-year survival rates. Payers may implement quality care improvement in low-volume surgeons.

  20. UK Renal Registry 15th annual report: Chapter 5 survival and causes of death of UK adult patients on renal replacement therapy in 2011: national and centre-specific analyses.

    Science.gov (United States)

    Steenkamp, Retha; Shaw, Catriona; Feest, Terry

    2013-01-01

    These analyses examine a) survival from the start of renal replacement therapy (RRT) based on the total incident UK RRT population reported to the UK Renal Registry, b) survival of prevalent patients. Changes in survival between 1997 and 2011 are also reported. Survival was calculated for both incident and prevalent patients on RRT and compared between the UK countries after adjustment for age. Survival of incident patients (starting RRT during 2010) was calculated both from the start of RRT and from 90 days after starting RRT, both with and without censoring at transplantation. Prevalent dialysis patients were censored at transplantation; this means that the patient is considered alive up to the point of transplantation, but the patient's status post-transplant is not considered. Both Kaplan-Meier and Cox adjusted models were used to calculate survival. Causes of death were analysed for both groups. The relative risk of death was calculated compared with the general UK population. The unadjusted 1 year after 90 day survival for patients starting RRT in 2010 was 87.3%, representing an increase from the previous year (86.6%). In incident patients aged 18-64 years, the unadjusted 1 year survival had risen from 86.0% in patients starting RRT in 1997 to 92.6% in patients starting RRT in 2010 and for those aged ≥65 it had increased from 63.9% to 77.0% over the same period. The age-adjusted one year survival (adjusted to age 60) of prevalent dialysis patients increased from 88.1% in the 2001 cohort to 89.8% in the 2010 cohort. Prevalent diabetic patient one year survival rose from 82.1% in the 2002 cohort to 84.7% in the 2010 cohort. The age-standardised mortality ratio for prevalent RRT patients compared with the general population was 18 for age group 30-34 and 2.5 at age 85+ years. In the prevalent RRT dialysis population, cardiovascular disease accounted for 22% of deaths, infection and treatment withdrawal 18% each and 25% were recorded as other causes of death

  1. Analyses adjusting for selective crossover show improved overall survival with adjuvant letrozole compared with tamoxifen in the BIG 1-98 study

    DEFF Research Database (Denmark)

    Colleoni, Marco; Giobbie-Hurder, Anita; Regan, Meredith M

    2011-01-01

    Among postmenopausal women with endocrine-responsive breast cancer, the aromatase inhibitor letrozole, when compared with tamoxifen, has been shown to significantly improve disease-free survival (DFS) and time to distant recurrence (TDR). We investigated whether letrozole monotherapy prolonged ov...

  2. Secondary mediation and regression analyses of the PTClinResNet database: determining causal relationships among the International Classification of Functioning, Disability and Health levels for four physical therapy intervention trials.

    Science.gov (United States)

    Mulroy, Sara J; Winstein, Carolee J; Kulig, Kornelia; Beneck, George J; Fowler, Eileen G; DeMuth, Sharon K; Sullivan, Katherine J; Brown, David A; Lane, Christianne J

    2011-12-01

    Each of the 4 randomized clinical trials (RCTs) hosted by the Physical Therapy Clinical Research Network (PTClinResNet) targeted a different disability group (low back disorder in the Muscle-Specific Strength Training Effectiveness After Lumbar Microdiskectomy [MUSSEL] trial, chronic spinal cord injury in the Strengthening and Optimal Movements for Painful Shoulders in Chronic Spinal Cord Injury [STOMPS] trial, adult stroke in the Strength Training Effectiveness Post-Stroke [STEPS] trial, and pediatric cerebral palsy in the Pediatric Endurance and Limb Strengthening [PEDALS] trial for children with spastic diplegic cerebral palsy) and tested the effectiveness of a muscle-specific or functional activity-based intervention on primary outcomes that captured pain (STOMPS, MUSSEL) or locomotor function (STEPS, PEDALS). The focus of these secondary analyses was to determine causal relationships among outcomes across levels of the International Classification of Functioning, Disability and Health (ICF) framework for the 4 RCTs. With the database from PTClinResNet, we used 2 separate secondary statistical approaches-mediation analysis for the MUSSEL and STOMPS trials and regression analysis for the STEPS and PEDALS trials-to test relationships among muscle performance, primary outcomes (pain related and locomotor related), activity and participation measures, and overall quality of life. Predictive models were stronger for the 2 studies with pain-related primary outcomes. Change in muscle performance mediated or predicted reductions in pain for the MUSSEL and STOMPS trials and, to some extent, walking speed for the STEPS trial. Changes in primary outcome variables were significantly related to changes in activity and participation variables for all 4 trials. Improvement in activity and participation outcomes mediated or predicted increases in overall quality of life for the 3 trials with adult populations. Variables included in the statistical models were limited to those

  3. Differentiating regressed melanoma from regressed lichenoid keratosis.

    Science.gov (United States)

    Chan, Aegean H; Shulman, Kenneth J; Lee, Bonnie A

    2017-04-01

    Distinguishing regressed lichen planus-like keratosis (LPLK) from regressed melanoma can be difficult on histopathologic examination, potentially resulting in mismanagement of patients. We aimed to identify histopathologic features by which regressed melanoma can be differentiated from regressed LPLK. Twenty actively inflamed LPLK, 12 LPLK with regression and 15 melanomas with regression were compared and evaluated by hematoxylin and eosin staining as well as Melan-A, microphthalmia transcription factor (MiTF) and cytokeratin (AE1/AE3) immunostaining. (1) A total of 40% of regressed melanomas showed complete or near complete loss of melanocytes within the epidermis with Melan-A and MiTF immunostaining, while 8% of regressed LPLK exhibited this finding. (2) Necrotic keratinocytes were seen in the epidermis in 33% regressed melanomas as opposed to all of the regressed LPLK. (3) A dense infiltrate of melanophages in the papillary dermis was seen in 40% of regressed melanomas, a feature not seen in regressed LPLK. In summary, our findings suggest that a complete or near complete loss of melanocytes within the epidermis strongly favors a regressed melanoma over a regressed LPLK. In addition, necrotic epidermal keratinocytes and the presence of a dense band-like distribution of dermal melanophages can be helpful in differentiating these lesions. © 2016 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

  4. Regression: A Bibliography.

    Science.gov (United States)

    Pedrini, D. T.; Pedrini, Bonnie C.

    Regression, another mechanism studied by Sigmund Freud, has had much research, e.g., hypnotic regression, frustration regression, schizophrenic regression, and infra-human-animal regression (often directly related to fixation). Many investigators worked with hypnotic age regression, which has a long history, going back to Russian reflexologists.…

  5. Body mass index and breast cancer survival

    DEFF Research Database (Denmark)

    Guo, Qi; Burgess, Stephen; Turman, Constance

    2017-01-01

    Background: There is increasing evidence that elevated body mass index (BMI) is associated with reduced survival for women with breast cancer. However, the underlying reasons remain unclear. We conducted a Mendelian randomization analysis to investigate a possible causal role of BMI in survival...... from breast cancer. Methods: We used individual-level data from six large breast cancer case-cohorts including a total of 36 210 individuals (2475 events) of European ancestry. We created a BMI genetic risk score (GRS) based on genotypes at 94 known BMI-associated genetic variants. Association between...... the BMI genetic score and breast cancer survival was analysed by Cox regression for each study separately. Study-specific hazard ratios were pooled using fixed-effect meta-analysis. Results: BMI genetic score was found to be associated with reduced breast cancer-specific survival for estrogen receptor (ER...

  6. ASURV: Astronomical SURVival Statistics

    Science.gov (United States)

    Feigelson, E. D.; Nelson, P. I.; Isobe, T.; LaValley, M.

    2014-06-01

    ASURV (Astronomical SURVival Statistics) provides astronomy survival analysis for right- and left-censored data including the maximum-likelihood Kaplan-Meier estimator and several univariate two-sample tests, bivariate correlation measures, and linear regressions. ASURV is written in FORTRAN 77, and is stand-alone and does not call any specialized libraries.

  7. Better Autologistic Regression

    Directory of Open Access Journals (Sweden)

    Mark A. Wolters

    2017-11-01

    Full Text Available Autologistic regression is an important probability model for dichotomous random variables observed along with covariate information. It has been used in various fields for analyzing binary data possessing spatial or network structure. The model can be viewed as an extension of the autologistic model (also known as the Ising model, quadratic exponential binary distribution, or Boltzmann machine to include covariates. It can also be viewed as an extension of logistic regression to handle responses that are not independent. Not all authors use exactly the same form of the autologistic regression model. Variations of the model differ in two respects. First, the variable coding—the two numbers used to represent the two possible states of the variables—might differ. Common coding choices are (zero, one and (minus one, plus one. Second, the model might appear in either of two algebraic forms: a standard form, or a recently proposed centered form. Little attention has been paid to the effect of these differences, and the literature shows ambiguity about their importance. It is shown here that changes to either coding or centering in fact produce distinct, non-nested probability models. Theoretical results, numerical studies, and analysis of an ecological data set all show that the differences among the models can be large and practically significant. Understanding the nature of the differences and making appropriate modeling choices can lead to significantly improved autologistic regression analyses. The results strongly suggest that the standard model with plus/minus coding, which we call the symmetric autologistic model, is the most natural choice among the autologistic variants.

  8. Congruence between distribution modelling and phylogeographical analyses reveals Quaternary survival of a toadflax species (Linaria elegans) in oceanic climate areas of a mountain ring range.

    Science.gov (United States)

    Fernández-Mazuecos, Mario; Vargas, Pablo

    2013-06-01

    · The role of Quaternary climatic shifts in shaping the distribution of Linaria elegans, an Iberian annual plant, was investigated using species distribution modelling and molecular phylogeographical analyses. Three hypotheses are proposed to explain the Quaternary history of its mountain ring range. · The distribution of L. elegans was modelled using the maximum entropy method and projected to the last interglacial and to the last glacial maximum (LGM) using two different paleoclimatic models: the Community Climate System Model (CCSM) and the Model for Interdisciplinary Research on Climate (MIROC). Two nuclear and three plastid DNA regions were sequenced for 24 populations (119 individuals sampled). Bayesian phylogenetic, phylogeographical, dating and coalescent-based population genetic analyses were conducted. · Molecular analyses indicated the existence of northern and southern glacial refugia and supported two routes of post-glacial recolonization. These results were consistent with the LGM distribution as inferred under the CCSM paleoclimatic model (but not under the MIROC model). Isolation between two major refugia was dated back to the Riss or Mindel glaciations, > 100 kyr before present (bp). · The Atlantic distribution of inferred refugia suggests that the oceanic (buffered)-continental (harsh) gradient may have played a key and previously unrecognized role in determining Quaternary distribution shifts of Mediterranean plants. © 2013 The Authors. New Phytologist © 2013 New Phytologist Trust.

  9. Reduced Rank Regression

    DEFF Research Database (Denmark)

    Johansen, Søren

    2008-01-01

    The reduced rank regression model is a multivariate regression model with a coefficient matrix with reduced rank. The reduced rank regression algorithm is an estimation procedure, which estimates the reduced rank regression model. It is related to canonical correlations and involves calculating...

  10. Regression analysis with categorized regression calibrated exposure: some interesting findings

    Directory of Open Access Journals (Sweden)

    Hjartåker Anette

    2006-07-01

    Full Text Available Abstract Background Regression calibration as a method for handling measurement error is becoming increasingly well-known and used in epidemiologic research. However, the standard version of the method is not appropriate for exposure analyzed on a categorical (e.g. quintile scale, an approach commonly used in epidemiologic studies. A tempting solution could then be to use the predicted continuous exposure obtained through the regression calibration method and treat it as an approximation to the true exposure, that is, include the categorized calibrated exposure in the main regression analysis. Methods We use semi-analytical calculations and simulations to evaluate the performance of the proposed approach compared to the naive approach of not correcting for measurement error, in situations where analyses are performed on quintile scale and when incorporating the original scale into the categorical variables, respectively. We also present analyses of real data, containing measures of folate intake and depression, from the Norwegian Women and Cancer study (NOWAC. Results In cases where extra information is available through replicated measurements and not validation data, regression calibration does not maintain important qualities of the true exposure distribution, thus estimates of variance and percentiles can be severely biased. We show that the outlined approach maintains much, in some cases all, of the misclassification found in the observed exposure. For that reason, regression analysis with the corrected variable included on a categorical scale is still biased. In some cases the corrected estimates are analytically equal to those obtained by the naive approach. Regression calibration is however vastly superior to the naive method when applying the medians of each category in the analysis. Conclusion Regression calibration in its most well-known form is not appropriate for measurement error correction when the exposure is analyzed on a

  11. Evaluation of the efficiency of continuous wavelet transform as processing and preprocessing algorithm for resolution of overlapped signals in univariate and multivariate regression analyses; an application to ternary and quaternary mixtures

    Science.gov (United States)

    Hegazy, Maha A.; Lotfy, Hayam M.; Mowaka, Shereen; Mohamed, Ekram Hany

    2016-07-01

    Wavelets have been adapted for a vast number of signal-processing applications due to the amount of information that can be extracted from a signal. In this work, a comparative study on the efficiency of continuous wavelet transform (CWT) as a signal processing tool in univariate regression and a pre-processing tool in multivariate analysis using partial least square (CWT-PLS) was conducted. These were applied to complex spectral signals of ternary and quaternary mixtures. CWT-PLS method succeeded in the simultaneous determination of a quaternary mixture of drotaverine (DRO), caffeine (CAF), paracetamol (PAR) and p-aminophenol (PAP, the major impurity of paracetamol). While, the univariate CWT failed to simultaneously determine the quaternary mixture components and was able to determine only PAR and PAP, the ternary mixtures of DRO, CAF, and PAR and CAF, PAR, and PAP. During the calculations of CWT, different wavelet families were tested. The univariate CWT method was validated according to the ICH guidelines. While for the development of the CWT-PLS model a calibration set was prepared by means of an orthogonal experimental design and their absorption spectra were recorded and processed by CWT. The CWT-PLS model was constructed by regression between the wavelet coefficients and concentration matrices and validation was performed by both cross validation and external validation sets. Both methods were successfully applied for determination of the studied drugs in pharmaceutical formulations.

  12. Survival of Sami cancer patients

    Directory of Open Access Journals (Sweden)

    Leena Soininen

    2012-07-01

    Full Text Available Objectives. The incidence of cancer among the indigenous Sami people of Northern Finland is lower than among the Finnish general population. The survival of Sami cancer patients is not known, and therefore it is the object of this study. Study design. The cohort consisted of 2,091 Sami and 4,161 non-Sami who lived on 31 December 1978 in the two Sami municipalities of Inari and Utsjoki, which are located in Northern Finland and are 300–500 km away from the nearest central hospital. The survival experience of Sami and non-Sami cancer patients diagnosed in this cohort during 1979–2009 was compared with that of the Finnish patients outside the cohort. Methods. The Sami and non-Sami cancer patients were matched to other Finnish cancer patients for gender, age and year of diagnosis and for the site of cancer. An additional matching was done for the stage at diagnosis. Cancer-specific survival analyses were made using the Kaplan–Meier method and Cox regression modelling. Results. There were 204 Sami and 391 non-Sami cancer cases in the cohort, 20,181 matched controls without matching with stage, and 7,874 stage-matched controls. In the cancer-specific analysis without stage variable, the hazard ratio for Sami was 1.05 (95% confidence interval 0.85–1.30 and for non-Sami 1.02 (0.86–1.20, indicating no difference between the survival of those groups and other patients in Finland. Likewise, when the same was done by also matching the stage, there was no difference in cancer survival. Conclusion. Long distances to medical care or Sami ethnicity have no influence on the cancer patient survival in Northern Finland.

  13. Vanadium NMR Chemical Shifts of (Imido)vanadium(V) Dichloride Complexes with Imidazolin-2-iminato and Imidazolidin-2-iminato Ligands: Cooperation with Quantum-Chemical Calculations and Multiple Linear Regression Analyses.

    Science.gov (United States)

    Yi, Jun; Yang, Wenhong; Sun, Wen-Hua; Nomura, Kotohiro; Hada, Masahiko

    2017-11-30

    The NMR chemical shifts of vanadium ( 51 V) in (imido)vanadium(V) dichloride complexes with imidazolin-2-iminato and imidazolidin-2-iminato ligands were calculated by the density functional theory (DFT) method with GIAO. The calculated 51 V NMR chemical shifts were analyzed by the multiple linear regression (MLR) analysis (MLRA) method with a series of calculated molecular properties. Some of calculated NMR chemical shifts were incorrect using the optimized molecular geometries of the X-ray structures. After the global minimum geometries of all of the molecules were determined, the trend of the observed chemical shifts was well reproduced by the present DFT method. The MLRA method was performed to investigate the correlation between the 51 V NMR chemical shift and the natural charge, band energy gap, and Wiberg bond index of the V═N bond. The 51 V NMR chemical shifts obtained with the present MLR model were well reproduced with a correlation coefficient of 0.97.

  14. Continuous and split-course radiotherapy in locally advanced carcinoma of the uterine cervix. Analyses of local control, distant metastases, crude survival, early and late morbidity and prognostic factors

    International Nuclear Information System (INIS)

    Pedersen, D.E.

    1994-01-01

    From 1974 to 1984, 442 consecutive patients with carcinoma of the uterine cervix were referred for combined intracavitary (IRT) and external radiotherapy (ERT). Dose prescriptions were performed based on the points A and B of the Manchester system. From 1978 the treatment strategy was changed from continuous (CRT) to split course radiotherapy (SCRT) with a higher total dose to point B, a lower dose to point A from the IRT, and a longer total treatment time (TTT). The purpose of the present thesis is: To evaluate local tumour control, distant metastases, survival and complications in the rectosigmoid and bladder in relation to treatment strategy (continuous and split course radiotherapy). To evaluate prognostic factors and importance of treatment strategy for local control, distant metastases, and survival by uni- and multivariate analyses. To develop a classification system (AADK, Aarhus, Denmark) for the recording of early and late radiation complications allowing and estimation of the importance of latency when reporting late radiotherapeutic morbidity and a rescoring of complication grade, and to compare results from AADK with those from the French-Italian glossary recording the maximal damage. To evaluate early and late radiotherapeutic morbidity and the importance of latency by comparing frequencies and actuarial estimates of late complications, to estimate the combined late organ morbidity and the probability of being alive, cured and without serious complications. (EG) (61 refs.)

  15. Regression analysis by example

    CERN Document Server

    Chatterjee, Samprit

    2012-01-01

    Praise for the Fourth Edition: ""This book is . . . an excellent source of examples for regression analysis. It has been and still is readily readable and understandable."" -Journal of the American Statistical Association Regression analysis is a conceptually simple method for investigating relationships among variables. Carrying out a successful application of regression analysis, however, requires a balance of theoretical results, empirical rules, and subjective judgment. Regression Analysis by Example, Fifth Edition has been expanded

  16. Quantile Regression Methods

    DEFF Research Database (Denmark)

    Fitzenberger, Bernd; Wilke, Ralf Andreas

    2015-01-01

    if the mean regression model does not. We provide a short informal introduction into the principle of quantile regression which includes an illustrative application from empirical labor market research. This is followed by briefly sketching the underlying statistical model for linear quantile regression based......Quantile regression is emerging as a popular statistical approach, which complements the estimation of conditional mean models. While the latter only focuses on one aspect of the conditional distribution of the dependent variable, the mean, quantile regression provides more detailed insights...... by modeling conditional quantiles. Quantile regression can therefore detect whether the partial effect of a regressor on the conditional quantiles is the same for all quantiles or differs across quantiles. Quantile regression can provide evidence for a statistical relationship between two variables even...

  17. Understanding logistic regression analysis

    OpenAIRE

    Sperandei, Sandro

    2014-01-01

    Logistic regression is used to obtain odds ratio in the presence of more than one explanatory variable. The procedure is quite similar to multiple linear regression, with the exception that the response variable is binomial. The result is the impact of each variable on the odds ratio of the observed event of interest. The main advantage is to avoid confounding effects by analyzing the association of all variables together. In this article, we explain the logistic regression procedure using ex...

  18. Introduction to regression graphics

    CERN Document Server

    Cook, R Dennis

    2009-01-01

    Covers the use of dynamic and interactive computer graphics in linear regression analysis, focusing on analytical graphics. Features new techniques like plot rotation. The authors have composed their own regression code, using Xlisp-Stat language called R-code, which is a nearly complete system for linear regression analysis and can be utilized as the main computer program in a linear regression course. The accompanying disks, for both Macintosh and Windows computers, contain the R-code and Xlisp-Stat. An Instructor's Manual presenting detailed solutions to all the problems in the book is ava

  19. Alternative Methods of Regression

    CERN Document Server

    Birkes, David

    2011-01-01

    Of related interest. Nonlinear Regression Analysis and its Applications Douglas M. Bates and Donald G. Watts ".an extraordinary presentation of concepts and methods concerning the use and analysis of nonlinear regression models.highly recommend[ed].for anyone needing to use and/or understand issues concerning the analysis of nonlinear regression models." --Technometrics This book provides a balance between theory and practice supported by extensive displays of instructive geometrical constructs. Numerous in-depth case studies illustrate the use of nonlinear regression analysis--with all data s

  20. Physical activity increases survival after heart valve surgery

    DEFF Research Database (Denmark)

    Lund, K.; Sibilitz, Kirstine Lærum; Kikkenborg Berg, Selina

    2016-01-01

    physical activity levels 6-12 months after heart valve surgery and (1) survival, (2) hospital readmission 18-24 months after surgery and (3) participation in exercise-based cardiac rehabilitation. METHODS: Prospective cohort study with registry data from The CopenHeart survey, The Danish National Patient......OBJECTIVES: Increased physical activity predicts survival and reduces risk of readmission in patients with coronary heart disease. However, few data show how physical activity is associated with survival and readmission after heart valve surgery. Objective were to assess the association between...... Register and The Danish Civil Registration System of 742 eligible patients. Physical activity was quantified with the International Physical Activity Questionnaire and analysed using Kaplan-Meier analysis and Cox regression and logistic regression methods. RESULTS: Patients with a moderate to high physical...

  1. Modelling survival

    DEFF Research Database (Denmark)

    Ashauer, Roman; Albert, Carlo; Augustine, Starrlight

    2016-01-01

    The General Unified Threshold model for Survival (GUTS) integrates previously published toxicokinetic-toxicodynamic models and estimates survival with explicitly defined assumptions. Importantly, GUTS accounts for time-variable exposure to the stressor. We performed three studies to test...

  2. Survival analysis

    International Nuclear Information System (INIS)

    Badwe, R.A.

    1999-01-01

    The primary endpoint in the majority of the studies has been either disease recurrence or death. This kind of analysis requires a special method since all patients in the study experience the endpoint. The standard method for estimating such survival distribution is Kaplan Meier method. The survival function is defined as the proportion of individuals who survive beyond certain time. Multi-variate comparison for survival has been carried out with Cox's proportional hazard model

  3. Equações de regressão para estimar valores energéticos do grão de trigo e seus subprodutos para frangos de corte, a partir de análises químicas Regression equations to evaluate the energy values of wheat grain and its by-products for broiler chickens from chemical analyses

    Directory of Open Access Journals (Sweden)

    F.M.O. Borges

    2003-12-01

    que significou pouca influência da metodologia sobre essa medida. A FDN não mostrou ser melhor preditor de EM do que a FB.One experiment was run with broiler chickens, to obtain prediction equations for metabolizable energy (ME based on feedstuffs chemical analyses, and determined ME of wheat grain and its by-products, using four different methodologies. Seven wheat grain by-products were used in five treatments: wheat grain, wheat germ, white wheat flour, dark wheat flour, wheat bran for human use, wheat bran for animal use and rough wheat bran. Based on chemical analyses of crude fiber (CF, ether extract (EE, crude protein (CP, ash (AS and starch (ST of the feeds and the determined values of apparent energy (MEA, true energy (MEV, apparent corrected energy (MEAn and true energy corrected by nitrogen balance (MEVn in five treatments, prediction equations were obtained using the stepwise procedure. CF showed the best relationship with metabolizable energy values, however, this variable alone was not enough for a good estimate of the energy values (R² below 0.80. When EE and CP were included in the equations, R² increased to 0.90 or higher in most estimates. When the equations were calculated with all treatments, the equation for MEA were less precise and R² decreased. When ME data of the traditional or force-feeding methods were used separately, the precision of the equations increases (R² higher than 0.85. For MEV and MEVn values, the best multiple linear equations included CF, EE and CP (R²>0.90, independently of using all experimental data or separating by methodology. The estimates of MEVn values showed high precision and the linear coefficients (a of the equations were similar for all treatments or methodologies. Therefore, it explains the small influence of the different methodologies on this parameter. NDF was not a better predictor of ME than CF.

  4. Older cancer patients in cancer clinical trials are underrepresented. Systematic literature review of almost 5000 meta- and pooled analyses of phase III randomized trials of survival from breast, prostate and lung cancer.

    Science.gov (United States)

    Dunn, Cita; Wilson, Andrew; Sitas, Freddy

    2017-12-01

    Older people represent increasing proportions of the population with cancer. To understand the representivity of cancer treatments in older people, we performed a systematic literature review using PRISMA guidelines of the age distribution of clinical trial participants for three leading cancer types, namely breast, prostate, and lung. We used PubMed to identify articles detailing meta or pooled-analyses of phase III, randomised controlled trials (RCTs) of survival for breast, prostate and lung cancer, published ≤5 years from 2016. We compared the age distribution of participants to that of these cancers for "More developed regions". 4993 potential papers were identified, but only three papers on breast cancer, three on lung cancer, and none on prostate cancer presented the age distribution of their participants. Except for one paper of breast cancer, participants ≥70 years in all other papers were underrepresented. We recommend the age distribution of patients be clearly reported in all clinical trials, as per guidelines. Clinical trials ought to be more representative of the populations most affected by the disease for which treatments are being tested. This should lead to better knowledge of effectiveness of treatments and better translation of trial results to optimal care of older cancer patients. Copyright © 2017 Elsevier Ltd. All rights reserved.

  5. A Simulation Investigation of Principal Component Regression.

    Science.gov (United States)

    Allen, David E.

    Regression analysis is one of the more common analytic tools used by researchers. However, multicollinearity between the predictor variables can cause problems in using the results of regression analyses. Problems associated with multicollinearity include entanglement of relative influences of variables due to reduced precision of estimation,…

  6. Boosted beta regression.

    Directory of Open Access Journals (Sweden)

    Matthias Schmid

    Full Text Available Regression analysis with a bounded outcome is a common problem in applied statistics. Typical examples include regression models for percentage outcomes and the analysis of ratings that are measured on a bounded scale. In this paper, we consider beta regression, which is a generalization of logit models to situations where the response is continuous on the interval (0,1. Consequently, beta regression is a convenient tool for analyzing percentage responses. The classical approach to fit a beta regression model is to use maximum likelihood estimation with subsequent AIC-based variable selection. As an alternative to this established - yet unstable - approach, we propose a new estimation technique called boosted beta regression. With boosted beta regression estimation and variable selection can be carried out simultaneously in a highly efficient way. Additionally, both the mean and the variance of a percentage response can be modeled using flexible nonlinear covariate effects. As a consequence, the new method accounts for common problems such as overdispersion and non-binomial variance structures.

  7. Applied survival analysis using R

    CERN Document Server

    Moore, Dirk F

    2016-01-01

    Applied Survival Analysis Using R covers the main principles of survival analysis, gives examples of how it is applied, and teaches how to put those principles to use to analyze data using R as a vehicle. Survival data, where the primary outcome is time to a specific event, arise in many areas of biomedical research, including clinical trials, epidemiological studies, and studies of animals. Many survival methods are extensions of techniques used in linear regression and categorical data, while other aspects of this field are unique to survival data. This text employs numerous actual examples to illustrate survival curve estimation, comparison of survivals of different groups, proper accounting for censoring and truncation, model variable selection, and residual analysis. Because explaining survival analysis requires more advanced mathematics than many other statistical topics, this book is organized with basic concepts and most frequently used procedures covered in earlier chapters, with more advanced topics...

  8. Understanding logistic regression analysis.

    Science.gov (United States)

    Sperandei, Sandro

    2014-01-01

    Logistic regression is used to obtain odds ratio in the presence of more than one explanatory variable. The procedure is quite similar to multiple linear regression, with the exception that the response variable is binomial. The result is the impact of each variable on the odds ratio of the observed event of interest. The main advantage is to avoid confounding effects by analyzing the association of all variables together. In this article, we explain the logistic regression procedure using examples to make it as simple as possible. After definition of the technique, the basic interpretation of the results is highlighted and then some special issues are discussed.

  9. Applied linear regression

    CERN Document Server

    Weisberg, Sanford

    2013-01-01

    Praise for the Third Edition ""...this is an excellent book which could easily be used as a course text...""-International Statistical Institute The Fourth Edition of Applied Linear Regression provides a thorough update of the basic theory and methodology of linear regression modeling. Demonstrating the practical applications of linear regression analysis techniques, the Fourth Edition uses interesting, real-world exercises and examples. Stressing central concepts such as model building, understanding parameters, assessing fit and reliability, and drawing conclusions, the new edition illus

  10. Applied logistic regression

    CERN Document Server

    Hosmer, David W; Sturdivant, Rodney X

    2013-01-01

     A new edition of the definitive guide to logistic regression modeling for health science and other applications This thoroughly expanded Third Edition provides an easily accessible introduction to the logistic regression (LR) model and highlights the power of this model by examining the relationship between a dichotomous outcome and a set of covariables. Applied Logistic Regression, Third Edition emphasizes applications in the health sciences and handpicks topics that best suit the use of modern statistical software. The book provides readers with state-of-

  11. Multilingual speaker age recognition: regression analyses on the Lwazi corpus

    CSIR Research Space (South Africa)

    Feld, M

    2009-12-01

    Full Text Available Multilinguality represents an area of significant opportunities for automatic speech-processing systems: whereas multilingual societies are commonplace, the majority of speechprocessing systems are developed with a single language in mind. As a step...

  12. Understanding poisson regression.

    Science.gov (United States)

    Hayat, Matthew J; Higgins, Melinda

    2014-04-01

    Nurse investigators often collect study data in the form of counts. Traditional methods of data analysis have historically approached analysis of count data either as if the count data were continuous and normally distributed or with dichotomization of the counts into the categories of occurred or did not occur. These outdated methods for analyzing count data have been replaced with more appropriate statistical methods that make use of the Poisson probability distribution, which is useful for analyzing count data. The purpose of this article is to provide an overview of the Poisson distribution and its use in Poisson regression. Assumption violations for the standard Poisson regression model are addressed with alternative approaches, including addition of an overdispersion parameter or negative binomial regression. An illustrative example is presented with an application from the ENSPIRE study, and regression modeling of comorbidity data is included for illustrative purposes. Copyright 2014, SLACK Incorporated.

  13. Vector regression introduced

    Directory of Open Access Journals (Sweden)

    Mok Tik

    2014-06-01

    Full Text Available This study formulates regression of vector data that will enable statistical analysis of various geodetic phenomena such as, polar motion, ocean currents, typhoon/hurricane tracking, crustal deformations, and precursory earthquake signals. The observed vector variable of an event (dependent vector variable is expressed as a function of a number of hypothesized phenomena realized also as vector variables (independent vector variables and/or scalar variables that are likely to impact the dependent vector variable. The proposed representation has the unique property of solving the coefficients of independent vector variables (explanatory variables also as vectors, hence it supersedes multivariate multiple regression models, in which the unknown coefficients are scalar quantities. For the solution, complex numbers are used to rep- resent vector information, and the method of least squares is deployed to estimate the vector model parameters after transforming the complex vector regression model into a real vector regression model through isomorphism. Various operational statistics for testing the predictive significance of the estimated vector parameter coefficients are also derived. A simple numerical example demonstrates the use of the proposed vector regression analysis in modeling typhoon paths.

  14. Profilin-1 overexpression in MDA-MB-231 breast cancer cells is associated with alterations in proteomics biomarkers of cell proliferation, survival, and motility as revealed by global proteomics analyses.

    Science.gov (United States)

    Coumans, Joëlle V F; Gau, David; Poljak, Anne; Wasinger, Valerie; Roy, Partha; Moens, Pierre D J

    2014-12-01

    Despite early screening programs and new therapeutic strategies, metastatic breast cancer is still the leading cause of cancer death in women in industrialized countries and regions. There is a need for novel biomarkers of susceptibility, progression, and therapeutic response. Global analyses or systems science approaches with omics technologies offer concrete ways forward in biomarker discovery for breast cancer. Previous studies have shown that expression of profilin-1 (PFN1), a ubiquitously expressed actin-binding protein, is downregulated in invasive and metastatic breast cancer. It has also been reported that PFN1 overexpression can suppress tumorigenic ability and motility/invasiveness of breast cancer cells. To obtain insights into the underlying molecular mechanisms of how elevating PFN1 level induces these phenotypic changes in breast cancer cells, we investigated the alteration in global protein expression profiles of breast cancer cells upon stable overexpression of PFN1 by a combination of three different proteome analysis methods (2-DE, iTRAQ, label-free). Using MDA-MB-231 as a model breast cancer cell line, we provide evidence that PFN1 overexpression is associated with alterations in the expression of proteins that have been functionally linked to cell proliferation (FKPB1A, HDGF, MIF, PRDX1, TXNRD1, LGALS1, STMN1, LASP1, S100A11, S100A6), survival (HSPE1, HSPB1, HSPD1, HSPA5 and PPIA, YWHAZ, CFL1, NME1) and motility (CFL1, CORO1B, PFN2, PLS3, FLNA, FLNB, NME2, ARHGDIB). In view of the pleotropic effects of PFN1 overexpression in breast cancer cells as suggested by these new findings, we propose that PFN1-induced phenotypic changes in cancer cells involve multiple mechanisms. Our data reported here might also offer innovative strategies for identification and validation of novel therapeutic targets and companion diagnostics for persons with, or susceptibility to, breast cancer.

  15. Multicollinearity and Regression Analysis

    Science.gov (United States)

    Daoud, Jamal I.

    2017-12-01

    In regression analysis it is obvious to have a correlation between the response and predictor(s), but having correlation among predictors is something undesired. The number of predictors included in the regression model depends on many factors among which, historical data, experience, etc. At the end selection of most important predictors is something objective due to the researcher. Multicollinearity is a phenomena when two or more predictors are correlated, if this happens, the standard error of the coefficients will increase [8]. Increased standard errors means that the coefficients for some or all independent variables may be found to be significantly different from In other words, by overinflating the standard errors, multicollinearity makes some variables statistically insignificant when they should be significant. In this paper we focus on the multicollinearity, reasons and consequences on the reliability of the regression model.

  16. Minimax Regression Quantiles

    DEFF Research Database (Denmark)

    Bache, Stefan Holst

    A new and alternative quantile regression estimator is developed and it is shown that the estimator is root n-consistent and asymptotically normal. The estimator is based on a minimax ‘deviance function’ and has asymptotically equivalent properties to the usual quantile regression estimator. It is......, however, a different and therefore new estimator. It allows for both linear- and nonlinear model specifications. A simple algorithm for computing the estimates is proposed. It seems to work quite well in practice but whether it has theoretical justification is still an open question....

  17. riskRegression

    DEFF Research Database (Denmark)

    Ozenne, Brice; Sørensen, Anne Lyngholm; Scheike, Thomas

    2017-01-01

    In the presence of competing risks a prediction of the time-dynamic absolute risk of an event can be based on cause-specific Cox regression models for the event and the competing risks (Benichou and Gail, 1990). We present computationally fast and memory optimized C++ functions with an R interface...... for predicting the covariate specific absolute risks, their confidence intervals, and their confidence bands based on right censored time to event data. We provide explicit formulas for our implementation of the estimator of the (stratified) baseline hazard function in the presence of tied event times. As a by...... functionals. The software presented here is implemented in the riskRegression package....

  18. Prediction, Regression and Critical Realism

    DEFF Research Database (Denmark)

    Næss, Petter

    2004-01-01

    This paper considers the possibility of prediction in land use planning, and the use of statistical research methods in analyses of relationships between urban form and travel behaviour. Influential writers within the tradition of critical realism reject the possibility of predicting social...... phenomena. This position is fundamentally problematic to public planning. Without at least some ability to predict the likely consequences of different proposals, the justification for public sector intervention into market mechanisms will be frail. Statistical methods like regression analyses are commonly...... seen as necessary in order to identify aggregate level effects of policy measures, but are questioned by many advocates of critical realist ontology. Using research into the relationship between urban structure and travel as an example, the paper discusses relevant research methods and the kinds...

  19. Regression modeling strategies with applications to linear models, logistic and ordinal regression, and survival analysis

    CERN Document Server

    Harrell , Jr , Frank E

    2015-01-01

    This highly anticipated second edition features new chapters and sections, 225 new references, and comprehensive R software. In keeping with the previous edition, this book is about the art and science of data analysis and predictive modeling, which entails choosing and using multiple tools. Instead of presenting isolated techniques, this text emphasizes problem solving strategies that address the many issues arising when developing multivariable models using real data and not standard textbook examples. It includes imputation methods for dealing with missing data effectively, methods for fitting nonlinear relationships and for making the estimation of transformations a formal part of the modeling process, methods for dealing with "too many variables to analyze and not enough observations," and powerful model validation techniques based on the bootstrap.  The reader will gain a keen understanding of predictive accuracy, and the harm of categorizing continuous predictors or outcomes.  This text realistically...

  20. Multiple linear regression analysis

    Science.gov (United States)

    Edwards, T. R.

    1980-01-01

    Program rapidly selects best-suited set of coefficients. User supplies only vectors of independent and dependent data and specifies confidence level required. Program uses stepwise statistical procedure for relating minimal set of variables to set of observations; final regression contains only most statistically significant coefficients. Program is written in FORTRAN IV for batch execution and has been implemented on NOVA 1200.

  1. Bayesian logistic regression analysis

    NARCIS (Netherlands)

    Van Erp, H.R.N.; Van Gelder, P.H.A.J.M.

    2012-01-01

    In this paper we present a Bayesian logistic regression analysis. It is found that if one wishes to derive the posterior distribution of the probability of some event, then, together with the traditional Bayes Theorem and the integrating out of nuissance parameters, the Jacobian transformation is an

  2. Linear Regression Analysis

    CERN Document Server

    Seber, George A F

    2012-01-01

    Concise, mathematically clear, and comprehensive treatment of the subject.* Expanded coverage of diagnostics and methods of model fitting.* Requires no specialized knowledge beyond a good grasp of matrix algebra and some acquaintance with straight-line regression and simple analysis of variance models.* More than 200 problems throughout the book plus outline solutions for the exercises.* This revision has been extensively class-tested.

  3. Nonlinear Regression with R

    CERN Document Server

    Ritz, Christian; Parmigiani, Giovanni

    2009-01-01

    R is a rapidly evolving lingua franca of graphical display and statistical analysis of experiments from the applied sciences. This book provides a coherent treatment of nonlinear regression with R by means of examples from a diversity of applied sciences such as biology, chemistry, engineering, medicine and toxicology.

  4. Bayesian ARTMAP for regression.

    Science.gov (United States)

    Sasu, L M; Andonie, R

    2013-10-01

    Bayesian ARTMAP (BA) is a recently introduced neural architecture which uses a combination of Fuzzy ARTMAP competitive learning and Bayesian learning. Training is generally performed online, in a single-epoch. During training, BA creates input data clusters as Gaussian categories, and also infers the conditional probabilities between input patterns and categories, and between categories and classes. During prediction, BA uses Bayesian posterior probability estimation. So far, BA was used only for classification. The goal of this paper is to analyze the efficiency of BA for regression problems. Our contributions are: (i) we generalize the BA algorithm using the clustering functionality of both ART modules, and name it BA for Regression (BAR); (ii) we prove that BAR is a universal approximator with the best approximation property. In other words, BAR approximates arbitrarily well any continuous function (universal approximation) and, for every given continuous function, there is one in the set of BAR approximators situated at minimum distance (best approximation); (iii) we experimentally compare the online trained BAR with several neural models, on the following standard regression benchmarks: CPU Computer Hardware, Boston Housing, Wisconsin Breast Cancer, and Communities and Crime. Our results show that BAR is an appropriate tool for regression tasks, both for theoretical and practical reasons. Copyright © 2013 Elsevier Ltd. All rights reserved.

  5. Bounded Gaussian process regression

    DEFF Research Database (Denmark)

    Jensen, Bjørn Sand; Nielsen, Jens Brehm; Larsen, Jan

    2013-01-01

    We extend the Gaussian process (GP) framework for bounded regression by introducing two bounded likelihood functions that model the noise on the dependent variable explicitly. This is fundamentally different from the implicit noise assumption in the previously suggested warped GP framework. We...... with the proposed explicit noise-model extension....

  6. and Multinomial Logistic Regression

    African Journals Online (AJOL)

    This work presented the results of an experimental comparison of two models: Multinomial Logistic Regression (MLR) and Artificial Neural Network (ANN) for classifying students based on their academic performance. The predictive accuracy for each model was measured by their average Classification Correct Rate (CCR).

  7. Mechanisms of neuroblastoma regression

    Science.gov (United States)

    Brodeur, Garrett M.; Bagatell, Rochelle

    2014-01-01

    Recent genomic and biological studies of neuroblastoma have shed light on the dramatic heterogeneity in the clinical behaviour of this disease, which spans from spontaneous regression or differentiation in some patients, to relentless disease progression in others, despite intensive multimodality therapy. This evidence also suggests several possible mechanisms to explain the phenomena of spontaneous regression in neuroblastomas, including neurotrophin deprivation, humoral or cellular immunity, loss of telomerase activity and alterations in epigenetic regulation. A better understanding of the mechanisms of spontaneous regression might help to identify optimal therapeutic approaches for patients with these tumours. Currently, the most druggable mechanism is the delayed activation of developmentally programmed cell death regulated by the tropomyosin receptor kinase A pathway. Indeed, targeted therapy aimed at inhibiting neurotrophin receptors might be used in lieu of conventional chemotherapy or radiation in infants with biologically favourable tumours that require treatment. Alternative approaches consist of breaking immune tolerance to tumour antigens or activating neurotrophin receptor pathways to induce neuronal differentiation. These approaches are likely to be most effective against biologically favourable tumours, but they might also provide insights into treatment of biologically unfavourable tumours. We describe the different mechanisms of spontaneous neuroblastoma regression and the consequent therapeutic approaches. PMID:25331179

  8. Ridge Regression Signal Processing

    Science.gov (United States)

    Kuhl, Mark R.

    1990-01-01

    The introduction of the Global Positioning System (GPS) into the National Airspace System (NAS) necessitates the development of Receiver Autonomous Integrity Monitoring (RAIM) techniques. In order to guarantee a certain level of integrity, a thorough understanding of modern estimation techniques applied to navigational problems is required. The extended Kalman filter (EKF) is derived and analyzed under poor geometry conditions. It was found that the performance of the EKF is difficult to predict, since the EKF is designed for a Gaussian environment. A novel approach is implemented which incorporates ridge regression to explain the behavior of an EKF in the presence of dynamics under poor geometry conditions. The basic principles of ridge regression theory are presented, followed by the derivation of a linearized recursive ridge estimator. Computer simulations are performed to confirm the underlying theory and to provide a comparative analysis of the EKF and the recursive ridge estimator.

  9. Subset selection in regression

    CERN Document Server

    Miller, Alan

    2002-01-01

    Originally published in 1990, the first edition of Subset Selection in Regression filled a significant gap in the literature, and its critical and popular success has continued for more than a decade. Thoroughly revised to reflect progress in theory, methods, and computing power, the second edition promises to continue that tradition. The author has thoroughly updated each chapter, incorporated new material on recent developments, and included more examples and references. New in the Second Edition:A separate chapter on Bayesian methodsComplete revision of the chapter on estimationA major example from the field of near infrared spectroscopyMore emphasis on cross-validationGreater focus on bootstrappingStochastic algorithms for finding good subsets from large numbers of predictors when an exhaustive search is not feasible Software available on the Internet for implementing many of the algorithms presentedMore examplesSubset Selection in Regression, Second Edition remains dedicated to the techniques for fitting...

  10. Regression in organizational leadership.

    Science.gov (United States)

    Kernberg, O F

    1979-02-01

    The choice of good leaders is a major task for all organizations. Inforamtion regarding the prospective administrator's personality should complement questions regarding his previous experience, his general conceptual skills, his technical knowledge, and the specific skills in the area for which he is being selected. The growing psychoanalytic knowledge about the crucial importance of internal, in contrast to external, object relations, and about the mutual relationships of regression in individuals and in groups, constitutes an important practical tool for the selection of leaders.

  11. Classification and regression trees

    CERN Document Server

    Breiman, Leo; Olshen, Richard A; Stone, Charles J

    1984-01-01

    The methodology used to construct tree structured rules is the focus of this monograph. Unlike many other statistical procedures, which moved from pencil and paper to calculators, this text's use of trees was unthinkable before computers. Both the practical and theoretical sides have been developed in the authors' study of tree methods. Classification and Regression Trees reflects these two sides, covering the use of trees as a data analysis method, and in a more mathematical framework, proving some of their fundamental properties.

  12. Comparison of Classical Linear Regression and Orthogonal Regression According to the Sum of Squares Perpendicular Distances

    OpenAIRE

    KELEŞ, Taliha; ALTUN, Murat

    2016-01-01

    Regression analysis is a statistical technique for investigating and modeling the relationship between variables. The purpose of this study was the trivial presentation of the equation for orthogonal regression (OR) and the comparison of classical linear regression (CLR) and OR techniques with respect to the sum of squared perpendicular distances. For that purpose, the analyses were shown by an example. It was found that the sum of squared perpendicular distances of OR is smaller. Thus, it wa...

  13. Logistic regression models

    CERN Document Server

    Hilbe, Joseph M

    2009-01-01

    This book really does cover everything you ever wanted to know about logistic regression … with updates available on the author's website. Hilbe, a former national athletics champion, philosopher, and expert in astronomy, is a master at explaining statistical concepts and methods. Readers familiar with his other expository work will know what to expect-great clarity.The book provides considerable detail about all facets of logistic regression. No step of an argument is omitted so that the book will meet the needs of the reader who likes to see everything spelt out, while a person familiar with some of the topics has the option to skip "obvious" sections. The material has been thoroughly road-tested through classroom and web-based teaching. … The focus is on helping the reader to learn and understand logistic regression. The audience is not just students meeting the topic for the first time, but also experienced users. I believe the book really does meet the author's goal … .-Annette J. Dobson, Biometric...

  14. Testing homogeneity in Weibull-regression models.

    Science.gov (United States)

    Bolfarine, Heleno; Valença, Dione M

    2005-10-01

    In survival studies with families or geographical units it may be of interest testing whether such groups are homogeneous for given explanatory variables. In this paper we consider score type tests for group homogeneity based on a mixing model in which the group effect is modelled as a random variable. As opposed to hazard-based frailty models, this model presents survival times that conditioned on the random effect, has an accelerated failure time representation. The test statistics requires only estimation of the conventional regression model without the random effect and does not require specifying the distribution of the random effect. The tests are derived for a Weibull regression model and in the uncensored situation, a closed form is obtained for the test statistic. A simulation study is used for comparing the power of the tests. The proposed tests are applied to real data sets with censored data.

  15. Steganalysis using logistic regression

    Science.gov (United States)

    Lubenko, Ivans; Ker, Andrew D.

    2011-02-01

    We advocate Logistic Regression (LR) as an alternative to the Support Vector Machine (SVM) classifiers commonly used in steganalysis. LR offers more information than traditional SVM methods - it estimates class probabilities as well as providing a simple classification - and can be adapted more easily and efficiently for multiclass problems. Like SVM, LR can be kernelised for nonlinear classification, and it shows comparable classification accuracy to SVM methods. This work is a case study, comparing accuracy and speed of SVM and LR classifiers in detection of LSB Matching and other related spatial-domain image steganography, through the state-of-art 686-dimensional SPAM feature set, in three image sets.

  16. SEPARATION PHENOMENA LOGISTIC REGRESSION

    Directory of Open Access Journals (Sweden)

    Ikaro Daniel de Carvalho Barreto

    2014-03-01

    Full Text Available This paper proposes an application of concepts about the maximum likelihood estimation of the binomial logistic regression model to the separation phenomena. It generates bias in the estimation and provides different interpretations of the estimates on the different statistical tests (Wald, Likelihood Ratio and Score and provides different estimates on the different iterative methods (Newton-Raphson and Fisher Score. It also presents an example that demonstrates the direct implications for the validation of the model and validation of variables, the implications for estimates of odds ratios and confidence intervals, generated from the Wald statistics. Furthermore, we present, briefly, the Firth correction to circumvent the phenomena of separation.

