Inferential Statistics from Black Hispanic Breast Cancer Survival Data

Directory of Open Access Journals (Sweden)

Hafiz M. R. Khan

2014-01-01

Full Text Available In this paper we test the statistical probability models for breast cancer survival data for race and ethnicity. Data was collected from breast cancer patients diagnosed in United States during the years 1973–2009. We selected a stratified random sample of Black Hispanic female patients from the Surveillance Epidemiology and End Results (SEER database to derive the statistical probability models. We used three common model building criteria which include Akaike Information Criteria (AIC, Bayesian Information Criteria (BIC, and Deviance Information Criteria (DIC to measure the goodness of fit tests and it was found that Black Hispanic female patients survival data better fit the exponentiated exponential probability model. A novel Bayesian method was used to derive the posterior density function for the model parameters as well as to derive the predictive inference for future response. We specifically focused on Black Hispanic race. Markov Chain Monte Carlo (MCMC method was used for obtaining the summary results of posterior parameters. Additionally, we reported predictive intervals for future survival times. These findings would be of great significance in treatment planning and healthcare resource allocation.

Understanding survival analysis: Kaplan-Meier estimate.

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Goel, Manish Kumar; Khanna, Pardeep; Kishore, Jugal

2010-10-01

Kaplan-Meier estimate is one of the best options to be used to measure the fraction of subjects living for a certain amount of time after treatment. In clinical trials or community trials, the effect of an intervention is assessed by measuring the number of subjects survived or saved after that intervention over a period of time. The time starting from a defined point to the occurrence of a given event, for example death is called as survival time and the analysis of group data as survival analysis. This can be affected by subjects under study that are uncooperative and refused to be remained in the study or when some of the subjects may not experience the event or death before the end of the study, although they would have experienced or died if observation continued, or we lose touch with them midway in the study. We label these situations as censored observations. The Kaplan-Meier estimate is the simplest way of computing the survival over time in spite of all these difficulties associated with subjects or situations. The survival curve can be created assuming various situations. It involves computing of probabilities of occurrence of event at a certain point of time and multiplying these successive probabilities by any earlier computed probabilities to get the final estimate. This can be calculated for two groups of subjects and also their statistical difference in the survivals. This can be used in Ayurveda research when they are comparing two drugs and looking for survival of subjects.