  17. Adaptive metric kernel regression

    DEFF Research Database (Denmark)

    Goutte, Cyril; Larsen, Jan

    2000-01-01

    Kernel smoothing is a widely used non-parametric pattern recognition technique. By nature, it suffers from the curse of dimensionality and is usually difficult to apply to high input dimensions. In this contribution, we propose an algorithm that adapts the input metric used in multivariate...... regression by minimising a cross-validation estimate of the generalisation error. This allows to automatically adjust the importance of different dimensions. The improvement in terms of modelling performance is illustrated on a variable selection task where the adaptive metric kernel clearly outperforms...

  18. Adaptive Metric Kernel Regression

    DEFF Research Database (Denmark)

    Goutte, Cyril; Larsen, Jan

    1998-01-01

    Kernel smoothing is a widely used nonparametric pattern recognition technique. By nature, it suffers from the curse of dimensionality and is usually difficult to apply to high input dimensions. In this paper, we propose an algorithm that adapts the input metric used in multivariate regression...... by minimising a cross-validation estimate of the generalisation error. This allows one to automatically adjust the importance of different dimensions. The improvement in terms of modelling performance is illustrated on a variable selection task where the adaptive metric kernel clearly outperforms the standard...

  19. Effect of bystander CPR initiation prior to the emergency call on ROSC and 30day survival

    DEFF Research Database (Denmark)

    Viereck, Søren; Palsgaard Møller, Thea; Kjær Ersbøll, Annette

    2017-01-01

    BACKGROUND: This study aimed at evaluating if time for initiation of bystander cardiopulmonary resuscitation (CPR) - prior to the emergency call (CPRprior) versus during the emergency call following dispatcher-assisted CPR (CPRduring) - was associated with return of spontaneous circulation (ROSC...... and corresponding emergency calls were evaluated. Multivariable logistic regression analyses were applied to evaluate the association between time for initiation of bystander CPR, ROSC, and 30-day survival. Univariable logistic regression analyses were applied to identify predictors of CPRprior. RESULTS: The study...... included 548 emergency calls for OHCA patients receiving bystander CPR, 34.9% (n=191) in the CPRpriorgroup and 65.1% (n=357) in the CPRduringgroup. Multivariable analyses showed no difference in ROSC (OR=0.88, 95% CI: 0.56-1.38) or 30-day survival (OR=1.14, 95% CI: 0.68-1.92) between CPRpriorand CPRduring...

  20. Surrogate endpoints for overall survival in chemotherapy and radiotherapy trials in operable and locally advanced lung cancer: a re-analysis of meta-analyses of individual patients' data

    NARCIS (Netherlands)

    Mauguen, Audrey; Pignon, Jean-Pierre; Burdett, Sarah; Domerg, Caroline; Fisher, David; Paulus, Rebecca; Mandrekar, Samithra J.; Belani, Chandra P.; Shepherd, Frances A.; Eisen, Tim; Pang, Herbert; Collette, Laurence; Sause, William T.; Dahlberg, Suzanne E.; Crawford, Jeffrey; O'Brien, Mary; Schild, Steven E.; Parmar, Mahesh; Tierney, Jayne F.; Le Pechoux, Cécile; Michiels, Stefan; Burdett, S.; Fisher, D.; Le Péchoux, C.; Mauguen, A.; Michiels, S.; Pignon, J. P.; Tierney, J. F.; Belani, C. P.; Collette, L.; Dahlberg, S.; Eisen, T.; Mandrekar, S.; O'Brien, M.; Parmar, M.; Pang, H.; Paulus, R.; Crawford, J.; Sause, W.; Schild, S. E.; Shepherd, F.; Arriagada, R.; Atagi, S.; Auperin, A.; Ball, D.; Baumann, M.; Behrendt, K.; Belderbos, J.; Koning, C. C. E.; Uitterhoeve, A.

    2013-01-01

    The gold standard endpoint in clinical trials of chemotherapy and radiotherapy for lung cancer is overall survival. Although reliable and simple to measure, this endpoint takes years to observe. Surrogate endpoints that would enable earlier assessments of treatment effects would be useful. We

  1. Survival Patterns Among Newcomers To Franchising

    OpenAIRE

    Timothy Bates

    1997-01-01

    This study analyzes survival patterns among franchisee firms and establishments that began operations in 1986 and 1987. Differing methodologies and data bases are utilized to demonstrate that 1) franchises have higher survival rates than independents, and 2) franchises have lower survival rates than independent business formations. Analyses of corporate establishment data generate high franchisee survival rates relative to independents, while analyses of young firm data generate the opposite ...

  2. Aid and growth regressions

    DEFF Research Database (Denmark)

    Hansen, Henrik; Tarp, Finn

    2001-01-01

    This paper examines the relationship between foreign aid and growth in real GDP per capita as it emerges from simple augmentations of popular cross country growth specifications. It is shown that aid in all likelihood increases the growth rate, and this result is not conditional on ‘good’ policy....... investment. We conclude by stressing the need for more theoretical work before this kind of cross-country regressions are used for policy purposes.......This paper examines the relationship between foreign aid and growth in real GDP per capita as it emerges from simple augmentations of popular cross country growth specifications. It is shown that aid in all likelihood increases the growth rate, and this result is not conditional on ‘good’ policy...

  3. Modified Regression Correlation Coefficient for Poisson Regression Model

    Science.gov (United States)

    Kaengthong, Nattacha; Domthong, Uthumporn

    2017-09-01

    This study gives attention to indicators in predictive power of the Generalized Linear Model (GLM) which are widely used; however, often having some restrictions. We are interested in regression correlation coefficient for a Poisson regression model. This is a measure of predictive power, and defined by the relationship between the dependent variable (Y) and the expected value of the dependent variable given the independent variables [E(Y|X)] for the Poisson regression model. The dependent variable is distributed as Poisson. The purpose of this research was modifying regression correlation coefficient for Poisson regression model. We also compare the proposed modified regression correlation coefficient with the traditional regression correlation coefficient in the case of two or more independent variables, and having multicollinearity in independent variables. The result shows that the proposed regression correlation coefficient is better than the traditional regression correlation coefficient based on Bias and the Root Mean Square Error (RMSE).

  4. Survival Analysis

    CERN Document Server

    Miller, Rupert G

    2011-01-01

    A concise summary of the statistical methods used in the analysis of survival data with censoring. Emphasizes recently developed nonparametric techniques. Outlines methods in detail and illustrates them with actual data. Discusses the theory behind each method. Includes numerous worked problems and numerical exercises.

  5. Benefits of marriage on relative and conditional relative cancer survival differ between males and females in the USA.

    Science.gov (United States)

    Merrill, Ray M; Johnson, Erin

    2017-10-01

    The purpose of the paper is to assess the influence of marital status on conditional relative survival of cancer according to sex. Analyses involved 779,978 males and 1,032,868 females diagnosed with 1 of 13 cancer types between 2000 and 2008, and followed through 2013. Data are from the Surveillance, Epidemiology, and End Results (SEER) Program. Regression models were adjusted for age, sex, race, and tumor stage. Five-year relative survival conditional on years already survived is higher among married patients with less lethal cancers (oral cavity and pharynx, colon and rectum, breast, urinary bladder, kidney and renal pelvis, melanoma of the skin, thyroid, lymphoma). For more lethal cancers, married patients have similar (liver, lung and bronchus, pancreas, leukemia) or poorer (brain and other nervous system) cancer survival. Separated/divorced or widowed patients have the lowest conditional relative survival rates. For most cancers, 5-year cancer relative survival rates conditional on time already survived through 5 years approach 70 to 90% of that for the general population. The beneficial effect of marriage on survival decreases with years already survived. Superior conditional relative survival rates in females decrease with time already survived and are less pronounced in married patients. Five-year relative survival rates improve with time already survived. The benefits of marriage on conditional relative survival are greater for less lethal cancers. Greater 5-year conditional relative survival rates in females narrow with time already survived and are less pronounced in married patients. Conditional relative survival rates of cancer can lead to more informed decisions and understanding regarding treatment and prognosis.

  6. Measurement Error in Education and Growth Regressions

    NARCIS (Netherlands)

    Portela, M.; Teulings, C.N.; Alessie, R.

    The perpetual inventory method used for the construction of education data per country leads to systematic measurement error. This paper analyses the effect of this measurement error on GDP regressions. There is a systematic difference in the education level between census data and observations

  7. Measurement error in education and growth regressions

    NARCIS (Netherlands)

    Portela, Miguel; Teulings, Coen; Alessie, R.

    2004-01-01

    The perpetual inventory method used for the construction of education data per country leads to systematic measurement error. This paper analyses the effect of this measurement error on GDP regressions. There is a systematic difference in the education level between census data and observations

  8. Panel data specifications in nonparametric kernel regression

    DEFF Research Database (Denmark)

    Czekaj, Tomasz Gerard; Henningsen, Arne

    parametric panel data estimators to analyse the production technology of Polish crop farms. The results of our nonparametric kernel regressions generally differ from the estimates of the parametric models but they only slightly depend on the choice of the kernel functions. Based on economic reasoning, we...

  9. Canonical variate regression.

    Science.gov (United States)

    Luo, Chongliang; Liu, Jin; Dey, Dipak K; Chen, Kun

    2016-07-01

    In many fields, multi-view datasets, measuring multiple distinct but interrelated sets of characteristics on the same set of subjects, together with data on certain outcomes or phenotypes, are routinely collected. The objective in such a problem is often two-fold: both to explore the association structures of multiple sets of measurements and to develop a parsimonious model for predicting the future outcomes. We study a unified canonical variate regression framework to tackle the two problems simultaneously. The proposed criterion integrates multiple canonical correlation analysis with predictive modeling, balancing between the association strength of the canonical variates and their joint predictive power on the outcomes. Moreover, the proposed criterion seeks multiple sets of canonical variates simultaneously to enable the examination of their joint effects on the outcomes, and is able to handle multivariate and non-Gaussian outcomes. An efficient algorithm based on variable splitting and Lagrangian multipliers is proposed. Simulation studies show the superior performance of the proposed approach. We demonstrate the effectiveness of the proposed approach in an [Formula: see text] intercross mice study and an alcohol dependence study. © The Author 2016. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

  10. Survival rates and predictors of survival among colorectal cancer patients in a Malaysian tertiary hospital.

    Science.gov (United States)

    Magaji, Bello Arkilla; Moy, Foong Ming; Roslani, April Camilla; Law, Chee Wei

    2017-05-18

    Colorectal cancer is the third most commonly diagnosed malignancy and the fourth leading cause of cancer-related death globally. It is the second most common cancer among both males and females in Malaysia. The economic burden of colorectal cancer is likely to increase over time owing to its current trend and aging population. Cancer survival analysis is an essential indicator for early detection and improvement in cancer treatment. However, there was a scarcity of studies concerning survival of colorectal cancer patients as well as its predictors. Therefore, we aimed to determine the 1-, 3- and 5-year survival rates, compare survival rates among ethnic groups and determine the predictors of survival among colorectal cancer patients. This was an ambidirectional cohort study conducted at the University Malaya Medical Centre (UMMC) in Kuala Lumpur, Malaysia. All Malaysian citizens or permanent residents with histologically confirmed diagnosis of colorectal cancer seen at UMMC from 1 January 2001 to 31 December 2010 were included in the study. Demographic and clinical characteristics were extracted from the medical records. Patients were followed-up until death or censored at the end of the study (31st December 2010). Censored patients' vital status (whether alive or dead) were cross checked with the National Registration Department. Survival analyses at 1-, 3- and 5-year intervals were performed using the Kaplan-Meier method. Log-rank test was used to compare the survival rates, while Cox proportional hazard regression analysis was carried out to determine the predictors of 5-year colorectal cancer survival. Among 1212 patients, the median survival for colorectal, colon and rectal cancers were 42.0, 42.0 and 41.0 months respectively; while the 1-, 3-, and 5-year relative survival rates ranged from 73.8 to 76.0%, 52.1 to 53.7% and 40.4 to 45.4% respectively. The Chinese patients had the lowest 5-year survival compared to Malay and Indian patients. Based on the 814

  11. Association of tRNA methyltransferase NSUN2/IGF-II molecular signature with ovarian cancer survival.

    Science.gov (United States)

    Yang, Jia-Cheng; Risch, Eric; Zhang, Meiqin; Huang, Chan; Huang, Huatian; Lu, Lingeng

    2017-09-01

    To investigate the association between NSUN2/IGF-II signature and ovarian cancer survival. Using a publicly accessible dataset of RNA sequencing and clinical follow-up data, we performed Classification and Regression Tree and survival analyses. Patients with NSUN2 high IGF-II low had significantly superior overall and disease progression-free survival, followed by NSUN2 low IGF-II low , NSUN2 high IGF-II high and NSUN2 low IGF-II high (p IGF-II signature with the risks of death and relapse remained significant in multivariate Cox regression models. Random-effects meta-analyses show the upregulated NSUN2 and IGF-II expression in ovarian cancer versus normal tissues. The NSUN2/IGF-II signature associates with heterogeneous outcome and may have clinical implications in managing ovarian cancer.

  12. Polynomial regression analysis and significance test of the regression function

    International Nuclear Information System (INIS)

    Gao Zhengming; Zhao Juan; He Shengping

    2012-01-01

    In order to analyze the decay heating power of a certain radioactive isotope per kilogram with polynomial regression method, the paper firstly demonstrated the broad usage of polynomial function and deduced its parameters with ordinary least squares estimate. Then significance test method of polynomial regression function is derived considering the similarity between the polynomial regression model and the multivariable linear regression model. Finally, polynomial regression analysis and significance test of the polynomial function are done to the decay heating power of the iso tope per kilogram in accord with the authors' real work. (authors)

  13. Recursive Algorithm For Linear Regression

    Science.gov (United States)

    Varanasi, S. V.

    1988-01-01

    Order of model determined easily. Linear-regression algorithhm includes recursive equations for coefficients of model of increased order. Algorithm eliminates duplicative calculations, facilitates search for minimum order of linear-regression model fitting set of data satisfactory.

  14. Combining Alphas via Bounded Regression

    Directory of Open Access Journals (Sweden)

    Zura Kakushadze

    2015-11-01

    Full Text Available We give an explicit algorithm and source code for combining alpha streams via bounded regression. In practical applications, typically, there is insufficient history to compute a sample covariance matrix (SCM for a large number of alphas. To compute alpha allocation weights, one then resorts to (weighted regression over SCM principal components. Regression often produces alpha weights with insufficient diversification and/or skewed distribution against, e.g., turnover. This can be rectified by imposing bounds on alpha weights within the regression procedure. Bounded regression can also be applied to stock and other asset portfolio construction. We discuss illustrative examples.

  15. Regression in autistic spectrum disorders.

    Science.gov (United States)

    Stefanatos, Gerry A

    2008-12-01

    A significant proportion of children diagnosed with Autistic Spectrum Disorder experience a developmental regression characterized by a loss of previously-acquired skills. This may involve a loss of speech or social responsitivity, but often entails both. This paper critically reviews the phenomena of regression in autistic spectrum disorders, highlighting the characteristics of regression, age of onset, temporal course, and long-term outcome. Important considerations for diagnosis are discussed and multiple etiological factors currently hypothesized to underlie the phenomenon are reviewed. It is argued that regressive autistic spectrum disorders can be conceptualized on a spectrum with other regressive disorders that may share common pathophysiological features. The implications of this viewpoint are discussed.

  16. Linear regression in astronomy. I

    Science.gov (United States)

    Isobe, Takashi; Feigelson, Eric D.; Akritas, Michael G.; Babu, Gutti Jogesh

    1990-01-01

    Five methods for obtaining linear regression fits to bivariate data with unknown or insignificant measurement errors are discussed: ordinary least-squares (OLS) regression of Y on X, OLS regression of X on Y, the bisector of the two OLS lines, orthogonal regression, and 'reduced major-axis' regression. These methods have been used by various researchers in observational astronomy, most importantly in cosmic distance scale applications. Formulas for calculating the slope and intercept coefficients and their uncertainties are given for all the methods, including a new general form of the OLS variance estimates. The accuracy of the formulas was confirmed using numerical simulations. The applicability of the procedures is discussed with respect to their mathematical properties, the nature of the astronomical data under consideration, and the scientific purpose of the regression. It is found that, for problems needing symmetrical treatment of the variables, the OLS bisector performs significantly better than orthogonal or reduced major-axis regression.

  17. Advanced statistics: linear regression, part I: simple linear regression.

    Science.gov (United States)

    Marill, Keith A

    2004-01-01

    Simple linear regression is a mathematical technique used to model the relationship between a single independent predictor variable and a single dependent outcome variable. In this, the first of a two-part series exploring concepts in linear regression analysis, the four fundamental assumptions and the mechanics of simple linear regression are reviewed. The most common technique used to derive the regression line, the method of least squares, is described. The reader will be acquainted with other important concepts in simple linear regression, including: variable transformations, dummy variables, relationship to inference testing, and leverage. Simplified clinical examples with small datasets and graphic models are used to illustrate the points. This will provide a foundation for the second article in this series: a discussion of multiple linear regression, in which there are multiple predictor variables.

  18. Geographical variations in the use of cancer treatments are associated with survival of lung cancer patients

    DEFF Research Database (Denmark)

    Møller, Henrik; Coupland, Victoria H; Tataru, Daniela

    2018-01-01

    INTRODUCTION: Lung cancer outcomes in England are inferior to comparable countries. Patient or disease characteristics, healthcare-seeking behaviour, diagnostic pathways, and oncology service provision may contribute. We aimed to quantify associations between geographic variations in treatment...... and survival of patients in England. METHODS: We retrieved detailed cancer registration data to analyse the variation in survival of 176,225 lung cancer patients, diagnosed 2010-2014. We used Kaplan-Meier analysis and Cox proportional hazards regression to investigate survival in the two-year period following...... diagnosis. RESULTS: Survival improved over the period studied. The use of active treatment varied between geographical areas, with inter-quintile ranges of 9%-17% for surgical resection, 4%-13% for radical radiotherapy, and 22%-35% for chemotherapy. At 2 years, there were 188 potentially avoidable deaths...

  19. Survival after Out-of-Hospital Cardiac Arrest in Nursing Homes

    DEFF Research Database (Denmark)

    Pape, Marianne; Rajan, Shahzleen; Hansen, Steen Møller

    2018-01-01

    BACKGROUND: Survival among nursing home residents who suffers out-of-hospital cardiac arrest (OHCA) is sparsely studied. Deployment of automated external defibrillators (AEDs) in nursing home facilities in Denmark is unknown. We examined 30-day survival following OHCA in nursing and private home...... residents. METHODS: This register-based, nationwide, follow-up study identified OHCA-patients ≥18 years of age with a resuscitation attempt in nursing homes and private homes using Danish Cardiac Arrest Register data from June 1, 2001 to December 31, 2014. The primary outcome measure was 30-day survival....... Multiple logistic regression analyses were used to assess factors potentially associated with survival among nursing and private home residents separately. RESULTS: Of 26,999 OCHAs, 2516 (9.3%) occurred in nursing homes, and 24,483 (90.7%) in private homes. Nursing home residents were older (median 83 (Q1...

  20. Is there a difference in survival between men and women suffering in-hospital cardiac arrest?

    Science.gov (United States)

    Israelsson, Johan; Persson, Carina; Strömberg, Anna; Arestedt, Kristofer

    2014-01-01

    To describe in-hospital cardiac arrest (CA) events with regard to sex and to investigate if sex is associated with survival. Previous studies exploring differences between sexes are incongruent with regard to clinical outcomes. In order to provide equality and improve care, further investigations into these aspects are warranted. This registry study included 286 CAs. To investigate if sex was associated with survival, logistic regression analyses were performed. The proportion of CA with a resuscitation attempt compared to CA without resuscitation was higher among men. There were no associations between sex and survival when controlling for previously known predictors and interaction effects. Sex does not appear to be a predictor for survival among patients suffering CA where resuscitation is attempted. The difference regarding proportion of resuscitation attempts requires more attention. It is important to consider possible interaction effects when studying the sex perspective. Copyright © 2014 Elsevier Inc. All rights reserved.

  1. Depression and Liver Transplant Survival.

    Science.gov (United States)

    Meller, William; Welle, Nicole; Sutley, Kristen; Thurber, Steven

    Patients who underwent liver transplantation and experienced clinical depression have heretofore evinced lower survival rates when compared to nondepressed counterparts. To investigate the hypothesis that transplant patients who seek and obtain medical treatment for depression would circumvent the prior reduced survival findings. A total of 765 patients with liver transplants were scrutinized for complications following transplantation. Further, 104 patients experienced posttransplant depression as manifested by diagnosis and treatment by medical personnel. Survival analyses were conducted comparing hazard and survival curves for these selected individuals and the remainder of transplant patients. Contrary to prior data and consistent with the aforementioned hypothesis, median survival durations, survival curves, and hazard functions (controlling for age and prolonged posttransplant survival for the depressed patients were better. The improved survival for the depressed patients may simply be related to an amelioration of depressed symptoms via antidepressant medications. However, this interpretation would only be congruent with reduced hazard, not elevated survival, beyond the norm (median) for other transplant participants. Assuming the reliability and generalization of our findings, perhaps a reasonable and compelling interpretation is that combined with the effectiveness of antidepressant medications, the seeking and receiving treatment for depression is a type of proxy measure of a more global pattern of adherence to recommended posttransplant medical regimens. Copyright © 2017 The Academy of Psychosomatic Medicine. Published by Elsevier Inc. All rights reserved.

  2. Biomarker analyses and final overall survival results from a phase III, randomized, open-label, first-line study of gefitinib versus carboplatin/paclitaxel in clinically selected patients with advanced non-small-cell lung cancer in Asia (IPASS).

    Science.gov (United States)

    Fukuoka, Masahiro; Wu, Yi-Long; Thongprasert, Sumitra; Sunpaweravong, Patrapim; Leong, Swan-Swan; Sriuranpong, Virote; Chao, Tsu-Yi; Nakagawa, Kazuhiko; Chu, Da-Tong; Saijo, Nagahiro; Duffield, Emma L; Rukazenkov, Yuri; Speake, Georgina; Jiang, Haiyi; Armour, Alison A; To, Ka-Fai; Yang, James Chih-Hsin; Mok, Tony S K

    2011-07-20

    The results of the Iressa Pan-Asia Study (IPASS), which compared gefitinib and carboplatin/paclitaxel in previously untreated never-smokers and light ex-smokers with advanced pulmonary adenocarcinoma were published previously. This report presents overall survival (OS) and efficacy according to epidermal growth factor receptor (EGFR) biomarker status. In all, 1,217 patients were randomly assigned. Biomarkers analyzed were EGFR mutation (amplification mutation refractory system; 437 patients evaluable), EGFR gene copy number (fluorescent in situ hybridization; 406 patients evaluable), and EGFR protein expression (immunohistochemistry; 365 patients evaluable). OS analysis was performed at 78% maturity. A Cox proportional hazards model was used to assess biomarker status by randomly assigned treatment interactions for progression-free survival (PFS) and OS. OS (954 deaths) was similar for gefitinib and carboplatin/paclitaxel with no significant difference between treatments overall (hazard ratio [HR], 0.90; 95% CI, 0.79 to 1.02; P = .109) or in EGFR mutation-positive (HR, 1.00; 95% CI, 0.76 to 1.33; P = .990) or EGFR mutation-negative (HR, 1.18; 95% CI, 0.86 to 1.63; P = .309; treatment by EGFR mutation interaction P = .480) subgroups. A high proportion (64.3%) of EGFR mutation-positive patients randomly assigned to carboplatin/paclitaxel received subsequent EGFR tyrosine kinase inhibitors. PFS was significantly longer with gefitinib for patients whose tumors had both high EGFR gene copy number and EGFR mutation (HR, 0.48; 95% CI, 0.34 to 0.67) but significantly shorter when high EGFR gene copy number was not accompanied by EGFR mutation (HR, 3.85; 95% CI, 2.09 to 7.09). EGFR mutations are the strongest predictive biomarker for PFS and tumor response to first-line gefitinib versus carboplatin/paclitaxel. The predictive value of EGFR gene copy number was driven by coexisting EGFR mutation (post hoc analysis). Treatment-related differences observed for PFS in the EGFR

  3. On the analysis of clonogenic survival data: Statistical alternatives to the linear-quadratic model

    International Nuclear Information System (INIS)

    Unkel, Steffen; Belka, Claus; Lauber, Kirsten

    2016-01-01

    the extraction of scores of radioresistance, which displayed significant correlations with the estimated parameters of the regression models. Undoubtedly, LQ regression is a robust method for the analysis of clonogenic survival data. Nevertheless, alternative approaches including non-linear regression and multivariate techniques such as cluster analysis and principal component analysis represent versatile tools for the extraction of parameters and/or scores of the cellular response towards ionizing irradiation with a more intuitive biological interpretation. The latter are highly informative for correlation analyses with other types of data, including functional genomics data that are increasingly beinggenerated

  4. Prognostic value of biochemical variables for survival after surgery for metastatic bone disease of the extremities.

    Science.gov (United States)

    Sørensen, Michala Skovlund; Hovgaard, Thea Bechman; Hindsø, Klaus; Petersen, Michael Mørk

    2017-03-01

    Prediction of survival in patients having surgery for metastatic bone disease in the extremities (MBDex) has been of interest in more than two decades. Hitherto no consensus on the value of biochemical variables has been achieved. Our purpose was (1) to investigate if standard biochemical variables have independent prognostic value for survival after surgery for MBDex and (2) to identify optimal prognostic cut off values for survival of biochemical variables. In a consecutive cohort of 270 patients having surgery for MBDex, we measured preoperative biochemical variables: hemoglobin, alkaline phosphatase, C-reactive protein and absolute, neutrophil and lymphocyte count. ROC curve analyses were performed to identify optimal cut off levels. Independent prognostic factors for variables were addressed with multiple Cox regression analyses. Optimal cut off levels were identified as: hemoglobin 7.45 mmol/L, absolute lymphocyte count 8.5 × 10 9 /L, neutrophil 5.68 × 10 9 /L, lymphocyte 1.37 × 10 9 /L, C-reactive protein 22.5 mg/L, and alkaline phosphatase 129 U/L. Regression analyses found alkaline phosphatase (HR 2.49) and neutrophil count (HR 2.49) to be independent prognostic factors. We found neutrophil count and alkaline phosphatase to be independent prognostic variables in predicting survival in patients after surgery for MBDex. © 2016 Wiley Periodicals, Inc.

  5. Linear regression in astronomy. II

    Science.gov (United States)

    Feigelson, Eric D.; Babu, Gutti J.

    1992-01-01

    A wide variety of least-squares linear regression procedures used in observational astronomy, particularly investigations of the cosmic distance scale, are presented and discussed. The classes of linear models considered are (1) unweighted regression lines, with bootstrap and jackknife resampling; (2) regression solutions when measurement error, in one or both variables, dominates the scatter; (3) methods to apply a calibration line to new data; (4) truncated regression models, which apply to flux-limited data sets; and (5) censored regression models, which apply when nondetections are present. For the calibration problem we develop two new procedures: a formula for the intercept offset between two parallel data sets, which propagates slope errors from one regression to the other; and a generalization of the Working-Hotelling confidence bands to nonstandard least-squares lines. They can provide improved error analysis for Faber-Jackson, Tully-Fisher, and similar cosmic distance scale relations.

  6. Time-adaptive quantile regression

    DEFF Research Database (Denmark)

    Møller, Jan Kloppenborg; Nielsen, Henrik Aalborg; Madsen, Henrik

    2008-01-01

    and an updating procedure are combined into a new algorithm for time-adaptive quantile regression, which generates new solutions on the basis of the old solution, leading to savings in computation time. The suggested algorithm is tested against a static quantile regression model on a data set with wind power......An algorithm for time-adaptive quantile regression is presented. The algorithm is based on the simplex algorithm, and the linear optimization formulation of the quantile regression problem is given. The observations have been split to allow a direct use of the simplex algorithm. The simplex method...... production, where the models combine splines and quantile regression. The comparison indicates superior performance for the time-adaptive quantile regression in all the performance parameters considered....

  7. Retro-regression--another important multivariate regression improvement.

    Science.gov (United States)

    Randić, M

    2001-01-01

    We review the serious problem associated with instabilities of the coefficients of regression equations, referred to as the MRA (multivariate regression analysis) "nightmare of the first kind". This is manifested when in a stepwise regression a descriptor is included or excluded from a regression. The consequence is an unpredictable change of the coefficients of the descriptors that remain in the regression equation. We follow with consideration of an even more serious problem, referred to as the MRA "nightmare of the second kind", arising when optimal descriptors are selected from a large pool of descriptors. This process typically causes at different steps of the stepwise regression a replacement of several previously used descriptors by new ones. We describe a procedure that resolves these difficulties. The approach is illustrated on boiling points of nonanes which are considered (1) by using an ordered connectivity basis; (2) by using an ordering resulting from application of greedy algorithm; and (3) by using an ordering derived from an exhaustive search for optimal descriptors. A novel variant of multiple regression analysis, called retro-regression (RR), is outlined showing how it resolves the ambiguities associated with both "nightmares" of the first and the second kind of MRA.

  8. Instrumental variable estimation in a survival context

    DEFF Research Database (Denmark)

    Tchetgen Tchetgen, Eric J; Walter, Stefan; Vansteelandt, Stijn

    2015-01-01

    for regression analysis in a survival context, primarily under an additive hazards model, for which we describe 2 simple methods for estimating causal effects. The first method is a straightforward 2-stage regression approach analogous to 2-stage least squares commonly used for IV analysis in linear regression....... The IV approach is very well developed in the context of linear regression and also for certain generalized linear models with a nonlinear link function. However, IV methods are not as well developed for regression analysis with a censored survival outcome. In this article, we develop the IV approach....... In this approach, the fitted value from a first-stage regression of the exposure on the IV is entered in place of the exposure in the second-stage hazard model to recover a valid estimate of the treatment effect of interest. The second method is a so-called control function approach, which entails adding...

  9. Quantile regression theory and applications

    CERN Document Server

    Davino, Cristina; Vistocco, Domenico

    2013-01-01

    A guide to the implementation and interpretation of Quantile Regression models This book explores the theory and numerous applications of quantile regression, offering empirical data analysis as well as the software tools to implement the methods. The main focus of this book is to provide the reader with a comprehensivedescription of the main issues concerning quantile regression; these include basic modeling, geometrical interpretation, estimation and inference for quantile regression, as well as issues on validity of the model, diagnostic tools. Each methodological aspect is explored and

  10. Logistic regression applied to natural hazards: rare event logistic regression with replications

    Directory of Open Access Journals (Sweden)

    M. Guns

    2012-06-01

    Full Text Available Statistical analysis of natural hazards needs particular attention, as most of these phenomena are rare events. This study shows that the ordinary rare event logistic regression, as it is now commonly used in geomorphologic studies, does not always lead to a robust detection of controlling factors, as the results can be strongly sample-dependent. In this paper, we introduce some concepts of Monte Carlo simulations in rare event logistic regression. This technique, so-called rare event logistic regression with replications, combines the strength of probabilistic and statistical methods, and allows overcoming some of the limitations of previous developments through robust variable selection. This technique was here developed for the analyses of landslide controlling factors, but the concept is widely applicable for statistical analyses of natural hazards.

  11. Logistic regression applied to natural hazards: rare event logistic regression with replications

    Science.gov (United States)

    Guns, M.; Vanacker, V.

    2012-06-01

    Statistical analysis of natural hazards needs particular attention, as most of these phenomena are rare events. This study shows that the ordinary rare event logistic regression, as it is now commonly used in geomorphologic studies, does not always lead to a robust detection of controlling factors, as the results can be strongly sample-dependent. In this paper, we introduce some concepts of Monte Carlo simulations in rare event logistic regression. This technique, so-called rare event logistic regression with replications, combines the strength of probabilistic and statistical methods, and allows overcoming some of the limitations of previous developments through robust variable selection. This technique was here developed for the analyses of landslide controlling factors, but the concept is widely applicable for statistical analyses of natural hazards.

  12. Predictors of adalimumab drug survival in psoriasis differ by reason for discontinuation: long-term results from the Bio-CAPTURE registry.

    Science.gov (United States)

    van den Reek, J M P A; Tummers, M; Zweegers, J; Seyger, M M B; van Lümig, P P M; Driessen, R J B; van de Kerkhof, P C M; Kievit, W; de Jong, E M G J

    2015-03-01

    Drug survival is an indicator for treatment success; insight in predictors associated with drug survival is important. To analyse the long-term drug survival for adalimumab in patients with psoriasis treated in daily practice and (II) to identify predictors of prolonged drug survival for adalimumab split for different reasons of discontinuation. Data were extracted from a prospective psoriasis cohort and analysed using Kaplan-Meier survival curves split for reasons of discontinuation. Baseline predictors associated with longer drug survival were identified using multivariate Cox-regression analysis. One hundred and sixteen patients were included with a total of 208 patient-years. Overall drug survival was 76% after 1 year and 52% after 4.5 years. In patients who stopped due to ineffectiveness, longer drug survival was associated with the absence of specific comorbidities (P = 0.03). In patients who stopped due to side-effects, longer drug survival was associated with male gender (P = 0.02). Predictors of adalimumab drug survival in psoriasis differ by reason for discontinuation. Strong, specific predictors can lead to patient-tailored treatment. © 2014 European Academy of Dermatology and Venereology.

  13. Surviving Sengstaken.

    Science.gov (United States)

    Jayakumar, S; Odulaja, A; Patel, S; Davenport, M; Ade-Ajayi, N

    2015-07-01

    To report the outcomes of children who underwent Sengstaken-Blakemore tube (SBT) insertion for life-threatening haemetemesis. Single institution retrospective review (1997-2012) of children managed with SBT insertion. Patient demographics, diagnosis and outcomes were noted. Data are expressed as median (range). 19 children [10 male, age 1 (0.4-16) yr] were identified; 18 had gastro-oesophageal varices and 1 aorto-oesophageal fistula. Varices were secondary to: biliary atresia (n=8), portal vein thrombosis (n=5), alpha-1-anti-trypsin deficiency (n=1), cystic fibrosis (n=1), intrahepatic cholestasis (n=1), sclerosing cholangitis (n=1) and nodular hyperplasia with arterio-portal shunt (n=1). Three children deteriorated rapidly and did not survive to have post-SBT endoscopy. The child with an aortooesophageal fistula underwent aortic stent insertion and subsequently oesophageal replacement. Complications included gastric mucosal ulceration (n=3, 16%), pressure necrosis at lips and cheeks (n=6, 31%) and SBT dislodgment (n=1, 6%). Six (31%) children died. The remaining 13 have been followed up for 62 (2-165) months; five required liver transplantation, two underwent a mesocaval shunt procedure and 6 have completed endoscopic variceal obliteration and are under surveillance. SBT can be an effective, albeit temporary, life-saving manoeuvre in children with catastrophic haematemesis. Copyright © 2015 Elsevier Inc. All rights reserved.

  14. Panel Smooth Transition Regression Models

    DEFF Research Database (Denmark)

    González, Andrés; Terasvirta, Timo; Dijk, Dick van

    We introduce the panel smooth transition regression model. This new model is intended for characterizing heterogeneous panels, allowing the regression coefficients to vary both across individuals and over time. Specifically, heterogeneity is allowed for by assuming that these coefficients are bou...

  15. Testing discontinuities in nonparametric regression

    KAUST Repository

    Dai, Wenlin

    2017-01-19

    In nonparametric regression, it is often needed to detect whether there are jump discontinuities in the mean function. In this paper, we revisit the difference-based method in [13 H.-G. Müller and U. Stadtmüller, Discontinuous versus smooth regression, Ann. Stat. 27 (1999), pp. 299–337. doi: 10.1214/aos/1018031100

  16. Testing discontinuities in nonparametric regression

    KAUST Repository

    Dai, Wenlin; Zhou, Yuejin; Tong, Tiejun

    2017-01-01

    In nonparametric regression, it is often needed to detect whether there are jump discontinuities in the mean function. In this paper, we revisit the difference-based method in [13 H.-G. Müller and U. Stadtmüller, Discontinuous versus smooth regression, Ann. Stat. 27 (1999), pp. 299–337. doi: 10.1214/aos/1018031100

  17. Logistic Regression: Concept and Application

    Science.gov (United States)

    Cokluk, Omay

    2010-01-01

    The main focus of logistic regression analysis is classification of individuals in different groups. The aim of the present study is to explain basic concepts and processes of binary logistic regression analysis intended to determine the combination of independent variables which best explain the membership in certain groups called dichotomous…

  18. Fungible weights in logistic regression.

    Science.gov (United States)

    Jones, Jeff A; Waller, Niels G

    2016-06-01

    In this article we develop methods for assessing parameter sensitivity in logistic regression models. To set the stage for this work, we first review Waller's (2008) equations for computing fungible weights in linear regression. Next, we describe 2 methods for computing fungible weights in logistic regression. To demonstrate the utility of these methods, we compute fungible logistic regression weights using data from the Centers for Disease Control and Prevention's (2010) Youth Risk Behavior Surveillance Survey, and we illustrate how these alternate weights can be used to evaluate parameter sensitivity. To make our work accessible to the research community, we provide R code (R Core Team, 2015) that will generate both kinds of fungible logistic regression weights. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

  19. Ordinary least square regression, orthogonal regression, geometric mean regression and their applications in aerosol science

    International Nuclear Information System (INIS)

    Leng Ling; Zhang Tianyi; Kleinman, Lawrence; Zhu Wei

    2007-01-01

    Regression analysis, especially the ordinary least squares method which assumes that errors are confined to the dependent variable, has seen a fair share of its applications in aerosol science. The ordinary least squares approach, however, could be problematic due to the fact that atmospheric data often does not lend itself to calling one variable independent and the other dependent. Errors often exist for both measurements. In this work, we examine two regression approaches available to accommodate this situation. They are orthogonal regression and geometric mean regression. Comparisons are made theoretically as well as numerically through an aerosol study examining whether the ratio of organic aerosol to CO would change with age

  20. Nivolumab vs investigator's choice in recurrent or metastatic squamous cell carcinoma of the head and neck: 2-year long-term survival update of CheckMate 141 with analyses by tumor PD-L1 expression.

    Science.gov (United States)

    Ferris, Robert L; Blumenschein, George; Fayette, Jerome; Guigay, Joel; Colevas, A Dimitrios; Licitra, Lisa; Harrington, Kevin J; Kasper, Stefan; Vokes, Everett E; Even, Caroline; Worden, Francis; Saba, Nabil F; Docampo, Lara Carmen Iglesias; Haddad, Robert; Rordorf, Tamara; Kiyota, Naomi; Tahara, Makoto; Lynch, Mark; Jayaprakash, Vijayvel; Li, Li; Gillison, Maura L

    2018-06-01

    We report 2-year results from CheckMate 141 to establish the long-term efficacy and safety profile of nivolumab and outcomes by tumor PD-L1 expression in patients with recurrent or metastatic (R/M),platinum-refractory squamous cell carcinoma of the head and neck (SCCHN). Patients with R/M SCCHN with tumor progression/recurrence within 6 months of platinum therapy were randomized 2:1 to nivolumab 3 mg/kg every 2 weeks or investigator's choice (IC). Primary endpoint: overall survival (OS). Data cutoff: September 2017. With 24.2 months' minimum follow-up, nivolumab (n = 240) continued to improve OS vs IC (n = 121), hazard ratio (HR) = 0.68 (95% CI 0.54-0.86). Nivolumab nearly tripled the estimated 24-month OS rate (16.9%) vs IC (6.0%), and demonstrated OS benefit across patients with tumor PD-L1 expression ≥1% (HR [95% CI] = 0.55 [0.39-0.78]) and  < 1% (HR [95% CI] = 0.73 [0.49-1.09]), and regardless of tumor HPV status. Estimated OS rates at 18, 24, and 30 months with nivolumab were consistent irrespective of PD-L1 expression (<1%/≥1%). In the nivolumab arm, there were no observed differences in baseline characteristics or safety profile between long-term survivors and the overall population. Grade 3-4 treatment-related adverse event rates were 15.3% and 36.9% for nivolumab and IC, respectively. Nivolumab significantly improved OS at the primary analysis and demonstrated prolonged OS benefit vs IC and maintenance of a manageable and consistent safety profile with 2-year follow-up. OS benefit was observed with nivolumab irrespective of PD-L1 expression and HPV status. (Clinicaltrials.gov: NCT02105636). Copyright © 2018. Published by Elsevier Ltd.

  1. Modeling time-to-event (survival) data using classification tree analysis.

    Science.gov (United States)

    Linden, Ariel; Yarnold, Paul R

    2017-12-01

    Time to the occurrence of an event is often studied in health research. Survival analysis differs from other designs in that follow-up times for individuals who do not experience the event by the end of the study (called censored) are accounted for in the analysis. Cox regression is the standard method for analysing censored data, but the assumptions required of these models are easily violated. In this paper, we introduce classification tree analysis (CTA) as a flexible alternative for modelling censored data. Classification tree analysis is a "decision-tree"-like classification model that provides parsimonious, transparent (ie, easy to visually display and interpret) decision rules that maximize predictive accuracy, derives exact P values via permutation tests, and evaluates model cross-generalizability. Using empirical data, we identify all statistically valid, reproducible, longitudinally consistent, and cross-generalizable CTA survival models and then compare their predictive accuracy to estimates derived via Cox regression and an unadjusted naïve model. Model performance is assessed using integrated Brier scores and a comparison between estimated survival curves. The Cox regression model best predicts average incidence of the outcome over time, whereas CTA survival models best predict either relatively high, or low, incidence of the outcome over time. Classification tree analysis survival models offer many advantages over Cox regression, such as explicit maximization of predictive accuracy, parsimony, statistical robustness, and transparency. Therefore, researchers interested in accurate prognoses and clear decision rules should consider developing models using the CTA-survival framework. © 2017 John Wiley & Sons, Ltd.

  2. Tumor regression patterns in retinoblastoma

    International Nuclear Information System (INIS)

    Zafar, S.N.; Siddique, S.N.; Zaheer, N.

    2016-01-01

    To observe the types of tumor regression after treatment, and identify the common pattern of regression in our patients. Study Design: Descriptive study. Place and Duration of Study: Department of Pediatric Ophthalmology and Strabismus, Al-Shifa Trust Eye Hospital, Rawalpindi, Pakistan, from October 2011 to October 2014. Methodology: Children with unilateral and bilateral retinoblastoma were included in the study. Patients were referred to Pakistan Institute of Medical Sciences, Islamabad, for chemotherapy. After every cycle of chemotherapy, dilated funds examination under anesthesia was performed to record response of the treatment. Regression patterns were recorded on RetCam II. Results: Seventy-four tumors were included in the study. Out of 74 tumors, 3 were ICRB group A tumors, 43 were ICRB group B tumors, 14 tumors belonged to ICRB group C, and remaining 14 were ICRB group D tumors. Type IV regression was seen in 39.1% (n=29) tumors, type II in 29.7% (n=22), type III in 25.6% (n=19), and type I in 5.4% (n=4). All group A tumors (100%) showed type IV regression. Seventeen (39.5%) group B tumors showed type IV regression. In group C, 5 tumors (35.7%) showed type II regression and 5 tumors (35.7%) showed type IV regression. In group D, 6 tumors (42.9%) regressed to type II non-calcified remnants. Conclusion: The response and success of the focal and systemic treatment, as judged by the appearance of different patterns of tumor regression, varies with the ICRB grouping of the tumor. (author)

  3. From basic survival analytic theory to a non-standard application

    CERN Document Server

    Zimmermann, Georg

    2017-01-01

    Georg Zimmermann provides a mathematically rigorous treatment of basic survival analytic methods. His emphasis is also placed on various questions and problems, especially with regard to life expectancy calculations arising from a particular real-life dataset on patients with epilepsy. The author shows both the step-by-step analyses of that dataset and the theory the analyses are based on. He demonstrates that one may face serious and sometimes unexpected problems, even when conducting very basic analyses. Moreover, the reader learns that a practically relevant research question may look rather simple at first sight. Nevertheless, compared to standard textbooks, a more detailed account of the theory underlying life expectancy calculations is needed in order to provide a mathematically rigorous framework. Contents Regression Models for Survival Data Model Checking Procedures Life Expectancy Target Groups Researchers, lecturers, and students in the fields of mathematics and statistics Academics and experts work...

  4. Regression to Causality : Regression-style presentation influences causal attribution

    DEFF Research Database (Denmark)

    Bordacconi, Mats Joe; Larsen, Martin Vinæs

    2014-01-01

    of equivalent results presented as either regression models or as a test of two sample means. Our experiment shows that the subjects who were presented with results as estimates from a regression model were more inclined to interpret these results causally. Our experiment implies that scholars using regression...... models – one of the primary vehicles for analyzing statistical results in political science – encourage causal interpretation. Specifically, we demonstrate that presenting observational results in a regression model, rather than as a simple comparison of means, makes causal interpretation of the results...... more likely. Our experiment drew on a sample of 235 university students from three different social science degree programs (political science, sociology and economics), all of whom had received substantial training in statistics. The subjects were asked to compare and evaluate the validity...

  5. Augmenting Data with Published Results in Bayesian Linear Regression

    Science.gov (United States)

    de Leeuw, Christiaan; Klugkist, Irene

    2012-01-01

    In most research, linear regression analyses are performed without taking into account published results (i.e., reported summary statistics) of similar previous studies. Although the prior density in Bayesian linear regression could accommodate such prior knowledge, formal models for doing so are absent from the literature. The goal of this…

  6. Predicting Word Reading Ability: A Quantile Regression Study

    Science.gov (United States)

    McIlraith, Autumn L.

    2018-01-01

    Predictors of early word reading are well established. However, it is unclear if these predictors hold for readers across a range of word reading abilities. This study used quantile regression to investigate predictive relationships at different points in the distribution of word reading. Quantile regression analyses used preschool and…

  7. Stereotactic Radiosurgery in the Management of Brain Metastases: An Institutional Retrospective Analysis of Survival

    International Nuclear Information System (INIS)

    Frazier, James L.; Batra, Sachin; Kapor, Sumit; Vellimana, Ananth; Gandhi, Rahul; Carson, Kathryn A.; Shokek, Ori; Lim, Michael; Kleinberg, Lawrence; Rigamonti, Daniele

    2010-01-01

    Purpose: The objective of this study was to report our experience with stereotactic radiosurgery performed with the Gamma Knife (GK) in the treatment of patients with brain metastases and to compare survival for those treated with radiosurgery alone with survival for those treated with radiosurgery and whole-brain radiotherapy. Methods and Materials: Prospectively collected demographic and clinical characteristics and treatment and survival data on 237 patients with intracranial metastases who underwent radiosurgery with the GK between 2003 and 2007 were reviewed. Kaplan-Meier and Cox proportional hazards regression analyses were used to compare survival by demographic and clinical characteristics and treatment. Results: The mean age of the patient population was 56 years. The most common tumor histologies were non-small-cell lung carcinoma (34.2%) and breast cancer (13.9%). The median overall survival time was 8.5 months from the time of treatment. The median survival times for patients with one, two/three, and four or more brain metastases were 8.5, 9.4, and 6.7 months, respectively. Patients aged 65 years or greater and those aged less than 65 years had median survival times of 7.8 and 9 months, respectively (p = 0.008). The Karnofsky Performance Score (KPS) at the time of treatment was a significant predictor of survival: those patients with a KPS of 70 or less had a median survival of 2.9 months compared with 10.3 months (p = 0.034) for those with a KPS of 80 or greater. There was no statistically significant difference in survival between patients treated with radiosurgery alone and those treated with radiosurgery plus whole-brain radiotherapy. Conclusions: Radiosurgery with the GK is an efficacious treatment modality for brain metastases. A KPS greater than 70, histology of breast cancer, smaller tumor volume, and age less than 65 years were associated with a longer median survival in our study.

  8. Advanced statistics: linear regression, part II: multiple linear regression.

    Science.gov (United States)

    Marill, Keith A

    2004-01-01

    The applications of simple linear regression in medical research are limited, because in most situations, there are multiple relevant predictor variables. Univariate statistical techniques such as simple linear regression use a single predictor variable, and they often may be mathematically correct but clinically misleading. Multiple linear regression is a mathematical technique used to model the relationship between multiple independent predictor variables and a single dependent outcome variable. It is used in medical research to model observational data, as well as in diagnostic and therapeutic studies in which the outcome is dependent on more than one factor. Although the technique generally is limited to data that can be expressed with a linear function, it benefits from a well-developed mathematical framework that yields unique solutions and exact confidence intervals for regression coefficients. Building on Part I of this series, this article acquaints the reader with some of the important concepts in multiple regression analysis. These include multicollinearity, interaction effects, and an expansion of the discussion of inference testing, leverage, and variable transformations to multivariate models. Examples from the first article in this series are expanded on using a primarily graphic, rather than mathematical, approach. The importance of the relationships among the predictor variables and the dependence of the multivariate model coefficients on the choice of these variables are stressed. Finally, concepts in regression model building are discussed.

  9. Logic regression and its extensions.

    Science.gov (United States)

    Schwender, Holger; Ruczinski, Ingo

    2010-01-01

    Logic regression is an adaptive classification and regression procedure, initially developed to reveal interacting single nucleotide polymorphisms (SNPs) in genetic association studies. In general, this approach can be used in any setting with binary predictors, when the interaction of these covariates is of primary interest. Logic regression searches for Boolean (logic) combinations of binary variables that best explain the variability in the outcome variable, and thus, reveals variables and interactions that are associated with the response and/or have predictive capabilities. The logic expressions are embedded in a generalized linear regression framework, and thus, logic regression can handle a variety of outcome types, such as binary responses in case-control studies, numeric responses, and time-to-event data. In this chapter, we provide an introduction to the logic regression methodology, list some applications in public health and medicine, and summarize some of the direct extensions and modifications of logic regression that have been proposed in the literature. Copyright © 2010 Elsevier Inc. All rights reserved.

  10. Clustered survival data with left-truncation

    DEFF Research Database (Denmark)

    Eriksson, Frank; Martinussen, Torben; Scheike, Thomas H.

    2015-01-01

    Left-truncation occurs frequently in survival studies, and it is well known how to deal with this for univariate survival times. However, there are few results on how to estimate dependence parameters and regression effects in semiparametric models for clustered survival data with delayed entry....... Surprisingly, existing methods only deal with special cases. In this paper, we clarify different kinds of left-truncation and suggest estimators for semiparametric survival models under specific truncation schemes. The large-sample properties of the estimators are established. Small-sample properties...

  11. Abstract Expression Grammar Symbolic Regression

    Science.gov (United States)

    Korns, Michael F.

    This chapter examines the use of Abstract Expression Grammars to perform the entire Symbolic Regression process without the use of Genetic Programming per se. The techniques explored produce a symbolic regression engine which has absolutely no bloat, which allows total user control of the search space and output formulas, which is faster, and more accurate than the engines produced in our previous papers using Genetic Programming. The genome is an all vector structure with four chromosomes plus additional epigenetic and constraint vectors, allowing total user control of the search space and the final output formulas. A combination of specialized compiler techniques, genetic algorithms, particle swarm, aged layered populations, plus discrete and continuous differential evolution are used to produce an improved symbolic regression sytem. Nine base test cases, from the literature, are used to test the improvement in speed and accuracy. The improved results indicate that these techniques move us a big step closer toward future industrial strength symbolic regression systems.

  12. Quantile Regression With Measurement Error

    KAUST Repository

    Wei, Ying; Carroll, Raymond J.

    2009-01-01

    . The finite sample performance of the proposed method is investigated in a simulation study, and compared to the standard regression calibration approach. Finally, we apply our methodology to part of the National Collaborative Perinatal Project growth data, a

  13. From Rasch scores to regression

    DEFF Research Database (Denmark)

    Christensen, Karl Bang

    2006-01-01

    Rasch models provide a framework for measurement and modelling latent variables. Having measured a latent variable in a population a comparison of groups will often be of interest. For this purpose the use of observed raw scores will often be inadequate because these lack interval scale propertie....... This paper compares two approaches to group comparison: linear regression models using estimated person locations as outcome variables and latent regression models based on the distribution of the score....

  14. Testing Heteroscedasticity in Robust Regression

    Czech Academy of Sciences Publication Activity Database

    Kalina, Jan

    2011-01-01

    Roč. 1, č. 4 (2011), s. 25-28 ISSN 2045-3345 Grant - others:GA ČR(CZ) GA402/09/0557 Institutional research plan: CEZ:AV0Z10300504 Keywords : robust regression * heteroscedasticity * regression quantiles * diagnostics Subject RIV: BB - Applied Statistics , Operational Research http://www.researchjournals.co.uk/documents/Vol4/06%20Kalina.pdf

  15. Regression methods for medical research

    CERN Document Server

    Tai, Bee Choo

    2013-01-01

    Regression Methods for Medical Research provides medical researchers with the skills they need to critically read and interpret research using more advanced statistical methods. The statistical requirements of interpreting and publishing in medical journals, together with rapid changes in science and technology, increasingly demands an understanding of more complex and sophisticated analytic procedures.The text explains the application of statistical models to a wide variety of practical medical investigative studies and clinical trials. Regression methods are used to appropriately answer the

  16. Forecasting with Dynamic Regression Models

    CERN Document Server

    Pankratz, Alan

    2012-01-01

    One of the most widely used tools in statistical forecasting, single equation regression models is examined here. A companion to the author's earlier work, Forecasting with Univariate Box-Jenkins Models: Concepts and Cases, the present text pulls together recent time series ideas and gives special attention to possible intertemporal patterns, distributed lag responses of output to input series and the auto correlation patterns of regression disturbance. It also includes six case studies.

  17. Probabilistic Survivability Versus Time Modeling

    Science.gov (United States)

    Joyner, James J., Sr.

    2016-01-01

    This presentation documents Kennedy Space Center's Independent Assessment work completed on three assessments for the Ground Systems Development and Operations (GSDO) Program to assist the Chief Safety and Mission Assurance Officer during key programmatic reviews and provided the GSDO Program with analyses of how egress time affects the likelihood of astronaut and ground worker survival during an emergency. For each assessment, a team developed probability distributions for hazard scenarios to address statistical uncertainty, resulting in survivability plots over time. The first assessment developed a mathematical model of probabilistic survivability versus time to reach a safe location using an ideal Emergency Egress System at Launch Complex 39B (LC-39B); the second used the first model to evaluate and compare various egress systems under consideration at LC-39B. The third used a modified LC-39B model to determine if a specific hazard decreased survivability more rapidly than other events during flight hardware processing in Kennedy's Vehicle Assembly Building.

  18. Primary tumor regression speed after radiotherapy and its prognostic significance in nasopharyngeal carcinoma: a retrospective study

    International Nuclear Information System (INIS)

    Zhang, Ning; Liu, Dong-Sheng; Chen, Yong; Liang, Shao-Bo; Deng, Yan-Ming; Lu, Rui-Liang; Chen, Hai-Yang; Zhao, Hai; Lv, Zhi-Qian; Liang, Shao-Qiang; Yang, Lin

    2014-01-01

    To observe the primary tumor (PT) regression speed after radiotherapy (RT) in nasopharyngeal carcinoma (NPC) and evaluate its prognostic significance. One hundred and eighty-eight consecutive newly diagnosed NPC patients were reviewed retrospectively. All patients underwent magnetic resonance imaging and fiberscope examination of the nasopharynx before RT, during RT when the accumulated dose was 46–50 Gy, at the end of RT, and 3–4 months after RT. Of 188 patients, 40.4% had complete response of PT (CRPT), 44.7% had partial response of PT (PRPT), and 14.9% had stable disease of PT (SDPT) at the end of RT. The 5-year overall survival (OS) rates for patients with CRPT, PRPT, and SDPT at the end of RT were 84.0%, 70.7%, and 44.3%, respectively (P < 0.001, hazard ratio [HR] = 2.177, 95% confidence interval [CI] = 1.480-3.202). The 5-year failure-free survival (FFS) and distant metastasis-free survival (DMFS) rates also differed significantly (87.8% vs. 74.3% vs. 52.7%, P = 0.001, HR = 2.148, 95% CI, 1.384-3.333; 91.7% vs. 84.7% vs. 66.1%, P = 0.004, HR = 2.252, 95% CI = 1.296-3.912). The 5-year local relapse–free survival (LRFS) rates were not significantly different (95.8% vs. 86.0% vs. 81.8%, P = 0.137, HR = 1.975, 95% CI, 0.976-3.995). By multivariate analyses, the PT regression speed at the end of RT was the only independent prognostic factor of OS, FFS, and DMFS (P < 0.001, P = 0.001, and P = 0.004, respectively). The 5-year FFS rates for patients with CRPT during RT and CRPT only at the end of RT were 80.2% and 97.1%, respectively (P = 0.033). For patients with persistent PT at the end of RT, the 5-year LRFS rates of patients without and with boost irradiation were 87.1% and 84.6%, respectively (P = 0.812). PT regression speed at the end of RT was an independent prognostic factor of OS, FFS, and DMFS in NPC patients. Immediate strengthening treatment may be provided to patients with poor tumor regression at the end of RT

  19. Better midterm survival in women after transcatheter aortic valve implantation.

    Science.gov (United States)

    Takagi, Hisato; Umemoto, Takuya

    2017-08-01

    In previous meta-analyses demonstrating better midterm overall survival in women undergoing transcatheter aortic valve implantation (TAVI), unadjusted risk and odds ratios were combined. To determine whether female gender is independently associated with better survival after TAVI, we performed a meta-analysis pooling adjusted hazard ratios (HRs) based on multivariate Cox proportional hazard regression. MEDLINE and EMBASE were searched through September 2015 using PubMed and OVID. Studies considered for inclusion met the following criteria: the study population was patients undergoing TAVI; and main outcomes included midterm (mean or median ≥6 months) overall survival or all-cause mortality in women and men. An unadjusted and/or adjusted HR of all-cause mortality for women versus men was abstracted from each individual study. Of 1347 potentially relevant articles screened initially, 16 reports of eligible studies were identified and included. A primary meta-analysis of the 9 adjusted HRs demonstrated a significantly better midterm overall survival in women than men (N.=6891; HR=0.80; 95% confidence interval [CI]: 0.65 to 0.97; P=0.03). A secondary meta-analysis adding 5 statistically non-significant unadjusted HR also indicated better survival in women (N.=8645; HR=0.83; 95% CI: 0.72 to 0.96; P=0.01). Although statistical tests for the primary meta-analysis revealed funnel plot asymmetry in favor of women, the secondary meta-analysis produced a symmetrical funnel plot. Female gender may be independently associated with better midterm overall survival after TAVI.

  20. The Poor Survival among Pulmonary Tuberculosis Patients in Chiapas, Mexico: The Case of Los Altos Region

    Science.gov (United States)

    Nájera-Ortiz, J. C.; Sánchez-Pérez, H. J.; Ochoa-Díaz-López, H.; Leal-Fernández, G.; Navarro-Giné, A.

    2012-01-01

    Objective. To analyse survival in patients with pulmonary tuberculosis (PTB) and factors associated with such survival. Design. Study of a cohort of patients aged over 14 years diagnosed with PTB from January 1, 1998 to July 31, 2005. During 2004–2006 a home visit was made to each patient and, during 2008-2009, they were visited again. During these visits a follow-up interview was administered; when the patient had died, a verbal autopsy was conducted with family members. Statistical analysis consisted of survival tests, Kaplan-Meier log-rank test and Cox regression. Results. Of 305 studied patients, 68 had died due to PTB by the time of the first evaluation, 237 were followed-up for a second evaluation, and 10 of them had died of PTB. According to the Cox regression, age (over 45 years) and treatment duration (under six months) were associated with a poorer survival. When treatment duration was excluded, the association between poorer survival with age persisted, whereas with having been treated via DOTS strategy, was barely significant. Conclusions. In the studied area it is necessary that patients receive a complete treatment scheme, and to give priority to patients aged over 45 years. PMID:22701170

  1. The Poor Survival among Pulmonary Tuberculosis Patients in Chiapas, Mexico: The Case of Los Altos Region

    Directory of Open Access Journals (Sweden)

    J. C. Nájera-Ortiz

    2012-01-01

    Full Text Available Objective. To analyse survival in patients with pulmonary tuberculosis (PTB and factors associated with such survival. Design. Study of a cohort of patients aged over 14 years diagnosed with PTB from January 1, 1998 to July 31, 2005. During 2004–2006 a home visit was made to each patient and, during 2008-2009, they were visited again. During these visits a follow-up interview was administered; when the patient had died, a verbal autopsy was conducted with family members. Statistical analysis consisted of survival tests, Kaplan-Meier log-rank test and Cox regression. Results. Of 305 studied patients, 68 had died due to PTB by the time of the first evaluation, 237 were followed-up for a second evaluation, and 10 of them had died of PTB. According to the Cox regression, age (over 45 years and treatment duration (under six months were associated with a poorer survival. When treatment duration was excluded, the association between poorer survival with age persisted, whereas with having been treated via DOTS strategy, was barely significant. Conclusions. In the studied area it is necessary that patients receive a complete treatment scheme, and to give priority to patients aged over 45 years.

  2. Overall survival and disease-free survival in endometrial cancer: prognostic factors in 276 patients

    Directory of Open Access Journals (Sweden)

    Tejerizo-García A

    2013-09-01

    Full Text Available Álvaro Tejerizo-García,1 Jesús S Jiménez-López,1 José L Muñoz-González,1 Sara Bartolomé-Sotillos,1 Laura Marqueta-Marqués,1 Gregorio López-González,1 José F Pérez-Regadera Gómez21Service of Obstetrics and Gynecology, 2Radiation Oncology Service, Hospital Universitario 12 de Octubre, Madrid, SpainObjective: The aim of the study reported here was to assess the disease-free survival and overall survival of patients with endometrial cancer and to determine independent factors affecting the prognosis.Materials and methods: This was a retrospective study of a single-center clinical series of 276 patients (mean age 64 years with histologically confirmed cancer of the corpus uteri. The standard treatments were extrafascial total hysterectomy and bilateral salpingo-oophorectomy with selective pelvic/para-aortic node dissection, according to risk for recurrence. Actuarial overall survival and disease-free survival were estimated according to the Kaplan–Meier method. Univariate and multivariate Cox proportional hazards analyses were used to assess the prognostic significance of the different variables.Results: The estimated median follow-up, determined using the inverse Kaplan–Meier method, was 45 months (95% confidence interval [CI] 41.2–48.8 for disease-free survival and 46 months (95% CI 43.0–49.0 for overall survival. The statistically significant variables affecting disease-free survival and overall survival were age, serous-papillary and clear-cell histological types, outer-half myometrial invasion, advanced International Federation of Gynecology and Obstetrics (FIGO stage, tumor grades G2 and G3, incomplete surgical resection, positive lymph nodes, lymphovascular space invasion, tumor remnants of >1 cm after surgery, and high-risk group. In the multivariate Cox regression model, predictors of tumor recurrence included advanced FIGO stage (hazard ratio [HR] 4.90, 95% CI 2.57–9.36, P < 0.001 and tumor grades G2 (HR 4.79, 95

  3. Logistic regression for dichotomized counts.

    Science.gov (United States)

    Preisser, John S; Das, Kalyan; Benecha, Habtamu; Stamm, John W

    2016-12-01

    Sometimes there is interest in a dichotomized outcome indicating whether a count variable is positive or zero. Under this scenario, the application of ordinary logistic regression may result in efficiency loss, which is quantifiable under an assumed model for the counts. In such situations, a shared-parameter hurdle model is investigated for more efficient estimation of regression parameters relating to overall effects of covariates on the dichotomous outcome, while handling count data with many zeroes. One model part provides a logistic regression containing marginal log odds ratio effects of primary interest, while an ancillary model part describes the mean count of a Poisson or negative binomial process in terms of nuisance regression parameters. Asymptotic efficiency of the logistic model parameter estimators of the two-part models is evaluated with respect to ordinary logistic regression. Simulations are used to assess the properties of the models with respect to power and Type I error, the latter investigated under both misspecified and correctly specified models. The methods are applied to data from a randomized clinical trial of three toothpaste formulations to prevent incident dental caries in a large population of Scottish schoolchildren. © The Author(s) 2014.

  4. Producing The New Regressive Left

    DEFF Research Database (Denmark)

    Crone, Christine

    members, this thesis investigates a growing political trend and ideological discourse in the Arab world that I have called The New Regressive Left. On the premise that a media outlet can function as a forum for ideology production, the thesis argues that an analysis of this material can help to trace...... the contexture of The New Regressive Left. If the first part of the thesis lays out the theoretical approach and draws the contextual framework, through an exploration of the surrounding Arab media-and ideoscapes, the second part is an analytical investigation of the discourse that permeates the programmes aired...... becomes clear from the analytical chapters is the emergence of the new cross-ideological alliance of The New Regressive Left. This emerging coalition between Shia Muslims, religious minorities, parts of the Arab Left, secular cultural producers, and the remnants of the political,strategic resistance...

  5. Survival after early-stage breast cancer of women previously treated for depression

    DEFF Research Database (Denmark)

    Suppli, Nis Frederik Palm; Johansen, Christoffer; Kessing, Lars Vedel

    2017-01-01

    treatment of depression and risk of receiving nonguideline treatment of breast cancer were assessed in multivariable logistic regression analyses. We compared the overall survival, breast cancer-specific survival, and risk of death by suicide of women who were and were not treated for depression before......Purpose The aim of this nationwide, register-based cohort study was to determine whether women treated for depression before primary early-stage breast cancer are at increased risk for receiving treatment that is not in accordance with national guidelines and for poorer survival. Material...... and Methods We identified 45,325 women with early breast cancer diagnosed in Denmark from 1998 to 2011. Of these, 744 women (2%) had had a previous hospital contact (as an inpatient or outpatient) for depression and another 6,068 (13%) had been treated with antidepressants. Associations between previous...

  6. Geographical variations in the use of cancer treatments are associated with survival of lung cancer patients

    DEFF Research Database (Denmark)

    Møller, Henrik; Coupland, Victoria H; Tataru, Daniela

    2018-01-01

    INTRODUCTION: Lung cancer outcomes in England are inferior to comparable countries. Patient or disease characteristics, healthcare-seeking behaviour, diagnostic pathways, and oncology service provision may contribute. We aimed to quantify associations between geographic variations in treatment...... and survival of patients in England. METHODS: We retrieved detailed cancer registration data to analyse the variation in survival of 176,225 lung cancer patients, diagnosed 2010-2014. We used Kaplan-Meier analysis and Cox proportional hazards regression to investigate survival in the two-year period following...... to statistical adjustments for age, sex, socio-economic status, performance status and co-morbidity. CONCLUSION: The extent of use of different treatment modalities varies between geographical areas in England. These variations are not attributable to measurable patient and tumour characteristics, and more...

  7. A Matlab program for stepwise regression

    Directory of Open Access Journals (Sweden)

    Yanhong Qi

    2016-03-01

    Full Text Available The stepwise linear regression is a multi-variable regression for identifying statistically significant variables in the linear regression equation. In present study, we presented the Matlab program of stepwise regression.

  8. Correlation and simple linear regression.

    Science.gov (United States)

    Zou, Kelly H; Tuncali, Kemal; Silverman, Stuart G

    2003-06-01

    In this tutorial article, the concepts of correlation and regression are reviewed and demonstrated. The authors review and compare two correlation coefficients, the Pearson correlation coefficient and the Spearman rho, for measuring linear and nonlinear relationships between two continuous variables. In the case of measuring the linear relationship between a predictor and an outcome variable, simple linear regression analysis is conducted. These statistical concepts are illustrated by using a data set from published literature to assess a computed tomography-guided interventional technique. These statistical methods are important for exploring the relationships between variables and can be applied to many radiologic studies.

  9. Regression filter for signal resolution

    International Nuclear Information System (INIS)

    Matthes, W.

    1975-01-01

    The problem considered is that of resolving a measured pulse height spectrum of a material mixture, e.g. gamma ray spectrum, Raman spectrum, into a weighed sum of the spectra of the individual constituents. The model on which the analytical formulation is based is described. The problem reduces to that of a multiple linear regression. A stepwise linear regression procedure was constructed. The efficiency of this method was then tested by transforming the procedure in a computer programme which was used to unfold test spectra obtained by mixing some spectra, from a library of arbitrary chosen spectra, and adding a noise component. (U.K.)

  10. Nonparametric Mixture of Regression Models.

    Science.gov (United States)

    Huang, Mian; Li, Runze; Wang, Shaoli

    2013-07-01

    Motivated by an analysis of US house price index data, we propose nonparametric finite mixture of regression models. We study the identifiability issue of the proposed models, and develop an estimation procedure by employing kernel regression. We further systematically study the sampling properties of the proposed estimators, and establish their asymptotic normality. A modified EM algorithm is proposed to carry out the estimation procedure. We show that our algorithm preserves the ascent property of the EM algorithm in an asymptotic sense. Monte Carlo simulations are conducted to examine the finite sample performance of the proposed estimation procedure. An empirical analysis of the US house price index data is illustrated for the proposed methodology.

  11. Association of MTHFR gene polymorphisms with breast cancer survival

    International Nuclear Information System (INIS)

    Martin, Damali N; Boersma, Brenda J; Howe, Tiffany M; Goodman, Julie E; Mechanic, Leah E; Chanock, Stephen J; Ambs, Stefan

    2006-01-01

    Two functional single nucleotide polymorphisms (SNPs) in the 5,10-methylenetetrahydrofolate reductase (MTHFR) gene, C677T and A1298C, lead to decreased enzyme activity and affect chemosensitivity of tumor cells. We investigated whether these MTHFR SNPs were associated with breast cancer survival in African-American and Caucasian women. African-American (n = 143) and Caucasian (n = 105) women, who had incident breast cancer with surgery, were recruited between 1993 and 2003 from the greater Baltimore area, Maryland, USA. Kaplan-Meier survival and multivariate Cox proportional hazards regression analyses were used to examine the relationship between MTHFR SNPs and disease-specific survival. We observed opposite effects of the MTHFR polymorphisms A1298C and C677T on breast cancer survival. Carriers of the variant allele at codon 1298 (A/C or C/C) had reduced survival when compared to homozygous carriers of the common A allele [Hazard ratio (HR) = 2.05; 95% confidence interval (CI), 1.05–4.00]. In contrast, breast cancer patients with the variant allele at codon 677 (C/T or T/T) had improved survival, albeit not statistically significant, when compared to individuals with the common C/C genotype (HR = 0.65; 95% CI, 0.31–1.35). The effects were stronger in patients with estrogen receptor-negative tumors (HR = 2.70; 95% CI, 1.17–6.23 for A/C or C/C versus A/A at codon 1298; HR = 0.36; 95% CI, 0.12–1.04 for C/T or T/T versus C/C at codon 677). Interactions between the two MTHFR genotypes and race/ethnicity on breast cancer survival were also observed (A1298C, p interaction = 0.088; C677T, p interaction = 0.026). We found that the MTHFR SNPs, C677T and A1298C, were associated with breast cancer survival. The variant alleles had opposite effects on disease outcome in the study population. Race/ethnicity modified the association between the two SNPs and breast cancer survival

  12. Cactus: An Introduction to Regression

    Science.gov (United States)

    Hyde, Hartley

    2008-01-01

    When the author first used "VisiCalc," the author thought it a very useful tool when he had the formulas. But how could he design a spreadsheet if there was no known formula for the quantities he was trying to predict? A few months later, the author relates he learned to use multiple linear regression software and suddenly it all clicked into…

  13. Regression Models for Repairable Systems

    Czech Academy of Sciences Publication Activity Database

    Novák, Petr

    2015-01-01

    Roč. 17, č. 4 (2015), s. 963-972 ISSN 1387-5841 Institutional support: RVO:67985556 Keywords : Reliability analysis * Repair models * Regression Subject RIV: BB - Applied Statistics, Operational Research Impact factor: 0.782, year: 2015 http://library.utia.cas.cz/separaty/2015/SI/novak-0450902.pdf

  14. Kernel regression with functional response

    OpenAIRE

    Ferraty, Frédéric; Laksaci, Ali; Tadj, Amel; Vieu, Philippe

    2011-01-01

    We consider kernel regression estimate when both the response variable and the explanatory one are functional. The rates of uniform almost complete convergence are stated as function of the small ball probability of the predictor and as function of the entropy of the set on which uniformity is obtained.

  15. Linear regression and the normality assumption.

    Science.gov (United States)

    Schmidt, Amand F; Finan, Chris

    2017-12-16

    Researchers often perform arbitrary outcome transformations to fulfill the normality assumption of a linear regression model. This commentary explains and illustrates that in large data settings, such transformations are often unnecessary, and worse may bias model estimates. Linear regression assumptions are illustrated using simulated data and an empirical example on the relation between time since type 2 diabetes diagnosis and glycated hemoglobin levels. Simulation results were evaluated on coverage; i.e., the number of times the 95% confidence interval included the true slope coefficient. Although outcome transformations bias point estimates, violations of the normality assumption in linear regression analyses do not. The normality assumption is necessary to unbiasedly estimate standard errors, and hence confidence intervals and P-values. However, in large sample sizes (e.g., where the number of observations per variable is >10) violations of this normality assumption often do not noticeably impact results. Contrary to this, assumptions on, the parametric model, absence of extreme observations, homoscedasticity, and independency of the errors, remain influential even in large sample size settings. Given that modern healthcare research typically includes thousands of subjects focusing on the normality assumption is often unnecessary, does not guarantee valid results, and worse may bias estimates due to the practice of outcome transformations. Copyright © 2017 Elsevier Inc. All rights reserved.

  16. Survival analysis of dialysis patients in selected hospitals of lahore city

    International Nuclear Information System (INIS)

    Ahmad, Z.; Shahzad, I.

    2015-01-01

    There are several reasons which are directly or indirectly relate to affect the survival time of End Stage Renal Disease (ESRD) patients. This study was done to analyse the survival rate of ESRD patients in Lahore city, and to evaluate the influence of various risk factors and prognostic factors on survival of these patients. Methods: A sample of 40 patients was taken from the Jinnah Hospital Lahore and Lahore General Hospital by using the convenience sampling technique. The Log Rank Test was used to determine the significant difference between the categories of qualitative variables of ESRD patients. Multivariate Cox Regression Analysis was used to analyse the effect of different clinical and socio-economic variables on the survival time of these patients. Results: Different qualitative variables like: age, marital status, BMI, comorbid factors, diabetes type, gender, income level, place, risk factor like diabetes, ischemic heart disease, hypertension and Hepatitis status were analysed on the basis of Log Rank Test. While age and comorbid factors were found to be statistically significant which showed that the distribution of age and comorbid factors were different. By using the Cox Regression analysis the coefficient of Mass, serum albumin and family history of diabetes were found to be significant. Conclusions: There were some of the factors which had been taken for the analysis came out less or more significant in patients of ESRD. So it was concluded that mostly clinical factors which were Mass of the Patient, Serum Albumin and Family History of Diabetes made significant contribution towards the survival status of patients. (author)

  17. Recognising out-of-hospital cardiac arrest during emergency calls increases bystander cardiopulmonary resuscitation and survival

    DEFF Research Database (Denmark)

    Viereck, Søren; Møller, Thea Palsgaard; Ersbøll, Annette Kjær

    2017-01-01

    BACKGROUND: Initiation of early bystander cardiopulmonary resuscitation (CPR) depends on bystanders' or medical dispatchers' recognition of out-of-hospital cardiac arrest (OHCA). The primary aim of our study was to investigate if OHCA recognition during the emergency call was associated...... with bystander CPR, return of spontaneous circulation (ROSC), and 30-day survival. Our secondary aim was to identify patient-, setting-, and dispatcher-related predictors of OHCA recognition. METHODS: We performed an observational study of all OHCA patients' emergency calls in the Capital Region of Denmark from...... the association between OHCA recognition and bystander CPR, ROSC, and 30-day survival. Univariable logistic regression analyses were applied to identify predictors of OHCA recognition. RESULTS: We included 779 emergency calls in the analyses. During the emergency calls, 70.1% (n=534) of OHCAs were recognised...

  18. Factors affecting survival of women diagnosed with breast cancer in El-Minia Governorate, Egypt.

    Science.gov (United States)

    Seedhom, Amany Edward; Kamal, Nashwa Nabil

    2011-07-01

    This study was conducted to determine breast cancer survival time and the association between breast cancer survival and socio-demographic and pathologic factors among women, in El-Minia, Egypt. While there has been much researches regarding prognostic factors for breast cancer but the majority of these studies were from developed countries. El-Minia has a population of approximately 4 million. To date, no research has been performed to determine breast cancer survival and the factors affecting it in El-minia. This retrospective study used data obtained from the cancer registry in the National Institute of Oncology in El-Minia and included 1207 women diagnosed with first primary breast cancer between 1(st) January 2005 and 31(st) December 2009 and followed to 30(th) June 2010. The association between survival and sociodemographic and pathological factors and distant metastasis at diagnosis, and treatment options was investigated using unifactorial chi-square test and multi-factorial (Cox regression) analyses. Kaplan-Meier analysis was used to compare survival time among different groups. Median survival time was 83.8 ± 3.2. Cox regression showed that high vs low educational level (Hazard ratio (HR)= 0.35, 95% CI; 0.27-0.46), metastases to bone (HR = 3.22, 95% CI: 1.71-6.05), metastases to lung (HR= 2.314, 95% CI: 1.225-4.373), tumor size (≤ 2 cm vs ≥ 5 cm: HR = 1.4, 95% CI: 1.1-1.8) and number of involved nodes (1 vs > 10 HR = 5.21, 95%CI: 3.1-9.01) were significantly related to survival. The results showed the need to develop screening programs and standardized treatment regimens in a tax-funded health care system.

  19. PROGNOSTIC FACTORS FOR SURVIVAL IN PATIENTS WITH METASTATIC COLORECTAL CANCER TREATED WITH FIRST - LINE CHEMOTHERAPY

    Directory of Open Access Journals (Sweden)

    Deyan Davidov

    2017-05-01

    Full Text Available Objective: The aim of this study was to investigate the prognostic significance for survival of certain clinical and pathological factors in patients with advanced or metastatic colorectal carcinoma (CRC treated with first- line chemotherapy. Methods: From 2002 to 2011 seventy- four consecutive patients with advanced or metastatic CRC, treated in UMHAT- Dr. G. Stranski, Department of Medical Oncology entered the study. Some patient’s characteristics, hematological and pathological parameters, were evaluated for their role as predictors of overall survival. The therapeutic regimens included FOLFOX or FOlFIRI. Survival analysis was evaluated by Kaplan- Meier test. The influence of pretreatment characteristics as prognostic factor for survival was analyzed using multivariate stepwise Cox regression analyses. Results: In multivariate analysis a significant correlation was exhibited between survival, poor performance status and multiple sites of metastasis. Variables significantly associated with overall survival in univariate analysis were performance status>1, thrombocytosis, anemia and number of metastatic sites >1. Conclusion: These results indicated that poor performance status, anemia, thrombocytosis as well as multiple site of metastasis could be useful prognostic factors in patients with metastatic CRC.

  20. ER and PR expression and survival after endometrial cancer.

    Science.gov (United States)

    Smith, Deborah; Stewart, Colin J R; Clarke, Edward M; Lose, Felicity; Davies, Claire; Armes, Jane; Obermair, Andreas; Brennan, Donal; Webb, Penelope M; Nagle, Christina M; Spurdle, Amanda B

    2018-02-01

    To measure association between endometrial carcinoma ER and PR status and endometrial cancer (EC) survival, accounting for inter-observer variation. The intensity and proportion of tumor cell expression of ER and PR in ECs were assessed independently and semi-quantitatively by two pathologists using digital images of duplicate tumor tissue microarrays (TMAs). Cases with inconsistent initial assessment were reviewed and final scoring agreed. The association between overall and EC-specific survival and hormone receptor expression (intensity, proportion and combined) was assessed using Cox regression analysis. The C-index was used to evaluate model discrimination with addition of ER and PR status. Tumor ER and PR analysis was possible in 659 TMAs from 255 patients, and in 459 TMAs from 243 patients, respectively. Initial ER and PR scoring was consistent in 82% and 80% of cases, respectively. In multivariate analyses decreased ER and PR expression was associated with increased tumor-related mortality. Associations reached statistical significance for ER proportion score (P=0.05), ER intensity score (P=0.003), and PR combined score (P=0.04). Decreased expression of combined ER/PR expression was associated with poorer EC-specific survival than decreased expression of either hormone receptor alone (P=0.005). However, hormone receptor status did not significantly improve mortality prediction in individual cases. ER and PR expression combined, using cut-points that capture variation in scoring and across cores, is significantly associated with EC-specific survival in analyses adjusting for known prognostic factors. However, at the individual level, ER and PR expression does not improve mortality prediction. Copyright © 2017 Elsevier Inc. All rights reserved.

  1. Quantile Regression With Measurement Error

    KAUST Repository

    Wei, Ying

    2009-08-27

    Regression quantiles can be substantially biased when the covariates are measured with error. In this paper we propose a new method that produces consistent linear quantile estimation in the presence of covariate measurement error. The method corrects the measurement error induced bias by constructing joint estimating equations that simultaneously hold for all the quantile levels. An iterative EM-type estimation algorithm to obtain the solutions to such joint estimation equations is provided. The finite sample performance of the proposed method is investigated in a simulation study, and compared to the standard regression calibration approach. Finally, we apply our methodology to part of the National Collaborative Perinatal Project growth data, a longitudinal study with an unusual measurement error structure. © 2009 American Statistical Association.

  2. Recognising out-of-hospital cardiac arrest during emergency calls increases bystander cardiopulmonary resuscitation and survival.

    Science.gov (United States)

    Viereck, Søren; Møller, Thea Palsgaard; Ersbøll, Annette Kjær; Bækgaard, Josefine Stokholm; Claesson, Andreas; Hollenberg, Jacob; Folke, Fredrik; Lippert, Freddy K

    2017-06-01

    Initiation of early bystander cardiopulmonary resuscitation (CPR) depends on bystanders' or medical dispatchers' recognition of out-of-hospital cardiac arrest (OHCA). The primary aim of our study was to investigate if OHCA recognition during the emergency call was associated with bystander CPR, return of spontaneous circulation (ROSC), and 30-day survival. Our secondary aim was to identify patient-, setting-, and dispatcher-related predictors of OHCA recognition. We performed an observational study of all OHCA patients' emergency calls in the Capital Region of Denmark from 01/01/2013-31/12/2013. OHCAs were collected from the Danish Cardiac Arrest Registry and the Mobile Critical Care Unit database. Emergency call recordings were identified and evaluated. Multivariable logistic regression analyses were applied to all OHCAs and witnessed OHCAs only to analyse the association between OHCA recognition and bystander CPR, ROSC, and 30-day survival. Univariable logistic regression analyses were applied to identify predictors of OHCA recognition. We included 779 emergency calls in the analyses. During the emergency calls, 70.1% (n=534) of OHCAs were recognised; OHCA recognition was positively associated with bystander CPR (odds ratio [OR]=7.84, 95% confidence interval [CI]: 5.10-12.05) in all OHCAs; and ROSC (OR=1.86, 95% CI: 1.13-3.06) and 30-day survival (OR=2.80, 95% CI: 1.58-4.96) in witnessed OHCA. Predictors of OHCA recognition were addressing breathing (OR=1.76, 95% CI: 1.17-2.66) and callers located by the patient's side (OR=2.16, 95% CI: 1.46-3.19). Recognition of OHCA during emergency calls was positively associated with the provision of bystander CPR, ROSC, and 30-day survival in witnessed OHCA. Copyright © 2017 The Authors. Published by Elsevier B.V. All rights reserved.

  3. Multivariate and semiparametric kernel regression

    OpenAIRE

    Härdle, Wolfgang; Müller, Marlene

    1997-01-01

    The paper gives an introduction to theory and application of multivariate and semiparametric kernel smoothing. Multivariate nonparametric density estimation is an often used pilot tool for examining the structure of data. Regression smoothing helps in investigating the association between covariates and responses. We concentrate on kernel smoothing using local polynomial fitting which includes the Nadaraya-Watson estimator. Some theory on the asymptotic behavior and bandwidth selection is pro...

  4. Regression algorithm for emotion detection

    OpenAIRE

    Berthelon , Franck; Sander , Peter

    2013-01-01

    International audience; We present here two components of a computational system for emotion detection. PEMs (Personalized Emotion Maps) store links between bodily expressions and emotion values, and are individually calibrated to capture each person's emotion profile. They are an implementation based on aspects of Scherer's theoretical complex system model of emotion~\\cite{scherer00, scherer09}. We also present a regression algorithm that determines a person's emotional feeling from sensor m...

  5. Directional quantile regression in R

    Czech Academy of Sciences Publication Activity Database

    Boček, Pavel; Šiman, Miroslav

    2017-01-01

    Roč. 53, č. 3 (2017), s. 480-492 ISSN 0023-5954 R&D Projects: GA ČR GA14-07234S Institutional support: RVO:67985556 Keywords : multivariate quantile * regression quantile * halfspace depth * depth contour Subject RIV: BD - Theory of Information OBOR OECD: Applied mathematics Impact factor: 0.379, year: 2016 http://library.utia.cas.cz/separaty/2017/SI/bocek-0476587.pdf

  6. Cross-validation and Peeling Strategies for Survival Bump Hunting using Recursive Peeling Methods

    Science.gov (United States)

    Dazard, Jean-Eudes; Choe, Michael; LeBlanc, Michael; Rao, J. Sunil

    2015-01-01

    We introduce a framework to build a survival/risk bump hunting model with a censored time-to-event response. Our Survival Bump Hunting (SBH) method is based on a recursive peeling procedure that uses a specific survival peeling criterion derived from non/semi-parametric statistics such as the hazards-ratio, the log-rank test or the Nelson--Aalen estimator. To optimize the tuning parameter of the model and validate it, we introduce an objective function based on survival or prediction-error statistics, such as the log-rank test and the concordance error rate. We also describe two alternative cross-validation techniques adapted to the joint task of decision-rule making by recursive peeling and survival estimation. Numerical analyses show the importance of replicated cross-validation and the differences between criteria and techniques in both low and high-dimensional settings. Although several non-parametric survival models exist, none addresses the problem of directly identifying local extrema. We show how SBH efficiently estimates extreme survival/risk subgroups unlike other models. This provides an insight into the behavior of commonly used models and suggests alternatives to be adopted in practice. Finally, our SBH framework was applied to a clinical dataset. In it, we identified subsets of patients characterized by clinical and demographic covariates with a distinct extreme survival outcome, for which tailored medical interventions could be made. An R package PRIMsrc (Patient Rule Induction Method in Survival, Regression and Classification settings) is available on CRAN (Comprehensive R Archive Network) and GitHub. PMID:27034730

  7. Polylinear regression analysis in radiochemistry

    International Nuclear Information System (INIS)

    Kopyrin, A.A.; Terent'eva, T.N.; Khramov, N.N.

    1995-01-01

    A number of radiochemical problems have been formulated in the framework of polylinear regression analysis, which permits the use of conventional mathematical methods for their solution. The authors have considered features of the use of polylinear regression analysis for estimating the contributions of various sources to the atmospheric pollution, for studying irradiated nuclear fuel, for estimating concentrations from spectral data, for measuring neutron fields of a nuclear reactor, for estimating crystal lattice parameters from X-ray diffraction patterns, for interpreting data of X-ray fluorescence analysis, for estimating complex formation constants, and for analyzing results of radiometric measurements. The problem of estimating the target parameters can be incorrect at certain properties of the system under study. The authors showed the possibility of regularization by adding a fictitious set of data open-quotes obtainedclose quotes from the orthogonal design. To estimate only a part of the parameters under consideration, the authors used incomplete rank models. In this case, it is necessary to take into account the possibility of confounding estimates. An algorithm for evaluating the degree of confounding is presented which is realized using standard software or regression analysis

  8. The association of cancer survival with four socioeconomic indicators: a longitudinal study of the older population of England and Wales 1981–2000

    Directory of Open Access Journals (Sweden)

    Young Harriet

    2007-01-01

    Full Text Available Abstract Background Many studies have found socioeconomic differentials in cancer survival. Previous studies have generally demonstrated poorer cancer survival with decreasing socioeconomic status but mostly used only ecological measures of status and analytical methods estimating simple survival. This study investigate socio-economic differentials in cancer survival using four indicators of socioeconomic status; three individual and one ecological. It uses a relative survival method which gives a measure of excess mortality due to cancer. Methods This study uses prospective record linkage data from The Office for National Statistics Longitudinal Study for England and Wales. The participants are Longitudinal Study members, recorded at census in 1971 and 1981 and with a primary malignant cancer diagnosed at age 45 or above, between 1981 and 1997, with follow-up until end 2000. The outcome measure is relative survival/excess mortality, compared with age and sex adjusted survival of the general population. Relative survival and Poisson regression analyses are presented, giving models of relative excess mortality, adjusted for covariates. Results Different socioeconomic indicators detect survival differentials of varying magnitude and definition. For all cancers combined, the four indicators show similar effects. For individual cancers there are differences between indicators. Where there is an association, all indicators show poorer survival with lower socioeconomic status. Conclusion Cancer survival differs markedly by socio-economic status. The commonly used ecological measure, the Carstairs Index, is adequate at demonstrating socioeconomic differentials in survival for combined cancers and some individual cancers. A combination of car access and housing tenure is more sensitive than the ecological Carstairs measure at detecting socioeconomic effects on survival – confirming Carstairs effects where they occur but additionally identifying

  9. Gaussian Process Regression Model in Spatial Logistic Regression

    Science.gov (United States)

    Sofro, A.; Oktaviarina, A.

    2018-01-01

    Spatial analysis has developed very quickly in the last decade. One of the favorite approaches is based on the neighbourhood of the region. Unfortunately, there are some limitations such as difficulty in prediction. Therefore, we offer Gaussian process regression (GPR) to accommodate the issue. In this paper, we will focus on spatial modeling with GPR for binomial data with logit link function. The performance of the model will be investigated. We will discuss the inference of how to estimate the parameters and hyper-parameters and to predict as well. Furthermore, simulation studies will be explained in the last section.

  10. Regression analysis of censored data using pseudo-observations

    DEFF Research Database (Denmark)

    Parner, Erik T.; Andersen, Per Kragh

    2010-01-01

    We draw upon a series of articles in which a method based on pseu- dovalues is proposed for direct regression modeling of the survival function, the restricted mean, and the cumulative incidence function in competing risks with right-censored data. The models, once the pseudovalues have been...... computed, can be fit using standard generalized estimating equation software. Here we present Stata procedures for computing these pseudo-observations. An example from a bone marrow transplantation study is used to illustrate the method....

  11. Simultaneous confidence bands for Cox regression from semiparametric random censorship.

    Science.gov (United States)

    Mondal, Shoubhik; Subramanian, Sundarraman

    2016-01-01

    Cox regression is combined with semiparametric random censorship models to construct simultaneous confidence bands (SCBs) for subject-specific survival curves. Simulation results are presented to compare the performance of the proposed SCBs with the SCBs that are based only on standard Cox. The new SCBs provide correct empirical coverage and are more informative. The proposed SCBs are illustrated with two real examples. An extension to handle missing censoring indicators is also outlined.

  12. Time dependent ethnic convergence in colorectal cancer survival in hawaii

    Directory of Open Access Journals (Sweden)

    Hundahl Scott A

    2003-02-01

    Full Text Available Abstract Background Although colorectal cancer death rates have been declining, this trend is not consistent across all ethnic groups. Biological, environmental, behavioral and socioeconomic explanations exist, but the reason for this discrepancy remains inconclusive. We examined the hypothesis that improved cancer screening across all ethnic groups will reduce ethnic differences in colorectal cancer survival. Methods Through the Hawaii Tumor Registry 16,424 patients diagnosed with colorectal cancer were identified during the years 1960–2000. Cox regression analyses were performed for each of three cohorts stratified by ethnicity (Caucasian, Japanese, Hawaiian, Filipino, and Chinese. The models included stage of diagnosis, year of diagnosis, age, and sex as predictors of survival. Results Mortality rates improved significantly for all ethnic groups. Moreover, with the exception of Hawaiians, rates for all ethnic groups converged over time. Persistently lower survival for Hawaiians appeared linked with more cancer treatment. Conclusion Ethnic disparities in colorectal cancer mortality rates appear primarily the result of differential utilization of health care. If modern screening procedures can be provided equally to all ethnic groups, ethnic outcome differences can be virtually eliminated.

  13. Tutorial on Using Regression Models with Count Outcomes Using R

    Directory of Open Access Journals (Sweden)

    A. Alexander Beaujean

    2016-02-01

    Full Text Available Education researchers often study count variables, such as times a student reached a goal, discipline referrals, and absences. Most researchers that study these variables use typical regression methods (i.e., ordinary least-squares either with or without transforming the count variables. In either case, using typical regression for count data can produce parameter estimates that are biased, thus diminishing any inferences made from such data. As count-variable regression models are seldom taught in training programs, we present a tutorial to help educational researchers use such methods in their own research. We demonstrate analyzing and interpreting count data using Poisson, negative binomial, zero-inflated Poisson, and zero-inflated negative binomial regression models. The count regression methods are introduced through an example using the number of times students skipped class. The data for this example are freely available and the R syntax used run the example analyses are included in the Appendix.

  14. A Simple Linear Regression Method for Quantitative Trait Loci Linkage Analysis With Censored Observations

    OpenAIRE

    Anderson, Carl A.; McRae, Allan F.; Visscher, Peter M.

    2006-01-01

    Standard quantitative trait loci (QTL) mapping techniques commonly assume that the trait is both fully observed and normally distributed. When considering survival or age-at-onset traits these assumptions are often incorrect. Methods have been developed to map QTL for survival traits; however, they are both computationally intensive and not available in standard genome analysis software packages. We propose a grouped linear regression method for the analysis of continuous survival data. Using...

  15. Individual social capital and survival

    DEFF Research Database (Denmark)

    Ejlskov, Linda; Mortensen, Rikke N; Overgaard, Charlotte

    2014-01-01

    BACKGROUND: The concept of social capital has received increasing attention as a determinant of population survival, but its significance is uncertain. We examined the importance of social capital on survival in a population study while focusing on gender differences. METHODS: We used data from...... a Danish regional health survey with a five-year follow-up period, 2007-2012 (n = 9288, 53.5% men, 46.5% women). We investigated the association between social capital and all-cause mortality, performing separate analyses on a composite measure as well as four specific dimensions of social capital while...... controlling for covariates. Analyses were performed with Cox proportional hazard models by which hazard ratios and 95% confidence intervals were calculated. RESULTS: For women, higher levels of social capital were associated with lower all-cause mortality regardless of age, socioeconomic status, health...

  16. Age of blood and survival after massive transfusion.

    Science.gov (United States)

    Sanz, C C; Pereira, A

    2017-11-01

    Massive transfusion is the clinical scenario where the presumed adverse effects of stored blood are expected to be more evident because the whole patient's blood volume is replaced by stored blood. To analyse the association between age of transfused red blood cells (RBC) and survival in massively transfused patients. In this retrospective study, clinical and transfusion data of all consecutive patients massively transfused between 2008 and 2014 in a large, tertiary-care hospital were electronically extracted from the Transfusion Service database and the patients' electronic medical records. Prognostic factors for in-hospital mortality were investigated by multivariate logistic regression. A total of 689 consecutive patients were analysed (median age: 61 years; 65% males) and 272 died in-hospital. Projected mortality at 2, 30, and 90 days was 21%, 35% and 45%, respectively. The odds ratio (OR) for in-hospital mortality among patients who survived after the 2nd day increased with patient age (OR: 1.037, 95% CI: 1.021-1.054; per year Ptransfused in the first 48hours (OR: 1.060; 95% CI: 1.038-1.020 per unit; Ptransfusion was associated with a higher proportion of old RBCs transfused in the first 48hours. Other factors associated with poor prognosis were older patient's age and larger volumes of transfused RBCs. Copyright © 2017 Elsevier Masson SAS. All rights reserved.

  17. Spontaneous regression of pulmonary bullae

    International Nuclear Information System (INIS)

    Satoh, H.; Ishikawa, H.; Ohtsuka, M.; Sekizawa, K.

    2002-01-01

    The natural history of pulmonary bullae is often characterized by gradual, progressive enlargement. Spontaneous regression of bullae is, however, very rare. We report a case in which complete resolution of pulmonary bullae in the left upper lung occurred spontaneously. The management of pulmonary bullae is occasionally made difficult because of gradual progressive enlargement associated with abnormal pulmonary function. Some patients have multiple bulla in both lungs and/or have a history of pulmonary emphysema. Others have a giant bulla without emphysematous change in the lungs. Our present case had treated lung cancer with no evidence of local recurrence. He had no emphysematous change in lung function test and had no complaints, although the high resolution CT scan shows evidence of underlying minimal changes of emphysema. Ortin and Gurney presented three cases of spontaneous reduction in size of bulla. Interestingly, one of them had a marked decrease in the size of a bulla in association with thickening of the wall of the bulla, which was observed in our patient. This case we describe is of interest, not only because of the rarity with which regression of pulmonary bulla has been reported in the literature, but also because of the spontaneous improvements in the radiological picture in the absence of overt infection or tumor. Copyright (2002) Blackwell Science Pty Ltd

  18. Quantum algorithm for linear regression

    Science.gov (United States)

    Wang, Guoming

    2017-07-01

    We present a quantum algorithm for fitting a linear regression model to a given data set using the least-squares approach. Differently from previous algorithms which yield a quantum state encoding the optimal parameters, our algorithm outputs these numbers in the classical form. So by running it once, one completely determines the fitted model and then can use it to make predictions on new data at little cost. Moreover, our algorithm works in the standard oracle model, and can handle data sets with nonsparse design matrices. It runs in time poly( log2(N ) ,d ,κ ,1 /ɛ ) , where N is the size of the data set, d is the number of adjustable parameters, κ is the condition number of the design matrix, and ɛ is the desired precision in the output. We also show that the polynomial dependence on d and κ is necessary. Thus, our algorithm cannot be significantly improved. Furthermore, we also give a quantum algorithm that estimates the quality of the least-squares fit (without computing its parameters explicitly). This algorithm runs faster than the one for finding this fit, and can be used to check whether the given data set qualifies for linear regression in the first place.

  19. Interpretation of commonly used statistical regression models.

    Science.gov (United States)

    Kasza, Jessica; Wolfe, Rory

    2014-01-01

    A review of some regression models commonly used in respiratory health applications is provided in this article. Simple linear regression, multiple linear regression, logistic regression and ordinal logistic regression are considered. The focus of this article is on the interpretation of the regression coefficients of each model, which are illustrated through the application of these models to a respiratory health research study. © 2013 The Authors. Respirology © 2013 Asian Pacific Society of Respirology.

  20. Multiple regression and beyond an introduction to multiple regression and structural equation modeling

    CERN Document Server

    Keith, Timothy Z

    2014-01-01

    Multiple Regression and Beyond offers a conceptually oriented introduction to multiple regression (MR) analysis and structural equation modeling (SEM), along with analyses that flow naturally from those methods. By focusing on the concepts and purposes of MR and related methods, rather than the derivation and calculation of formulae, this book introduces material to students more clearly, and in a less threatening way. In addition to illuminating content necessary for coursework, the accessibility of this approach means students are more likely to be able to conduct research using MR or SEM--and more likely to use the methods wisely. Covers both MR and SEM, while explaining their relevance to one another Also includes path analysis, confirmatory factor analysis, and latent growth modeling Figures and tables throughout provide examples and illustrate key concepts and techniques For additional resources, please visit: http://tzkeith.com/.

  1. Estimating haplotype effects for survival data

    DEFF Research Database (Denmark)

    Scheike, Thomas; Martinussen, Torben; Silver, J

    2010-01-01

    Genetic association studies often investigate the effect of haplotypes on an outcome of interest. Haplotypes are not observed directly, and this complicates the inclusion of such effects in survival models. We describe a new estimating equations approach for Cox's regression model to assess haplo...

  2. Fledgling survival increases with development time and adult survival across north and south temperate zones

    Science.gov (United States)

    Lloyd, Penn; Martin, Thomas E.

    2016-01-01

    Slow life histories are characterized by high adult survival and few offspring, which are thought to allow increased investment per offspring to increase juvenile survival. Consistent with this pattern, south temperate zone birds are commonly longer-lived and have fewer young than north temperate zone species. However, comparative analyses of juvenile survival, including during the first few weeks of the post-fledging period when most juvenile mortality occurs, are largely lacking. We combined our measurements of fledgling survival for eight passerines in South Africa with estimates from published studies of 57 north and south temperate zone songbird species to test three predictions: (1) fledgling survival increases with length of development time in the nest; (2) fledgling survival increases with adult survival and reduced brood size controlled for development time; and (3) south temperate zone species, with their higher adult survival and smaller brood sizes, exhibit higher fledgling survival than north temperate zone species controlled for development time. We found that fledgling survival was higher among south temperate zone species and generally increased with development time and adult survival within and between latitudinal regions. Clutch size did not explain additional variation, but was confounded with adult survival. Given the importance of age-specific mortality to life history evolution, understanding the causes of these geographical patterns of mortality is important.

  3. Survival pathways under stress

    Indian Academy of Sciences (India)

    First page Back Continue Last page Graphics. Survival pathways under stress. Bacteria survive by changing gene expression. pattern. Three important pathways will be discussed: Stringent response. Quorum sensing. Proteins performing function to control oxidative damage.

  4. On Weighted Support Vector Regression

    DEFF Research Database (Denmark)

    Han, Xixuan; Clemmensen, Line Katrine Harder

    2014-01-01

    We propose a new type of weighted support vector regression (SVR), motivated by modeling local dependencies in time and space in prediction of house prices. The classic weights of the weighted SVR are added to the slack variables in the objective function (OF‐weights). This procedure directly...... shrinks the coefficient of each observation in the estimated functions; thus, it is widely used for minimizing influence of outliers. We propose to additionally add weights to the slack variables in the constraints (CF‐weights) and call the combination of weights the doubly weighted SVR. We illustrate...... the differences and similarities of the two types of weights by demonstrating the connection between the Least Absolute Shrinkage and Selection Operator (LASSO) and the SVR. We show that an SVR problem can be transformed to a LASSO problem plus a linear constraint and a box constraint. We demonstrate...

  5. The effect of health insurance on childhood cancer survival in the United States.

    Science.gov (United States)

    Lee, Jong Min; Wang, Xiaoyan; Ojha, Rohit P; Johnson, Kimberly J

    2017-12-15

    The effect of health insurance on childhood cancer survival has not been well studied. Using Surveillance, Epidemiology, and End Results (SEER) data, this study was designed to assess the association between health insurance status and childhood cancer survival. Data on cancers diagnosed among children less than 15 years old from 2007 to 2009 were obtained from the SEER 18 registries. The effect of health insurance at diagnosis on 5-year childhood cancer mortality was estimated with marginal survival probabilities, restricted mean survival times, and Cox proportional hazards (PH) regression analyses, which were adjusted for age, sex, race/ethnicity, and county-level poverty. Among 8219 childhood cancer cases, the mean survival time was 1.32 months shorter (95% confidence interval [CI], -4.31 to 1.66) after 5 years for uninsured children (n = 131) versus those with private insurance (n = 4297), whereas the mean survival time was 0.62 months shorter (95% CI, -1.46 to 0.22) for children with Medicaid at diagnosis (n = 2838). In Cox PH models, children who were uninsured had a 1.26-fold higher risk of cancer death (95% CI, 0.84-1.90) than those who were privately insured at diagnosis. The risk for those with Medicaid was similar to the risk for those with private insurance at diagnosis (hazard ratio, 1.06; 95% CI, 0.93-1.21). Overall, the results suggest that cancer survival is largely similar for children with Medicaid and those with private insurance at diagnosis. Slightly inferior survival was observed for those who were uninsured in comparison with those with private insurance at diagnosis. The latter result is based on a small number of uninsured children and should be interpreted cautiously. Further study is needed to confirm and clarify the reasons for these patterns. Cancer 2017;123:4878-85. © 2017 American Cancer Society. © 2017 American Cancer Society.

  6. Men and women show similar survival outcome in stage IV breast cancer.

    Science.gov (United States)

    Wu, San-Gang; Zhang, Wen-Wen; Liao, Xu-Lin; Sun, Jia-Yuan; Li, Feng-Yan; Su, Jing-Jun; He, Zhen-Yu

    2017-08-01

    To evaluate the clinicopathological features, patterns of distant metastases, and survival outcome between stage IV male breast cancer (MBC) and female breast cancer (FBC). Patients diagnosed with stage IV MBC and FBC between 2010 and 2013 were included using the Surveillance, Epidemiology, and End Results program. Univariate and multivariate Cox regression analyses were used to analyze risk factors for overall survival (OS). A total of 4997 patients were identified, including 60 MBC and 4937 FBC. Compared with FBC, patients with MBC were associated with a significantly higher rate of estrogen receptor-positive, progesterone receptor-positive, unmarried, lung metastases, and a lower frequency of liver metastases. Univariate and multivariate analyses showed no significant difference in OS between MBC and FBC. In the propensity score-matched population, there was also no difference in survival between MBC and FBC. Multivariate analysis of MBC showed that OS was longer for patients aged 50-69 years and with estrogen receptor-positive disease. There was no significant difference in survival outcome between stage IV MBC and FBC, but significant differences in clinicopathological features and patterns of metastases between the genders. Copyright © 2017 Elsevier Ltd. All rights reserved.

  7. High serum uric acid concentration predicts poor survival in patients with breast cancer.

    Science.gov (United States)

    Yue, Cai-Feng; Feng, Pin-Ning; Yao, Zhen-Rong; Yu, Xue-Gao; Lin, Wen-Bin; Qian, Yuan-Min; Guo, Yun-Miao; Li, Lai-Sheng; Liu, Min

    2017-10-01

    Uric acid is a product of purine metabolism. Recently, uric acid has gained much attraction in cancer. In this study, we aim to investigate the clinicopathological and prognostic significance of serum uric acid concentration in breast cancer patients. A total of 443 female patients with histopathologically diagnosed breast cancer were included. After a mean follow-up time of 56months, survival was analysed using the Kaplan-Meier method. To further evaluate the prognostic significance of uric acid concentrations, univariate and multivariate Cox regression analyses were applied. Of the clinicopathological parameters, uric acid concentration was associated with age, body mass index, ER status and PR status. Univariate analysis identified that patients with increased uric acid concentration had a significantly inferior overall survival (HR 2.13, 95% CI 1.15-3.94, p=0.016). In multivariate analysis, we found that high uric acid concentration is an independent prognostic factor predicting death, but insufficient to predict local relapse or distant metastasis. Kaplan-Meier analysis indicated that high uric acid concentration is related to the poor overall survival (p=0.013). High uric acid concentration predicts poor survival in patients with breast cancer, and might serve as a potential marker for appropriate management of breast cancer patients. Copyright © 2017 Elsevier B.V. All rights reserved.

  8. Determinants of LSIL Regression in Women from a Colombian Cohort

    International Nuclear Information System (INIS)

    Molano, Monica; Gonzalez, Mauricio; Gamboa, Oscar; Ortiz, Natasha; Luna, Joaquin; Hernandez, Gustavo; Posso, Hector; Murillo, Raul; Munoz, Nubia

    2010-01-01

    Objective: To analyze the role of Human Papillomavirus (HPV) and other risk factors in the regression of cervical lesions in women from the Bogota Cohort. Methods: 200 HPV positive women with abnormal cytology were included for regression analysis. The time of lesion regression was modeled using methods for interval censored survival time data. Median duration of total follow-up was 9 years. Results: 80 (40%) women were diagnosed with Atypical Squamous Cells of Undetermined Significance (ASCUS) or Atypical Glandular Cells of Undetermined Significance (AGUS) while 120 (60%) were diagnosed with Low Grade Squamous Intra-epithelial Lesions (LSIL). Globally, 40% of the lesions were still present at first year of follow up, while 1.5% was still present at 5 year check-up. The multivariate model showed similar regression rates for lesions in women with ASCUS/AGUS and women with LSIL (HR= 0.82, 95% CI 0.59-1.12). Women infected with HR HPV types and those with mixed infections had lower regression rates for lesions than did women infected with LR types (HR=0.526, 95% CI 0.33-0.84, for HR types and HR=0.378, 95% CI 0.20-0.69, for mixed infections). Furthermore, women over 30 years had a higher lesion regression rate than did women under 30 years (HR1.53, 95% CI 1.03-2.27). The study showed that the median time for lesion regression was 9 months while the median time for HPV clearance was 12 months. Conclusions: In the studied population, the type of infection and the age of the women are critical factors for the regression of cervical lesions.

  9. Application of principal component regression and partial least squares regression in ultraviolet spectrum water quality detection

    Science.gov (United States)

    Li, Jiangtong; Luo, Yongdao; Dai, Honglin

    2018-01-01

    Water is the source of life and the essential foundation of all life. With the development of industrialization, the phenomenon of water pollution is becoming more and more frequent, which directly affects the survival and development of human. Water quality detection is one of the necessary measures to protect water resources. Ultraviolet (UV) spectral analysis is an important research method in the field of water quality detection, which partial least squares regression (PLSR) analysis method is becoming predominant technology, however, in some special cases, PLSR's analysis produce considerable errors. In order to solve this problem, the traditional principal component regression (PCR) analysis method was improved by using the principle of PLSR in this paper. The experimental results show that for some special experimental data set, improved PCR analysis method performance is better than PLSR. The PCR and PLSR is the focus of this paper. Firstly, the principal component analysis (PCA) is performed by MATLAB to reduce the dimensionality of the spectral data; on the basis of a large number of experiments, the optimized principal component is extracted by using the principle of PLSR, which carries most of the original data information. Secondly, the linear regression analysis of the principal component is carried out with statistic package for social science (SPSS), which the coefficients and relations of principal components can be obtained. Finally, calculating a same water spectral data set by PLSR and improved PCR, analyzing and comparing two results, improved PCR and PLSR is similar for most data, but improved PCR is better than PLSR for data near the detection limit. Both PLSR and improved PCR can be used in Ultraviolet spectral analysis of water, but for data near the detection limit, improved PCR's result better than PLSR.

  10. Disparities in survival after Hodgkin lymphoma: a population-based study

    Science.gov (United States)

    Keegan, Theresa H.M.; Clarke, Christina A.; Chang, Ellen T.; Shema, Sarah J.; Glaser, Sally L.

    2009-01-01

    Survival after Hodgkin lymphoma (HL) is generally favorable, but may vary by patient demographic characteristics. The authors examined HL survival according to race/ethnicity and neighborhood socioeconomic status (SES), determined from residential census block group at diagnosis. For 12,492 classical HL patients ≥15 years diagnosed in California during 1988-2006 and followed through 2007, we determined risk of overall and HL-specific death using Cox proportional hazards regression; analyses were stratified by age and Ann Arbor stage. Irrespective of disease stage, patients with lower neighborhood SES had worse overall and HL-specific survival than patients with higher SES. Patients with the lowest quintile of neighborhood SES had a 64% (patients aged 15-44 years) and 36% (≥45 years) increased risk of HL-death compared to patients with the highest quintile of SES; SES results were similar for overall survival. Even after adjustment for neighborhood SES, blacks and Hispanics had increased risks of HL-death 74% and 43% (15-44 years) and 40% and 17% (≥45 years), respectively, higher than white patients. The racial/ethnic differences in survival were evident for all stages of disease. These data provide evidence for substantial, and probably remediable, racial/ethnic and neighborhood SES disparities in HL outcomes. PMID:19557531

  11. Marital status and survival in patients with rectal cancer: A population-based STROBE cohort study.

    Science.gov (United States)

    Li, Zhuyue; Wang, Kang; Zhang, Xuemei; Wen, Jin

    2018-05-01

    To examine the impact of marital status on overall survival (OS) and rectal cancer-specific survival (RCSS) for aged patients.We used the Surveillance, Epidemiology and End Results database to identify aged patients (>65 years) with early stage rectal cancer (RC) (T1-T4, N0, M0) in the United States from 2004 to 2010. Propensity score matching was conducted to avoid potential confounding factors with ratio at 1:1. We used Kaplan-Meier to compare OS and RCSS between the married patients and the unmarried, respectively. We used cox proportion hazard regressions to obtain hazard rates for OS, and proportional subdistribution hazard model was performed to calculate hazard rates for RCSS.Totally, 5196 patients were included. The married (2598 [50%]) aged patients had better crude 5-year overall survival rate (64.2% vs 57.3%, P vs 75.9%, P unmarried (2598 (50%)), respectively. In multivariate analyses, married patients had significantly lower overall death than unmarried patients (HR = 0.77, 95% CI = 0.71-0.83, P married patients had no cancer-specific survival benefit versus the unmarried aged patients (HR = 0.92, 95% CI = 0.81-1.04, P = .17).Among old population, married patients with early stage RC had better OS than the unmarried, while current evidence showed that marital status might have no protective effect on cancer-specific survival.

  12. Impact of Marital Status on Tumor Stage at Diagnosis and on Survival in Male Breast Cancer.

    Science.gov (United States)

    Adekolujo, Orimisan Samuel; Tadisina, Shourya; Koduru, Ujwala; Gernand, Jill; Smith, Susan Jane; Kakarala, Radhika Ramani

    2017-07-01

    The effect of marital status (MS) on survival varies according to cancer type and gender. There has been no report on the impact of MS on survival in male breast cancer (MBC). This study aims to determine the influence of MS on tumor stage at diagnosis and survival in MBC. Men with MBC ≥18 years of age in the SEER database from 1990 to 2011 were included in the study. MS was classified as married and unmarried (including single, divorced, separated, widowed). Kaplan-Meier method was used to estimate the 5-year cancer-specific survival. Multivariate regression analyses were done to determine the effect of MS on presence of Stage IV disease at diagnosis and on cancer-specific mortality. The study included 3,761 men; 2,647 (70.4%) were married. Unmarried men were more often diagnosed with Stage IV MBC compared with married (10.7% vs. 5.5%, p Unmarried men (compared with married) were significantly less likely to undergo surgery (92.4% vs. 96.7%, p unmarried males with Stages II, III, and IV MBC have significantly worse 5-year cancer-specific survival compared with married. On multivariate analysis, being unmarried was associated with increased hazard of death (HR = 1.43, p Unmarried males with breast cancer are at greater risk for Stage IV disease at diagnosis and poorer outcomes compared with married males.

  13. Survival and clinical outcome of dogs with ischaemic stroke

    DEFF Research Database (Denmark)

    Gredal, Hanne Birgit; Toft, Nils; Westrup, Ulrik

    2013-01-01

    The objectives of the present study were to investigate survival time, possible predictors of survival and clinical outcome in dogs with ischaemic stroke. A retrospective study of dogs with a previous diagnosis of ischaemic stroke diagnosed by magnetic resonance imaging (MRI) was performed....... The association between survival and the hypothesised risk factors was examined using univariable exact logistic regression. Survival was examined using Kaplan-Meier and Cox regression. Twenty-two dogs were identified. Five dogs (23%) died within the first 30days of the stroke event. Median survival in 30-day...... survivors was 505days. Four dogs (18%) were still alive by the end of the study. Right-sided lesions posed a significantly increased risk of mortality with a median survival time in dogs with right-sided lesions of 24days vs. 602days in dogs with left sided lesions (P=0.006). Clinical outcome was considered...

  14. The influence of sarcopenia on survival and surgical complications in ovarian cancer patients undergoing primary debulking surgery.

    Science.gov (United States)

    Rutten, I J G; Ubachs, J; Kruitwagen, R F P M; van Dijk, D P J; Beets-Tan, R G H; Massuger, L F A G; Olde Damink, S W M; Van Gorp, T

    2017-04-01

    Sarcopenia, severe skeletal muscle loss, has been identified as a prognostic factor in various malignancies. This study aims to investigate whether sarcopenia is associated with overall survival (OS) and surgical complications in patients with advanced ovarian cancer undergoing primary debulking surgery (PDS). Ovarian cancer patients (n = 216) treated with PDS were enrolled retrospectively. Total skeletal muscle surface area was measured on axial computed tomography at the level of the third lumbar vertebra. Optimum stratification was used to find the optimal skeletal muscle index cut-off to define sarcopenia (≤38.73 cm 2 /m 2 ). Cox-regression and Kaplan-Meier analysis were used to analyse the relationship between sarcopenia and OS. The effect of sarcopenia on the development of major surgical complications was studied with logistic regression. Kaplan-Meier analysis showed a significant survival disadvantage for patients with sarcopenia compared to patients without sarcopenia (p = 0.010). Sarcopenia univariably predicted OS (HR 1.536 (95% CI 1.105-2.134), p = 0.011) but was not significant in multivariable Cox-regression analysis (HR 1.362 (95% CI 0.968-1.916), p = 0.076). Significant predictors for OS in multivariable Cox-regression analysis were complete PDS, treatment in a specialised centre and the development of major complications. Sarcopenia was not predictive of major complications. Sarcopenia was not predictive of OS or major complications in ovarian cancer patients undergoing primary debulking surgery. However a strong trend towards a survival disadvantage for patients with sarcopenia was seen. Future prospective studies should focus on interventions to prevent or reverse sarcopenia and possibly increase ovarian cancer survival. Complete cytoreduction remains the strongest predictor of ovarian cancer survival. Copyright © 2017 Elsevier Ltd, BASO ~ The Association for Cancer Surgery, and the European Society of Surgical Oncology. All rights

  15. Credit Scoring Problem Based on Regression Analysis

    OpenAIRE

    Khassawneh, Bashar Suhil Jad Allah

    2014-01-01

    ABSTRACT: This thesis provides an explanatory introduction to the regression models of data mining and contains basic definitions of key terms in the linear, multiple and logistic regression models. Meanwhile, the aim of this study is to illustrate fitting models for the credit scoring problem using simple linear, multiple linear and logistic regression models and also to analyze the found model functions by statistical tools. Keywords: Data mining, linear regression, logistic regression....

  16. [Medulloblastoma: improved survival in recent decades. Unicentric experience].

    Science.gov (United States)

    Igual Estellés, Lucía; Berlanga Charriel, Pablo; Cañete Nieto, Adela

    2017-01-01

    The aim of the study is to analyse variations in the treatment of medulloblastoma, the most common childhood brain tumour, and its impact on survival over the past two decades, as well as its clinical and pathological features. Survival analysis of all patients under 14 years old diagnosed with medulloblastoma between January 1990 and December 2013 in a Paediatric Oncology Unit. Sixty-three patients were diagnosed and treated for medulloblastoma, with a median follow-up of 5.1 years (range 0.65-21.7 years). The overall survival (OS) at 3 and 5 years was 66±13% and 55±14%, respectively. The OS at 5 years was 44%±25% in patients diagnosed in the 1990's, showing an increase to 70%±23% (p=0.032) since 2000. Clinical prognosis factors were included in the logistic regression model: age (p=0.008), presence of metastases and/or residual tumour (p=0.007), and receiving chemotherapy with radiotherapy after surgery (p=0.008). Statistically significant differences were observed for all of them. In our institution there has been a significant increase in medulloblastoma survival in the last decades. Multivariate analysis showed that this improvement was not related to the date of diagnosis, but with the introduction of chemotherapy in adjuvant treatment. This study confirmed that clinical factors significantly associated with worse outcome were age and presence of metastases at diagnosis. Copyright © 2016 Asociación Española de Pediatría. Publicado por Elsevier España, S.L.U. All rights reserved.

  17. Variable selection and model choice in geoadditive regression models.

    Science.gov (United States)

    Kneib, Thomas; Hothorn, Torsten; Tutz, Gerhard

    2009-06-01

    Model choice and variable selection are issues of major concern in practical regression analyses, arising in many biometric applications such as habitat suitability analyses, where the aim is to identify the influence of potentially many environmental conditions on certain species. We describe regression models for breeding bird communities that facilitate both model choice and variable selection, by a boosting algorithm that works within a class of geoadditive regression models comprising spatial effects, nonparametric effects of continuous covariates, interaction surfaces, and varying coefficients. The major modeling components are penalized splines and their bivariate tensor product extensions. All smooth model terms are represented as the sum of a parametric component and a smooth component with one degree of freedom to obtain a fair comparison between the model terms. A generic representation of the geoadditive model allows us to devise a general boosting algorithm that automatically performs model choice and variable selection.

  18. An Original Stepwise Multilevel Logistic Regression Analysis of Discriminatory Accuracy

    DEFF Research Database (Denmark)

    Merlo, Juan; Wagner, Philippe; Ghith, Nermin

    2016-01-01

    BACKGROUND AND AIM: Many multilevel logistic regression analyses of "neighbourhood and health" focus on interpreting measures of associations (e.g., odds ratio, OR). In contrast, multilevel analysis of variance is rarely considered. We propose an original stepwise analytical approach that disting...

  19. Interpreting Multiple Linear Regression: A Guidebook of Variable Importance

    Science.gov (United States)

    Nathans, Laura L.; Oswald, Frederick L.; Nimon, Kim

    2012-01-01

    Multiple regression (MR) analyses are commonly employed in social science fields. It is also common for interpretation of results to typically reflect overreliance on beta weights, often resulting in very limited interpretations of variable importance. It appears that few researchers employ other methods to obtain a fuller understanding of what…

  20. Network survivability performance

    Science.gov (United States)

    1993-11-01

    This technical report has been developed to address the survivability of telecommunications networks including services. It responds to the need for a common understanding of, and assessment techniques for network survivability, availability, integrity, and reliability. It provides a basis for designing and operating telecommunications networks to user expectations for network survivability and a foundation for continuing industry activities in the subject area. This report focuses on the survivability of both public and private networks and covers a wide range of users. Two frameworks are established for quantifying and categorizing service outages, and for classifying network survivability techniques and measures. The performance of the network survivability techniques is considered; however, recommended objectives are not established for network survivability performance.

  1. Regularized Label Relaxation Linear Regression.

    Science.gov (United States)

    Fang, Xiaozhao; Xu, Yong; Li, Xuelong; Lai, Zhihui; Wong, Wai Keung; Fang, Bingwu

    2018-04-01

    Linear regression (LR) and some of its variants have been widely used for classification problems. Most of these methods assume that during the learning phase, the training samples can be exactly transformed into a strict binary label matrix, which has too little freedom to fit the labels adequately. To address this problem, in this paper, we propose a novel regularized label relaxation LR method, which has the following notable characteristics. First, the proposed method relaxes the strict binary label matrix into a slack variable matrix by introducing a nonnegative label relaxation matrix into LR, which provides more freedom to fit the labels and simultaneously enlarges the margins between different classes as much as possible. Second, the proposed method constructs the class compactness graph based on manifold learning and uses it as the regularization item to avoid the problem of overfitting. The class compactness graph is used to ensure that the samples sharing the same labels can be kept close after they are transformed. Two different algorithms, which are, respectively, based on -norm and -norm loss functions are devised. These two algorithms have compact closed-form solutions in each iteration so that they are easily implemented. Extensive experiments show that these two algorithms outperform the state-of-the-art algorithms in terms of the classification accuracy and running time.

  2. Estimating the exceedance probability of rain rate by logistic regression

    Science.gov (United States)

    Chiu, Long S.; Kedem, Benjamin

    1990-01-01

    Recent studies have shown that the fraction of an area with rain intensity above a fixed threshold is highly correlated with the area-averaged rain rate. To estimate the fractional rainy area, a logistic regression model, which estimates the conditional probability that rain rate over an area exceeds a fixed threshold given the values of related covariates, is developed. The problem of dependency in the data in the estimation procedure is bypassed by the method of partial likelihood. Analyses of simulated scanning multichannel microwave radiometer and observed electrically scanning microwave radiometer data during the Global Atlantic Tropical Experiment period show that the use of logistic regression in pixel classification is superior to multiple regression in predicting whether rain rate at each pixel exceeds a given threshold, even in the presence of noisy data. The potential of the logistic regression technique in satellite rain rate estimation is discussed.

  3. Use of probabilistic weights to enhance linear regression myoelectric control.

    Science.gov (United States)

    Smith, Lauren H; Kuiken, Todd A; Hargrove, Levi J

    2015-12-01

    Clinically available prostheses for transradial amputees do not allow simultaneous myoelectric control of degrees of freedom (DOFs). Linear regression methods can provide simultaneous myoelectric control, but frequently also result in difficulty with isolating individual DOFs when desired. This study evaluated the potential of using probabilistic estimates of categories of gross prosthesis movement, which are commonly used in classification-based myoelectric control, to enhance linear regression myoelectric control. Gaussian models were fit to electromyogram (EMG) feature distributions for three movement classes at each DOF (no movement, or movement in either direction) and used to weight the output of linear regression models by the probability that the user intended the movement. Eight able-bodied and two transradial amputee subjects worked in a virtual Fitts' law task to evaluate differences in controllability between linear regression and probability-weighted regression for an intramuscular EMG-based three-DOF wrist and hand system. Real-time and offline analyses in able-bodied subjects demonstrated that probability weighting improved performance during single-DOF tasks (p linear regression control. Use of probability weights can improve the ability to isolate individual during linear regression myoelectric control, while maintaining the ability to simultaneously control multiple DOFs.

  4. Independent contrasts and PGLS regression estimators are equivalent.

    Science.gov (United States)

    Blomberg, Simon P; Lefevre, James G; Wells, Jessie A; Waterhouse, Mary

    2012-05-01

    We prove that the slope parameter of the ordinary least squares regression of phylogenetically independent contrasts (PICs) conducted through the origin is identical to the slope parameter of the method of generalized least squares (GLSs) regression under a Brownian motion model of evolution. This equivalence has several implications: 1. Understanding the structure of the linear model for GLS regression provides insight into when and why phylogeny is important in comparative studies. 2. The limitations of the PIC regression analysis are the same as the limitations of the GLS model. In particular, phylogenetic covariance applies only to the response variable in the regression and the explanatory variable should be regarded as fixed. Calculation of PICs for explanatory variables should be treated as a mathematical idiosyncrasy of the PIC regression algorithm. 3. Since the GLS estimator is the best linear unbiased estimator (BLUE), the slope parameter estimated using PICs is also BLUE. 4. If the slope is estimated using different branch lengths for the explanatory and response variables in the PIC algorithm, the estimator is no longer the BLUE, so this is not recommended. Finally, we discuss whether or not and how to accommodate phylogenetic covariance in regression analyses, particularly in relation to the problem of phylogenetic uncertainty. This discussion is from both frequentist and Bayesian perspectives.

  5. Survival in Malnourished Older Patients Receiving Post-Discharge Nutritional Support; Long-Term Results of a Randomized Controlled Trial.

    Science.gov (United States)

    Neelemaat, F; van Keeken, S; Langius, J A E; de van der Schueren, M A E; Thijs, A; Bosmans, J E

    2017-01-01

    Previous analyses have shown that a post-discharge individualized nutritional intervention had positive effects on body weight, lean body mass, functional limitations and fall incidents in malnourished older patients. However, the impact of this intervention on survival has not yet been studied. The objective of this randomized controlled study was to examine the effect of a post-discharge individualized nutritional intervention on survival in malnourished older patients. Malnourished older patients, aged ≥ 60 years, were randomized during hospitalization to a three-months post-discharge nutritional intervention group (protein and energy enriched diet, oral nutritional supplements, vitamin D3/calcium supplement and telephone counseling by a dietitian) or to a usual care regimen (control group). Survival data were collected 4 years after enrollment. Survival analyses were performed using intention-to-treat analysis by Log-rank tests and Cox regression adjusted for confounders. The study population consisted of 94 men (45%) and 116 women with a mean age of 74.5 (SD 9.5) years. There were no statistically significant differences in baseline characteristics. Survival data was available in 208 out of 210 patients. After 1 and 4 years of follow-up, survival rates were respectively 66% and 29% in the intervention group (n=104) and 73% and 30% in the control group (n=104). There were no statistically significant differences in survival between the two groups 1 year (HR= 0.933, 95% CI=0.675-1.289) and 4 years after enrollment (HR=0.928, 95% CI=0.671-1.283). The current study failed to show an effect of a three-months post-discharge multi-component nutritional intervention in malnourished older patients on long-term survival, despite the positive effects on short-term outcome such as functional limitations and falls.

  6. Lung cancer incidence and survival among HIV-infected and uninfected women and men.

    Science.gov (United States)

    Hessol, Nancy A; Martínez-Maza, Otoniel; Levine, Alexandra M; Morris, Alison; Margolick, Joseph B; Cohen, Mardge H; Jacobson, Lisa P; Seaberg, Eric C

    2015-06-19

    To determine the lung cancer incidence and survival time among HIV-infected and uninfected women and men. Two longitudinal studies of HIV infection in the United States. Data from 2549 women in the Women's Interagency HIV Study (WIHS) and 4274 men in the Multicenter AIDS Cohort Study (MACS), all with a history of cigarette smoking, were analyzed. Lung cancer incidence rates and incidence rate ratios were calculated using Poisson regression analyses. Survival time was assessed using Kaplan-Meier and Cox proportional-hazard analyses. Thirty-seven women and 23 men developed lung cancer (46 HIV-infected and 14 HIV-uninfected) during study follow-up. In multivariable analyses, the factors that were found to be independently associated with a higher lung cancer incidence rate ratios were older age, less education, 10 or more pack-years of smoking, and a prior diagnosis of AIDS pneumonia (vs. HIV-uninfected women). In an adjusted Cox model that allowed different hazard functions for each cohort, a history of injection drug use was associated with shorter survival, and a lung cancer diagnosis after 2001 was associated with longer survival. In an adjusted Cox model restricted to HIV-infected participants, nadir CD4 lymphocyte cell count less than 200 was associated with shorter survival time. Our data suggest that pulmonary damage and inflammation associated with HIV infection may be causative for the increased risk of lung cancer. Encouraging and assisting younger HIV-infected smokers to quit and to sustain cessation of smoking is imperative to reduce the lung cancer burden in this population.

  7. Combining epidemiologic and biostatistical tools to enhance variable selection in HIV cohort analyses.

    Directory of Open Access Journals (Sweden)

    Christopher Rentsch

    Full Text Available BACKGROUND: Variable selection is an important step in building a multivariate regression model for which several methods and statistical packages are available. A comprehensive approach for variable selection in complex multivariate regression analyses within HIV cohorts is explored by utilizing both epidemiological and biostatistical procedures. METHODS: Three different methods for variable selection were illustrated in a study comparing survival time between subjects in the Department of Defense's National History Study and the Atlanta Veterans Affairs Medical Center's HIV Atlanta VA Cohort Study. The first two methods were stepwise selection procedures, based either on significance tests (Score test, or on information theory (Akaike Information Criterion, while the third method employed a Bayesian argument (Bayesian Model Averaging. RESULTS: All three methods resulted in a similar parsimonious survival model. Three of the covariates previously used in the multivariate model were not included in the final model suggested by the three approaches. When comparing the parsimonious model to the previously published model, there was evidence of less variance in the main survival estimates. CONCLUSIONS: The variable selection approaches considered in this study allowed building a model based on significance tests, on an information criterion, and on averaging models using their posterior probabilities. A parsimonious model that balanced these three approaches was found to provide a better fit than the previously reported model.

  8. Cancer survival classification using integrated data sets and intermediate information.

    Science.gov (United States)

    Kim, Shinuk; Park, Taesung; Kon, Mark

    2014-09-01

    Although numerous studies related to cancer survival have been published, increasing the prediction accuracy of survival classes still remains a challenge. Integration of different data sets, such as microRNA (miRNA) and mRNA, might increase the accuracy of survival class prediction. Therefore, we suggested a machine learning (ML) approach to integrate different data sets, and developed a novel method based on feature selection with Cox proportional hazard regression model (FSCOX) to improve the prediction of cancer survival time. FSCOX provides us with intermediate survival information, which is usually discarded when separating survival into 2 groups (short- and long-term), and allows us to perform survival analysis. We used an ML-based protocol for feature selection, integrating information from miRNA and mRNA expression profiles at the feature level. To predict survival phenotypes, we used the following classifiers, first, existing ML methods, support vector machine (SVM) and random forest (RF), second, a new median-based classifier using FSCOX (FSCOX_median), and third, an SVM classifier using FSCOX (FSCOX_SVM). We compared these methods using 3 types of cancer tissue data sets: (i) miRNA expression, (ii) mRNA expression, and (iii) combined miRNA and mRNA expression. The latter data set included features selected either from the combined miRNA/mRNA profile or independently from miRNAs and mRNAs profiles (IFS). In the ovarian data set, the accuracy of survival classification using the combined miRNA/mRNA profiles with IFS was 75% using RF, 86.36% using SVM, 84.09% using FSCOX_median, and 88.64% using FSCOX_SVM with a balanced 22 short-term and 22 long-term survivor data set. These accuracies are higher than those using miRNA alone (70.45%, RF; 75%, SVM; 75%, FSCOX_median; and 75%, FSCOX_SVM) or mRNA alone (65.91%, RF; 63.64%, SVM; 72.73%, FSCOX_median; and 70.45%, FSCOX_SVM). Similarly in the glioblastoma multiforme data, the accuracy of miRNA/mRNA using IFS

  9. Biostatistics series module 9: Survival analysis

    Directory of Open Access Journals (Sweden)

    Avijit Hazra

    2017-01-01

    Full Text Available Survival analysis is concerned with “time to event“ data. Conventionally, it dealt with cancer death as the event in question, but it can handle any event occurring over a time frame, and this need not be always adverse in nature. When the outcome of a study is the time to an event, it is often not possible to wait until the event in question has happened to all the subjects, for example, until all are dead. In addition, subjects may leave the study prematurely. Such situations lead to what is called censored observations as complete information is not available for these subjects. The data set is thus an assemblage of times to the event in question and times after which no more information on the individual is available. Survival analysis methods are the only techniques capable of handling censored observations without treating them as missing data. They also make no assumption regarding normal distribution of time to event data. Descriptive methods for exploring survival times in a sample include life table and Kaplan–Meier techniques as well as various kinds of distribution fitting as advanced modeling techniques. The Kaplan–Meier cumulative survival probability over time plot has become the signature plot for biomedical survival analysis. Several techniques are available for comparing the survival experience in two or more groups – the log-rank test is popularly used. This test can also be used to produce an odds ratio as an estimate of risk of the event in the test group; this is called hazard ratio (HR. Limitations of the traditional log-rank test have led to various modifications and enhancements. Finally, survival analysis offers different regression models for estimating the impact of multiple predictors on survival. Cox's proportional hazard model is the most general of the regression methods that allows the hazard function to be modeled on a set of explanatory variables without making restrictive assumptions concerning the

  10. Principal component regression analysis with SPSS.

    Science.gov (United States)

    Liu, R X; Kuang, J; Gong, Q; Hou, X L

    2003-06-01

    The paper introduces all indices of multicollinearity diagnoses, the basic principle of principal component regression and determination of 'best' equation method. The paper uses an example to describe how to do principal component regression analysis with SPSS 10.0: including all calculating processes of the principal component regression and all operations of linear regression, factor analysis, descriptives, compute variable and bivariate correlations procedures in SPSS 10.0. The principal component regression analysis can be used to overcome disturbance of the multicollinearity. The simplified, speeded up and accurate statistical effect is reached through the principal component regression analysis with SPSS.

  11. Comparing parametric and nonparametric regression methods for panel data

    DEFF Research Database (Denmark)

    Czekaj, Tomasz Gerard; Henningsen, Arne

    We investigate and compare the suitability of parametric and non-parametric stochastic regression methods for analysing production technologies and the optimal firm size. Our theoretical analysis shows that the most commonly used functional forms in empirical production analysis, Cobb......-Douglas and Translog, are unsuitable for analysing the optimal firm size. We show that the Translog functional form implies an implausible linear relationship between the (logarithmic) firm size and the elasticity of scale, where the slope is artificially related to the substitutability between the inputs....... The practical applicability of the parametric and non-parametric regression methods is scrutinised and compared by an empirical example: we analyse the production technology and investigate the optimal size of Polish crop farms based on a firm-level balanced panel data set. A nonparametric specification test...

  12. Multinationals and plant survival

    DEFF Research Database (Denmark)

    Bandick, Roger

    2010-01-01

    The aim of this paper is twofold: first, to investigate how different ownership structures affect plant survival, and second, to analyze how the presence of foreign multinational enterprises (MNEs) affects domestic plants’ survival. Using a unique and detailed data set on the Swedish manufacturing...... sector, I am able to separate plants into those owned by foreign MNEs, domestic MNEs, exporting non-MNEs, and purely domestic firms. In line with previous findings, the result, when conditioned on other factors affecting survival, shows that foreign MNE plants have lower survival rates than non......-MNE plants. However, separating the non-MNEs into exporters and non-exporters, the result shows that foreign MNE plants have higher survival rates than non-exporting non-MNEs, while the survival rates of foreign MNE plants and exporting non-MNE plants do not seem to differ. Moreover, the simple non...

  13. Perioperative blood transfusion: does it influence survival and cancer progression in metastatic spine tumor surgery?

    Science.gov (United States)

    Zaw, Aye Sandar; Kantharajanna, Shashidhar B; Maharajan, Karthikeyan; Tan, Barry; Vellayappan, Balamurugan; Kumar, Naresh

    2017-02-01

    Despite advances in surgical techniques for spinal metastases, there is often substantial blood loss, resulting in patients requiring blood transfusion during the perioperative period. Allogeneic blood transfusion (ABT) has been the main replenishment method for lost blood. However, the impact of ABT on cancer-related outcomes has been controversial in various studies. We aimed to evaluate the influence of perioperative ABT on disease progression and survival in patients undergoing metastatic spinal tumor surgery (MSTS). We conducted a retrospective study that included 247 patients who underwent MSTS at a single tertiary institution between 2005 and 2014. The impact of using perioperative ABT (either exposure to or quantities of transfusion) on disease progression and survival was assessed using Cox regression analyses while adjusting for potential confounding variables. Of 247 patients, 133 (54%) received ABT. The overall median number of blood units transfused was 2 (range, 0-10 units). Neither blood transfusion exposure nor quantities of transfusion were associated with overall survival (hazard ratio [HR], 1.15 [p = 0.35] and 1.10 [p = 0.11], respectively) and progression-free survival (HR, 0.87 [p = 0.18] and 0.98 [p = 0.11], respectively). The factors that influenced overall survival were primary tumor type and preoperative Eastern Cooperative Oncology Group performance status, whereas primary tumor type was the only factor that had an impact on progression-free survival. This is the first study providing evidence that disease progression and survival in patients who undergo MSTS are less likely to be influenced by perioperative ABT. The worst oncologic outcomes are more likely to be caused by the clinical circumstances necessitating blood transfusion, but not transfusion itself. However, because ABT can have a propensity toward developing postoperative infections, including surgical site infection, the use of patient blood management

  14. Outcome of cardiopulmonary resuscitation - predictors of survival

    International Nuclear Information System (INIS)

    Ishtiaq, O.; Iqbal, M.; Zubair, M.; Qayyum, R.; Adil, M.

    2008-01-01

    To assess the outcomes of patients undergoing cardiopulmonary resuscitation (CPR). Data were collected retrospectively of all adult patients who underwent CPR. Clinical outcomes of interest were survival at the end of CPR and survival at discharge from hospital. Factors associated with survival were evaluated using logistic regression analysis. Of the 159 patients included, 55 (35%) were alive at the end of CPR and 17 (11%) were discharged alive from the hospital. At the end of CPR, univariate logistic regression analysis found the following factors associated with survival: cardiac arrest within hospital as compared to outside the hospital (odds ratio = 2.8, 95% CI = 1.27-6.20, p-value = 0.01), both cardiac and pulmonary arrest as compared to either cardiac or pulmonary arrest (odds ratio = 0.37, 95% CI = 0.19- 0.73, p-value = 0.004), asystole as cardiac rhythm at presentation (odds ratio = 0.47, 95% CI = 0.24-0.93, p-value = 0.03), and total atropine dose given during CPR (odds ratio = 0.78, 95% CI = 0.62-0.97, p-value = 0.02). In multivariate logistic regression, cardiac arrest within hospital (odds ratio = 2.52, 95% CI = 1.06-5.99, p-value = 0.04) and both cardiac and pulmonary arrest as compared to cardiac or pulmonary arrest (odds ratio = 0.44, 95% CI = 0.21-0.91, p-value = 0.03) were associated with survival at the end of CPR. At the time of discharge from hospital, univariate logistic regression analysis found following factors that were associated with survival: cardiac arrest within hospital (odds ratio = 8.4, 95% CI = 1.09-65.64, p-value = 0.04), duration of CPR (odds ratio = 0.91, 95% CI = 0.85-0.96, p-value = 0.001), and total atropine dose given during CPR (odds ratio = 0.68, 95% CI = 0.47-0.99, p-value = 0.05). In multivariate logistic regression analysis cardiac arrest within hospital (odds ratio 8.69, 95% CI = 1.01-74.6, p-value = 0.05) and duration of CPR (odds ratio 0.92, 95% CI = 0.87-0.98, p-value = 0.01) were associated with survival at

  15. Risk factors for pedicled flap necrosis in hand soft tissue reconstruction: a multivariate logistic regression analysis.

    Science.gov (United States)

    Gong, Xu; Cui, Jianli; Jiang, Ziping; Lu, Laijin; Li, Xiucun

    2018-03-01

    Few clinical retrospective studies have reported the risk factors of pedicled flap necrosis in hand soft tissue reconstruction. The aim of this study was to identify non-technical risk factors associated with pedicled flap perioperative necrosis in hand soft tissue reconstruction via a multivariate logistic regression analysis. For patients with hand soft tissue reconstruction, we carefully reviewed hospital records and identified 163 patients who met the inclusion criteria. The characteristics of these patients, flap transfer procedures and postoperative complications were recorded. Eleven predictors were identified. The correlations between pedicled flap necrosis and risk factors were analysed using a logistic regression model. Of 163 skin flaps, 125 flaps survived completely without any complications. The pedicled flap necrosis rate in hands was 11.04%, which included partial flap necrosis (7.36%) and total flap necrosis (3.68%). Soft tissue defects in fingers were noted in 68.10% of all cases. The logistic regression analysis indicated that the soft tissue defect site (P = 0.046, odds ratio (OR) = 0.079, confidence interval (CI) (0.006, 0.959)), flap size (P = 0.020, OR = 1.024, CI (1.004, 1.045)) and postoperative wound infection (P < 0.001, OR = 17.407, CI (3.821, 79.303)) were statistically significant risk factors for pedicled flap necrosis of the hand. Soft tissue defect site, flap size and postoperative wound infection were risk factors associated with pedicled flap necrosis in hand soft tissue defect reconstruction. © 2017 Royal Australasian College of Surgeons.

  16. Unbalanced Regressions and the Predictive Equation

    DEFF Research Database (Denmark)

    Osterrieder, Daniela; Ventosa-Santaulària, Daniel; Vera-Valdés, J. Eduardo

    Predictive return regressions with persistent regressors are typically plagued by (asymptotically) biased/inconsistent estimates of the slope, non-standard or potentially even spurious statistical inference, and regression unbalancedness. We alleviate the problem of unbalancedness in the theoreti......Predictive return regressions with persistent regressors are typically plagued by (asymptotically) biased/inconsistent estimates of the slope, non-standard or potentially even spurious statistical inference, and regression unbalancedness. We alleviate the problem of unbalancedness...

  17. Semiparametric regression during 2003–2007

    KAUST Repository

    Ruppert, David; Wand, M.P.; Carroll, Raymond J.

    2009-01-01

    Semiparametric regression is a fusion between parametric regression and nonparametric regression that integrates low-rank penalized splines, mixed model and hierarchical Bayesian methodology – thus allowing more streamlined handling of longitudinal and spatial correlation. We review progress in the field over the five-year period between 2003 and 2007. We find semiparametric regression to be a vibrant field with substantial involvement and activity, continual enhancement and widespread application.

  18. Gaussian process regression analysis for functional data

    CERN Document Server

    Shi, Jian Qing

    2011-01-01

    Gaussian Process Regression Analysis for Functional Data presents nonparametric statistical methods for functional regression analysis, specifically the methods based on a Gaussian process prior in a functional space. The authors focus on problems involving functional response variables and mixed covariates of functional and scalar variables.Covering the basics of Gaussian process regression, the first several chapters discuss functional data analysis, theoretical aspects based on the asymptotic properties of Gaussian process regression models, and new methodological developments for high dime

  19. Regression Analysis by Example. 5th Edition

    Science.gov (United States)

    Chatterjee, Samprit; Hadi, Ali S.

    2012-01-01

    Regression analysis is a conceptually simple method for investigating relationships among variables. Carrying out a successful application of regression analysis, however, requires a balance of theoretical results, empirical rules, and subjective judgment. "Regression Analysis by Example, Fifth Edition" has been expanded and thoroughly…

  20. Standards for Standardized Logistic Regression Coefficients

    Science.gov (United States)

    Menard, Scott

    2011-01-01

    Standardized coefficients in logistic regression analysis have the same utility as standardized coefficients in linear regression analysis. Although there has been no consensus on the best way to construct standardized logistic regression coefficients, there is now sufficient evidence to suggest a single best approach to the construction of a…

  1. A Seemingly Unrelated Poisson Regression Model

    OpenAIRE

    King, Gary

    1989-01-01

    This article introduces a new estimator for the analysis of two contemporaneously correlated endogenous event count variables. This seemingly unrelated Poisson regression model (SUPREME) estimator combines the efficiencies created by single equation Poisson regression model estimators and insights from "seemingly unrelated" linear regression models.

  2. Extended cox regression model: The choice of timefunction

    Science.gov (United States)

    Isik, Hatice; Tutkun, Nihal Ata; Karasoy, Durdu

    2017-07-01

    Cox regression model (CRM), which takes into account the effect of censored observations, is one the most applicative and usedmodels in survival analysis to evaluate the effects of covariates. Proportional hazard (PH), requires a constant hazard ratio over time, is the assumptionofCRM. Using extended CRM provides the test of including a time dependent covariate to assess the PH assumption or an alternative model in case of nonproportional hazards. In this study, the different types of real data sets are used to choose the time function and the differences between time functions are analyzed and discussed.

  3. Marginal regression analysis of recurrent events with coarsened censoring times.

    Science.gov (United States)

    Hu, X Joan; Rosychuk, Rhonda J

    2016-12-01

    Motivated by an ongoing pediatric mental health care (PMHC) study, this article presents weakly structured methods for analyzing doubly censored recurrent event data where only coarsened information on censoring is available. The study extracted administrative records of emergency department visits from provincial health administrative databases. The available information of each individual subject is limited to a subject-specific time window determined up to concealed data. To evaluate time-dependent effect of exposures, we adapt the local linear estimation with right censored survival times under the Cox regression model with time-varying coefficients (cf. Cai and Sun, Scandinavian Journal of Statistics 2003, 30, 93-111). We establish the pointwise consistency and asymptotic normality of the regression parameter estimator, and examine its performance by simulation. The PMHC study illustrates the proposed approach throughout the article. © 2016, The International Biometric Society.

  4. Incidence, treatment, and survival patterns for sacral chordoma in the United States, 1974-2011

    Directory of Open Access Journals (Sweden)

    Esther Yu

    2016-09-01

    Full Text Available IntroductionSacral chordomas represent one half of all chordomas, a rare neoplasm of notochordal remnants. Current NCCN guidelines recommend surgical resection with or without adjuvant radiotherapy, or definitive radiation for unresectable cases. Recent advances in radiation for chordomas include conformal photon and proton beam radiation. We investigated incidence, treatment, and survival outcomes to observe any trends in response to improvements in surgical and radiation techniques over a near 40 year time period.Materials and Methods345 microscopically confirmed cases of sacral chordoma were identified between 1974 and 2011 from the Surveillance, Epidemiology, and End Results (SEER program of the National Cancer Institute. Cases were divided into three cohorts by calendar year, 1974-1989, 1990-1999, and 2000-2011, as well as into two groups by age less than or equal to 65 versus greater than 65 to investigate trends over time and age via Chi-square analysis. Kaplan-Meier analyses were performed to determine effects of treatment on survival. Multivariate Cox regression analysis was performed to determine predictors of overall survival.Results5-year overall survival for the entire cohort was 60.0%. Overall survival correlated significantly with treatment modality, with 44% surviving at 5 years with no treatment, 52% with radiation alone, 82% surgery alone, and 78% surgery and radiation (p<.001. Age greater than 65 was significantly associated with non-surgical management with radiation alone or no treatment (p<.001. Relatively fewer patients received radiation between 2000 and 2011 compared to prior time periods (p=.03 versus surgery, for which rates which did not vary significantly over time (p=.55. However, 5-year overall survival was not significantly different by time period. Age group and treatment modality were predictive for overall survival on multivariate analysis (p<.001. ConclusionSurgery remains an important component in the

  5. PARAMETRIC AND NON PARAMETRIC (MARS: MULTIVARIATE ADDITIVE REGRESSION SPLINES) LOGISTIC REGRESSIONS FOR PREDICTION OF A DICHOTOMOUS RESPONSE VARIABLE WITH AN EXAMPLE FOR PRESENCE/ABSENCE OF AMPHIBIANS

    Science.gov (United States)

    The purpose of this report is to provide a reference manual that could be used by investigators for making informed use of logistic regression using two methods (standard logistic regression and MARS). The details for analyses of relationships between a dependent binary response ...

  6. Regression with Sparse Approximations of Data

    DEFF Research Database (Denmark)

    Noorzad, Pardis; Sturm, Bob L.

    2012-01-01

    We propose sparse approximation weighted regression (SPARROW), a method for local estimation of the regression function that uses sparse approximation with a dictionary of measurements. SPARROW estimates the regression function at a point with a linear combination of a few regressands selected...... by a sparse approximation of the point in terms of the regressors. We show SPARROW can be considered a variant of \\(k\\)-nearest neighbors regression (\\(k\\)-NNR), and more generally, local polynomial kernel regression. Unlike \\(k\\)-NNR, however, SPARROW can adapt the number of regressors to use based...

  7. Spontaneous regression of a congenital melanocytic nevus

    Directory of Open Access Journals (Sweden)

    Amiya Kumar Nath

    2011-01-01

    Full Text Available Congenital melanocytic nevus (CMN may rarely regress which may also be associated with a halo or vitiligo. We describe a 10-year-old girl who presented with CMN on the left leg since birth, which recently started to regress spontaneously with associated depigmentation in the lesion and at a distant site. Dermoscopy performed at different sites of the regressing lesion demonstrated loss of epidermal pigments first followed by loss of dermal pigments. Histopathology and Masson-Fontana stain demonstrated lymphocytic infiltration and loss of pigment production in the regressing area. Immunohistochemistry staining (S100 and HMB-45, however, showed that nevus cells were present in the regressing areas.

  8. The Use of Nonparametric Kernel Regression Methods in Econometric Production Analysis

    DEFF Research Database (Denmark)

    Czekaj, Tomasz Gerard

    and nonparametric estimations of production functions in order to evaluate the optimal firm size. The second paper discusses the use of parametric and nonparametric regression methods to estimate panel data regression models. The third paper analyses production risk, price uncertainty, and farmers' risk preferences...... within a nonparametric panel data regression framework. The fourth paper analyses the technical efficiency of dairy farms with environmental output using nonparametric kernel regression in a semiparametric stochastic frontier analysis. The results provided in this PhD thesis show that nonparametric......This PhD thesis addresses one of the fundamental problems in applied econometric analysis, namely the econometric estimation of regression functions. The conventional approach to regression analysis is the parametric approach, which requires the researcher to specify the form of the regression...

  9. Survival after out-of-hospital cardiac arrest in relation to sex: a nationwide registry-based study.

    Science.gov (United States)

    Wissenberg, Mads; Hansen, Carolina Malta; Folke, Fredrik; Lippert, Freddy K; Weeke, Peter; Karlsson, Lena; Rajan, Shahzleen; Søndergaard, Kathrine Bach; Kragholm, Kristian; Christensen, Erika Frischknecht; Nielsen, Søren L; Køber, Lars; Gislason, Gunnar H; Torp-Pedersen, Christian

    2014-09-01

    Crude survival has increased following an out-of-hospital cardiac arrest (OHCA). We aimed to study sex-related differences in patient characteristics and survival during a 10-year study period. Patients≥12 years old with OHCA of a presumed cardiac cause, and in whom resuscitation was attempted, were identified through the Danish Cardiac Arrest Registry 2001-2010. A total of 19,372 patients were included. One-third were female, with a median age of 75 years (IQR 65-83). Compared to females, males were five years younger; and less likely to have severe comorbidities, e.g., chronic obstructive pulmonary disease (12.8% vs. 16.5%); but more likely to have arrest outside of the home (29.4% vs. 18.7%), receive bystander CPR (32.9% vs. 25.9%), and have a shockable rhythm (32.6% vs. 17.2%), all p<0.001. Thirty-day crude survival increased in males (3.0% in 2001 to 12.9% in 2010); and in females (4.8% in 2001 to 6.7% in 2010), p<0.001. Multivariable logistic regression analyses adjusted for patient characteristics including comorbidities, showed no survival difference between sexes in patients with a non-shockable rhythm (OR 1.00; CI 0.72-1.40), while female sex was positively associated with survival in patients with a shockable rhythm (OR 1.31; CI 1.07-1.59). Analyses were rhythm-stratified due to interaction between sex and heart rhythm; there was no interaction between sex and calendar-year. Temporal increase in crude survival was more marked in males due to poorer prognostic characteristics in females with a lower proportion of shockable rhythm. In an adjusted model, female sex was positively associated with survival in patients with a shockable rhythm. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

  10. Delay of Treatment Initiation Does Not Adversely Affect Survival Outcome in Breast Cancer.

    Science.gov (United States)

    Yoo, Tae-Kyung; Han, Wonshik; Moon, Hyeong-Gon; Kim, Jisun; Lee, Jun Woo; Kim, Min Kyoon; Lee, Eunshin; Kim, Jongjin; Noh, Dong-Young

    2016-07-01

    Previous studies examining the relationship between time to treatment and survival outcome in breast cancer have shown inconsistent results. The aim of this study was to analyze the overall impact of delay of treatment initiation on patient survival and to determine whether certain subgroups require more prompt initiation of treatment. This study is a retrospective analysis of stage I-III patients who were treated in a single tertiary institution between 2005 and 2008. Kaplan-Meier survival analysis and Cox proportional hazards regression model were used to evaluate the impact of interval between diagnosis and treatment initiation in breast cancer and various subgroups. A total of 1,702 patients were included. Factors associated with longer delay of treatment initiation were diagnosis at another hospital, medical comorbidities, and procedures performed before admission for surgery. An interval between diagnosis and treatment initiation as a continuous variable or with a cutoff value of 15, 30, 45, and 60 days had no impact on disease-free survival (DFS). Subgroup analyses for hormone-responsiveness, triple-negative breast cancer, young age, clinical stage, and type of initial treatment showed no significant association between longer delay of treatment initiation and DFS. Our results show that an interval between diagnosis and treatment initiation of 60 days or shorter does not appear to adversely affect DFS in breast cancer.

  11. The inflammation-based Glasgow Prognostic Score predicts survival in patients with cervical cancer.

    Science.gov (United States)

    Polterauer, Stephan; Grimm, Christoph; Seebacher, Veronika; Rahhal, Jasmin; Tempfer, Clemens; Reinthaller, Alexander; Hefler, Lukas

    2010-08-01

    The Glasgow Prognostic Score (GPS) is known to reflect the degree of tumor-associated cachexia and inflammation and is associated with survival in various malignancies. We investigated the value of the GPS in patients with cervical cancer. We included 244 consecutive patients with cervical cancer in our study. The pretherapeutic GPS was calculated as follows: patients with elevated C-reactive protein serum levels (>10 mg/L) and hypoalbuminemia (L) were allocated a score of 2, and patients with 1 or no abnormal value were allocated a score of 1 or 0, respectively. The association between GPS and survival was evaluated by univariate log-rank tests and multivariate Cox regression models. The GPS was correlated with clinicopathologic parameters as shown by performing chi2 tests. In univariate analyses, GPS (P GPS (P = 0.03, P = 0.04), FIGO stage (P = 0.006, P = 0.006), and lymph node involvement (P = 0.003, P = 0.002), but not patients' age (P = 0.5, P = 0.5), histological grade (P = 0.7, P = 0.6), and histological type (P = 0.4, P = 0.6) were associated with disease-free and overall survival, respectively. The GPS was associated with FIGO stage (P GPS can be used as an inflammation-based predictor for survival in patients with cervical cancer.

  12. Quality of life assessment as a predictor of survival in non-small cell lung cancer

    Directory of Open Access Journals (Sweden)

    Staren Edgar D

    2011-08-01

    Full Text Available Abstract Background There are conflicting and inconsistent results in the literature on the prognostic role of quality of life (QoL in cancer. We investigated whether QoL at admission could predict survival in lung cancer patients. Methods The study population consisted of 1194 non-small cell lung cancer patients treated at our institution between Jan 2001 and Dec 2008. QoL was evaluated using EORTC-QLQ-C30 prior to initiation of treatment. Patient survival was defined as the time interval between the date of first patient visit and the date of death from any cause/date of last contact. Univariate and multivariate Cox regression evaluated the prognostic significance of QoL. Results Mean age at presentation was 58.3 years. There were 605 newly diagnosed and 589 previously treated patients; 601 males and 593 females. Stage of disease at diagnosis was I, 100; II, 63; III, 348; IV, 656; and 27 indeterminate. Upon multivariate analyses, global QoL as well as physical function predicted patient survival in the entire study population. Every 10-point increase in physical function was associated with a 10% increase in survival (95% CI = 6% to 14%, p Conclusions Baseline global QoL and physical function provide useful prognostic information in non-small cell lung cancer patients.

  13. Effect of Radiotherapy Planning Complexity on Survival of Elderly Patients With Unresected Localized Lung Cancer

    International Nuclear Information System (INIS)

    Park, Chang H.; Bonomi, Marcelo; Cesaretti, Jamie; Neugut, Alfred I.; Wisnivesky, Juan P.

    2011-01-01

    Purpose: To evaluate whether complex radiotherapy (RT) planning was associated with improved outcomes in a cohort of elderly patients with unresected Stage I-II non-small-cell lung cancer (NSCLC). Methods and Materials: Using the Surveillance, Epidemiology, and End Results registry linked to Medicare claims, we identified 1998 patients aged >65 years with histologically confirmed, unresected stage I-II NSCLC. Patients were classified into an intermediate or complex RT planning group using Medicare physician codes. To address potential selection bias, we used propensity score modeling. Survival of patients who received intermediate and complex simulation was compared using Cox regression models adjusting for propensity scores and in a stratified and matched analysis according to propensity scores. Results: Overall, 25% of patients received complex RT planning. Complex RT planning was associated with better overall (hazard ratio 0.84; 95% confidence interval, 0.75-0.95) and lung cancer-specific (hazard ratio 0.81; 95% confidence interval, 0.71-0.93) survival after controlling for propensity scores. Similarly, stratified and matched analyses showed better overall and lung cancer-specific survival of patients treated with complex RT planning. Conclusions: The use of complex RT planning is associated with improved survival among elderly patients with unresected Stage I-II NSCLC. These findings should be validated in prospective randomized controlled trials.

  14. Analyses of developmental rate isomorphy in ectotherms: Introducing the dirichlet regression

    Czech Academy of Sciences Publication Activity Database

    Boukal S., David; Ditrich, Tomáš; Kutcherov, D.; Sroka, Pavel; Dudová, Pavla; Papáček, M.

    2015-01-01

    Roč. 10, č. 6 (2015), e0129341 E-ISSN 1932-6203 R&D Projects: GA ČR GAP505/10/0096 Grant - others:European Fund(CZ) PERG04-GA-2008-239543; GA JU(CZ) 145/2013/P Institutional support: RVO:60077344 Keywords : ectotherms Subject RIV: ED - Physiology Impact factor: 3.057, year: 2015 http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0129341

  15. The benefits of using quantile regression for analysing the effect of weeds on organic winter wheat

    NARCIS (Netherlands)

    Casagrande, M.; Makowski, D.; Jeuffroy, M.H.; Valantin-Morison, M.; David, C.

    2010-01-01

    P>In organic farming, weeds are one of the threats that limit crop yield. An early prediction of weed effect on yield loss and the size of late weed populations could help farmers and advisors to improve weed management. Numerous studies predicting the effect of weeds on yield have already been

  16. Quantitative Research Methods in Chaos and Complexity: From Probability to Post Hoc Regression Analyses

    Science.gov (United States)

    Gilstrap, Donald L.

    2013-01-01

    In addition to qualitative methods presented in chaos and complexity theories in educational research, this article addresses quantitative methods that may show potential for future research studies. Although much in the social and behavioral sciences literature has focused on computer simulations, this article explores current chaos and…

  17. Differential item functioning (DIF) analyses of health-related quality of life instruments using logistic regression

    DEFF Research Database (Denmark)

    Scott, Neil W.; Fayers, Peter M.; Aaronson, Neil K.

    2010-01-01

    Differential item functioning (DIF) methods can be used to determine whether different subgroups respond differently to particular items within a health-related quality of life (HRQoL) subscale, after allowing for overall subgroup differences in that scale. This article reviews issues that arise...

  18. Modelling survival after treatment of intraocular melanoma using artificial neural networks and Bayes theorem

    International Nuclear Information System (INIS)

    Taktak, Azzam F G; Fisher, Anthony C; Damato, Bertil E

    2004-01-01

    This paper describes the development of an artificial intelligence (AI) system for survival prediction from intraocular melanoma. The system used artificial neural networks (ANNs) with five input parameters: coronal and sagittal tumour location, anterior tumour margin, largest basal tumour diameter and the cell type. After excluding records with missing data, 2331 patients were included in the study. These were split randomly into training and test sets. Date censorship was applied to the records to deal with patients who were lost to follow-up and patients who died from general causes. Bayes theorem was then applied to the ANN output to construct survival probability curves. A validation set with 34 patients unseen to both training and test sets was used to compare the AI system with Cox's regression (CR) and Kaplan-Meier (KM) analyses. Results showed large differences in the mean 5 year survival probability figures when the number of records with matching characteristics was small. However, as the number of matches increased to >100 the system tended to agree with CR and KM. The validation set was also used to compare the system with a clinical expert in predicting time to metastatic death. The rms error was 3.7 years for the system and 4.3 years for the clinical expert for 15 years survival. For <10 years survival, these figures were 2.7 and 4.2, respectively. We concluded that the AI system can match if not better the clinical expert's prediction. There were significant differences with CR and KM analyses when the number of records was small, but it was not known which model is more accurate

  19. Modelling survival after treatment of intraocular melanoma using artificial neural networks and Bayes theorem

    Energy Technology Data Exchange (ETDEWEB)

    Taktak, Azzam F G [Department of Clinical Engineering, Duncan Building, Royal Liverpool University Hospital, Liverpool L7 8XP (United Kingdom); Fisher, Anthony C [Department of Clinical Engineering, Duncan Building, Royal Liverpool University Hospital, Liverpool L7 8XP (United Kingdom); Damato, Bertil E [Department of Ophthalmology, Royal Liverpool University Hospital, Liverpool L7 8XP (United Kingdom)

    2004-01-07

    This paper describes the development of an artificial intelligence (AI) system for survival prediction from intraocular melanoma. The system used artificial neural networks (ANNs) with five input parameters: coronal and sagittal tumour location, anterior tumour margin, largest basal tumour diameter and the cell type. After excluding records with missing data, 2331 patients were included in the study. These were split randomly into training and test sets. Date censorship was applied to the records to deal with patients who were lost to follow-up and patients who died from general causes. Bayes theorem was then applied to the ANN output to construct survival probability curves. A validation set with 34 patients unseen to both training and test sets was used to compare the AI system with Cox's regression (CR) and Kaplan-Meier (KM) analyses. Results showed large differences in the mean 5 year survival probability figures when the number of records with matching characteristics was small. However, as the number of matches increased to >100 the system tended to agree with CR and KM. The validation set was also used to compare the system with a clinical expert in predicting time to metastatic death. The rms error was 3.7 years for the system and 4.3 years for the clinical expert for 15 years survival. For <10 years survival, these figures were 2.7 and 4.2, respectively. We concluded that the AI system can match if not better the clinical expert's prediction. There were significant differences with CR and KM analyses when the number of records was small, but it was not known which model is more accurate.

  20. Does exclusion of cancers registered only from death-certificate information diminish socio-demographic disparities in recorded survival?

    Science.gov (United States)

    Tervonen, Hanna E; Roder, David; Morrell, Stephen; You, Hui; Currow, David C

    2017-06-01

    Death Certificate Only (DCO) cancer cases are commonly excluded from survival analyses due to unknown survival time. This study examines whether socio-demographic factors are associated with DCO diagnosis, and the potential effects of excluding DCO cases on socio-demographic cancer survival disparities in NSW, Australia. NSW Cancer Registry data for cases diagnosed in 2000-2008 were used in this study. Logistic regression was used to estimate the odds of DCO registration by socio-demographic sub-group (socio-economic disadvantage, residential remoteness, country of birth, age at diagnosis). Cox proportional hazard regression was used to estimate the probability of death from cancer by socio-demographic subgroup when DCO cases were included and excluded from analyses. DCO cases consisted of 1.5% (n=4336) of all cases (n=299,651). DCO diagnosis was associated with living in socio-economically disadvantaged areas (most disadvantaged compared with least disadvantaged quintile: odds ratio OR 1.25, 95%CI 1.12-1.40), living in inner regional (OR 1.16, 95%CI 1.08-1.25) or remote areas (OR 1.48, 95%CI 1.01-2.19), having an unknown country of birth (OR 1.63, 95%CI 1.47-1.81) and older age. Including or excluding DCO cases had no significant impact on hazard ratios for cancer death by socio-economic disadvantage quintile or remoteness category, and only a minor impact on hazard ratios by age. Socio-demographic factors were associated with DCO diagnosis in NSW. However, socio-demographic cancer survival disparities remained unchanged or varied only slightly irrespective of including/excluding DCO cases. Further research could examine the upper limits of DCO proportions that significantly alter estimated cancer survival differentials if DCOs are excluded. Crown Copyright © 2017. Published by Elsevier Ltd. All rights reserved.

  1. Clinical Nomogram for Predicting Survival Outcomes in Early Mucinous Breast Cancer.

    Directory of Open Access Journals (Sweden)

    Jianfei Fu

    Full Text Available The features related to the prognosis of patients with mucinous breast cancer (MBC remain controversial. We aimed to explore the prognostic factors of MBC and develop a nomogram for predicting survival outcomes.The Surveillance, Epidemiology, and End Results (SEER database was searched to identify 139611 women with resectable breast cancer from 1990 to 2007. Survival curves were generated using Kaplan-Meier methods. The 5-year and 10-year cancer-specific survival (CSS rates were calculated using the Life-Table method. Based on Cox models, a nomogram was constructed to predict the probabilities of CSS for an individual patient. The competing risk regression model was used to analyse the specific survival of patients with MBC.There were 136569 (97.82% infiltrative ductal cancer (IDC patients and 3042 (2.18% MBC patients. Patients with MBC had less lymph node involvement, a higher frequency of well-differentiated lesions, and more estrogen receptor (ER-positive tumors. Patients with MBC had significantly higher 5 and10-year CSS rates (98.23 and 96.03%, respectively than patients with IDC (91.44 and 85.48%, respectively. Univariate and multivariate analyses showed that MBC was an independent factor for better prognosis. As for patients with MBC, the event of death caused by another disease exceeded the event of death caused by breast cancer. A competing risk regression model further showed that lymph node involvement, poorly differentiated grade and advanced T-classification were independent factors of poor prognosis in patients with MBC. The Nomogram can accurately predict CSS with a high C-index (0.816. Risk scores developed from the nomogram can more accurately predict the prognosis of patients with MBC (C-index = 0.789 than the traditional TNM system (C-index = 0.704, P< 0.001.Patients with MBC have a better prognosis than patients with IDC. Nomograms could help clinicians make more informed decisions in clinical practice. The competing risk

  2. The effect of parathyroidectomy on patient survival in secondary hyperparathyroidism.

    Science.gov (United States)

    Ivarsson, Kerstin M; Akaberi, Shahriar; Isaksson, Elin; Reihnér, Eva; Rylance, Rebecca; Prütz, Karl-Göran; Clyne, Naomi; Almquist, Martin

    2015-12-01

    Secondary hyperparathyroidism is a common condition in patients with end-stage renal disease and is associated with osteoporosis and cardiovascular disease. Despite improved medical treatment, parathyroidectomy (PTX) is still necessary for many patients on renal replacement therapy. The aim of this study was to evaluate the effect of PTX on patient survival. A nested index-referent study was performed within the Swedish Renal Registry (SRR). Patients on maintenance dialysis and transplantation at the time of PTX were analysed separately. The PTX patients in each of these strata were matched for age, sex and underlying renal diseases with up to five referent patients who had not undergone PTX. To calculate survival time and hazard ratios, indexes and referents were assigned the calendar date (d) of the PTX of the index patient. The risk of death after PTX was calculated using crude and adjusted Cox proportional hazards regressions. There were 20 056 patients in the SRR between 1991 and 2009. Of these, 579 (423 on dialysis and 156 with a renal transplant at d) incident patients with PTX were matched with 1234/892 non-PTX patients. The adjusted relative risk of death was a hazard ratio (HR) of 0.80 [95% confidence interval (CI) 0.65-0.99] for dialysis patients at d who had undergone PTX compared with matched patients who had not. Corresponding results for the patients with a renal allograft at d were an HR of 1.10 (95% CI 0.71-1.70). PTX was associated with improved survival in patients on maintenance dialysis but not in patients with renal allograft. © The Author 2015. Published by Oxford University Press on behalf of ERA-EDTA. All rights reserved.

  3. Penalized estimation for competing risks regression with applications to high-dimensional covariates

    DEFF Research Database (Denmark)

    Ambrogi, Federico; Scheike, Thomas H.

    2016-01-01

    of competing events. The direct binomial regression model of Scheike and others (2008. Predicting cumulative incidence probability by direct binomial regression. Biometrika 95: (1), 205-220) is reformulated in a penalized framework to possibly fit a sparse regression model. The developed approach is easily...... Research 19: (1), 29-51), the research regarding competing risks is less developed (Binder and others, 2009. Boosting for high-dimensional time-to-event data with competing risks. Bioinformatics 25: (7), 890-896). The aim of this work is to consider how to do penalized regression in the presence...... implementable using existing high-performance software to do penalized regression. Results from simulation studies are presented together with an application to genomic data when the endpoint is progression-free survival. An R function is provided to perform regularized competing risks regression according...

  4. Intermediate and advanced topics in multilevel logistic regression analysis.

    Science.gov (United States)

    Austin, Peter C; Merlo, Juan

    2017-09-10

    Multilevel data occur frequently in health services, population and public health, and epidemiologic research. In such research, binary outcomes are common. Multilevel logistic regression models allow one to account for the clustering of subjects within clusters of higher-level units when estimating the effect of subject and cluster characteristics on subject outcomes. A search of the PubMed database demonstrated that the use of multilevel or hierarchical regression models is increasing rapidly. However, our impression is that many analysts simply use multilevel regression models to account for the nuisance of within-cluster homogeneity that is induced by clustering. In this article, we describe a suite of analyses that can complement the fitting of multilevel logistic regression models. These ancillary analyses permit analysts to estimate the marginal or population-average effect of covariates measured at the subject and cluster level, in contrast to the within-cluster or cluster-specific effects arising from the original multilevel logistic regression model. We describe the interval odds ratio and the proportion of opposed odds ratios, which are summary measures of effect for cluster-level covariates. We describe the variance partition coefficient and the median odds ratio which are measures of components of variance and heterogeneity in outcomes. These measures allow one to quantify the magnitude of the general contextual effect. We describe an R 2 measure that allows analysts to quantify the proportion of variation explained by different multilevel logistic regression models. We illustrate the application and interpretation of these measures by analyzing mortality in patients hospitalized with a diagnosis of acute myocardial infarction. © 2017 The Authors. Statistics in Medicine published by John Wiley & Sons Ltd. © 2017 The Authors. Statistics in Medicine published by John Wiley & Sons Ltd.

  5. The influence of marital status on the stage at diagnosis, treatment, and survival of adult patients with gastric cancer: a population-based study.

    Science.gov (United States)

    Zhang, Jieyun; Gan, Lu; Wu, Zhenhua; Yan, Shican; Liu, Xiyu; Guo, Weijian

    2017-04-04

    Marital status was reported as a prognostic factor in many cancers. However, its role in gastric cancer (GC) hasn't been thoroughly explored. In this study, we aimed to investigate the effect of marital status on survival, stage, treatment, and survival in subgroups. We used the Surveillance, Epidemiology and End Results (SEER) database and identified 16910 GC patients. These patients were categorized into married (58.44%) and unmarred (41.56%) groups. Pearson chi-square, Wilcoxon-Mann-Whitney, Log-rank, multivariate Cox regression, univariate and multivariate binomial or multinomial logistic regression analysis were used in our analysis. Subgroup analyses of married versus unmarried patients were summarized in a forest plot. Married patients had better 5-year overall survival (OS) (32.09% VS 24.61%, PVS 32.79%, Punmarried ones. Then we studied several underlying mechanisms. Firstly, married patients weren't in earlier stage at diagnosis (P=0.159). Secondly, married patients were more likely to receive surgery (P unmarried. Thirdly, in subgroup analyses, married patients still had survival advantage in subgroups with stage II-IV and no radiotherapy. These results showed that marital status was an independently prognostic factor for both OS and CSS in GC patients. Undertreatment and lack of social support in unmarried patients were potential explanations. With the knowledge of heterogeneous effects of marriage in subgroups, we can target unmarried patients with better social support, especially who are diagnosed at late stage and undergo no treatment.

  6. Applied regression analysis a research tool

    CERN Document Server

    Pantula, Sastry; Dickey, David

    1998-01-01

    Least squares estimation, when used appropriately, is a powerful research tool. A deeper understanding of the regression concepts is essential for achieving optimal benefits from a least squares analysis. This book builds on the fundamentals of statistical methods and provides appropriate concepts that will allow a scientist to use least squares as an effective research tool. Applied Regression Analysis is aimed at the scientist who wishes to gain a working knowledge of regression analysis. The basic purpose of this book is to develop an understanding of least squares and related statistical methods without becoming excessively mathematical. It is the outgrowth of more than 30 years of consulting experience with scientists and many years of teaching an applied regression course to graduate students. Applied Regression Analysis serves as an excellent text for a service course on regression for non-statisticians and as a reference for researchers. It also provides a bridge between a two-semester introduction to...

  7. Mesothelin-specific Immune Responses Predict Survival of Patients With Brain Metastasis

    DEFF Research Database (Denmark)

    Zhenjiang, Liu; Rao, Martin; Luo, Xiaohua

    2017-01-01

    BACKGROUND: Patients with advanced malignancies, e.g. lung cancer, ovarian cancer or melanoma, frequently present with brain metastases. Clinical presentation and disease progression of cancer is in part shaped by the interaction of the immune system with malignant cells. Antigen-targeted immune ...... of the primary tumor origin. Analyses of immunological markers could potentially serve as prognostic markers in patients with brain metastases and help to select patients in need for adjunct, immunological, treatment strategies....... were tested for interferon gamma (IFN-γ) production, after which univariate and multivariate analyses (Cox stepwise regression model) were performed to identify independent clinical and immunological factors associated with patient survival. Patients were followed-up for at least 500days after surgery...

  8. Comparative Survival in Patients With Postresection Recurrent Versus Newly Diagnosed Non-Small-Cell Lung Cancer Treated With Radiotherapy

    International Nuclear Information System (INIS)

    Cai Xuwei; Xu Luying; Wang Li; Hayman, James A.; Chang, Andrew C.; Pickens, Allan; Cease, Kemp B.; Orringer, Mark B.; Kong, F.-M.

    2010-01-01

    Purpose: To compare the survival of postresection recurrent vs. newly diagnosed non-small-cell lung cancer (NSCLC) patients treated with radiotherapy or chemoradiotherapy. Methods and Materials: The study population consisted of 661 consecutive patients with NSCLC registered in the radiation oncology databases at two medical centers in the United States between 1992 and 2004. Of the 661 patients, 54 had postresection recurrent NSCLC and 607 had newly diagnosed NSCLC. Kaplan-Meier and Cox regression models were used for the survival analyses. Results: The distribution of relevant clinical factors between these two groups was similar. The median survival time and 5-year overall survival rates were 19.8 months (95% confidence interval [CI], 13.9-25.7) and 14.8% (95% confidence interval, 5.4-24.2%) vs. 12.2 months (95% CI, 10.8-13.6) and 11.0% (95% CI, 8.5-13.5%) for recurrent vs. newly diagnosed patients, respectively (p = .037). For Stage I-III patients, no significant difference was observed in the 5-year overall survival (p = .297) or progression-free survival (p = .935) between recurrent and newly diagnosed patients. For the 46 patients with Stage I-III recurrent disease, multivariate analysis showed that chemotherapy was a significant prognostic factor for 5-year progression-free survival (hazard ratio, 0.45; 95% CI, 0.224-0.914; p = .027). Conclusion: Our institutional data have shown that patients with postresection recurrent NSCLC achieved survival comparable to that of newly diagnosed NSCLC patients when they were both treated with radiotherapy or chemoradiotherapy. These findings suggest that patients with postresection recurrent NSCLC should be treated as aggressively as those with newly diagnosed disease.

  9. A nomogram to predict the survival of stage IIIA-N2 non-small cell lung cancer after surgery.

    Science.gov (United States)

    Mao, Qixing; Xia, Wenjie; Dong, Gaochao; Chen, Shuqi; Wang, Anpeng; Jin, Guangfu; Jiang, Feng; Xu, Lin

    2018-04-01

    Postoperative survival of patients with stage IIIA-N2 non-small cell lung cancer (NSCLC) is highly heterogeneous. Here, we aimed to identify variables associated with postoperative survival and develop a tool for survival prediction. A retrospective review was performed in the Surveillance, Epidemiology, and End Results database from January 2004 to December 2009. Significant variables were selected by use of the backward stepwise method. The nomogram was constructed with multivariable Cox regression. The model's performance was evaluated by concordance index and calibration curve. The model was validated via an independent cohort from the Jiangsu Cancer Hospital Lung Cancer Center. A total of 1809 patients with stage IIIA-N2 NSCLC who underwent surgery were included in the training cohort. Age, sex, grade, histology, tumor size, visceral pleural invasion, positive lymph nodes, lymph nodes examined, and surgery type (lobectomy vs pneumonectomy) were identified as significant prognostic variables using backward stepwise method. A nomogram was developed from the training cohort and validated using an independent Chinese cohort. The concordance index of the model was 0.673 (95% confidence interval, 0.654-0.692) in training cohort and 0.664 in validation cohort (95% confidence interval, 0.614-0.714). The calibration plot showed optimal consistency between nomogram predicted survival and observed survival. Survival analyses demonstrated significant differences between different subgroups stratified by prognostic scores. This nomogram provided the individual survival prediction for patients with stage IIIA-N2 NSCLC after surgery, which might benefit survival counseling for patients and clinicians, clinical trial design and follow-up, as well as postoperative strategy-making. Copyright © 2017 The American Association for Thoracic Surgery. Published by Elsevier Inc. All rights reserved.

  10. Is cancer survival associated with cancer symptom awareness and barriers to seeking medical help in England? An ecological study.

    Science.gov (United States)

    Niksic, Maja; Rachet, Bernard; Duffy, Stephen W; Quaresma, Manuela; Møller, Henrik; Forbes, Lindsay Jl

    2016-09-27

    Campaigns aimed at raising cancer awareness and encouraging early presentation have been implemented in England. However, little is known about whether people with low cancer awareness and increased barriers to seeking medical help have worse cancer survival, and whether there is a geographical variation in cancer awareness and barriers in England. From population-based surveys (n=35 308), using the Cancer Research UK Cancer Awareness Measure, we calculated the age- and sex-standardised symptom awareness and barriers scores for 52 primary care trusts (PCTs). These measures were evaluated in relation to the sex-, age-, and type of cancer-standardised cancer survival index of the corresponding PCT, from the National Cancer Registry, using linear regression. Breast, lung, and bowel cancer survival were analysed separately. Cancer symptom awareness and barriers scores varied greatly between geographical regions in England, with the worst scores observed in socioeconomically deprived parts of East London. Low cancer awareness score was associated with poor cancer survival at PCT level (estimated slope=1.56, 95% CI: 0.56; 2.57). The barriers score was not associated with overall cancer survival, but it was associated with breast cancer survival (estimated slope=-0.66, 95% CI: -1.20; -0.11). Specific barriers, such as embarrassment and difficulties in arranging transport to the doctor's surgery, were associated with worse breast cancer survival. Cancer symptom awareness and cancer survival are associated. Campaigns should focus on improving awareness about cancer symptoms, especially in socioeconomically deprived areas. Efforts should be made to alleviate barriers to seeking medical help in women with symptoms of breast cancer.

  11. Clinical characteristics and quality-of-life in patients surviving a decade of prostate cancer with bone metastases.

    Science.gov (United States)

    Klaff, Rami; Berglund, Anders; Varenhorst, Eberhard; Hedlund, Per Olov; Jǿnler, Morten; Sandblom, Gabriel

    2016-06-01

    To describe characteristics and quality-of-life (QoL), and to define factors associated with long-term survival in a subgroup of patients with prostate cancer with M1b disease. The study was based on 915 patients from a prospective randomised multicentre trial (No. 5) by the Scandinavian Prostate Cancer Group, comparing parenteral oestrogen with total androgen blockade. Long-term survival was defined as patients having an overall survival of ≥10 years, and logistic regression models were constructed to identity clinical predictors of survival. QoL during follow-up was assessed using the European Organisation for Research and Treatment of Cancer Quality-of-Life Questionnaire - C30 version 1 (EORTC-C30) ratings. In all, 40 (4.4%) of the 915 men survived for >10 years. Factors significantly associated with increased likelihood of surviving for >10 years in the univariate analyses were: absence of cancer-related pain; Eastern Cooperative Oncology Group (ECOG) performance status of patients with short survival, but slowly declined over the decade. A subgroup of patients with prostate cancer with M1b disease and certain characteristics showed a positive long-term response to androgen-deprivation therapy with an acceptable QoL over a decade or more. Independent predictors of long-term survival were identified as ECOG performance status of <2, limited extent of bone metastases (Soloway score of 1), and a PSA level of <231 μg/L at the time of enrolment. © 2015 The Authors BJU International © 2015 BJU International Published by John Wiley & Sons Ltd.

  12. Survival Outcomes in Resected Extrahepatic Cholangiocarcinoma: Effect of Adjuvant Radiotherapy in a Surveillance, Epidemiology, and End Results Analysis

    International Nuclear Information System (INIS)

    Vern-Gross, Tamara Z.; Shivnani, Anand T.; Chen, Ke; Lee, Christopher M.; Tward, Jonathan D.; MacDonald, O. Kenneth; Crane, Christopher H.; Talamonti, Mark S.; Munoz, Louis L.; Small, William

    2011-01-01

    Purpose: The benefit of adjuvant radiotherapy (RT) after surgical resection for extrahepatic cholangiocarcinoma has not been clearly established. We analyzed survival outcomes of patients with resected extrahepatic cholangiocarcinoma and examined the effect of adjuvant RT. Methods and Materials: Data were obtained from the Surveillance, Epidemiology, and End Results (SEER) program between 1973 and 2003. The primary endpoint was the overall survival time. Cox regression analysis was used to perform univariate and multivariate analyses of the following clinical variables: age, year of diagnosis, histologic grade, localized (Stage T1-T2) vs. regional (Stage T3 or greater and/or node positive) stage, gender, race, and the use of adjuvant RT after surgical resection. Results: The records for 2,332 patients were obtained. Patients with previous malignancy, distant disease, incomplete or conflicting records, atypical histologic features, and those treated with preoperative/intraoperative RT were excluded. Of the remaining 1,491 patients eligible for analysis, 473 (32%) had undergone adjuvant RT. After a median follow-up of 27 months (among surviving patients), the median overall survival time for the entire cohort was 20 months. Patients with localized and regional disease had a median survival time of 33 and 18 months, respectively (p < .001). The addition of adjuvant RT was not associated with an improvement in overall or cause-specific survival for patients with local or regional disease. Conclusion: Patients with localized disease had significantly better overall survival than those with regional disease. Adjuvant RT was not associated with an improvement in long-term overall survival in patients with resected extrahepatic bile duct cancer. Key data, including margin status and the use of combined chemotherapy, was not available through the SEER database.

  13. Regression models of reactor diagnostic signals

    International Nuclear Information System (INIS)

    Vavrin, J.

    1989-01-01

    The application is described of an autoregression model as the simplest regression model of diagnostic signals in experimental analysis of diagnostic systems, in in-service monitoring of normal and anomalous conditions and their diagnostics. The method of diagnostics is described using a regression type diagnostic data base and regression spectral diagnostics. The diagnostics is described of neutron noise signals from anomalous modes in the experimental fuel assembly of a reactor. (author)

  14. Influence of beta blockers on survival in dogs with severe subaortic stenosis.

    Science.gov (United States)

    Eason, B D; Fine, D M; Leeder, D; Stauthammer, C; Lamb, K; Tobias, A H

    2014-01-01

    Subaortic stenosis (SAS) is one of the most common congenital cardiac defects in dogs. Severe SAS frequently is treated with a beta adrenergic receptor blocker (beta blocker), but this approach largely is empirical. To determine the influence of beta blocker treatment on survival time in dogs with severe SAS. Retrospective review of medical records of dogs diagnosed with severe, uncomplicated SAS (pressure gradient [PG] ≥80 mmHg) between 1999 and 2011. Fifty dogs met the inclusion criteria. Twenty-seven dogs were treated with a beta blocker and 23 received no treatment. Median age at diagnosis was significantly greater in the untreated group (1.2 versus 0.6 years, respectively; P = .03). Median PG at diagnosis did not differ between the treated and untreated groups (127 versus 121 mmHg, respectively; P = .2). Cox proportional hazards regression was used to identify the influence of PG at diagnosis, age at diagnosis, and beta blocker treatment on survival. In the all-cause multivariate mortality analysis, only age at diagnosis (P = .02) and PG at diagnosis (P = .03) affected survival time. In the cardiac mortality analysis, only PG influenced survival time (P = .03). Treatment with a beta blocker did not influence survival time in either the all-cause (P = .93) or cardiac-cause (P = .97) mortality analyses. Beta blocker treatment did not influence survival in dogs with severe SAS in our study, and a higher PG at diagnosis was associated with increased risk of death. Copyright © 2014 by the American College of Veterinary Internal Medicine.

  15. Challenges in the estimation of Net SURvival: The CENSUR working survival group.

    Science.gov (United States)

    Giorgi, R

    2016-10-01

    Net survival, the survival probability that would be observed, in a hypothetical world, where the cancer of interest would be the only possible cause of death, is a key indicator in population-based cancer studies. Accounting for mortality due to other causes, it allows cross-country comparisons or trends analysis and provides a useful indicator for public health decision-making. The objective of this study was to show how the creation and formalization of a network comprising established research teams, which already had substantial and complementary experience in both cancer survival analysis and methodological development, make it possible to meet challenges and thus provide more adequate tools, to improve the quality and the comparability of cancer survival data, and to promote methodological transfers in areas of emerging interest. The Challenges in the Estimation of Net SURvival (CENSUR) working survival group is composed of international researchers highly skilled in biostatistics, methodology, and epidemiology, from different research organizations in France, the United Kingdom, Italy, Slovenia, and Canada, and involved in French (FRANCIM) and European (EUROCARE) cancer registry networks. The expected advantages are an interdisciplinary, international, synergistic network capable of addressing problems in public health, for decision-makers at different levels; tools for those in charge of net survival analyses; a common methodology that makes unbiased cross-national comparisons of cancer survival feasible; transfer of methods for net survival estimations to other specific applications (clinical research, occupational epidemiology); and dissemination of results during an international training course. The formalization of the international CENSUR working survival group was motivated by a need felt by scientists conducting population-based cancer research to discuss, develop, and monitor implementation of a common methodology to analyze net survival in order

  16. Normalization Ridge Regression in Practice I: Comparisons Between Ordinary Least Squares, Ridge Regression and Normalization Ridge Regression.

    Science.gov (United States)

    Bulcock, J. W.

    The problem of model estimation when the data are collinear was examined. Though the ridge regression (RR) outperforms ordinary least squares (OLS) regression in the presence of acute multicollinearity, it is not a problem free technique for reducing the variance of the estimates. It is a stochastic procedure when it should be nonstochastic and it…

  17. Multivariate Regression Analysis and Slaughter Livestock,

    Science.gov (United States)

    AGRICULTURE, *ECONOMICS), (*MEAT, PRODUCTION), MULTIVARIATE ANALYSIS, REGRESSION ANALYSIS , ANIMALS, WEIGHT, COSTS, PREDICTIONS, STABILITY, MATHEMATICAL MODELS, STORAGE, BEEF, PORK, FOOD, STATISTICAL DATA, ACCURACY

  18. [From clinical judgment to linear regression model.

    Science.gov (United States)

    Palacios-Cruz, Lino; Pérez, Marcela; Rivas-Ruiz, Rodolfo; Talavera, Juan O

    2013-01-01

    When we think about mathematical models, such as linear regression model, we think that these terms are only used by those engaged in research, a notion that is far from the truth. Legendre described the first mathematical model in 1805, and Galton introduced the formal term in 1886. Linear regression is one of the most commonly used regression models in clinical practice. It is useful to predict or show the relationship between two or more variables as long as the dependent variable is quantitative and has normal distribution. Stated in another way, the regression is used to predict a measure based on the knowledge of at least one other variable. Linear regression has as it's first objective to determine the slope or inclination of the regression line: Y = a + bx, where "a" is the intercept or regression constant and it is equivalent to "Y" value when "X" equals 0 and "b" (also called slope) indicates the increase or decrease that occurs when the variable "x" increases or decreases in one unit. In the regression line, "b" is called regression coefficient. The coefficient of determination (R 2 ) indicates the importance of independent variables in the outcome.

  19. Network ties and survival

    DEFF Research Database (Denmark)

    Acheampong, George; Narteh, Bedman; Rand, John

    2017-01-01

    Poultry farming has been touted as one of the major ways by which poverty can be reduced in low-income economies like Ghana. Yet, anecdotally there is a high failure rate among these poultry farms. This current study seeks to understand the relationship between network ties and survival chances...... of small commercial poultry farms (SCPFs). We utilize data from a 2-year network survey of SCPFs in rural Ghana. The survival of these poultry farms are modelled using a lagged probit model of farms that persisted from 2014 into 2015. We find that network ties are important to the survival chances...... but this probability reduces as the number of industry ties increases but moderation with dynamic capability of the firm reverses this trend. Our findings show that not all network ties aid survival and therefore small commercial poultry farmers need to be circumspect in the network ties they cultivate and develop....

  20. Survival of falling robots

    Science.gov (United States)

    Cameron, Jonathan M.; Arkin, Ronald C.

    1992-01-01

    As mobile robots are used in more uncertain and dangerous environments, it will become important to design them so that they can survive falls. In this paper, we examine a number of mechanisms and strategies that animals use to withstand these potentially catastrophic events and extend them to the design of robots. A brief survey of several aspects of how common cats survive falls provides an understanding of the issues involved in preventing traumatic injury during a falling event. After outlining situations in which robots might fall, a number of factors affecting their survival are described. From this background, several robot design guidelines are derived. These include recommendations for the physical structure of the robot as well as requirements for the robot control architecture. A control architecture is proposed based on reactive control techniques and action-oriented perception that is geared to support this form of survival behavior.

  1. Survivability and Hope

    Science.gov (United States)

    ... Current Issue Past Issues Special Section Survivability and Hope Past Issues / Spring 2007 Table of Contents For ... cure or long-term survivorship." This message of hope is a hallmark of the latest advances in ...

  2. Survival of falling robots

    Science.gov (United States)

    Cameron, Jonathan M.; Arkin, Ronald C.

    1992-02-01

    As mobile robots are used in more uncertain and dangerous environments, it will become important to design them so that they can survive falls. In this paper, we examine a number of mechanisms and strategies that animals use to withstand these potentially catastrophic events and extend them to the design of robots. A brief survey of several aspects of how common cats survive falls provides an understanding of the issues involved in preventing traumatic injury during a falling event. After outlining situations in which robots might fall, a number of factors affecting their survival are described. From this background, several robot design guidelines are derived. These include recommendations for the physical structure of the robot as well as requirements for the robot control architecture. A control architecture is proposed based on reactive control techniques and action-oriented perception that is geared to support this form of survival behavior.

  3. A simple linear regression method for quantitative trait loci linkage analysis with censored observations.

    Science.gov (United States)

    Anderson, Carl A; McRae, Allan F; Visscher, Peter M

    2006-07-01

    Standard quantitative trait loci (QTL) mapping techniques commonly assume that the trait is both fully observed and normally distributed. When considering survival or age-at-onset traits these assumptions are often incorrect. Methods have been developed to map QTL for survival traits; however, they are both computationally intensive and not available in standard genome analysis software packages. We propose a grouped linear regression method for the analysis of continuous survival data. Using simulation we compare this method to both the Cox and Weibull proportional hazards models and a standard linear regression method that ignores censoring. The grouped linear regression method is of equivalent power to both the Cox and Weibull proportional hazards methods and is significantly better than the standard linear regression method when censored observations are present. The method is also robust to the proportion of censored individuals and the underlying distribution of the trait. On the basis of linear regression methodology, the grouped linear regression model is computationally simple and fast and can be implemented readily in freely available statistical software.

  4. Evaluation of Linear Regression Simultaneous Myoelectric Control Using Intramuscular EMG.

    Science.gov (United States)

    Smith, Lauren H; Kuiken, Todd A; Hargrove, Levi J

    2016-04-01

    The objective of this study was to evaluate the ability of linear regression models to decode patterns of muscle coactivation from intramuscular electromyogram (EMG) and provide simultaneous myoelectric control of a virtual 3-DOF wrist/hand system. Performance was compared to the simultaneous control of conventional myoelectric prosthesis methods using intramuscular EMG (parallel dual-site control)-an approach that requires users to independently modulate individual muscles in the residual limb, which can be challenging for amputees. Linear regression control was evaluated in eight able-bodied subjects during a virtual Fitts' law task and was compared to performance of eight subjects using parallel dual-site control. An offline analysis also evaluated how different types of training data affected prediction accuracy of linear regression control. The two control systems demonstrated similar overall performance; however, the linear regression method demonstrated improved performance for targets requiring use of all three DOFs, whereas parallel dual-site control demonstrated improved performance for targets that required use of only one DOF. Subjects using linear regression control could more easily activate multiple DOFs simultaneously, but often experienced unintended movements when trying to isolate individual DOFs. Offline analyses also suggested that the method used to train linear regression systems may influence controllability. Linear regression myoelectric control using intramuscular EMG provided an alternative to parallel dual-site control for 3-DOF simultaneous control at the wrist and hand. The two methods demonstrated different strengths in controllability, highlighting the tradeoff between providing simultaneous control and the ability to isolate individual DOFs when desired.

  5. Use of probabilistic weights to enhance linear regression myoelectric control

    Science.gov (United States)

    Smith, Lauren H.; Kuiken, Todd A.; Hargrove, Levi J.

    2015-12-01

    Objective. Clinically available prostheses for transradial amputees do not allow simultaneous myoelectric control of degrees of freedom (DOFs). Linear regression methods can provide simultaneous myoelectric control, but frequently also result in difficulty with isolating individual DOFs when desired. This study evaluated the potential of using probabilistic estimates of categories of gross prosthesis movement, which are commonly used in classification-based myoelectric control, to enhance linear regression myoelectric control. Approach. Gaussian models were fit to electromyogram (EMG) feature distributions for three movement classes at each DOF (no movement, or movement in either direction) and used to weight the output of linear regression models by the probability that the user intended the movement. Eight able-bodied and two transradial amputee subjects worked in a virtual Fitts’ law task to evaluate differences in controllability between linear regression and probability-weighted regression for an intramuscular EMG-based three-DOF wrist and hand system. Main results. Real-time and offline analyses in able-bodied subjects demonstrated that probability weighting improved performance during single-DOF tasks (p < 0.05) by preventing extraneous movement at additional DOFs. Similar results were seen in experiments with two transradial amputees. Though goodness-of-fit evaluations suggested that the EMG feature distributions showed some deviations from the Gaussian, equal-covariance assumptions used in this experiment, the assumptions were sufficiently met to provide improved performance compared to linear regression control. Significance. Use of probability weights can improve the ability to isolate individual during linear regression myoelectric control, while maintaining the ability to simultaneously control multiple DOFs.

  6. Regression modeling methods, theory, and computation with SAS

    CERN Document Server

    Panik, Michael

    2009-01-01

    Regression Modeling: Methods, Theory, and Computation with SAS provides an introduction to a diverse assortment of regression techniques using SAS to solve a wide variety of regression problems. The author fully documents the SAS programs and thoroughly explains the output produced by the programs.The text presents the popular ordinary least squares (OLS) approach before introducing many alternative regression methods. It covers nonparametric regression, logistic regression (including Poisson regression), Bayesian regression, robust regression, fuzzy regression, random coefficients regression,

  7. Regression models for the restricted residual mean life for right-censored and left-truncated data

    DEFF Research Database (Denmark)

    Cortese, Giuliana; Holmboe, Stine A.; Scheike, Thomas H.

    2017-01-01

    The hazard ratios resulting from a Cox's regression hazards model are hard to interpret and to be converted into prolonged survival time. As the main goal is often to study survival functions, there is increasing interest in summary measures based on the survival function that are easier to inter......The hazard ratios resulting from a Cox's regression hazards model are hard to interpret and to be converted into prolonged survival time. As the main goal is often to study survival functions, there is increasing interest in summary measures based on the survival function that are easier...... to interpret than the hazard ratio; the residual mean time is an important example of those measures. However, because of the presence of right censoring, the tail of the survival distribution is often difficult to estimate correctly. Therefore, we consider the restricted residual mean time, which represents...... a partial area under the survival function, given any time horizon τ, and is interpreted as the residual life expectancy up to τ of a subject surviving up to time t. We present a class of regression models for this measure, based on weighted estimating equations and inverse probability of censoring weighted...

  8. Influence of nutrient levels in Tamarix on Diorhabda sublineata (Coleoptera: Chrysomelidae) survival and fitness with implications for biological control.

    Science.gov (United States)

    Guenther, D A; Gardner, K T; Thompson, D C

    2011-02-01

    Establishment of the saltcedar leaf beetle (Diorhabda spp.) has been unpredictable when caged or released in the field for saltcedar (Tamarix spp.) biocontrol. It has been observed that one caged tree might be voraciously fed upon by beetles while an adjacent tree in the cage is left untouched. We hypothesized that differences in the nutrient content of individual trees may explain this behavior. We evaluated survival, development rate, and egg production of beetles fed in the laboratory on saltcedar foliage from trees that had been grown under a range of fertilizer treatments. Tissue samples from the experimental trees and from the field were analyzed for percent nitrogen, phosphorus, and potassium. There was essentially no survival of beetle larvae fed foliage from saltcedar trees at nitrogen levels below 2.0%. At levels above 2.0% N, beetle larvae had corresponding increased survival rates and shorter development times. Multiple regression analyses indicated that nitrogen and phosphorus are important for larval survival and faster development rates. Higher levels of potassium were important for increased egg cluster production. The plant tissue analysis showed that the percentage of nitrogen in the experimental trees reflected the range of trees in the field and also that there is high variability within trees in the field. Our research indicates that if beetles are released on trees with poor nutrient quality, the larvae will not survive. © 2011 Entomological Society of America

  9. Prediction of radiation levels in residences: A methodological comparison of CART [Classification and Regression Tree Analysis] and conventional regression

    International Nuclear Information System (INIS)

    Janssen, I.; Stebbings, J.H.

    1990-01-01

    In environmental epidemiology, trace and toxic substance concentrations frequently have very highly skewed distributions ranging over one or more orders of magnitude, and prediction by conventional regression is often poor. Classification and Regression Tree Analysis (CART) is an alternative in such contexts. To compare the techniques, two Pennsylvania data sets and three independent variables are used: house radon progeny (RnD) and gamma levels as predicted by construction characteristics in 1330 houses; and ∼200 house radon (Rn) measurements as predicted by topographic parameters. CART may identify structural variables of interest not identified by conventional regression, and vice versa, but in general the regression models are similar. CART has major advantages in dealing with other common characteristics of environmental data sets, such as missing values, continuous variables requiring transformations, and large sets of potential independent variables. CART is most useful in the identification and screening of independent variables, greatly reducing the need for cross-tabulations and nested breakdown analyses. There is no need to discard cases with missing values for the independent variables because surrogate variables are intrinsic to CART. The tree-structured approach is also independent of the scale on which the independent variables are measured, so that transformations are unnecessary. CART identifies important interactions as well as main effects. The major advantages of CART appear to be in exploring data. Once the important variables are identified, conventional regressions seem to lead to results similar but more interpretable by most audiences. 12 refs., 8 figs., 10 tabs

  10. RAWS II: A MULTIPLE REGRESSION ANALYSIS PROGRAM,

    Science.gov (United States)

    This memorandum gives instructions for the use and operation of a revised version of RAWS, a multiple regression analysis program. The program...of preprocessed data, the directed retention of variable, listing of the matrix of the normal equations and its inverse, and the bypassing of the regression analysis to provide the input variable statistics only. (Author)

  11. Hierarchical regression analysis in structural Equation Modeling

    NARCIS (Netherlands)

    de Jong, P.F.

    1999-01-01

    In a hierarchical or fixed-order regression analysis, the independent variables are entered into the regression equation in a prespecified order. Such an analysis is often performed when the extra amount of variance accounted for in a dependent variable by a specific independent variable is the main

  12. Categorical regression dose-response modeling

    Science.gov (United States)

    The goal of this training is to provide participants with training on the use of the U.S. EPA’s Categorical Regression soft¬ware (CatReg) and its application to risk assessment. Categorical regression fits mathematical models to toxicity data that have been assigned ord...

  13. Variable importance in latent variable regression models

    NARCIS (Netherlands)

    Kvalheim, O.M.; Arneberg, R.; Bleie, O.; Rajalahti, T.; Smilde, A.K.; Westerhuis, J.A.

    2014-01-01

    The quality and practical usefulness of a regression model are a function of both interpretability and prediction performance. This work presents some new graphical tools for improved interpretation of latent variable regression models that can also assist in improved algorithms for variable

  14. Stepwise versus Hierarchical Regression: Pros and Cons

    Science.gov (United States)

    Lewis, Mitzi

    2007-01-01

    Multiple regression is commonly used in social and behavioral data analysis. In multiple regression contexts, researchers are very often interested in determining the "best" predictors in the analysis. This focus may stem from a need to identify those predictors that are supportive of theory. Alternatively, the researcher may simply be interested…

  15. Suppression Situations in Multiple Linear Regression

    Science.gov (United States)

    Shieh, Gwowen

    2006-01-01

    This article proposes alternative expressions for the two most prevailing definitions of suppression without resorting to the standardized regression modeling. The formulation provides a simple basis for the examination of their relationship. For the two-predictor regression, the author demonstrates that the previous results in the literature are…

  16. Gibrat’s law and quantile regressions

    DEFF Research Database (Denmark)

    Distante, Roberta; Petrella, Ivan; Santoro, Emiliano

    2017-01-01

    The nexus between firm growth, size and age in U.S. manufacturing is examined through the lens of quantile regression models. This methodology allows us to overcome serious shortcomings entailed by linear regression models employed by much of the existing literature, unveiling a number of important...

  17. Regression Analysis and the Sociological Imagination

    Science.gov (United States)

    De Maio, Fernando

    2014-01-01

    Regression analysis is an important aspect of most introductory statistics courses in sociology but is often presented in contexts divorced from the central concerns that bring students into the discipline. Consequently, we present five lesson ideas that emerge from a regression analysis of income inequality and mortality in the USA and Canada.

  18. Repeated Results Analysis for Middleware Regression Benchmarking

    Czech Academy of Sciences Publication Activity Database

    Bulej, Lubomír; Kalibera, T.; Tůma, P.

    2005-01-01

    Roč. 60, - (2005), s. 345-358 ISSN 0166-5316 R&D Projects: GA ČR GA102/03/0672 Institutional research plan: CEZ:AV0Z10300504 Keywords : middleware benchmarking * regression benchmarking * regression testing Subject RIV: JD - Computer Applications, Robotics Impact factor: 0.756, year: 2005

  19. Principles of Quantile Regression and an Application

    Science.gov (United States)

    Chen, Fang; Chalhoub-Deville, Micheline

    2014-01-01

    Newer statistical procedures are typically introduced to help address the limitations of those already in practice or to deal with emerging research needs. Quantile regression (QR) is introduced in this paper as a relatively new methodology, which is intended to overcome some of the limitations of least squares mean regression (LMR). QR is more…

  20. ON REGRESSION REPRESENTATIONS OF STOCHASTIC-PROCESSES

    NARCIS (Netherlands)

    RUSCHENDORF, L; DEVALK, [No Value

    We construct a.s. nonlinear regression representations of general stochastic processes (X(n))n is-an-element-of N. As a consequence we obtain in particular special regression representations of Markov chains and of certain m-dependent sequences. For m-dependent sequences we obtain a constructive

  1. ESC guidelines adherence is associated with improved survival in patients from the Norwegian Heart Failure Registry.

    Science.gov (United States)

    De Blois, Jonathan; Fagerland, Morten Wang; Grundtvig, Morten; Semb, Anne Grete; Gullestad, Lars; Westheim, Arne; Hole, Torstein; Atar, Dan; Agewall, Stefan

    2015-01-01

    To assess the adherence to heart failure (HF) guidelines for angiotensin-converting enzyme-I (ACE-I), angiotensin II receptor blockers (ARB), and β-blockers and the possible association of ACE-I or ARB, β-blockers, and statins with survival in the large contemporary Norwegian Heart Failure Registry. The study included 5761 outpatients who were diagnosed with HF of any aetiology (mean left ventricular ejection fraction 32% ± 11%) from January 2000 to January 2010 and followed up until death or February 2010. Adherence to treatment according to the guidelines was high. Cox regression analysis to identify risk factors for all-cause mortality, after adjustment for many factors, showed that ACE-I ≥ 50% of target dose, use of beta-blockers, and statins were significantly related to improved survival (P = 0.003, P < 0.001, and P < 0.001, respectively). Propensity scoring showed the same benefit for these variables. Both multivariable and propensity scoring analyses showed survival benefits with β-blockers, statins, and adequate doses of ACE-I in this contemporary HF cohort. This study stresses the importance of guidelines adherence, even in the context of high levels of adherence to guidelines. Moreover, respecting the recommended target doses of ACE-I appears to have a crucial role in survival improvement and, in the multivariate Cox regression analysis, ARB treatment was not significantly associated with a lower all-cause mortality. Published on behalf of the European Society of Cardiology. All rights reserved. ©The Author 2015. For permissions please email: journals.permissions@oup.com.

  2. Spontaneous regression of a large hepatocellular carcinoma: case report

    Directory of Open Access Journals (Sweden)

    Alqutub, Adel

    2011-01-01

    Full Text Available The prognosis of untreated advanced hepatocellular carcinoma (HCC is grim with a median survival of less than 6 months. Spontaneous regression of HCC has been defined as the disappearance of the hepatic lesions in the absence of any specific therapy. The spontaneous regression of a very large HCC is very rare and limited data is available in the English literature. We describe spontaneous regression of hepatocellular carcinoma in a 65-year-old male who presented to our clinic with vague abdominal pain and weight loss of two months duration. He was found to have multiple hepatic lesions with elevation of serum alpha-fetoprotein (AFP level to 6,500 µg/L (normal <20 µg/L. Computed tomography revealed advanced HCC replacing almost 80% of the right hepatic lobe. Without any intervention the patient showed gradual improvement over a period of few months. Follow-up CT scan revealed disappearance of hepatic lesions with progressive decline of AFP levels to normal. Various mechanisms have been postulated to explain this rare phenomenon, but the exact mechanism remains a mystery.

  3. Regression of environmental noise in LIGO data

    International Nuclear Information System (INIS)

    Tiwari, V; Klimenko, S; Mitselmakher, G; Necula, V; Drago, M; Prodi, G; Frolov, V; Yakushin, I; Re, V; Salemi, F; Vedovato, G

    2015-01-01

    We address the problem of noise regression in the output of gravitational-wave (GW) interferometers, using data from the physical environmental monitors (PEM). The objective of the regression analysis is to predict environmental noise in the GW channel from the PEM measurements. One of the most promising regression methods is based on the construction of Wiener–Kolmogorov (WK) filters. Using this method, the seismic noise cancellation from the LIGO GW channel has already been performed. In the presented approach the WK method has been extended, incorporating banks of Wiener filters in the time–frequency domain, multi-channel analysis and regulation schemes, which greatly enhance the versatility of the regression analysis. Also we present the first results on regression of the bi-coherent noise in the LIGO data. (paper)

  4. Pathological assessment of liver fibrosis regression

    Directory of Open Access Journals (Sweden)

    WANG Bingqiong

    2017-03-01

    Full Text Available Hepatic fibrosis is the common pathological outcome of chronic hepatic diseases. An accurate assessment of fibrosis degree provides an important reference for a definite diagnosis of diseases, treatment decision-making, treatment outcome monitoring, and prognostic evaluation. At present, many clinical studies have proven that regression of hepatic fibrosis and early-stage liver cirrhosis can be achieved by effective treatment, and a correct evaluation of fibrosis regression has become a hot topic in clinical research. Liver biopsy has long been regarded as the gold standard for the assessment of hepatic fibrosis, and thus it plays an important role in the evaluation of fibrosis regression. This article reviews the clinical application of current pathological staging systems in the evaluation of fibrosis regression from the perspectives of semi-quantitative scoring system, quantitative approach, and qualitative approach, in order to propose a better pathological evaluation system for the assessment of fibrosis regression.

  5. Should metacognition be measured by logistic regression?

    Science.gov (United States)

    Rausch, Manuel; Zehetleitner, Michael

    2017-03-01

    Are logistic regression slopes suitable to quantify metacognitive sensitivity, i.e. the efficiency with which subjective reports differentiate between correct and incorrect task responses? We analytically show that logistic regression slopes are independent from rating criteria in one specific model of metacognition, which assumes (i) that rating decisions are based on sensory evidence generated independently of the sensory evidence used for primary task responses and (ii) that the distributions of evidence are logistic. Given a hierarchical model of metacognition, logistic regression slopes depend on rating criteria. According to all considered models, regression slopes depend on the primary task criterion. A reanalysis of previous data revealed that massive numbers of trials are required to distinguish between hierarchical and independent models with tolerable accuracy. It is argued that researchers who wish to use logistic regression as measure of metacognitive sensitivity need to control the primary task criterion and rating criteria. Copyright © 2017 Elsevier Inc. All rights reserved.

  6. Population-based study of survival for women with serous cancer of the ovary, fallopian tube, peritoneum or undesignated origin - on behalf of the Swedish gynecological cancer group (SweGCG).

    Science.gov (United States)

    Dahm-Kähler, Pernilla; Borgfeldt, Christer; Holmberg, Erik; Staf, Christian; Falconer, Henrik; Bjurberg, Maria; Kjölhede, Preben; Rosenberg, Per; Stålberg, Karin; Högberg, Thomas; Åvall-Lundqvist, Elisabeth

    2017-01-01

    The aim of the study was to determine survival outcome in patients with serous cancer in the ovary, fallopian tube, peritoneum and of undesignated origin. Nation-wide population-based study of women≥18years with histologically verified non-uterine serous cancer, included in the Swedish Quality Registry for primary cancer of the ovary, fallopian tube and peritoneum diagnosed 2009-2013. Relative survival (RS) was estimated using the Ederer II method. Simple and multivariable analyses were estimated by Poisson regression models. Of 5627 women identified, 1246 (22%) had borderline tumors and 4381 had malignant tumors. In total, 2359 women had serous cancer; 71% originated in the ovary (OC), 9% in the fallopian tube (FTC), 9% in the peritoneum (PPC) and 11% at an undesignated primary site (UPS). Estimated RS at 5-years was 37%; for FTC 54%, 40% for OC, 34% for PPC and 13% for UPS. In multivariable regression analyses restricted to women who had undergone primary or interval debulking surgery for OC, FTC and PPC, site of origin was not independently associated with survival. Significant associations with worse survival were found for advanced stages (RR 2.63, Pcancer at UPS than for ovarian, fallopian tube and peritoneal cancer. Serous cancer at UPS needs to be addressed when reporting and comparing survival rates of ovarian cancer. Copyright © 2016 Elsevier Inc. All rights reserved.

  7. Multidimensional Poverty and Child Survival in India

    Science.gov (United States)

    Mohanty, Sanjay K.

    2011-01-01

    Background Though the concept of multidimensional poverty has been acknowledged cutting across the disciplines (among economists, public health professionals, development thinkers, social scientists, policy makers and international organizations) and included in the development agenda, its measurement and application are still limited. Objectives and Methodology Using unit data from the National Family and Health Survey 3, India, this paper measures poverty in multidimensional space and examine the linkages of multidimensional poverty with child survival. The multidimensional poverty is measured in the dimension of knowledge, health and wealth and the child survival is measured with respect to infant mortality and under-five mortality. Descriptive statistics, principal component analyses and the life table methods are used in the analyses. Results The estimates of multidimensional poverty are robust and the inter-state differentials are large. While infant mortality rate and under-five mortality rate are disproportionately higher among the abject poor compared to the non-poor, there are no significant differences in child survival among educationally, economically and health poor at the national level. State pattern in child survival among the education, economical and health poor are mixed. Conclusion Use of multidimensional poverty measures help to identify abject poor who are unlikely to come out of poverty trap. The child survival is significantly lower among abject poor compared to moderate poor and non-poor. We urge to popularize the concept of multiple deprivations in research and program so as to reduce poverty and inequality in the population. PMID:22046384

  8. Multidimensional poverty and child survival in India.

    Science.gov (United States)

    Mohanty, Sanjay K

    2011-01-01

    Though the concept of multidimensional poverty has been acknowledged cutting across the disciplines (among economists, public health professionals, development thinkers, social scientists, policy makers and international organizations) and included in the development agenda, its measurement and application are still limited. OBJECTIVES AND METHODOLOGY: Using unit data from the National Family and Health Survey 3, India, this paper measures poverty in multidimensional space and examine the linkages of multidimensional poverty with child survival. The multidimensional poverty is measured in the dimension of knowledge, health and wealth and the child survival is measured with respect to infant mortality and under-five mortality. Descriptive statistics, principal component analyses and the life table methods are used in the analyses. The estimates of multidimensional poverty are robust and the inter-state differentials are large. While infant mortality rate and under-five mortality rate are disproportionately higher among the abject poor compared to the non-poor, there are no significant differences in child survival among educationally, economically and health poor at the national level. State pattern in child survival among the education, economical and health poor are mixed. Use of multidimensional poverty measures help to identify abject poor who are unlikely to come out of poverty trap. The child survival is significantly lower among abject poor compared to moderate poor and non-poor. We urge to popularize the concept of multiple deprivations in research and program so as to reduce poverty and inequality in the population.

  9. Multidimensional poverty and child survival in India.

    Directory of Open Access Journals (Sweden)

    Sanjay K Mohanty

    Full Text Available Though the concept of multidimensional poverty has been acknowledged cutting across the disciplines (among economists, public health professionals, development thinkers, social scientists, policy makers and international organizations and included in the development agenda, its measurement and application are still limited. OBJECTIVES AND METHODOLOGY: Using unit data from the National Family and Health Survey 3, India, this paper measures poverty in multidimensional space and examine the linkages of multidimensional poverty with child survival. The multidimensional poverty is measured in the dimension of knowledge, health and wealth and the child survival is measured with respect to infant mortality and under-five mortality. Descriptive statistics, principal component analyses and the life table methods are used in the analyses.The estimates of multidimensional poverty are robust and the inter-state differentials are large. While infant mortality rate and under-five mortality rate are disproportionately higher among the abject poor compared to the non-poor, there are no significant differences in child survival among educationally, economically and health poor at the national level. State pattern in child survival among the education, economical and health poor are mixed.Use of multidimensional poverty measures help to identify abject poor who are unlikely to come out of poverty trap. The child survival is significantly lower among abject poor compared to moderate poor and non-poor. We urge to popularize the concept of multiple deprivations in research and program so as to reduce poverty and inequality in the population.

  10. [A SAS marco program for batch processing of univariate Cox regression analysis for great database].

    Science.gov (United States)

    Yang, Rendong; Xiong, Jie; Peng, Yangqin; Peng, Xiaoning; Zeng, Xiaomin

    2015-02-01

    To realize batch processing of univariate Cox regression analysis for great database by SAS marco program. We wrote a SAS macro program, which can filter, integrate, and export P values to Excel by SAS9.2. The program was used for screening survival correlated RNA molecules of ovarian cancer. A SAS marco program could finish the batch processing of univariate Cox regression analysis, the selection and export of the results. The SAS macro program has potential applications in reducing the workload of statistical analysis and providing a basis for batch processing of univariate Cox regression analysis.

  11. Influence of human development and predators on nest survival of tundra birds, Arctic Coastal Plain, Alaska.

    Science.gov (United States)

    Liebezeit, J R; Kendall, S J; Brown, S; Johnson, C B; Martin, P; McDonald, T L; Payer, D C; Rea, C L; Streever, B; Wildman, A M; Zack, S

    2009-09-01

    Nest predation may influence population dynamics of birds on the Arctic Coastal Plain (ACP) of Alaska, USA. Anthropogenic development on the ACP is increasing, which may attract nest predators by providing artificial sources of food, perches, den sites, and nest sites. Enhanced populations or concentrations of human-subsidized predators may reduce nest survival for tundra-nesting birds. In this study, we tested the hypothesis that nest survival decreases in proximity to human infrastructure. We monitored 1257 nests of 13 shorebird species and 619 nests of four passerine species at seven sites on the ACP from 2002 to 2005. Study sites were chosen to represent a range of distances to infrastructure from 100 m to 80 km. We used Cox proportional hazards regression models to evaluate the effects of background (i.e., natural) factors and infrastructure on nest survival. We documented high spatial and temporal variability in nest survival, and site and year were both included in the best background model. We did not detect an effect of human infrastructure on nest survival for shorebirds as a group. In contrast, we found evidence that risk of predation for passerine nests increased within 5 km of infrastructure. This finding provides quantitative evidence of a relationship between infrastructure and nest survival for breeding passerines on the ACP. A posteriori finer-scale analyses (within oil field sites and individual species) suggested that Red and Red-necked Phalaropes combined (Phalaropus fulicarius, P. lobatus) had lower productivity closer to infrastructure and in areas with higher abundance of subsidized predators. However, we did not detect such a relationship between infrastructure and nest survival for Semipalmated and Pectoral Sandpipers (Calidris pusilla, C. melanotos), the two most abundant shorebirds. High variability in environmental conditions, nest survival, and predator numbers between sites and years may have contributed to these inconsistent results

  12. Logistic Regression Analysis of Operational Errors and Routine Operations Using Sector Characteristics

    National Research Council Canada - National Science Library

    Pfleiderer, Elaine M; Scroggins, Cheryl L; Manning, Carol A

    2009-01-01

    Two separate logistic regression analyses were conducted for low- and high-altitude sectors to determine whether a set of dynamic sector characteristics variables could reliably discriminate between operational error (OE...

  13. Mutation in filamin A causes periventricular heterotopia, developmental regression, and West syndrome in males.

    Science.gov (United States)

    Masruha, Marcelo R; Caboclo, Luis O S F; Carrete, Henrique; Cendes, Iscia L; Rodrigues, Murilo G; Garzon, Eliana; Yacubian, Elza M T; Sakamoto, Américo C; Sheen, Volney; Harney, Megan; Neal, Jason; Hill, R Sean; Bodell, Adria; Walsh, Christopher; Vilanova, Luiz C P

    2006-01-01

    Familial periventricular heterotopia (PH) represents a disorder of neuronal migration resulting in multiple gray-matter nodules along the lateral ventricular walls. Prior studies have shown that mutations in the filamin A (FLNA) gene can cause PH through an X-linked dominant pattern. Heterozygotic female patients usually remain asymptomatic until the second or third decade of life, when they may have predominantly focal seizures, whereas hemizygotic male fetuses typically die in utero. Recent studies have also reported mutations in FLNA in male patients with PH who are cognitively normal. We describe PH in three male siblings with PH due to FLNA, severe developmental regression, and West syndrome. The study includes the three affected brothers and their parents. Video-EEG recordings and magnetic resonance image (MRI) scanning were performed on all individuals. Mutations for FLNA were detected by using polymerase chain reaction (PCR) on genomic DNA followed by single-stranded conformational polymorphism (SSCP) analysis or sequencing. Two of the siblings are monozygotic twins, and all had West syndrome with hypsarrhythmia on EEG. MRI of the brain revealed periventricular nodules of cerebral gray-matter intensity, typical for PH. Mutational analyses demonstrated a cytosine-to-thymidine missense mutation (c. C1286T), resulting in a threonine-to-methionine amino acid substitution in exon 9 of the FLNA gene. The association between PH and West syndrome, to our knowledge, has not been previously reported. Males with PH have been known to harbor FLNA mutations, although uniformly, they either show early lethality or survive and have a normal intellect. The current studies show that FLNA mutations can cause periventricular heterotopia, developmental regression, and West syndrome in male patients, suggesting that this type of FLNA mutation may contribute to severe neurologic deficits.

  14. Easy methods for extracting individual regression slopes: Comparing SPSS, R, and Excel

    Directory of Open Access Journals (Sweden)

    Roland Pfister

    2013-10-01

    Full Text Available Three different methods for extracting coefficientsof linear regression analyses are presented. The focus is on automatic and easy-to-use approaches for common statistical packages: SPSS, R, and MS Excel / LibreOffice Calc. Hands-on examples are included for each analysis, followed by a brief description of how a subsequent regression coefficient analysis is performed.

  15. Prognostic factorsin inoperable adenocarcinoma of the lung: A multivariate regression analysis of 259 patiens

    DEFF Research Database (Denmark)

    Sørensen, Jens Benn; Badsberg, Jens Henrik; Olsen, Jens

    1989-01-01

    The prognostic factors for survival in advanced adenocarcinoma of the lung were investigated in a consecutive series of 259 patients treated with chemotherapy. Twenty-eight pretreatment variables were investigated by use of Cox's multivariate regression model, including histological subtypes and ...

  16. Using a Regression Discontinuity Design to Estimate the Impact of Placement Decisions in Developmental Math

    Science.gov (United States)

    Melguizo, Tatiana; Bos, Johannes M.; Ngo, Federick; Mills, Nicholas; Prather, George

    2016-01-01

    This study evaluates the effectiveness of math placement policies for entering community college students on these students' academic success in math. We estimate the impact of placement decisions by using a discrete-time survival model within a regression discontinuity framework. The primary conclusion that emerges is that initial placement in a…

  17. Cox regression with missing covariate data using a modified partial likelihood method

    DEFF Research Database (Denmark)

    Martinussen, Torben; Holst, Klaus K.; Scheike, Thomas H.

    2016-01-01

    Missing covariate values is a common problem in survival analysis. In this paper we propose a novel method for the Cox regression model that is close to maximum likelihood but avoids the use of the EM-algorithm. It exploits that the observed hazard function is multiplicative in the baseline hazard...

  18. Prognostic value of tumor regression evaluated after first course of radiotherapy for anal canal cancer

    International Nuclear Information System (INIS)

    Chapet, Olivier; Gerard, Jean-Pierre; Riche, Benjamin; Alessio, Annunziato; Mornex, Francoise; Romestaing, Pascale

    2005-01-01

    Purpose: To evaluate whether the tumor response after an initial course of irradiation predicts for colostomy-free survival and overall survival in patients with anal canal cancer. Methods and Materials: Between 1980 and 1998, 252 patients were treated by pelvic external-beam radiotherapy (EBRT) followed by a brachytherapy boost in 218 or EBRT in 34. EBRT was combined with chemotherapy in 168 patients. An evaluation of tumor regression, before the boost, was available for 221 patients. They were divided into four groups according to the tumor response: 80% but 80% vs. ≤80%. The group with a T3-T4 lesion and tumor regression ≤80% had the poorest overall (52.8% ± 12.3%), disease-free (19.9% ± 9.9%), and colostomy-free survival (24.8% ± 11.2%) rates. Conclusion: The amount of tumor regression before EBRT or brachytherapy boost is a strong prognostic factor of disease control without colostomy. When regression is ≤80% in patients with an initial T3-T4 lesion, the use of conservative RT should be carefully evaluated because of the very poor disease-free and colostomy-free survival

  19. Survival of Alzheimer's disease patients in Korea.

    Science.gov (United States)

    Go, Seok Min; Lee, Kang Soo; Seo, Sang Won; Chin, Juhee; Kang, Sue J; Moon, So Young; Na, Duk L; Cheong, Hae-Kwan

    2013-01-01

    The natural history of Alzheimer's disease (AD) has rarely been studied in the Korean population. Our study on survival analyses in Korean AD patients potentially provides a basis for cross-cultural comparisons. We studied 724 consecutive patients from a memory disorder clinic in a tertiary hospital in Seoul, who were diagnosed as having AD between April 1995 and December 2005. Deaths were identified by the Statistics Korea database. The Kaplan-Meier method was used for survival analysis, and a Cox proportional hazard model was used to assess factors related to patient survival. The overall median survival from the onset of first symptoms and from the time of diagnosis was 12.6 years (95% confidence interval 11.7-13.4) and 9.3 years (95% confidence interval 8.7-9.9), respectively. The age of onset, male gender, history of diabetes mellitus, lower Mini-Mental State Examination score, and higher Clinical Dementia Rating score were negatively associated with survival. There was a reversal of risk of AD between early-onset and later-onset AD, 9.1 years after onset. The results of our study show a different pattern of survival compared to those studies carried out with western AD populations. Mortality risk of early-onset AD varied depending on the duration of follow-up. Copyright © 2013 S. Karger AG, Basel.

  20. Regression modeling of ground-water flow

    Science.gov (United States)

    Cooley, R.L.; Naff, R.L.

    1985-01-01

    Nonlinear multiple regression methods are developed to model and analyze groundwater flow systems. Complete descriptions of regression methodology as applied to groundwater flow models allow scientists and engineers engaged in flow modeling to apply the methods to a wide range of problems. Organization of the text proceeds from an introduction that discusses the general topic of groundwater flow modeling, to a review of basic statistics necessary to properly apply regression techniques, and then to the main topic: exposition and use of linear and nonlinear regression to model groundwater flow. Statistical procedures are given to analyze and use the regression models. A number of exercises and answers are included to exercise the student on nearly all the methods that are presented for modeling and statistical analysis. Three computer programs implement the more complex methods. These three are a general two-dimensional, steady-state regression model for flow in an anisotropic, heterogeneous porous medium, a program to calculate a measure of model nonlinearity with respect to the regression parameters, and a program to analyze model errors in computed dependent variables such as hydraulic head. (USGS)

  1. Progression-free survival as a potential surrogate for overall survival in metastatic breast cancer

    Directory of Open Access Journals (Sweden)

    Beauchemin C

    2014-06-01

    Full Text Available Catherine Beauchemin,1 Dan Cooper,2 Marie-Ève Lapierre,1 Louise Yelle,3 Jean Lachaine11Université de Montréal, Faculté de pharmacie, Montreal, 2Institut national d'excellence en santé et en services sociaux (INESSS, 3Centre Hospitalier de l'Université de Montréal – Hôpital Notre-Dame, Département de médecine, Université de Montréal, Montreal, QC, CanadaBackground: Progression-free survival (PFS and time to progression (TTP are frequently used to establish the clinical efficacy of anti-cancer drugs. However, the surrogacy of PFS/TTP for overall survival (OS remains a matter of uncertainty in metastatic breast cancer (mBC. This study assessed the relationship between PFS/TTP and OS in mBC using a trial-based approach.Methods: We conducted a systematic literature review according to the PICO method: 'Population' consisted of women with mBC; 'Interventions' and 'Comparators' were standard treatments for mBC or best supportive care; 'Outcomes' of interest were median PFS/TTP and OS. We first performed a correlation analysis between median PFS/TTP and OS, and then conducted subgroup analyses to explore possible reasons for heterogeneity. Then, we assessed the relationship between the treatment effect on PFS/TTP and OS. The treatment effect on PFS/TTP and OS was quantified by the absolute difference of median values. We also conducted linear regression analysis to predict the effects of a new anti-cancer drug on OS on the basis of its effects on PFS/TTP.Results: A total of 5,041 studies were identified, and 144 fulfilled the eligibility criteria. There was a statistically significant relationship between median PFS/TTP and OS across included trials (r=0.428; P<0.01. Correlation coefficient for the treatment effect on PFS/TTP and OS was estimated at 0.427 (P<0.01. The obtained linear regression equation was ΔOS =−0.088 (95% confidence interval [CI] −1.347–1.172 + 1.753 (95% CI 1.307–2.198 × ΔPFS (R2=0.86.Conclusion: Results of

  2. Logistic Regression in the Identification of Hazards in Construction

    Science.gov (United States)

    Drozd, Wojciech

    2017-10-01

    The construction site and its elements create circumstances that are conducive to the formation of risks to safety during the execution of works. Analysis indicates the critical importance of these factors in the set of characteristics that describe the causes of accidents in the construction industry. This article attempts to analyse the characteristics related to the construction site, in order to indicate their importance in defining the circumstances of accidents at work. The study includes sites inspected in 2014 - 2016 by the employees of the District Labour Inspectorate in Krakow (Poland). The analysed set of detailed (disaggregated) data includes both quantitative and qualitative characteristics. The substantive task focused on classification modelling in the identification of hazards in construction and identifying those of the analysed characteristics that are important in an accident. In terms of methodology, resource data analysis using statistical classifiers, in the form of logistic regression, was the method used.

  3. Variable and subset selection in PLS regression

    DEFF Research Database (Denmark)

    Høskuldsson, Agnar

    2001-01-01

    The purpose of this paper is to present some useful methods for introductory analysis of variables and subsets in relation to PLS regression. We present here methods that are efficient in finding the appropriate variables or subset to use in the PLS regression. The general conclusion...... is that variable selection is important for successful analysis of chemometric data. An important aspect of the results presented is that lack of variable selection can spoil the PLS regression, and that cross-validation measures using a test set can show larger variation, when we use different subsets of X, than...

  4. Applied Regression Modeling A Business Approach

    CERN Document Server

    Pardoe, Iain

    2012-01-01

    An applied and concise treatment of statistical regression techniques for business students and professionals who have little or no background in calculusRegression analysis is an invaluable statistical methodology in business settings and is vital to model the relationship between a response variable and one or more predictor variables, as well as the prediction of a response value given values of the predictors. In view of the inherent uncertainty of business processes, such as the volatility of consumer spending and the presence of market uncertainty, business professionals use regression a

  5. Accelerated failure time regression for backward recurrence times and current durations

    DEFF Research Database (Denmark)

    Keiding, N; Fine, J P; Hansen, O H

    2011-01-01

    Backward recurrence times in stationary renewal processes and current durations in dynamic populations observed at a cross-section may yield estimates of underlying interarrival times or survival distributions under suitable stationarity assumptions. Regression models have been proposed for these......Backward recurrence times in stationary renewal processes and current durations in dynamic populations observed at a cross-section may yield estimates of underlying interarrival times or survival distributions under suitable stationarity assumptions. Regression models have been proposed...... for these situations, but accelerated failure time models have the particularly attractive feature that they are preserved when going from the backward recurrence times to the underlying survival distribution of interest. This simple fact has recently been noticed in a sociological context and is here illustrated...... by a study of current duration of time to pregnancy...

  6. Predictors of survival in surgically treated patients of spinal metastasis

    Directory of Open Access Journals (Sweden)

    Pravin Padalkar

    2011-01-01

    Full Text Available Background: The spinal metastasis occurs in up to 40% of cancer patient. We compared the Tokuhashi and Tomita scoring systems, two commonly used scoring systems for prognosis in spinal metastases. We also assessed the different variables separately with respect to their value in predicting postsurgical life expectancy. Finally, we suggest criteria for selecting patients for surgery based on the postoperative survival pattern. Materials and Methods: We retrospectively analyzed 102 patients who had been operated for metastatic disease of the spine. Predictive scoring was done according to the scoring systems proposed by Tokuhashi and Tomita. Overall survival was assessed using Kaplan-Meier survival analysis. Using the log rank test and Cox regression model we assessed the value of the individual components of each scoring system for predicting survival in these patients. Result: The factors that were most significantly associated with survival were the general condition score (Karnofsky Performance Scale (P=.000, log rank test, metastasis to internal organs (P=.0002 log rank test, and number of extraspinal bone metastases (P=.0058. Type of primary tumor was not found to be significantly associated with survival according to the revised Tokuhashi scoring system (P=.9131, log rank test. Stepwise logistic regression revealed that the Tomita score correlated more closely with survival than the Tokuhashi score. Conclusion: The patient′s performance status, extent of visceral metastasis, and extent of bone metastases are significant predictors of survival in patients with metastatic disease. Both revised Tokuhashi and Tomita scores were significantly correlated with survival. A revised Tokuhashi score of 7 or more and a Tomita score of 6 or less indicated >50% chance of surviving 6 months postoperatively. We recommend that the Tomita score be used for prognostication in patients who are contemplating surgery, as it is simpler to score and has a higher

  7. Linear regression metamodeling as a tool to summarize and present simulation model results.

    Science.gov (United States)

    Jalal, Hawre; Dowd, Bryan; Sainfort, François; Kuntz, Karen M

    2013-10-01

    Modelers lack a tool to systematically and clearly present complex model results, including those from sensitivity analyses. The objective was to propose linear regression metamodeling as a tool to increase transparency of decision analytic models and better communicate their results. We used a simplified cancer cure model to demonstrate our approach. The model computed the lifetime cost and benefit of 3 treatment options for cancer patients. We simulated 10,000 cohorts in a probabilistic sensitivity analysis (PSA) and regressed the model outcomes on the standardized input parameter values in a set of regression analyses. We used the regression coefficients to describe measures of sensitivity analyses, including threshold and parameter sensitivity analyses. We also compared the results of the PSA to deterministic full-factorial and one-factor-at-a-time designs. The regression intercept represented the estimated base-case outcome, and the other coefficients described the relative parameter uncertainty in the model. We defined simple relationships that compute the average and incremental net benefit of each intervention. Metamodeling produced outputs similar to traditional deterministic 1-way or 2-way sensitivity analyses but was more reliable since it used all parameter values. Linear regression metamodeling is a simple, yet powerful, tool that can assist modelers in communicating model characteristics and sensitivity analyses.

  8. Fingertip replantation: determinants of survival.

    Science.gov (United States)

    Li, Jing; Guo, Zheng; Zhu, Qingsheng; Lei, Wei; Han, Yisheng; Li, Mingquan; Wang, Zhen

    2008-09-01

    The purpose of this study was to determine the risk factors for an unsuccessful replanted fingertip. Two hundred eleven complete fingertip amputations in 211 patients who underwent replantation surgery between August of 1990 and March of 2006 were included in this study. The patients' age, gender, smoking history, digit position, dominant hand, amputation level, injury mechanism, platelet count, ischemia time, preservation method of the amputated part, anesthesia, number of arteries repaired, venous drainage, use of vein grafting, neurorrhaphy, bone shortening, and smoking after operation were tested for their impact on fingertip survival. One hundred seventy-two of 211 patients (81.5 percent) had a successful replantation. Univariate analysis showed crush or avulsion injury, high platelet count, and inappropriate preservation of the amputated part in saline solution or ethanol to be associated with a high incidence of replantation failure. Twenty-two of 54 patients (41 percent) who had a crush or avulsion trauma had failed replantation. Logistic regression analysis identified injury mechanism, platelet count, smoking after operation, preservation method of the amputated part, and the use of vein grafting as statistically significant predictive factors for success or failure. Injury mechanism, platelet count, smoking after operation, preservation method of amputated part, and the use of vein grafting were found to be the main predictors for the survival of the replanted fingertip. Applying external bleeding in zone 1 and venous drainage through the medullary cavity in zone 2 or venous anastomosis combined with vein grafting rather than venous anastomosis alone were strongly recommended in the fingertip replantation of crush or avulsion injury.

  9. Pre-therapeutic factors for predicting survival after radioembolization: a single-center experience in 389 patients

    International Nuclear Information System (INIS)

    Paprottka, K.J.; Schoeppe, F.; Ingrisch, M.; Ruebenthaler, J.; Sommer, N.N.; Paprottka, P.M.; Toni, E. de; Ilhan, H.; Zacherl, M.; Todica, A.

    2017-01-01

    To determine pre-therapeutic predictive factors for overall survival (OS) after yttrium (Y)-90 radioembolization (RE). We retrospectively analyzed the pre-therapeutic characteristics (sex, age, tumor entity, hepatic tumor burden, extrahepatic disease [EHD] and liver function [with focus on bilirubin and cholinesterase level]) of 389 consecutive patients with various refractory liver-dominant tumors (hepatocellular carcinoma [HCC], cholangiocarcinoma [CCC], neuroendocrine tumor [NET], colorectal cancer [CRC] and metastatic breast cancer [MBC]), who received Y-90 radioembolization for predicting survival. Predictive factors were selected by univariate Cox regression analysis and subsequently tested by multivariate analysis for predicting patient survival. The median OS was 356 days (95% CI 285-427 days). Stable disease was observed in 132 patients, an objective response in 71 (one of which was complete remission) and progressive disease in 122. The best survival rate was observed in patients with NET, and the worst in patients with MBC. In the univariate analyses, extrahepatic disease (P < 0.001), large tumor burden (P = 0.001), high bilirubin levels (>1.9 mg/dL, P < 0.001) and low cholinesterase levels (CHE <4.62 U/I, P < 0.001) at baseline were significantly associated with poor survival. Tumor entity, tumor burden, extrahepatic disease and CHE were confirmed in the multivariate analysis as independent predictors of survival. Sex, applied RE dose and age had no significant influence on OS. Pre-therapeutic baseline bilirubin and CHE levels, extrahepatic disease and hepatic tumor burden are associated with patient survival after RE. Such parameters may be used to improve patient selection for RE of primary or metastatic liver tumors. (orig.)

  10. The difference in association between aspirin use and other thrombocyte aggregation inhibitors and survival in patients with colorectal cancer.

    Science.gov (United States)

    Frouws, M A; Rademaker, E; Bastiaannet, E; van Herk-Sukel, M P P; Lemmens, V E; Van de Velde, C J H; Portielje, J E A; Liefers, G J

    2017-05-01

    Several studies have suggested that the association between aspirin and improved cancer survival is mediated through the mechanism of aspirin as thrombocyte aggregation inhibitors (TAI). The aim of this study was to provide epidemiological evidence for this mechanism assessing the association between overall survival and the use of aspirin and non-aspirin TAI in patients with colorectal cancer. In this observational study, data from the Netherlands Comprehensive Cancer Organisation were linked to PHARMO Database Network. Patients using aspirin or aspirin in combination with non-aspirin TAI (dual users) were selected and compared with non-users. The association between overall survival and the use of (non-)aspirin TAI was analysed using Cox regression models with the use of (non-)aspirin TAI as a time-varying covariate. In total, 9196 patients were identified with colorectal cancer and 1766 patients used TAI after diagnosis. Non-aspirin TAI were mostly clopidogrel and dipyridamole. Aspirin use was associated with a significant increased overall survival and hazard ratio (HR) 0.41 (95% confidence interval [CI] 0.37-0.47), and the use of non-aspirin TAI was not associated with survival of HR 0.92 (95% CI 0.70-1.22). Dual users did not have an improved overall survival when compared with patients using solely aspirin. Aspirin use after diagnosis of colorectal cancer was associated with significantly lower mortality rates and this effect remained significant after adjusting for potential confounders. No additional survival benefit was observed in patients using both aspirin and another TAI. Copyright © 2017 Elsevier Ltd. All rights reserved.

  11. Pre-therapeutic factors for predicting survival after radioembolization: a single-center experience in 389 patients

    Energy Technology Data Exchange (ETDEWEB)

    Paprottka, K.J.; Schoeppe, F.; Ingrisch, M.; Ruebenthaler, J.; Sommer, N.N.; Paprottka, P.M. [LMU - University of Munich, Department of Clinical Radiology, Munich (Germany); Toni, E. de [LMU - University of Munich, Department of Hepatology, Munich (Germany); Ilhan, H.; Zacherl, M.; Todica, A. [LMU - University of Munich, Department of Nuclear Medicine, Munich (Germany)

    2017-07-15

    To determine pre-therapeutic predictive factors for overall survival (OS) after yttrium (Y)-90 radioembolization (RE). We retrospectively analyzed the pre-therapeutic characteristics (sex, age, tumor entity, hepatic tumor burden, extrahepatic disease [EHD] and liver function [with focus on bilirubin and cholinesterase level]) of 389 consecutive patients with various refractory liver-dominant tumors (hepatocellular carcinoma [HCC], cholangiocarcinoma [CCC], neuroendocrine tumor [NET], colorectal cancer [CRC] and metastatic breast cancer [MBC]), who received Y-90 radioembolization for predicting survival. Predictive factors were selected by univariate Cox regression analysis and subsequently tested by multivariate analysis for predicting patient survival. The median OS was 356 days (95% CI 285-427 days). Stable disease was observed in 132 patients, an objective response in 71 (one of which was complete remission) and progressive disease in 122. The best survival rate was observed in patients with NET, and the worst in patients with MBC. In the univariate analyses, extrahepatic disease (P < 0.001), large tumor burden (P = 0.001), high bilirubin levels (>1.9 mg/dL, P < 0.001) and low cholinesterase levels (CHE <4.62 U/I, P < 0.001) at baseline were significantly associated with poor survival. Tumor entity, tumor burden, extrahepatic disease and CHE were confirmed in the multivariate analysis as independent predictors of survival. Sex, applied RE dose and age had no significant influence on OS. Pre-therapeutic baseline bilirubin and CHE levels, extrahepatic disease and hepatic tumor burden are associated with patient survival after RE. Such parameters may be used to improve patient selection for RE of primary or metastatic liver tumors. (orig.)

  12. Vectors, a tool in statistical regression theory

    NARCIS (Netherlands)

    Corsten, L.C.A.

    1958-01-01

    Using linear algebra this thesis developed linear regression analysis including analysis of variance, covariance analysis, special experimental designs, linear and fertility adjustments, analysis of experiments at different places and times. The determination of the orthogonal projection, yielding

  13. Genetics Home Reference: caudal regression syndrome

    Science.gov (United States)

    ... umbilical artery: Further support for a caudal regression-sirenomelia spectrum. Am J Med Genet A. 2007 Dec ... AK, Dickinson JE, Bower C. Caudal dysgenesis and sirenomelia-single centre experience suggests common pathogenic basis. Am ...

  14. Dynamic travel time estimation using regression trees.

    Science.gov (United States)

    2008-10-01

    This report presents a methodology for travel time estimation by using regression trees. The dissemination of travel time information has become crucial for effective traffic management, especially under congested road conditions. In the absence of c...

  15. Quality of life as predictor of survival: A prospective study on patients treated with combined surgery and radiotherapy for advanced oral and oropharyngeal cancer

    International Nuclear Information System (INIS)

    Oskam, Inge M.; Verdonck-de Leeuw, Irma M.; Aaronson, Neil K.; Kuik, Dirk J.; Bree, Remco de; Doornaert, Patricia; Langendijk, Johannes A.; Leemans, Rene C.

    2010-01-01

    Background and purpose: The relation between health-related quality of life (HRQOL) and survival was investigated at baseline and 6 months in 80 patients with advanced oral or oropharyngeal cancer after microvascular reconstructive surgery and (almost all) adjuvant radiotherapy. Materials and methods: Multivariate Cox regression analyses of overall and disease-specific survival were performed including sociodemographic (age, gender, marital status, comorbidity), and clinical (tumor stage and site, radical surgical, metastasis, radiotherapy) parameters, and HRQOL (EORTC QLQ-C30 global quality of life scale). Results: Before treatment, younger age and having a partner were predictors of disease-specific survival; younger age predicted overall survival. At 6 months post-treatment, disease-specific and overall survival was predicted by (deterioration of) global quality of life solely. Global health-related quality of life after treatment was mainly influenced by emotional functioning. Conclusion: Deterioration of global quality of life after treatment is an independent predictor of survival in patients with advanced oral or oropharyngeal cancer.

  16. Survival Analysis of Factors Influencing Cyclic Fatigue of Nickel-Titanium Endodontic Instruments

    Directory of Open Access Journals (Sweden)

    Eva Fišerová

    2015-01-01

    Full Text Available Objective. The aim of this study was to validate a survival analysis assessing the effect of type of rotary system, canal curvature, and instrument size on cyclic resistance. Materials and Methods. Cyclic fatigue testing was carried out in stainless steel artificial canals with radii of curvature of 3 or 5 mm and the angle of curvature of 60 degrees. All the instruments were new and 25 mm in working length, and ISO colour coding indicated the instrument size (yellow for size 20; red for size 25. Wizard Navigator instruments, Mtwo instruments, ProTaper instruments, and Revo-S instruments were passively rotated at 250 rotations per minute, and the time fracture was being recorded. Subsequently, fractographic analysis of broken tips was performed by scanning electron microscope. The data were then analysed by the Kaplan-Meier estimator of the survival function, the Cox proportional hazards model, the Wald test for regression covariates, and the Wald test for significance of regression model. Conclusion. The lifespan registered for the tested instruments was Mtwo > Wizard Navigator > Revo-S > ProTaper; 5 mm radius > 3 mm radius; and yellow > red in ISO colour coding system.

  17. Two Paradoxes in Linear Regression Analysis

    Science.gov (United States)

    FENG, Ge; PENG, Jing; TU, Dongke; ZHENG, Julia Z.; FENG, Changyong

    2016-01-01

    Summary Regression is one of the favorite tools in applied statistics. However, misuse and misinterpretation of results from regression analysis are common in biomedical research. In this paper we use statistical theory and simulation studies to clarify some paradoxes around this popular statistical method. In particular, we show that a widely used model selection procedure employed in many publications in top medical journals is wrong. Formal procedures based on solid statistical theory should be used in model selection. PMID:28638214

  18. Discriminative Elastic-Net Regularized Linear Regression.

    Science.gov (United States)

    Zhang, Zheng; Lai, Zhihui; Xu, Yong; Shao, Ling; Wu, Jian; Xie, Guo-Sen

    2017-03-01

    In this paper, we aim at learning compact and discriminative linear regression models. Linear regression has been widely used in different problems. However, most of the existing linear regression methods exploit the conventional zero-one matrix as the regression targets, which greatly narrows the flexibility of the regression model. Another major limitation of these methods is that the learned projection matrix fails to precisely project the image features to the target space due to their weak discriminative capability. To this end, we present an elastic-net regularized linear regression (ENLR) framework, and develop two robust linear regression models which possess the following special characteristics. First, our methods exploit two particular strategies to enlarge the margins of different classes by relaxing the strict binary targets into a more feasible variable matrix. Second, a robust elastic-net regularization of singular values is introduced to enhance the compactness and effectiveness of the learned projection matrix. Third, the resulting optimization problem of ENLR has a closed-form solution in each iteration, which can be solved efficiently. Finally, rather than directly exploiting the projection matrix for recognition, our methods employ the transformed features as the new discriminate representations to make final image classification. Compared with the traditional linear regression model and some of its variants, our method is much more accurate in image classification. Extensive experiments conducted on publicly available data sets well demonstrate that the proposed framework can outperform the state-of-the-art methods. The MATLAB codes of our methods can be available at http://www.yongxu.org/lunwen.html.

  19. Fuzzy multiple linear regression: A computational approach

    Science.gov (United States)

    Juang, C. H.; Huang, X. H.; Fleming, J. W.

    1992-01-01

    This paper presents a new computational approach for performing fuzzy regression. In contrast to Bardossy's approach, the new approach, while dealing with fuzzy variables, closely follows the conventional regression technique. In this approach, treatment of fuzzy input is more 'computational' than 'symbolic.' The following sections first outline the formulation of the new approach, then deal with the implementation and computational scheme, and this is followed by examples to illustrate the new procedure.

  20. Computing multiple-output regression quantile regions

    Czech Academy of Sciences Publication Activity Database

    Paindaveine, D.; Šiman, Miroslav

    2012-01-01

    Roč. 56, č. 4 (2012), s. 840-853 ISSN 0167-9473 R&D Projects: GA MŠk(CZ) 1M06047 Institutional research plan: CEZ:AV0Z10750506 Keywords : halfspace depth * multiple-output regression * parametric linear programming * quantile regression Subject RIV: BA - General Mathematics Impact factor: 1.304, year: 2012 http://library.utia.cas.cz/separaty/2012/SI/siman-0376413.pdf

  1. There is No Quantum Regression Theorem

    International Nuclear Information System (INIS)

    Ford, G.W.; OConnell, R.F.

    1996-01-01

    The Onsager regression hypothesis states that the regression of fluctuations is governed by macroscopic equations describing the approach to equilibrium. It is here asserted that this hypothesis fails in the quantum case. This is shown first by explicit calculation for the example of quantum Brownian motion of an oscillator and then in general from the fluctuation-dissipation theorem. It is asserted that the correct generalization of the Onsager hypothesis is the fluctuation-dissipation theorem. copyright 1996 The American Physical Society

  2. Caudal regression syndrome : a case report

    International Nuclear Information System (INIS)

    Lee, Eun Joo; Kim, Hi Hye; Kim, Hyung Sik; Park, So Young; Han, Hye Young; Lee, Kwang Hun

    1998-01-01

    Caudal regression syndrome is a rare congenital anomaly, which results from a developmental failure of the caudal mesoderm during the fetal period. We present a case of caudal regression syndrome composed of a spectrum of anomalies including sirenomelia, dysplasia of the lower lumbar vertebrae, sacrum, coccyx and pelvic bones,genitourinary and anorectal anomalies, and dysplasia of the lung, as seen during infantography and MR imaging

  3. Caudal regression syndrome : a case report

    Energy Technology Data Exchange (ETDEWEB)

    Lee, Eun Joo; Kim, Hi Hye; Kim, Hyung Sik; Park, So Young; Han, Hye Young; Lee, Kwang Hun [Chungang Gil Hospital, Incheon (Korea, Republic of)

    1998-07-01

    Caudal regression syndrome is a rare congenital anomaly, which results from a developmental failure of the caudal mesoderm during the fetal period. We present a case of caudal regression syndrome composed of a spectrum of anomalies including sirenomelia, dysplasia of the lower lumbar vertebrae, sacrum, coccyx and pelvic bones,genitourinary and anorectal anomalies, and dysplasia of the lung, as seen during infantography and MR imaging.

  4. Spontaneous regression of metastatic Merkel cell carcinoma.

    LENUS (Irish Health Repository)

    Hassan, S J

    2010-01-01

    Merkel cell carcinoma is a rare aggressive neuroendocrine carcinoma of the skin predominantly affecting elderly Caucasians. It has a high rate of local recurrence and regional lymph node metastases. It is associated with a poor prognosis. Complete spontaneous regression of Merkel cell carcinoma has been reported but is a poorly understood phenomenon. Here we present a case of complete spontaneous regression of metastatic Merkel cell carcinoma demonstrating a markedly different pattern of events from those previously published.

  5. Forecasting exchange rates: a robust regression approach

    OpenAIRE

    Preminger, Arie; Franck, Raphael

    2005-01-01

    The least squares estimation method as well as other ordinary estimation method for regression models can be severely affected by a small number of outliers, thus providing poor out-of-sample forecasts. This paper suggests a robust regression approach, based on the S-estimation method, to construct forecasting models that are less sensitive to data contamination by outliers. A robust linear autoregressive (RAR) and a robust neural network (RNN) models are estimated to study the predictabil...

  6. Marginal longitudinal semiparametric regression via penalized splines

    KAUST Repository

    Al Kadiri, M.

    2010-08-01

    We study the marginal longitudinal nonparametric regression problem and some of its semiparametric extensions. We point out that, while several elaborate proposals for efficient estimation have been proposed, a relative simple and straightforward one, based on penalized splines, has not. After describing our approach, we then explain how Gibbs sampling and the BUGS software can be used to achieve quick and effective implementation. Illustrations are provided for nonparametric regression and additive models.

  7. Marginal longitudinal semiparametric regression via penalized splines

    KAUST Repository

    Al Kadiri, M.; Carroll, R.J.; Wand, M.P.

    2010-01-01

    We study the marginal longitudinal nonparametric regression problem and some of its semiparametric extensions. We point out that, while several elaborate proposals for efficient estimation have been proposed, a relative simple and straightforward one, based on penalized splines, has not. After describing our approach, we then explain how Gibbs sampling and the BUGS software can be used to achieve quick and effective implementation. Illustrations are provided for nonparametric regression and additive models.

  8. COX-2 activation is associated with Akt phosphorylation and poor survival in ER-negative, HER2-positive breast cancer

    International Nuclear Information System (INIS)

    Glynn, Sharon A; Ambs, Stefan; Prueitt, Robyn L; Ridnour, Lisa A; Boersma, Brenda J; Dorsey, Tiffany M; Wink, David A; Goodman, Julie E; Yfantis, Harris G; Lee, Dong H

    2010-01-01

    Inducible cyclooxgenase-2 (COX-2) is commonly overexpressed in breast tumors and is a target for cancer therapy. Here, we studied the association of COX-2 with breast cancer survival and how this association is influenced by tumor estrogen and HER2 receptor status and Akt pathway activation. Tumor COX-2, HER2 and estrogen receptor α (ER) expression and phosphorylation of Akt, BAD, and caspase-9 were analyzed immunohistochemically in 248 cases of breast cancer. Spearman's correlation and multivariable logistic regression analyses were used to examine the relationship between COX-2 and tumor characteristics. Kaplan-Meier survival and multivariable Cox proportional hazards regression analyses were used to examine the relationship between COX-2 and disease-specific survival. COX-2 was significantly associated with breast cancer outcome in ER-negative [Hazard ratio (HR) = 2.72; 95% confidence interval (CI), 1.36-5.41; comparing high versus low COX-2] and HER2 overexpressing breast cancer (HR = 2.84; 95% CI, 1.07-7.52). However, the hazard of poor survival associated with increased COX-2 was highest among patients who were both ER-negative and HER2-positive (HR = 5.95; 95% CI, 1.01-34.9). Notably, COX-2 expression in the ER-negative and HER2-positive tumors correlated significantly with increased phosphorylation of Akt and of the two Akt targets, BAD at Ser136 and caspase-9 at Ser196. Up-regulation of COX-2 in ER-negative and HER2-positive breast tumors is associated with Akt pathway activation and is a marker of poor outcome. The findings suggest that COX-2-specific inhibitors and inhibitors of the Akt pathway may act synergistically as anticancer drugs in the ER-negative and HER2-positive breast cancer subtype

  9. Post-processing through linear regression

    Science.gov (United States)

    van Schaeybroeck, B.; Vannitsem, S.

    2011-03-01

    Various post-processing techniques are compared for both deterministic and ensemble forecasts, all based on linear regression between forecast data and observations. In order to evaluate the quality of the regression methods, three criteria are proposed, related to the effective correction of forecast error, the optimal variability of the corrected forecast and multicollinearity. The regression schemes under consideration include the ordinary least-square (OLS) method, a new time-dependent Tikhonov regularization (TDTR) method, the total least-square method, a new geometric-mean regression (GM), a recently introduced error-in-variables (EVMOS) method and, finally, a "best member" OLS method. The advantages and drawbacks of each method are clarified. These techniques are applied in the context of the 63 Lorenz system, whose model version is affected by both initial condition and model errors. For short forecast lead times, the number and choice of predictors plays an important role. Contrarily to the other techniques, GM degrades when the number of predictors increases. At intermediate lead times, linear regression is unable to provide corrections to the forecast and can sometimes degrade the performance (GM and the best member OLS with noise). At long lead times the regression schemes (EVMOS, TDTR) which yield the correct variability and the largest correlation between ensemble error and spread, should be preferred.

  10. Post-processing through linear regression

    Directory of Open Access Journals (Sweden)

    B. Van Schaeybroeck

    2011-03-01

    Full Text Available Various post-processing techniques are compared for both deterministic and ensemble forecasts, all based on linear regression between forecast data and observations. In order to evaluate the quality of the regression methods, three criteria are proposed, related to the effective correction of forecast error, the optimal variability of the corrected forecast and multicollinearity. The regression schemes under consideration include the ordinary least-square (OLS method, a new time-dependent Tikhonov regularization (TDTR method, the total least-square method, a new geometric-mean regression (GM, a recently introduced error-in-variables (EVMOS method and, finally, a "best member" OLS method. The advantages and drawbacks of each method are clarified.

    These techniques are applied in the context of the 63 Lorenz system, whose model version is affected by both initial condition and model errors. For short forecast lead times, the number and choice of predictors plays an important role. Contrarily to the other techniques, GM degrades when the number of predictors increases. At intermediate lead times, linear regression is unable to provide corrections to the forecast and can sometimes degrade the performance (GM and the best member OLS with noise. At long lead times the regression schemes (EVMOS, TDTR which yield the correct variability and the largest correlation between ensemble error and spread, should be preferred.

  11. Unbalanced Regressions and the Predictive Equation

    DEFF Research Database (Denmark)

    Osterrieder, Daniela; Ventosa-Santaulària, Daniel; Vera-Valdés, J. Eduardo

    Predictive return regressions with persistent regressors are typically plagued by (asymptotically) biased/inconsistent estimates of the slope, non-standard or potentially even spurious statistical inference, and regression unbalancedness. We alleviate the problem of unbalancedness in the theoreti......Predictive return regressions with persistent regressors are typically plagued by (asymptotically) biased/inconsistent estimates of the slope, non-standard or potentially even spurious statistical inference, and regression unbalancedness. We alleviate the problem of unbalancedness...... in the theoretical predictive equation by suggesting a data generating process, where returns are generated as linear functions of a lagged latent I(0) risk process. The observed predictor is a function of this latent I(0) process, but it is corrupted by a fractionally integrated noise. Such a process may arise due...... to aggregation or unexpected level shifts. In this setup, the practitioner estimates a misspecified, unbalanced, and endogenous predictive regression. We show that the OLS estimate of this regression is inconsistent, but standard inference is possible. To obtain a consistent slope estimate, we then suggest...

  12. Surviving After Suicide

    Science.gov (United States)

    ... fewer tools for communicating their feelings. Surviving After Suicide Fact Sheet 3 Children are especially vulnerable to feelings of guilt and ... to take care of them. Secrecy about the suicide in the hopes of protecting children may cause further complications. Explain the situation and ...

  13. Survivability via Control Objectives

    Energy Technology Data Exchange (ETDEWEB)

    CAMPBELL,PHILIP L.

    2000-08-11

    Control objectives open an additional front in the survivability battle. A given set of control objectives is valuable if it represents good practices, it is complete (it covers all the necessary areas), and it is auditable. CobiT and BS 7799 are two examples of control objective sets.

  14. Education for Survival.

    Science.gov (United States)

    Allen, James E., Jr.

    In this address, James E. Allen, Jr., Assistant Secretary for Education and U.S. Commissioner of Education, discusses the relationship of education to the problem of ecological destruction. He states that the solutions to the problems of air, water, and soil pollution may be found in redirected education. This "education for survival" can serve to…

  15. Artists’ Survival Rate

    DEFF Research Database (Denmark)

    Bille, Trine; Jensen, Søren

    2017-01-01

    The literature of cultural economics generally finds that an artistic education has no significant impact on artists’ income and careers in the arts. In our research, we have readdressed this question by looking at the artists’ survival in the arts occupations. The results show that an artistic...... education has a significant impact on artists’ careers in the arts and we find important industry differences....

  16. Climate change: Bio-technologies are facing a huge challenge. Why is climate changing? Control and measurement of greenhouse gases in the atmosphere. Soils at the heart of climate change. Between pollution and climate change, the survival of soil organisms. Modelling microbial degradation in soils to analyse greenhouse gas releases. A threat against plant health. The opinion of the seed industry. Truly living clouds. Language, the other stake of the struggle against climate changes

    International Nuclear Information System (INIS)

    Salas y Melia, David; Delmotte, Marc; Chenu, Claire; Chevallier, Tiphaine; Mougin, Christian; Lamy, Isabelle; Caquet, Thierry; Garnier, Patricia; Sache, Ivan; Pagesse, Pierre; Amato, Pierre; Desprez, Basile; Vernet, Agnes

    2015-01-01

    As the Rio Earth Summit in 1992 decided to react to limit the irrecoverable global warming, this publication, through several articles, outlines that this issue has not progressed at all after 23 years on a political point of view, and has even regressed with respect to initially defined objectives, but has progressed in terms of understanding of climate change under the influence of our production modes, notably in the agriculture sector. Thus, the articles discuss or recall the origin and process of climate change, how greenhouse gas emissions are controlled and measured, how soil are impacted or play a role in climate change as the survival of soil organisms is at stake under the pressure of pollution and climate change, how climate change can be a threat for plants, how the seed industry perceives these issues, how micro-organisms present in the air and clouds are now a topic in atmosphere sciences. The last article discusses the importance of intelligibility of scientific publications on these issues

  17. Choline kinase alpha and hexokinase-2 protein expression in hepatocellular carcinoma: association with survival.

    Directory of Open Access Journals (Sweden)

    Sandi A Kwee

    Full Text Available PURPOSE: Hexokinase-2 (HK2 and more recently choline kinase alpha (CKA expression has been correlated with clinical outcomes in several major cancers. This study examines the protein expression of HK2 and CKA in hepatocellular carcinoma (HCC in association with patient survival and other clinicopathologic parameters. METHODS: Immunohistochemical analysis for HK2 and CKA expression was performed on a tissue microarray of 157 HCC tumor samples. Results were analyzed in relation to clinicopathologic data from Surveillance, Epidemiology, and End-Results Program registries. Mortality rates were assessed by Kaplan-Meier estimates and compared using log-rank tests. Predictors of overall survival were assessed using proportional hazards regression. RESULTS: Immunohistochemical expression of HK2 and CKA was detected in 71 (45% and 55 (35% tumor samples, respectively. Differences in tumor HK2 expression were associated with tumor grade (p = 0.008 and cancer stage (p = 0.001, while CKA expression differed significantly only across cancer stage (p = 0.048. Increased mortality was associated with tumor HK2 expression (p = 0.003 as well as CKA expression (p = 0.03 with hazard ratios of 1.86 (95% confidence interval (CI 1.23-2.83 and 1.59 (95% CI 1.04-2.41, respectively. Similar effects on overall survival were noted in a subset analysis of early stage (I and II HCC. Tumor HK2 expression, but not CKA expression, remained a significant predictor of survival in multivariable analyses. CONCLUSION: HK2 and CKA expression may have biologic and prognostic significance in HCC, with tumor HK2 expression being a potential independent predictor of survival.

  18. Dedifferentiated chondrosarcoma: A survival analysis of 159 cases from the SEER database (2001-2011).

    Science.gov (United States)

    Strotman, Patrick K; Reif, Taylor J; Kliethermes, Stephanie A; Sandhu, Jasmin K; Nystrom, Lukas M

    2017-08-01

    Dedifferentiated chondrosarcoma is a rare malignancy with reported 5-year overall survival rates ranging from 7% to 24%. The purpose of this investigation is to determine the overall survival of dedifferentiated chondrosarcoma in a modern patient series and how it is impacted by patient demographics, tumor characteristics, and surgical treatment factors. This is a retrospective review of the Surveillance, Epidemiology, and End Results (SEER) database from 2001 to 2011. Kaplan Meier analyses were used for overall and disease-specific survival. Univariable and multivariable cox regression models were used to identify prognostic factors. Five year overall- and disease-specific survival was 18% (95% CI: 12-26%) and 28% (95% CI: 18-37%), respectively. Individuals with extremity tumors had a worse prognosis than individuals with a primary tumor in the chest wall or axial skeleton (HR 0.20, 95% CI: 0.07-0.56; P = 0.002 and HR 0.60, 95% CI: 0.36-0.99; P = 0.04, respectively). Patients with AJCC stage III or IV disease (HR 2.51, 95% CI: 1.50-4.20; P = 0.001), tumors larger than 8 cm (HR 2.17, 95% CI: 1.11-4.27; P = 0.046), metastatic disease at diagnosis (HR 3.25, 95% CI: 1.98-5.33; P chondrosarcoma is poor with a 5-year overall survival of 18%. Patients with a primary tumor located in the chest wall had a better prognosis. Tumors larger than 8 cm, presence of metastases at diagnosis, and treatment without surgical resection were significant predictors of mortality. © 2017 Wiley Periodicals, Inc.

  19. Differential Survival for Men and Women with HIV/AIDS-Related Neurologic Diagnoses.

    Directory of Open Access Journals (Sweden)

    Martha L Carvour

    Full Text Available Neurologic complications of human immunodeficiency virus (HIV infection and acquired immune deficiency syndrome (AIDS frequently lead to disability or death in affected patients. The aim of this study was to determine whether survival patterns differ between men and women with HIV/AIDS-related neurologic disease (neuro-AIDS.Retrospective cohort data from a statewide surveillance database for HIV/AIDS were used to characterize survival following an HIV/AIDS-related neurologic diagnosis for men and women with one or more of the following conditions: cryptococcosis, toxoplasmosis, primary central nervous system lymphoma, progressive multifocal leukoencephalopathy, and HIV-associated dementia. A second, non-independent cohort was formed using university-based cases to confirm and extend the findings from the statewide data. Kaplan-Meier analysis was used to compare the survival experiences for men and women in the cohorts. Cox regression was employed to characterize survival while controlling for potential confounders in the study population.Women (n=27 had significantly poorer outcomes than men (n=198 in the statewide cohort (adjusted hazard ratio=2.31, 95% CI: 1.22 to 4.35, and a similar, non-significant trend was observed among university-based cases (n=17 women, 154 men. Secondary analyses suggested that this difference persisted over the course of the AIDS epidemic and was not attributable to differential antiretroviral therapy responses among men and women.The survival disadvantage of women compared to men should be confirmed and the mechanisms underlying this disparity elucidated. If this relationship is confirmed, targeted clinical and public health efforts might be directed towards screening, treatment, and support for women affected by neuro-AIDS.

  20. An introduction to using Bayesian linear regression with clinical data.

    Science.gov (United States)

    Baldwin, Scott A; Larson, Michael J

    2017-11-01

    Statistical training psychology focuses on frequentist methods. Bayesian methods are an alternative to standard frequentist methods. This article provides researchers with an introduction to fundamental ideas in Bayesian modeling. We use data from an electroencephalogram (EEG) and anxiety study to illustrate Bayesian models. Specifically, the models examine the relationship between error-related negativity (ERN), a particular event-related potential, and trait anxiety. Methodological topics covered include: how to set up a regression model in a Bayesian framework, specifying priors, examining convergence of the model, visualizing and interpreting posterior distributions, interval estimates, expected and predicted values, and model comparison tools. We also discuss situations where Bayesian methods can outperform frequentist methods as well has how to specify more complicated regression models. Finally, we conclude with recommendations about reporting guidelines for those using Bayesian methods in their own research. We provide data and R code for replicating our analyses. Copyright © 2017 Elsevier Ltd. All rights reserved.

  1. The R Package threg to Implement Threshold Regression Models

    Directory of Open Access Journals (Sweden)

    Tao Xiao

    2015-08-01

    This new package includes four functions: threg, and the methods hr, predict and plot for threg objects returned by threg. The threg function is the model-fitting function which is used to calculate regression coefficient estimates, asymptotic standard errors and p values. The hr method for threg objects is the hazard-ratio calculation function which provides the estimates of hazard ratios at selected time points for specified scenarios (based on given categories or value settings of covariates. The predict method for threg objects is used for prediction. And the plot method for threg objects provides plots for curves of estimated hazard functions, survival functions and probability density functions of the first-hitting-time; function curves corresponding to different scenarios can be overlaid in the same plot for comparison to give additional research insights.

  2. Covariate Imbalance and Adjustment for Logistic Regression Analysis of Clinical Trial Data

    Science.gov (United States)

    Ciolino, Jody D.; Martin, Reneé H.; Zhao, Wenle; Jauch, Edward C.; Hill, Michael D.; Palesch, Yuko Y.

    2014-01-01

    In logistic regression analysis for binary clinical trial data, adjusted treatment effect estimates are often not equivalent to unadjusted estimates in the presence of influential covariates. This paper uses simulation to quantify the benefit of covariate adjustment in logistic regression. However, International Conference on Harmonization guidelines suggest that covariate adjustment be pre-specified. Unplanned adjusted analyses should be considered secondary. Results suggest that that if adjustment is not possible or unplanned in a logistic setting, balance in continuous covariates can alleviate some (but never all) of the shortcomings of unadjusted analyses. The case of log binomial regression is also explored. PMID:24138438

  3. Physical activity and survival in breast cancer

    DEFF Research Database (Denmark)

    Ammitzbøll, Gunn; Søgaard, Karen; Karlsen, Randi V

    2016-01-01

    PURPOSE: Knowledge about lifestyle factors possibly influencing survival after breast cancer (BC) is paramount. We examined associations between two types of postdiagnosis physical activity (PA) and overall survival after BC. PATIENTS AND METHODS: We used prospective data on 959 BC survivors from...... the Diet, Cancer, and Health cohort, all enrolled before diagnosis. Self-reported PA was measured as time per activity, and estimated metabolic equivalent task (MET)-hours per week were summed for each activity. We constructed measures for household, exercise, and total PA. The association between...... from all causes during the study period. In adjusted analyses, exercise PA above eight MET h/week compared to lower levels of activity was significantly associated with improved overall survival (HR, 0.68; confidence interval [CI]: 0.47-0.99). When comparing participation in exercise to non...

  4. Stability of alert survivable forces during reductions

    Energy Technology Data Exchange (ETDEWEB)

    Canavan, G.H.

    1998-01-01

    The stability of current and projected strategic forces are discussed within a framework that contains elements of current US and Russian analyses. For current force levels and high alert, stability levels are high, as are the levels of potential strikes, due to the large forces deployed. As force levels drop towards those of current value target sets, the analysis becomes linear, concern shifts from stability to reconstitution, and survivable forces drop out. Adverse marginal costs generally provide disincentives for the reduction of vulnerable weapons, but the exchange of vulnerable for survivable weapons could reduce cost while increasing stability even for aggressive participants. Exchanges between effective vulnerable and survivable missile forces are studied with an aggregated, probabilistic model, which optimizes each sides` first and determines each sides` second strikes and costs by minimizing first strike costs.

  5. Economic Analyses of Ware Yam Production in Orlu Agricultural ...

    African Journals Online (AJOL)

    Economic Analyses of Ware Yam Production in Orlu Agricultural Zone of Imo State. ... International Journal of Agriculture and Rural Development ... statistics, gross margin analysis, marginal analysis and multiple regression analysis. Results ...

  6. Total Laryngectomy Versus Larynx Preservation for T4a Larynx Cancer: Patterns of Care and Survival Outcomes

    International Nuclear Information System (INIS)

    Grover, Surbhi; Swisher-McClure, Samuel; Mitra, Nandita; Li, Jiaqi; Cohen, Roger B.; Ahn, Peter H.; Lukens, John N.; Chalian, Ara A.; Weinstein, Gregory S.; O'Malley, Bert W.; Lin, Alexander

    2015-01-01

    Purpose: To examine practice patterns and compare survival outcomes between total laryngectomy (TL) and larynx preservation chemoradiation (LP-CRT) in the setting of T4a larynx cancer, using a large national cancer registry. Methods and Materials: Using the National Cancer Database, we identified 969 patients from 2003 to 2006 with T4a squamous cell larynx cancer receiving definitive treatment with either initial TL plus adjuvant therapy or LP-CRT. Univariate and multivariable logistic regression were used to assess predictors of undergoing surgery. Survival outcomes were compared using Kaplan-Meier and propensity score–adjusted and inverse probability of treatment–weighted Cox proportional hazards methods. Sensitivity analyses were performed to account for unmeasured confounders. Results: A total of 616 patients (64%) received LP-CRT, and 353 (36%) received TL. On multivariable logistic regression, patients with advanced nodal disease were less likely to receive TL (N2 vs N0, 26.6% vs 43.4%, odds ratio [OR] 0.52, 95% confidence interval [CI] 0.37-0.73; N3 vs N0, 19.1% vs 43.4%, OR 0.23, 95% CI 0.07-0.77), whereas patients treated in high case-volume facilities were more likely to receive TL (46.1% vs 31.5%, OR 1.78, 95% CI 1.27-2.48). Median survival for TL versus LP was 61 versus 39 months (P<.001). After controlling for potential confounders, LP-CRT had inferior overall survival compared with TL (hazard ratio 1.31, 95% CI 1.10-1.57), and with the inverse probability of treatment–weighted model (hazard ratio 1.25, 95% CI 1.05-1.49). This survival difference was shown to be robust on additional sensitivity analyses. Conclusions: Most patients with T4a larynx cancer receive LP-CRT, despite guidelines suggesting TL as the preferred initial approach. Patients receiving LP-CRT had more advanced nodal disease and worse overall survival. Previous studies of (non-T4a) locally advanced larynx cancer showing no difference in survival between LP-CRT and TL may not

  7. The best of both worlds: Phylogenetic eigenvector regression and mapping

    Directory of Open Access Journals (Sweden)

    José Alexandre Felizola Diniz Filho

    2015-09-01

    Full Text Available Eigenfunction analyses have been widely used to model patterns of autocorrelation in time, space and phylogeny. In a phylogenetic context, Diniz-Filho et al. (1998 proposed what they called Phylogenetic Eigenvector Regression (PVR, in which pairwise phylogenetic distances among species are submitted to a Principal Coordinate Analysis, and eigenvectors are then used as explanatory variables in regression, correlation or ANOVAs. More recently, a new approach called Phylogenetic Eigenvector Mapping (PEM was proposed, with the main advantage of explicitly incorporating a model-based warping in phylogenetic distance in which an Ornstein-Uhlenbeck (O-U process is fitted to data before eigenvector extraction. Here we compared PVR and PEM in respect to estimated phylogenetic signal, correlated evolution under alternative evolutionary models and phylogenetic imputation, using simulated data. Despite similarity between the two approaches, PEM has a slightly higher prediction ability and is more general than the original PVR. Even so, in a conceptual sense, PEM may provide a technique in the best of both worlds, combining the flexibility of data-driven and empirical eigenfunction analyses and the sounding insights provided by evolutionary models well known in comparative analyses.

  8. Cerebrospinal fluid cytotoxicity does not affect survival in amyotrophic lateral sclerosis.

    Science.gov (United States)

    Galán, L; Matías-Guiu, J; Matias-Guiu, J A; Yáñez, M; Pytel, V; Guerrero-Sola, A; Vela-Souto, A; Arranz-Tagarro, J A; Gómez-Pinedo, U; García, A G

    2017-09-01

    Cerebrospinal fluid (CSF) from some patients with amyotrophic lateral sclerosis (ALS) has been demonstrated to significantly reduce the neuronal viability of primary cell cultures of motor neurons. We aimed to study the potential clinical consequences associated with the cytotoxicity of CSF in a cohort of patients with ALS. We collected CSF from thirty-one patients with ALS. We analysed cytotoxicity by incubating it into the primary cultures of motor cortex neurons. Neural viability was quantified after 24 hours using the colorimetric MTT reduction assay. All patients were followed up from the moment of diagnosis to death, and a complete evaluation during disease progression and survival was performed, including gastrostomy and respiratory assistance. Twenty-one patients (67.7%) presented a cytotoxic CSF. There were no significant differences between patients with and without cytotoxicity regarding mean time from symptom onset to the diagnosis, from the diagnosis to death, from the diagnosis to respiratory assistance with BIPAP, from diagnosis to gastrostomy and from the onset of symptoms to death. In Cox regression analysis, bulbar onset, but not cytotoxicity, gender or age at onset, was associated with a lower risk of survival. Cerebrospinal fluid cytotoxicity was not associated with differential survival rates. This suggests that the presence of cytotoxicity in CSF, measured through neuronal viability in primary cultures of motor cortex neurons, could reflect different mechanisms of the disease, but it does not predict disease outcome. © 2016 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

  9. CASAS: Cancer Survival Analysis Suite, a web based application.

    Science.gov (United States)

    Rupji, Manali; Zhang, Xinyan; Kowalski, Jeanne

    2017-01-01

    We present CASAS, a shiny R based tool for interactive survival analysis and visualization of results. The tool provides a web-based one stop shop to perform the following types of survival analysis:  quantile, landmark and competing risks, in addition to standard survival analysis.  The interface makes it easy to perform such survival analyses and obtain results using the interactive Kaplan-Meier and cumulative incidence plots.  Univariate analysis can be performed on one or several user specified variable(s) simultaneously, the results of which are displayed in a single table that includes log rank p-values and hazard ratios along with their significance. For several quantile survival analyses from multiple cancer types, a single summary grid is constructed. The CASAS package has been implemented in R and is available via http://shinygispa.winship.emory.edu/CASAS/. The developmental repository is available at https://github.com/manalirupji/CASAS/.

  10. Atrial fibrillation and survival in colorectal cancer

    Directory of Open Access Journals (Sweden)

    Justin Timothy A

    2004-11-01

    Full Text Available Abstract Background Survival in colorectal cancer may correlate with the degree of systemic inflammatory response to the tumour. Atrial fibrillation may be regarded as an inflammatory complication. We aimed to determine if atrial fibrillation is a prognostic factor in colorectal cancer. Patients and methods A prospective colorectal cancer patient database was cross-referenced with the hospital clinical-coding database to identify patients who had underwent colorectal cancer surgery and were in atrial fibrillation pre- or postoperatively. Results A total of 175 patients underwent surgery for colorectal cancer over a two-year period. Of these, 13 patients had atrial fibrillation pre- or postoperatively. Atrial fibrillation correlated with worse two-year survival (p = 0.04; log-rank test. However, in a Cox regression analysis, atrial fibrillation was not significantly associated with survival. Conclusion The presence or development of atrial fibrillation in patients undergoing surgery for colorectal cancer is associated with worse overall survival, however it was not found to be an independent factor in multivariate analysis.

  11. Mental vulnerability and survival after cancer

    DEFF Research Database (Denmark)

    Nakaya, Naoki; Bidstrup, Pernille E; Eplov, Lene F

    2009-01-01

    BACKGROUND: It has been hypothesized that personality traits affect survival after cancer, but studies have produced inconsistent results. This study examined the association between mental vulnerability and survival after cancer in Denmark in a prospective cohort study. METHODS: Between 1976...... and 2001, 12733 residents of Copenhagen completed a questionnaire eliciting information on a 12-item mental vulnerability scale, as well as various personal data. Follow-up in the Danish Cancer Registry until 2003 identified 884 incident cases of primary cancer, and follow-up for death from the date...... of cancer diagnosis until 2003 identified 382 deaths. Mental vulnerability scores were divided into 4 approximately equal-sized groups. Cox proportional hazards regression models were used to estimate the hazard ratio (HR) of all-cause mortality. RESULTS: Multivariate HR for all-cause mortality for persons...

  12. Time series regression model for infectious disease and weather.

    Science.gov (United States)

    Imai, Chisato; Armstrong, Ben; Chalabi, Zaid; Mangtani, Punam; Hashizume, Masahiro

    2015-10-01

    Time series regression has been developed and long used to evaluate the short-term associations of air pollution and weather with mortality or morbidity of non-infectious diseases. The application of the regression approaches from this tradition to infectious diseases, however, is less well explored and raises some new issues. We discuss and present potential solutions for five issues often arising in such analyses: changes in immune population, strong autocorrelations, a wide range of plausible lag structures and association patterns, seasonality adjustments, and large overdispersion. The potential approaches are illustrated with datasets of cholera cases and rainfall from Bangladesh and influenza and temperature in Tokyo. Though this article focuses on the application of the traditional time series regression to infectious diseases and weather factors, we also briefly introduce alternative approaches, including mathematical modeling, wavelet analysis, and autoregressive integrated moving average (ARIMA) models. Modifications proposed to standard time series regression practice include using sums of past cases as proxies for the immune population, and using the logarithm of lagged disease counts to control autocorrelation due to true contagion, both of which are motivated from "susceptible-infectious-recovered" (SIR) models. The complexity of lag structures and association patterns can often be informed by biological mechanisms and explored by using distributed lag non-linear models. For overdispersed models, alternative distribution models such as quasi-Poisson and negative binomial should be considered. Time series regression can be used to investigate dependence of infectious diseases on weather, but may need modifying to allow for features specific to this context. Copyright © 2015 The Authors. Published by Elsevier Inc. All rights reserved.

  13. Regression analysis using dependent Polya trees.

    Science.gov (United States)

    Schörgendorfer, Angela; Branscum, Adam J

    2013-11-30

    Many commonly used models for linear regression analysis force overly simplistic shape and scale constraints on the residual structure of data. We propose a semiparametric Bayesian model for regression analysis that produces data-driven inference by using a new type of dependent Polya tree prior to model arbitrary residual distributions that are allowed to evolve across increasing levels of an ordinal covariate (e.g., time, in repeated measurement studies). By modeling residual distributions at consecutive covariate levels or time points using separate, but dependent Polya tree priors, distributional information is pooled while allowing for broad pliability to accommodate many types of changing residual distributions. We can use the proposed dependent residual structure in a wide range of regression settings, including fixed-effects and mixed-effects linear and nonlinear models for cross-sectional, prospective, and repeated measurement data. A simulation study illustrates the flexibility of our novel semiparametric regression model to accurately capture evolving residual distributions. In an application to immune development data on immunoglobulin G antibodies in children, our new model outperforms several contemporary semiparametric regression models based on a predictive model selection criterion. Copyright © 2013 John Wiley & Sons, Ltd.

  14. Is past life regression therapy ethical?

    Science.gov (United States)

    Andrade, Gabriel

    2017-01-01

    Past life regression therapy is used by some physicians in cases with some mental diseases. Anxiety disorders, mood disorders, and gender dysphoria have all been treated using life regression therapy by some doctors on the assumption that they reflect problems in past lives. Although it is not supported by psychiatric associations, few medical associations have actually condemned it as unethical. In this article, I argue that past life regression therapy is unethical for two basic reasons. First, it is not evidence-based. Past life regression is based on the reincarnation hypothesis, but this hypothesis is not supported by evidence, and in fact, it faces some insurmountable conceptual problems. If patients are not fully informed about these problems, they cannot provide an informed consent, and hence, the principle of autonomy is violated. Second, past life regression therapy has the great risk of implanting false memories in patients, and thus, causing significant harm. This is a violation of the principle of non-malfeasance, which is surely the most important principle in medical ethics.

  15. Survival analysis and classification methods for forest fire size.

    Science.gov (United States)

    Tremblay, Pier-Olivier; Duchesne, Thierry; Cumming, Steven G

    2018-01-01

    Factors affecting wildland-fire size distribution include weather, fuels, and fire suppression activities. We present a novel application of survival analysis to quantify the effects of these factors on a sample of sizes of lightning-caused fires from Alberta, Canada. Two events were observed for each fire: the size at initial assessment (by the first fire fighters to arrive at the scene) and the size at "being held" (a state when no further increase in size is expected). We developed a statistical classifier to try to predict cases where there will be a growth in fire size (i.e., the size at "being held" exceeds the size at initial assessment). Logistic regression was preferred over two alternative classifiers, with covariates consistent with similar past analyses. We conducted survival analysis on the group of fires exhibiting a size increase. A screening process selected three covariates: an index of fire weather at the day the fire started, the fuel type burning at initial assessment, and a factor for the type and capabilities of the method of initial attack. The Cox proportional hazards model performed better than three accelerated failure time alternatives. Both fire weather and fuel type were highly significant, with effects consistent with known fire behaviour. The effects of initial attack method were not statistically significant, but did suggest a reverse causality that could arise if fire management agencies were to dispatch resources based on a-priori assessment of fire growth potentials. We discuss how a more sophisticated analysis of larger data sets could produce unbiased estimates of fire suppression effect under such circumstances.

  16. Survival analysis and classification methods for forest fire size

    Science.gov (United States)

    2018-01-01

    Factors affecting wildland-fire size distribution include weather, fuels, and fire suppression activities. We present a novel application of survival analysis to quantify the effects of these factors on a sample of sizes of lightning-caused fires from Alberta, Canada. Two events were observed for each fire: the size at initial assessment (by the first fire fighters to arrive at the scene) and the size at “being held” (a state when no further increase in size is expected). We developed a statistical classifier to try to predict cases where there will be a growth in fire size (i.e., the size at “being held” exceeds the size at initial assessment). Logistic regression was preferred over two alternative classifiers, with covariates consistent with similar past analyses. We conducted survival analysis on the group of fires exhibiting a size increase. A screening process selected three covariates: an index of fire weather at the day the fire started, the fuel type burning at initial assessment, and a factor for the type and capabilities of the method of initial attack. The Cox proportional hazards model performed better than three accelerated failure time alternatives. Both fire weather and fuel type were highly significant, with effects consistent with known fire behaviour. The effects of initial attack method were not statistically significant, but did suggest a reverse causality that could arise if fire management agencies were to dispatch resources based on a-priori assessment of fire growth potentials. We discuss how a more sophisticated analysis of larger data sets could produce unbiased estimates of fire suppression effect under such circumstances. PMID:29320497

  17. Interpret with caution: multicollinearity in multiple regression of cognitive data.

    Science.gov (United States)

    Morrison, Catriona M

    2003-08-01

    Shibihara and Kondo in 2002 reported a reanalysis of the 1997 Kanji picture-naming data of Yamazaki, Ellis, Morrison, and Lambon-Ralph in which independent variables were highly correlated. Their addition of the variable visual familiarity altered the previously reported pattern of results, indicating that visual familiarity, but not age of acquisition, was important in predicting Kanji naming speed. The present paper argues that caution should be taken when drawing conclusions from multiple regression analyses in which the independent variables are so highly correlated, as such multicollinearity can lead to unreliable output.

  18. Preference learning with evolutionary Multivariate Adaptive Regression Spline model

    DEFF Research Database (Denmark)

    Abou-Zleikha, Mohamed; Shaker, Noor; Christensen, Mads Græsbøll

    2015-01-01

    This paper introduces a novel approach for pairwise preference learning through combining an evolutionary method with Multivariate Adaptive Regression Spline (MARS). Collecting users' feedback through pairwise preferences is recommended over other ranking approaches as this method is more appealing...... for function approximation as well as being relatively easy to interpret. MARS models are evolved based on their efficiency in learning pairwise data. The method is tested on two datasets that collectively provide pairwise preference data of five cognitive states expressed by users. The method is analysed...

  19. Nonparametric regression using the concept of minimum energy

    International Nuclear Information System (INIS)

    Williams, Mike

    2011-01-01

    It has recently been shown that an unbinned distance-based statistic, the energy, can be used to construct an extremely powerful nonparametric multivariate two sample goodness-of-fit test. An extension to this method that makes it possible to perform nonparametric regression using multiple multivariate data sets is presented in this paper. The technique, which is based on the concept of minimizing the energy of the system, permits determination of parameters of interest without the need for parametric expressions of the parent distributions of the data sets. The application and performance of this new method is discussed in the context of some simple example analyses.

  20. Radiobilogical cell survival models

    International Nuclear Information System (INIS)

    Zackrisson, B.

    1992-01-01

    A central issue in clinical radiobiological research is the prediction of responses to different radiation qualities. The choice of cell survival and dose-response model greatly influences the results. In this context the relationship between theory and model is emphasized. Generally, the interpretations of experimental data depend on the model. Cell survival models are systematized with respect to their relations to radiobiological theories of cell kill. The growing knowlegde of biological, physical, and chemical mechanisms is reflected in the formulation of new models. The present overview shows that recent modelling has been more oriented towards the stochastic fluctuations connected to radiation energy deposition. This implies that the traditional cell surivival models ought to be complemented by models of stochastic energy deposition processes and repair processes at the intracellular level. (orig.)

  1. On Solving Lq-Penalized Regressions

    Directory of Open Access Journals (Sweden)

    Tracy Zhou Wu

    2007-01-01

    Full Text Available Lq-penalized regression arises in multidimensional statistical modelling where all or part of the regression coefficients are penalized to achieve both accuracy and parsimony of statistical models. There is often substantial computational difficulty except for the quadratic penalty case. The difficulty is partly due to the nonsmoothness of the objective function inherited from the use of the absolute value. We propose a new solution method for the general Lq-penalized regression problem based on space transformation and thus efficient optimization algorithms. The new method has immediate applications in statistics, notably in penalized spline smoothing problems. In particular, the LASSO problem is shown to be polynomial time solvable. Numerical studies show promise of our approach.

  2. Refractive regression after laser in situ keratomileusis.

    Science.gov (United States)

    Yan, Mabel K; Chang, John Sm; Chan, Tommy Cy

    2018-04-26

    Uncorrected refractive errors are a leading cause of visual impairment across the world. In today's society, laser in situ keratomileusis (LASIK) has become the most commonly performed surgical procedure to correct refractive errors. However, regression of the initially achieved refractive correction has been a widely observed phenomenon following LASIK since its inception more than two decades ago. Despite technological advances in laser refractive surgery and various proposed management strategies, post-LASIK regression is still frequently observed and has significant implications for the long-term visual performance and quality of life of patients. This review explores the mechanism of refractive regression after both myopic and hyperopic LASIK, predisposing risk factors and its clinical course. In addition, current preventative strategies and therapies are also reviewed. © 2018 Royal Australian and New Zealand College of Ophthalmologists.

  3. Influence diagnostics in meta-regression model.

    Science.gov (United States)

    Shi, Lei; Zuo, ShanShan; Yu, Dalei; Zhou, Xiaohua

    2017-09-01

    This paper studies the influence diagnostics in meta-regression model including case deletion diagnostic and local influence analysis. We derive the subset deletion formulae for the estimation of regression coefficient and heterogeneity variance and obtain the corresponding influence measures. The DerSimonian and Laird estimation and maximum likelihood estimation methods in meta-regression are considered, respectively, to derive the results. Internal and external residual and leverage measure are defined. The local influence analysis based on case-weights perturbation scheme, responses perturbation scheme, covariate perturbation scheme, and within-variance perturbation scheme are explored. We introduce a method by simultaneous perturbing responses, covariate, and within-variance to obtain the local influence measure, which has an advantage of capable to compare the influence magnitude of influential studies from different perturbations. An example is used to illustrate the proposed methodology. Copyright © 2017 John Wiley & Sons, Ltd.

  4. Principal component regression for crop yield estimation

    CERN Document Server

    Suryanarayana, T M V

    2016-01-01

    This book highlights the estimation of crop yield in Central Gujarat, especially with regard to the development of Multiple Regression Models and Principal Component Regression (PCR) models using climatological parameters as independent variables and crop yield as a dependent variable. It subsequently compares the multiple linear regression (MLR) and PCR results, and discusses the significance of PCR for crop yield estimation. In this context, the book also covers Principal Component Analysis (PCA), a statistical procedure used to reduce a number of correlated variables into a smaller number of uncorrelated variables called principal components (PC). This book will be helpful to the students and researchers, starting their works on climate and agriculture, mainly focussing on estimation models. The flow of chapters takes the readers in a smooth path, in understanding climate and weather and impact of climate change, and gradually proceeds towards downscaling techniques and then finally towards development of ...

  5. Regression Models for Market-Shares

    DEFF Research Database (Denmark)

    Birch, Kristina; Olsen, Jørgen Kai; Tjur, Tue

    2005-01-01

    On the background of a data set of weekly sales and prices for three brands of coffee, this paper discusses various regression models and their relation to the multiplicative competitive-interaction model (the MCI model, see Cooper 1988, 1993) for market-shares. Emphasis is put on the interpretat......On the background of a data set of weekly sales and prices for three brands of coffee, this paper discusses various regression models and their relation to the multiplicative competitive-interaction model (the MCI model, see Cooper 1988, 1993) for market-shares. Emphasis is put...... on the interpretation of the parameters in relation to models for the total sales based on discrete choice models.Key words and phrases. MCI model, discrete choice model, market-shares, price elasitcity, regression model....

  6. Gender Gaps in Mathematics, Science and Reading Achievements in Muslim Countries: A Quantile Regression Approach

    Science.gov (United States)

    Shafiq, M. Najeeb

    2013-01-01

    Using quantile regression analyses, this study examines gender gaps in mathematics, science, and reading in Azerbaijan, Indonesia, Jordan, the Kyrgyz Republic, Qatar, Tunisia, and Turkey among 15-year-old students. The analyses show that girls in Azerbaijan achieve as well as boys in mathematics and science and overachieve in reading. In Jordan,…

  7. The analysis of nonstationary time series using regression, correlation and cointegration

    DEFF Research Database (Denmark)

    Johansen, Søren

    2012-01-01

    There are simple well-known conditions for the validity of regression and correlation as statistical tools. We analyse by examples the effect of nonstationarity on inference using these methods and compare them to model based inference using the cointegrated vector autoregressive model. Finally we...... analyse some monthly data from US on interest rates as an illustration of the methods...

  8. The Analysis of Nonstationary Time Series Using Regression, Correlation and Cointegration

    Directory of Open Access Journals (Sweden)

    Søren Johansen

    2012-06-01

    Full Text Available There are simple well-known conditions for the validity of regression and correlation as statistical tools. We analyse by examples the effect of nonstationarity on inference using these methods and compare them to model based inference using the cointegrated vector autoregressive model. Finally we analyse some monthly data from US on interest rates as an illustration of the methods.

  9. Carbonaceous Survivability on Impact

    Science.gov (United States)

    Bunch, T. E.; Becker, Luann; Morrison, David (Technical Monitor)

    1994-01-01

    In order to gain knowledge about the potential contributions of comets and cosmic dust to the origin of life on Earth, we need to explore the survivability of their potential organic compounds on impact and the formation of secondary products that may have arisen from the chaotic events sustained by the carriers as they fell to Earth. We have performed a series of hypervelocity impact experiments using carbon-bearing impactors (diamond, graphite, kerogens, PAH crystals, and Murchison and Nogoya meteorites) into Al plate targets at velocities - 6 km/s. Estimated peak shock pressures probably did not exceed 120 GPa and peak shock temperatures were probably less than 4000 K for times of nano- to microsecs. Nominal crater dia. are less than one mm. The most significant results of these experiments are the preservation of the higher mass PAHs (e. g., pyrene relative to napthalene) and the formation of additional alkylated PAHs. We have also examined the residues of polystyrene projectiles impacted by a microparticle accelerator into targets at velocities up to 15 km/s. This talk will discuss the results of these experiments and their implications with respect to the survival of carbonaceous deliverables to early Earth. The prospects of survivability of organic molecules on "intact" capture of cosmic dust in space via soft: and hard cosmic dust collectors will also be discussed.

  10. On directional multiple-output quantile regression

    Czech Academy of Sciences Publication Activity Database

    Paindaveine, D.; Šiman, Miroslav

    2011-01-01

    Roč. 102, č. 2 (2011), s. 193-212 ISSN 0047-259X R&D Projects: GA MŠk(CZ) 1M06047 Grant - others:Commision EC(BE) Fonds National de la Recherche Scientifique Institutional research plan: CEZ:AV0Z10750506 Keywords : multivariate quantile * quantile regression * multiple-output regression * halfspace depth * portfolio optimization * value-at risk Subject RIV: BA - General Mathematics Impact factor: 0.879, year: 2011 http://library.utia.cas.cz/separaty/2011/SI/siman-0364128.pdf

  11. Removing Malmquist bias from linear regressions

    Science.gov (United States)

    Verter, Frances

    1993-01-01

    Malmquist bias is present in all astronomical surveys where sources are observed above an apparent brightness threshold. Those sources which can be detected at progressively larger distances are progressively more limited to the intrinsically luminous portion of the true distribution. This bias does not distort any of the measurements, but distorts the sample composition. We have developed the first treatment to correct for Malmquist bias in linear regressions of astronomical data. A demonstration of the corrected linear regression that is computed in four steps is presented.

  12. Robust median estimator in logisitc regression

    Czech Academy of Sciences Publication Activity Database

    Hobza, T.; Pardo, L.; Vajda, Igor

    2008-01-01

    Roč. 138, č. 12 (2008), s. 3822-3840 ISSN 0378-3758 R&D Projects: GA MŠk 1M0572 Grant - others:Instituto Nacional de Estadistica (ES) MPO FI - IM3/136; GA MŠk(CZ) MTM 2006-06872 Institutional research plan: CEZ:AV0Z10750506 Keywords : Logistic regression * Median * Robustness * Consistency and asymptotic normality * Morgenthaler * Bianco and Yohai * Croux and Hasellbroeck Subject RIV: BB - Applied Statistics, Operational Research Impact factor: 0.679, year: 2008 http://library.utia.cas.cz/separaty/2008/SI/vajda-robust%20median%20estimator%20in%20logistic%20regression.pdf

  13. Laser Beam Focus Analyser

    DEFF Research Database (Denmark)

    Nielsen, Peter Carøe; Hansen, Hans Nørgaard; Olsen, Flemming Ove

    2007-01-01

    the obtainable features in direct laser machining as well as heat affected zones in welding processes. This paper describes the development of a measuring unit capable of analysing beam shape and diameter of lasers to be used in manufacturing processes. The analyser is based on the principle of a rotating......The quantitative and qualitative description of laser beam characteristics is important for process implementation and optimisation. In particular, a need for quantitative characterisation of beam diameter was identified when using fibre lasers for micro manufacturing. Here the beam diameter limits...... mechanical wire being swept through the laser beam at varying Z-heights. The reflected signal is analysed and the resulting beam profile determined. The development comprised the design of a flexible fixture capable of providing both rotation and Z-axis movement, control software including data capture...

  14. Survival analysis models and applications

    CERN Document Server

    Liu, Xian

    2012-01-01

    Survival analysis concerns sequential occurrences of events governed by probabilistic laws.  Recent decades have witnessed many applications of survival analysis in various disciplines. This book introduces both classic survival models and theories along with newly developed techniques. Readers will learn how to perform analysis of survival data by following numerous empirical illustrations in SAS. Survival Analysis: Models and Applications: Presents basic techniques before leading onto some of the most advanced topics in survival analysis.Assumes only a minimal knowledge of SAS whilst enablin

  15. A genetic polymorphism in TOX3 is associated with survival of gastric cancer in a Chinese population.

    Directory of Open Access Journals (Sweden)

    Xiaojing Zhang

    Full Text Available PURPOSE: Recently, genetic polymorphism (rs3803662C>T in TOX3 was reported to induce the risk of breast cancer. In this study, we hypothesized that rs3803662 could influence gastric cancer survival outcomes. METHODS: With multiplex SNaPshot method, we genotyped TOX3 rs3803662 in 880 gastric patients with surgical resection. The association between genotype and survival outcomes was performed by the Kaplan-Meier method, Cox regression analysis models and the log-rank test. RESULTS: There was no association in the analyses of rs3803662 and survival of gastric cancer. However, the stratified analysis by histology showed that rs3803662 CT/TT genotype was associated with a significantly better survival for diffuse-type gastric cancer (log-rank p = 0.030, hazard ratio [HR]  = 0.67, 95% confidence interval [CI]  = 0.46-0.96, than the CC genotype. In addition, this favorable effect was especially obvious among gastric cancer patients with tumor size >5 cm, T3 and T4 depth of invasion, lymph node metastasis, no drinking, no distant metastasis, no chemotherapy and gastric cardia cancer. CONCLUSIONS: TOX3 rs3803662 might play an important role in the prognostic outcome and treatment of gastric cancer, especially perhaps further help in explaining the reduced risk of death associated with diffuse-type gastric cancer.

  16. THROMBOCYTOSIS AS PROGNOSTIC FACTOR FOR SURVIVAL IN PATIENTS WITH ADVANCED NON SMALL CELL LUNG CANCER TREATED WITH FIRST- LINE CHEMOTHERAPY.

    Directory of Open Access Journals (Sweden)

    Deyan Davidov

    2014-12-01

    Full Text Available Objective: The aim of this study was to evaluate elevated platelet count as a prognostic factor for survival in patients with advanced (stage IIIB/ IV non- small cell lung cancer (NSCLC receiving first- line chemotherapy. Methods: From 2005 to 2009 three hundreds forty seven consecutive patients with stage IIIB or IV NSCLC, treated in Department of Medical Oncology, UMHAT "Dr Georgi Stranski" entered the study. The therapeutic regimens included intravenous administration of platinum- based doublets. Survival analysis was evaluated by Kaplan- Meier test. The influence of pretreatment thrombocytosis as prognostic factor for survival was analyzed using multivariate stepwise Cox regression analyses. Results: Elevated platelet counts were found in 78 patients. The overall survival for patients without elevated platelet counts was 9,6 months versus 6,9 months for these with thrombocytosis. In multivariate analysis as independent poor prognostic factors were identified: stage, performance status and elevated platelet counts. Conclusions: These results indicated that platelet counts as well as some clinical pathologic characteristics could be useful prognostic factors in patients with unresectable NSCLC.

  17. Effect of Radiotherapy Interruptions on Survival in Medicare Enrollees With Local and Regional Head-and-Neck Cancer

    International Nuclear Information System (INIS)

    Fesinmeyer, Megan Dann; Mehta, Vivek; Blough, David; Tock, Lauri; Ramsey, Scott D.

    2010-01-01

    Purpose: To investigate whether interruptions in radiotherapy are associated with decreased survival in a population-based sample of head-and-neck cancer patients. Methods and Materials: Using the Surveillance, Epidemiology, and End Results-Medicare linked database we identified Medicare beneficiaries aged 66 years and older diagnosed with local-regional head-and-neck cancer during the period 1997-2003. We examined claims records of 3864 patients completing radiotherapy for the presence of one or more 5-30-day interruption(s) in therapy. We then performed Cox regression analyses to estimate the association between therapy interruptions and survival. Results: Patients with laryngeal tumors who experienced an interruption in radiotherapy had a 68% (95% confidence interval, 41-200%) increased risk of death, compared with patients with no interruptions. Patients with nasal cavity, nasopharynx, oral, salivary gland, and sinus tumors had similar associations between interruptions and increased risk of death, but these did not reach statistical significance because of small sample sizes. Conclusions: Treatment interruptions seem to influence survival time among patients with laryngeal tumors completing a full course of radiotherapy. At all head-and-neck sites, the association between interruptions and survival is sensitive to confounding by stage and other treatments. Further research is needed to develop methods to identify patients most susceptible to interruption-induced mortality.

  18. Edmondson-Steiner grade: A crucial predictor of recurrence and survival in hepatocellular carcinoma without microvascular invasio.

    Science.gov (United States)

    Zhou, Li; Rui, Jing-An; Zhou, Wei-Xun; Wang, Shao-Bin; Chen, Shu-Guang; Qu, Qiang

    2017-07-01

    Microvascular invasion (MVI), an important pathologic parameter, has been proven to be a powerful predictor of long-term prognosis in hepatocellular carcinoma (HCC). However, prognostic factors in HCC without MVI remain unknown. The present study aimed to identify the risk factors of recurrence and poor post-resectional survival in this type of HCC. A total of 109 patients with MVI-absent HCC underwent radical hepatectomy were enrolled. The influence of clinicopathologic variables on recurrence and patient survival was assessed using univariate and multivariate analyses. Chi-square test found that Edmondson-Steiner grade and satellite nodule were significantly associated with recurrence, while the former was the single marker for early recurrence. Stepwise logistic regression analysis demonstrated the independent predictive role of Edmondson-Steiner grade for recurrence. On the other hand, Edmondson-Steiner grade, serum AFP level and satellite nodule were significant for overall and disease-free survival in univariate analysis, whereas tumor size was linked to disease-free survival. Of the variables, Edmondson-Steiner grade, serum AFP level and satellite nodule were independent indicators. Edmondson-Steiner grade, a histological classification, carries robust prognostic implications for all the endpoints for prognosis, thus being potential to be a crucial prognosticator in HCC without MVI. Copyright © 2017 Elsevier GmbH. All rights reserved.

  19. Contesting Citizenship: Comparative Analyses

    DEFF Research Database (Denmark)

    Siim, Birte; Squires, Judith

    2007-01-01

    importance of particularized experiences and multiple ineequality agendas). These developments shape the way citizenship is both practiced and analysed. Mapping neat citizenship modles onto distinct nation-states and evaluating these in relation to formal equality is no longer an adequate approach....... Comparative citizenship analyses need to be considered in relation to multipleinequalities and their intersections and to multiple governance and trans-national organisinf. This, in turn, suggests that comparative citizenship analysis needs to consider new spaces in which struggles for equal citizenship occur...

  20. Demonstration of a Fiber Optic Regression Probe

    Science.gov (United States)

    Korman, Valentin; Polzin, Kurt A.

    2010-01-01

    The capability to provide localized, real-time monitoring of material regression rates in various applications has the potential to provide a new stream of data for development testing of various components and systems, as well as serving as a monitoring tool in flight applications. These applications include, but are not limited to, the regression of a combusting solid fuel surface, the ablation of the throat in a chemical rocket or the heat shield of an aeroshell, and the monitoring of erosion in long-life plasma thrusters. The rate of regression in the first application is very fast, while the second and third are increasingly slower. A recent fundamental sensor development effort has led to a novel regression, erosion, and ablation sensor technology (REAST). The REAST sensor allows for measurement of real-time surface erosion rates at a discrete surface location. The sensor is optical, using two different, co-located fiber-optics to perform the regression measurement. The disparate optical transmission properties of the two fiber-optics makes it possible to measure the regression rate by monitoring the relative light attenuation through the fibers. As the fibers regress along with the parent material in which they are embedded, the relative light intensities through the two fibers changes, providing a measure of the regression rate. The optical nature of the system makes it relatively easy to use in a variety of harsh, high temperature environments, and it is also unaffected by the presence of electric and magnetic fields. In addition, the sensor could be used to perform optical spectroscopy on the light emitted by a process and collected by fibers, giving localized measurements of various properties. The capability to perform an in-situ measurement of material regression rates is useful in addressing a variety of physical issues in various applications. An in-situ measurement allows for real-time data regarding the erosion rates, providing a quick method for

  1. Identification of subgroups by risk of graft failure after paediatric renal transplantation: application of survival tree models on the ESPN/ERA-EDTA Registry.

    Science.gov (United States)

    Lofaro, Danilo; Jager, Kitty J; Abu-Hanna, Ameen; Groothoff, Jaap W; Arikoski, Pekka; Hoecker, Britta; Roussey-Kesler, Gwenaelle; Spasojević, Brankica; Verrina, Enrico; Schaefer, Franz; van Stralen, Karlijn J

    2016-02-01

    Identification of patient groups by risk of renal graft loss might be helpful for accurate patient counselling and clinical decision-making. Survival tree models are an alternative statistical approach to identify subgroups, offering cut-off points for covariates and an easy-to-interpret representation. Within the European Society of Pediatric Nephrology/European Renal Association-European Dialysis and Transplant Association (ESPN/ERA-EDTA) Registry data we identified paediatric patient groups with specific profiles for 5-year renal graft survival. Two analyses were performed, including (i) parameters known at time of transplantation and (ii) additional clinical measurements obtained early after transplantation. The identified subgroups were added as covariates in two survival models. The prognostic performance of the models was tested and compared with conventional Cox regression analyses. The first analysis included 5275 paediatric renal transplants. The best 5-year graft survival (90.4%) was found among patients who received a renal graft as a pre-emptive transplantation or after short-term dialysis (2.2 years). The Cox model including both pre-transplant factors and tree subgroups had a significantly better predictive performance than conventional Cox regression (P 30 mL/min/1.73 m(2) and dialysis 20 months). Also in this case combining tree findings and clinical factors improved the predictive performance as compared with conventional Cox model models (P tree model to be an accurate and attractive tool to predict graft failure for patients with specific characteristics. This may aid the evaluation of individual graft prognosis and thereby the design of measures to improve graft survival in the poor prognosis groups. © The Author 2015. Published by Oxford University Press on behalf of ERA-EDTA. All rights reserved.

  2. Method for nonlinear exponential regression analysis

    Science.gov (United States)

    Junkin, B. G.

    1972-01-01

    Two computer programs developed according to two general types of exponential models for conducting nonlinear exponential regression analysis are described. Least squares procedure is used in which the nonlinear problem is linearized by expanding in a Taylor series. Program is written in FORTRAN 5 for the Univac 1108 computer.

  3. Measurement Error in Education and Growth Regressions

    NARCIS (Netherlands)

    Portela, Miguel; Alessie, Rob; Teulings, Coen

    2010-01-01

    The use of the perpetual inventory method for the construction of education data per country leads to systematic measurement error. This paper analyzes its effect on growth regressions. We suggest a methodology for correcting this error. The standard attenuation bias suggests that using these

  4. The M Word: Multicollinearity in Multiple Regression.

    Science.gov (United States)

    Morrow-Howell, Nancy

    1994-01-01

    Notes that existence of substantial correlation between two or more independent variables creates problems of multicollinearity in multiple regression. Discusses multicollinearity problem in social work research in which independent variables are usually intercorrelated. Clarifies problems created by multicollinearity, explains detection of…

  5. Regression Discontinuity Designs Based on Population Thresholds

    DEFF Research Database (Denmark)

    Eggers, Andrew C.; Freier, Ronny; Grembi, Veronica

    In many countries, important features of municipal government (such as the electoral system, mayors' salaries, and the number of councillors) depend on whether the municipality is above or below arbitrary population thresholds. Several papers have used a regression discontinuity design (RDD...

  6. Deriving the Regression Line with Algebra

    Science.gov (United States)

    Quintanilla, John A.

    2017-01-01

    Exploration with spreadsheets and reliance on previous skills can lead students to determine the line of best fit. To perform linear regression on a set of data, students in Algebra 2 (or, in principle, Algebra 1) do not have to settle for using the mysterious "black box" of their graphing calculators (or other classroom technologies).…

  7. Piecewise linear regression splines with hyperbolic covariates

    International Nuclear Information System (INIS)

    Cologne, John B.; Sposto, Richard

    1992-09-01

    Consider the problem of fitting a curve to data that exhibit a multiphase linear response with smooth transitions between phases. We propose substituting hyperbolas as covariates in piecewise linear regression splines to obtain curves that are smoothly joined. The method provides an intuitive and easy way to extend the two-phase linear hyperbolic response model of Griffiths and Miller and Watts and Bacon to accommodate more than two linear segments. The resulting regression spline with hyperbolic covariates may be fit by nonlinear regression methods to estimate the degree of curvature between adjoining linear segments. The added complexity of fitting nonlinear, as opposed to linear, regression models is not great. The extra effort is particularly worthwhile when investigators are unwilling to assume that the slope of the response changes abruptly at the join points. We can also estimate the join points (the values of the abscissas where the linear segments would intersect if extrapolated) if their number and approximate locations may be presumed known. An example using data on changing age at menarche in a cohort of Japanese women illustrates the use of the method for exploratory data analysis. (author)

  8. Targeting: Logistic Regression, Special Cases and Extensions

    Directory of Open Access Journals (Sweden)

    Helmut Schaeben

    2014-12-01

    Full Text Available Logistic regression is a classical linear model for logit-transformed conditional probabilities of a binary target variable. It recovers the true conditional probabilities if the joint distribution of predictors and the target is of log-linear form. Weights-of-evidence is an ordinary logistic regression with parameters equal to the differences of the weights of evidence if all predictor variables are discrete and conditionally independent given the target variable. The hypothesis of conditional independence can be tested in terms of log-linear models. If the assumption of conditional independence is violated, the application of weights-of-evidence does not only corrupt the predicted conditional probabilities, but also their rank transform. Logistic regression models, including the interaction terms, can account for the lack of conditional independence, appropriate interaction terms compensate exactly for violations of conditional independence. Multilayer artificial neural nets may be seen as nested regression-like models, with some sigmoidal activation function. Most often, the logistic function is used as the activation function. If the net topology, i.e., its control, is sufficiently versatile to mimic interaction terms, artificial neural nets are able to account for violations of conditional independence and yield very similar results. Weights-of-evidence cannot reasonably include interaction terms; subsequent modifications of the weights, as often suggested, cannot emulate the effect of interaction terms.

  9. Functional data analysis of generalized regression quantiles

    KAUST Repository

    Guo, Mengmeng

    2013-11-05

    Generalized regression quantiles, including the conditional quantiles and expectiles as special cases, are useful alternatives to the conditional means for characterizing a conditional distribution, especially when the interest lies in the tails. We develop a functional data analysis approach to jointly estimate a family of generalized regression quantiles. Our approach assumes that the generalized regression quantiles share some common features that can be summarized by a small number of principal component functions. The principal component functions are modeled as splines and are estimated by minimizing a penalized asymmetric loss measure. An iterative least asymmetrically weighted squares algorithm is developed for computation. While separate estimation of individual generalized regression quantiles usually suffers from large variability due to lack of sufficient data, by borrowing strength across data sets, our joint estimation approach significantly improves the estimation efficiency, which is demonstrated in a simulation study. The proposed method is applied to data from 159 weather stations in China to obtain the generalized quantile curves of the volatility of the temperature at these stations. © 2013 Springer Science+Business Media New York.

  10. Regression testing Ajax applications : Coping with dynamism

    NARCIS (Netherlands)

    Roest, D.; Mesbah, A.; Van Deursen, A.

    2009-01-01

    Note: This paper is a pre-print of: Danny Roest, Ali Mesbah and Arie van Deursen. Regression Testing AJAX Applications: Coping with Dynamism. In Proceedings of the 3rd International Conference on Software Testing, Verification and Validation (ICST’10), Paris, France. IEEE Computer Society, 2010.

  11. Group-wise partial least square regression

    NARCIS (Netherlands)

    Camacho, José; Saccenti, Edoardo

    2018-01-01

    This paper introduces the group-wise partial least squares (GPLS) regression. GPLS is a new sparse PLS technique where the sparsity structure is defined in terms of groups of correlated variables, similarly to what is done in the related group-wise principal component analysis. These groups are

  12. Functional data analysis of generalized regression quantiles

    KAUST Repository

    Guo, Mengmeng; Zhou, Lan; Huang, Jianhua Z.; Hä rdle, Wolfgang Karl

    2013-01-01

    Generalized regression quantiles, including the conditional quantiles and expectiles as special cases, are useful alternatives to the conditional means for characterizing a conditional distribution, especially when the interest lies in the tails. We develop a functional data analysis approach to jointly estimate a family of generalized regression quantiles. Our approach assumes that the generalized regression quantiles share some common features that can be summarized by a small number of principal component functions. The principal component functions are modeled as splines and are estimated by minimizing a penalized asymmetric loss measure. An iterative least asymmetrically weighted squares algorithm is developed for computation. While separate estimation of individual generalized regression quantiles usually suffers from large variability due to lack of sufficient data, by borrowing strength across data sets, our joint estimation approach significantly improves the estimation efficiency, which is demonstrated in a simulation study. The proposed method is applied to data from 159 weather stations in China to obtain the generalized quantile curves of the volatility of the temperature at these stations. © 2013 Springer Science+Business Media New York.

  13. Finite Algorithms for Robust Linear Regression

    DEFF Research Database (Denmark)

    Madsen, Kaj; Nielsen, Hans Bruun

    1990-01-01

    The Huber M-estimator for robust linear regression is analyzed. Newton type methods for solution of the problem are defined and analyzed, and finite convergence is proved. Numerical experiments with a large number of test problems demonstrate efficiency and indicate that this kind of approach may...

  14. Function approximation with polynomial regression slines

    International Nuclear Information System (INIS)

    Urbanski, P.

    1996-01-01

    Principles of the polynomial regression splines as well as algorithms and programs for their computation are presented. The programs prepared using software package MATLAB are generally intended for approximation of the X-ray spectra and can be applied in the multivariate calibration of radiometric gauges. (author)

  15. Assessing risk factors for periodontitis using regression

    Science.gov (United States)

    Lobo Pereira, J. A.; Ferreira, Maria Cristina; Oliveira, Teresa

    2013-10-01

    Multivariate statistical analysis is indispensable to assess the associations and interactions between different factors and the risk of periodontitis. Among others, regression analysis is a statistical technique widely used in healthcare to investigate and model the relationship between variables. In our work we study the impact of socio-demographic, medical and behavioral factors on periodontal health. Using regression, linear and logistic models, we can assess the relevance, as risk factors for periodontitis disease, of the following independent variables (IVs): Age, Gender, Diabetic Status, Education, Smoking status and Plaque Index. The multiple linear regression analysis model was built to evaluate the influence of IVs on mean Attachment Loss (AL). Thus, the regression coefficients along with respective p-values will be obtained as well as the respective p-values from the significance tests. The classification of a case (individual) adopted in the logistic model was the extent of the destruction of periodontal tissues defined by an Attachment Loss greater than or equal to 4 mm in 25% (AL≥4mm/≥25%) of sites surveyed. The association measures include the Odds Ratios together with the correspondent 95% confidence intervals.

  16. Predicting Social Trust with Binary Logistic Regression

    Science.gov (United States)

    Adwere-Boamah, Joseph; Hufstedler, Shirley

    2015-01-01

    This study used binary logistic regression to predict social trust with five demographic variables from a national sample of adult individuals who participated in The General Social Survey (GSS) in 2012. The five predictor variables were respondents' highest degree earned, race, sex, general happiness and the importance of personally assisting…

  17. Yet another look at MIDAS regression

    NARCIS (Netherlands)

    Ph.H.B.F. Franses (Philip Hans)

    2016-01-01

    textabstractA MIDAS regression involves a dependent variable observed at a low frequency and independent variables observed at a higher frequency. This paper relates a true high frequency data generating process, where also the dependent variable is observed (hypothetically) at the high frequency,

  18. Revisiting Regression in Autism: Heller's "Dementia Infantilis"

    Science.gov (United States)

    Westphal, Alexander; Schelinski, Stefanie; Volkmar, Fred; Pelphrey, Kevin

    2013-01-01

    Theodor Heller first described a severe regression of adaptive function in normally developing children, something he termed dementia infantilis, over one 100 years ago. Dementia infantilis is most closely related to the modern diagnosis, childhood disintegrative disorder. We translate Heller's paper, Uber Dementia Infantilis, and discuss…

  19. Fast multi-output relevance vector regression

    OpenAIRE

    Ha, Youngmin

    2017-01-01

    This paper aims to decrease the time complexity of multi-output relevance vector regression from O(VM^3) to O(V^3+M^3), where V is the number of output dimensions, M is the number of basis functions, and V

  20. Regression Equations for Birth Weight Estimation using ...

    African Journals Online (AJOL)

    In this study, Birth Weight has been estimated from anthropometric measurements of hand and foot. Linear regression equations were formed from each of the measured variables. These simple equations can be used to estimate Birth Weight of new born babies, in order to identify those with low birth weight and referred to ...

  1. Superquantile Regression: Theory, Algorithms, and Applications

    Science.gov (United States)

    2014-12-01

    Highway, Suite 1204, Arlington, Va 22202-4302, and to the Office of Management and Budget, Paperwork Reduction Project (0704-0188) Washington DC 20503. 1...Navy submariners, reliability engineering, uncertainty quantification, and financial risk management . Superquantile, superquantile regression...Royset Carlos F. Borges Associate Professor of Operations Research Dissertation Supervisor Professor of Applied Mathematics Lyn R. Whitaker Javier

  2. transformation of independent variables in polynomial regression ...

    African Journals Online (AJOL)

    Ada

    preferable when possible to work with a simple functional form in transformed variables rather than with a more complicated form in the original variables. In this paper, it is shown that linear transformations applied to independent variables in polynomial regression models affect the t ratio and hence the statistical ...

  3. Multiple Linear Regression: A Realistic Reflector.

    Science.gov (United States)

    Nutt, A. T.; Batsell, R. R.

    Examples of the use of Multiple Linear Regression (MLR) techniques are presented. This is done to show how MLR aids data processing and decision-making by providing the decision-maker with freedom in phrasing questions and by accurately reflecting the data on hand. A brief overview of the rationale underlying MLR is given, some basic definitions…

  4. Risico-analyse brandstofpontons

    NARCIS (Netherlands)

    Uijt de Haag P; Post J; LSO

    2001-01-01

    Voor het bepalen van de risico's van brandstofpontons in een jachthaven is een generieke risico-analyse uitgevoerd. Er is een referentiesysteem gedefinieerd, bestaande uit een betonnen brandstofponton met een relatief grote inhoud en doorzet. Aangenomen is dat de ponton gelegen is in een

  5. Fast multichannel analyser

    Energy Technology Data Exchange (ETDEWEB)

    Berry, A; Przybylski, M M; Sumner, I [Science Research Council, Daresbury (UK). Daresbury Lab.

    1982-10-01

    A fast multichannel analyser (MCA) capable of sampling at a rate of 10/sup 7/ s/sup -1/ has been developed. The instrument is based on an 8 bit parallel encoding analogue to digital converter (ADC) reading into a fast histogramming random access memory (RAM) system, giving 256 channels of 64 k count capacity. The prototype unit is in CAMAC format.

  6. A fast multichannel analyser

    International Nuclear Information System (INIS)

    Berry, A.; Przybylski, M.M.; Sumner, I.

    1982-01-01

    A fast multichannel analyser (MCA) capable of sampling at a rate of 10 7 s -1 has been developed. The instrument is based on an 8 bit parallel encoding analogue to digital converter (ADC) reading into a fast histogramming random access memory (RAM) system, giving 256 channels of 64 k count capacity. The prototype unit is in CAMAC format. (orig.)

  7. Regression Models and Fuzzy Logic Prediction of TBM Penetration Rate

    Directory of Open Access Journals (Sweden)

    Minh Vu Trieu

    2017-03-01

    Full Text Available This paper presents statistical analyses of rock engineering properties and the measured penetration rate of tunnel boring machine (TBM based on the data of an actual project. The aim of this study is to analyze the influence of rock engineering properties including uniaxial compressive strength (UCS, Brazilian tensile strength (BTS, rock brittleness index (BI, the distance between planes of weakness (DPW, and the alpha angle (Alpha between the tunnel axis and the planes of weakness on the TBM rate of penetration (ROP. Four (4 statistical regression models (two linear and two nonlinear are built to predict the ROP of TBM. Finally a fuzzy logic model is developed as an alternative method and compared to the four statistical regression models. Results show that the fuzzy logic model provides better estimations and can be applied to predict the TBM performance. The R-squared value (R2 of the fuzzy logic model scores the highest value of 0.714 over the second runner-up of 0.667 from the multiple variables nonlinear regression model.

  8. Regression Models and Fuzzy Logic Prediction of TBM Penetration Rate

    Science.gov (United States)

    Minh, Vu Trieu; Katushin, Dmitri; Antonov, Maksim; Veinthal, Renno

    2017-03-01

    This paper presents statistical analyses of rock engineering properties and the measured penetration rate of tunnel boring machine (TBM) based on the data of an actual project. The aim of this study is to analyze the influence of rock engineering properties including uniaxial compressive strength (UCS), Brazilian tensile strength (BTS), rock brittleness index (BI), the distance between planes of weakness (DPW), and the alpha angle (Alpha) between the tunnel axis and the planes of weakness on the TBM rate of penetration (ROP). Four (4) statistical regression models (two linear and two nonlinear) are built to predict the ROP of TBM. Finally a fuzzy logic model is developed as an alternative method and compared to the four statistical regression models. Results show that the fuzzy logic model provides better estimations and can be applied to predict the TBM performance. The R-squared value (R2) of the fuzzy logic model scores the highest value of 0.714 over the second runner-up of 0.667 from the multiple variables nonlinear regression model.

  9. Physics constrained nonlinear regression models for time series

    International Nuclear Information System (INIS)

    Majda, Andrew J; Harlim, John

    2013-01-01

    A central issue in contemporary science is the development of data driven statistical nonlinear dynamical models for time series of partial observations of nature or a complex physical model. It has been established recently that ad hoc quadratic multi-level regression (MLR) models can have finite-time blow up of statistical solutions and/or pathological behaviour of their invariant measure. Here a new class of physics constrained multi-level quadratic regression models are introduced, analysed and applied to build reduced stochastic models from data of nonlinear systems. These models have the advantages of incorporating memory effects in time as well as the nonlinear noise from energy conserving nonlinear interactions. The mathematical guidelines for the performance and behaviour of these physics constrained MLR models as well as filtering algorithms for their implementation are developed here. Data driven applications of these new multi-level nonlinear regression models are developed for test models involving a nonlinear oscillator with memory effects and the difficult test case of the truncated Burgers–Hopf model. These new physics constrained quadratic MLR models are proposed here as process models for Bayesian estimation through Markov chain Monte Carlo algorithms of low frequency behaviour in complex physical data. (paper)

  10. Effect of bystander CPR initiation prior to the emergency call on ROSC and 30day survival-An evaluation of 548 emergency calls.

    Science.gov (United States)

    Viereck, Søren; Palsgaard Møller, Thea; Kjær Ersbøll, Annette; Folke, Fredrik; Lippert, Freddy

    2017-02-01

    This study aimed at evaluating if time for initiation of bystander cardiopulmonary resuscitation (CPR) - prior to the emergency call (CPR prior ) versus during the emergency call following dispatcher-assisted CPR (CPR during ) - was associated with return of spontaneous circulation (ROSC) and 30-day survival. The secondary aim was to identify predictors of CPR prior . This observational study evaluated out-of-hospital cardiac arrests (OHCA) occurring in the Capital Region of Denmark from 01.01.2013 to 31.12.2013. OHCAs were linked to emergency medical dispatch centre records and corresponding emergency calls were evaluated. Multivariable logistic regression analyses were applied to evaluate the association between time for initiation of bystander CPR, ROSC, and 30-day survival. Univariable logistic regression analyses were applied to identify predictors of CPR prior . The study included 548 emergency calls for OHCA patients receiving bystander CPR, 34.9% (n=191) in the CPR prior group and 65.1% (n=357) in the CPR during group. Multivariable analyses showed no difference in ROSC (OR=0.88, 95% CI: 0.56-1.38) or 30-day survival (OR=1.14, 95% CI: 0.68-1.92) between CPR prior and CPR during . Predictors positively associated with CPR prior included witnessed OHCA and healthcare professional bystanders. Predictors negatively associated with CPR prior included residential location, solitary bystanders, and bystanders related to the patient. The majority of bystander CPR (65%) was initiated during the emergency call, following dispatcher-assisted CPR instructions. Whether bystander CPR was initiated prior to emergency call versus during the emergency call following dispatcher-assisted CPR was not associated with ROSC or 30-day survival. Dispatcher-assisted CPR was especially beneficial for the initiation of bystander CPR in residential areas. Copyright © 2016 The Authors. Published by Elsevier Ireland Ltd.. All rights reserved.

  11. Low temperature and dust favour in vitro survival of Mycoplasma hyopneumoniae: time to revisit indirect transmission in pig housing.

    Science.gov (United States)

    Browne, C; Loeffler, A; Holt, H R; Chang, Y M; Lloyd, D H; Nevel, A

    2017-01-01

    Porcine enzootic pneumonia (EP) caused by Mycoplasma hyopneumoniae adversely affects pig welfare and is associated with major economic losses in the pig industry worldwide. Transmission is predominantly by direct contact, but the role of indirect transmission remains poorly understood. This study examined survival of six M. hyopneumoniae isolates dried onto five different surfaces encountered in pig units and exposed to temperatures of 4, 25 and 37°C for up to 12 days. Survival of the organisms was determined by recovering the organism from the surface material and culturing in Friis broth. Data were analysed by logistic regression to identify factors influencing survival of M. hyopneumoniae. Maximum survival was 8 days for all isolates on at least one surface (except stainless steel) at 4°C and was limited to 2 days at 25 and 37°C. Overall, dust and polypropylene copolymer supported M. hyopneumoniae survival the longest when compared with other surface materials. In conclusion, we have demonstrated that M. hyopneumoniae can survive outside the host for at least 8 days. Understanding the transmission of Mycoplasma hyopneumoniae and optimizing biosecurity practices are keys to reducing the use of antimicrobial agents to control this pathogen. Direct transmission of the pathogen between pigs is the main route of spread and its lack of cell wall may compromise its resilience outside the host. The results from our study show that M. hyopneumoniae can survive for up to several days on dry surfaces and therefore may have the potential to infect pigs by indirect transmission. Factors influencing the survival of M. hyopneumoniae outside the host are further elucidated. © 2016 The Society for Applied Microbiology.

  12. Resection of oligometastatic lung cancer to the pancreas may yield a survival benefit in select patients--a systematic review.

    Science.gov (United States)

    DeLuzio, Matthew R; Moores, Craig; Dhamija, Ankit; Wang, Zuoheng; Cha, Charles; Boffa, Daniel J; Detterbeck, Frank C; Kim, Anthony W

    2015-01-01

    To conduct a systematic review of the existing literature regarding surgical therapy for oligometastatic lung cancer to the pancreas. Data was collected on patients with singular pancreatic metastases from lung cancer from papers published between January 1970 and June 2014. This was performed following the Preferred Reporting Items for Systematic reviews and Meta-analysis (PRISMA) guidelines. Kaplan-Meier and Cox Regression analyses were then used to determine and compare survival. There were 27 papers that fulfilled the search criteria, from which data on 32 patients was collected. Non-small cell lung cancer (NSCLC) was the most prevalent type of primary lung malignancy, and metachronous presentations of metastases were most common. Lesions were most frequently located in the pancreatic head and consequently the most common curative intent metastasectomy was pancreaticoduodenectomy. There was a statistically significant survival benefit for patients whose metastasis were discovered incidentally by surveillance CT as opposed to those whose metastasis were discovered during a work up for new somatic complaints (p = 0.024). The overall median survival for patients undergoing curative intent resection was 29 months, with 2-year and 5-year survivals of 65% and 21% respectively. Palliative surgery or medical only management was associated with a median survival of 8 months and 2-year and 5-year survivals of 25% and 8% respectively. Curative intent resection of isolated pancreatic metastasis from lung cancer may be beneficial in a select group of patients. Copyright © 2015 IAP and EPC. Published by Elsevier B.V. All rights reserved.

  13. Number of Lymph Nodes Removed and Survival after Gastric Cancer Resection: An Analysis from the US Gastric Cancer Collaborative.

    Science.gov (United States)

    Gholami, Sepideh; Janson, Lucas; Worhunsky, David J; Tran, Thuy B; Squires, Malcolm Hart; Jin, Linda X; Spolverato, Gaya; Votanopoulos, Konstantinos I; Schmidt, Carl; Weber, Sharon M; Bloomston, Mark; Cho, Clifford S; Levine, Edward A; Fields, Ryan C; Pawlik, Timothy M; Maithel, Shishir K; Efron, Bradley; Norton, Jeffrey A; Poultsides, George A

    2015-08-01

    Examination of at least 16 lymph nodes (LNs) has been traditionally recommended during gastric adenocarcinoma resection to optimize staging, but the impact of this strategy on survival is uncertain. Because recent randomized trials have demonstrated a therapeutic benefit from extended lymphadenectomy, we sought to investigate the impact of the number of LNs removed on prognosis after gastric adenocarcinoma resection. We analyzed patients who underwent gastrectomy for gastric adenocarcinoma from 2000 to 2012, at 7 US academic institutions. Patients with M1 disease or R2 resections were excluded. Disease-specific survival (DSS) was calculated using the Kaplan-Meier method and compared using log-rank and Cox regression analyses. Of 742 patients, 257 (35%) had 7 to 15 LNs removed and 485 (65%) had ≥16 LNs removed. Disease-specific survival was not significantly longer after removal of ≥16 vs 7 to 15 LNs (10-year survival, 55% vs 47%, respectively; p = 0.53) for the entire cohort, but was significantly improved in the subset of patients with stage IA to IIIA (10-year survival, 74% vs 57%, respectively; p = 0.018) or N0-2 disease (72% vs 55%, respectively; p = 0.023). Similarly, for patients who were classified to more likely be "true N0-2," based on frequentist analysis incorporating both the number of positive and of total LNs removed, the hazard ratio for disease-related death (adjusted for T stage, R status, grade, receipt of neoadjuvant and adjuvant therapy, and institution) significantly decreased as the number of LNs removed increased. The number of LNs removed during gastrectomy for adenocarcinoma appears itself to have prognostic implications for long-term survival. Copyright © 2015 American College of Surgeons. Published by Elsevier Inc. All rights reserved.

  14. Impact of Symptomatic Metastatic Spinal Cord Compression on Survival of Patients with Non-Small-Cell Lung Cancer.

    Science.gov (United States)

    da Silva, Gustavo Telles; Bergmann, Anke; Thuler, Luiz Claudio Santos

    2017-12-01

    Non-small-cell lung cancer (NSCLC) is one of the most common primary tumor sites among patients with metastatic spinal cord compression (MSCC). This disorder is related to neurologic dysfunction and can reduce the quality of life, but the association between MSCC and death is unclear. The aim of this study was to analyze the impact of the occurrence of symptomatic MSCC on overall survival of patients with NSCLC. A cohort study was carried out involving 1112 patients with NSCLC who were enrolled between 2006 and 2014 in a single cancer center. Clinical and sociodemographic data were extracted from the physical and electronic records. Survival analysis of patients with NSCLC was conducted using the Kaplan-Meier method. A log-rank test was used to assess differences between survival curves. Cox proportional hazards regression analyses were carried out to quantify the relationship between the independent variable (MSCC) and the outcome (overall survival). During the study period, the incidence of MSCC was 4.1%. Patients who presented with MSCC were 1.43 times more likely to die than were those with no history of MSCC (hazard ratio, 1.43; 95% confidence interval [CI], 1.03-2.00; P = 0.031). The median survival time was 8.04 months (95% CI, 6.13-9.96) for those who presented MSCC and 11.95 months (95% CI, 10.80-13.11) for those who did not presented MSCC during the course of disease (P = 0.002). MSCC is an important and independent predictor of NSCLC worse survival. This effect was not influenced by sociodemographic and clinical factors. Copyright © 2017 Elsevier Inc. All rights reserved.

  15. Sparing Sphincters and Laparoscopic Resection Improve Survival by Optimizing the Circumferential Resection Margin in Rectal Cancer Patients.

    Science.gov (United States)

    Keskin, Metin; Bayraktar, Adem; Sivirikoz, Emre; Yegen, Gülcin; Karip, Bora; Saglam, Esra; Bulut, Mehmet Türker; Balik, Emre

    2016-02-01

    The goal of rectal cancer treatment is to minimize the local recurrence rate and extend the disease-free survival period and survival. For this aim, obtainment of negative circumferential radial margin (CRM) plays an important role. This study evaluated predictive factors for positive CRM status and its effect on patient survival in mid- and distal rectal tumors.Patients who underwent curative resection for rectal cancer were included. The main factors were demographic data, tumor location, surgical technique, neoadjuvant therapy, tumor diameter, tumor depth, lymph node metastasis, mesorectal integrity, CRM, the rate of local recurrence, distant metastasis, and overall and disease-free survival. Statistical analyses were performed by using the Chi-squared test, Fisher exact test, Student t test, Mann-Whitney U test and the Mantel-Cox log-rank sum test.A total of 420 patients were included, 232 (55%) of whom were male. We observed no significant differences in patient characteristics or surgical treatment between the patients who had positive CRM and who had negative CRM, but a higher positive CRM rate was observed in patients undergone abdominoperineal resection (APR) (P CRM status. Logistic regression analysis revealed that APR (P CRM status. Moreover, positive CRM was associated with decreased 5-year overall and disease-free survival (P = 0.002 and P = 0.004, respectively).This large single-institution series demonstrated that APR and open resection were independent predictive factors for positive CRM status in rectal cancer. Positive CRM independently decreased the 5-year overall and disease-free survival rates.

  16. Tax System in Poland – Progressive or Regressive?

    Directory of Open Access Journals (Sweden)

    Jacek Tomkiewicz

    2016-03-01

    Full Text Available Purpose: To analyse the impact of the Polish fiscal regime on the general revenue of the country, and specifically to establish whether the cumulative tax burden borne by Polish households is progressive or regressive.Methodology: On the basis of Eurostat and OECD data, the author has analysed fiscal regimes in EU Member States and in OECD countries. The tax burden of households within different income groups has also been examined pursuant to applicable fiscal laws and data pertaining to the revenue and expenditure of households published by the Central Statistical Office (CSO.Conclusions: The fiscal regime in Poland is regressive; that is, the relative fiscal burden decreases as the taxpayer’s income increases.Research Implications: The article contributes to the on-going discussion on social cohesion, in particular with respect to economic policy instruments aimed at the redistribution of income within the economy.Originality: The author presents an analysis of data pertaining to fiscal policies in EU Member States and OECD countries and assesses the impact of the legal environment (fiscal regime and social security system in Poland on income distribution within the economy. The impact of the total tax burden (direct and indirect taxes, social security contributions on the economic situation of households from different income groups has been calculated using an original formula.

  17. Detecting overdispersion in count data: A zero-inflated Poisson regression analysis

    Science.gov (United States)

    Afiqah Muhamad Jamil, Siti; Asrul Affendi Abdullah, M.; Kek, Sie Long; Nor, Maria Elena; Mohamed, Maryati; Ismail, Norradihah

    2017-09-01

    This study focusing on analysing count data of butterflies communities in Jasin, Melaka. In analysing count dependent variable, the Poisson regression model has been known as a benchmark model for regression analysis. Continuing from the previous literature that used Poisson regression analysis, this study comprising the used of zero-inflated Poisson (ZIP) regression analysis to gain acute precision on analysing the count data of butterfly communities in Jasin, Melaka. On the other hands, Poisson regression should be abandoned in the favour of count data models, which are capable of taking into account the extra zeros explicitly. By far, one of the most popular models include ZIP regression model. The data of butterfly communities which had been called as the number of subjects in this study had been taken in Jasin, Melaka and consisted of 131 number of subjects visits Jasin, Melaka. Since the researchers are considering the number of subjects, this data set consists of five families of butterfly and represent the five variables involve in the analysis which are the types of subjects. Besides, the analysis of ZIP used the SAS procedure of overdispersion in analysing zeros value and the main purpose of continuing the previous study is to compare which models would be better than when exists zero values for the observation of the count data. The analysis used AIC, BIC and Voung test of 5% level significance in order to achieve the objectives. The finding indicates that there is a presence of over-dispersion in analysing zero value. The ZIP regression model is better than Poisson regression model when zero values exist.

  18. Association between pre-transplant dialysis modality and patient and graft survival after kidney transplantation

    DEFF Research Database (Denmark)

    Kramer, Anneke; Jager, Kitty J; Fogarty, Damian G

    2012-01-01

    Previous studies have found inconsistent associations between pre-transplant dialysis modality and subsequent post-transplant survival. We aimed to examine this relationship using the instrumental variable method and to compare the results with standard Cox regression.......Previous studies have found inconsistent associations between pre-transplant dialysis modality and subsequent post-transplant survival. We aimed to examine this relationship using the instrumental variable method and to compare the results with standard Cox regression....

  19. Nuclear War Survival Skills

    Energy Technology Data Exchange (ETDEWEB)

    Kearny, C.H.

    2002-06-24

    The purpose of this book is to provide Americans with information and instructions that will significantly increase their chances of surviving a possible nuclear attack. It brings together field-tested instructions that, if followed by a large fraction of Americans during a crisis that preceded an attack, could save millions of lives. The author is convinced that the vulnerability of our country to nuclear threat or attack must be reduced and that the wide dissemination of the information contained in this book would help achieve that objective of our overall defense strategy.

  20. Survival after blood transfusion

    DEFF Research Database (Denmark)

    Kamper-Jørgensen, Mads; Ahlgren, Martin; Rostgaard, Klaus

    2008-01-01

    of transfusion recipients in Denmark and Sweden followed for up to 20 years after their first blood transfusion. Main outcome measure was all-cause mortality. RESULTS: A total of 1,118,261 transfusion recipients were identified, of whom 62.0 percent were aged 65 years or older at the time of their first...... the SMR remained significantly 1.3-fold increased. CONCLUSION: The survival and relative mortality patterns among blood transfusion recipients were characterized with unprecedented detail and precision. Our results are relevant to assessments of the consequences of possible transfusion-transmitted disease...... as well as for cost-benefit estimation of new blood safety interventions....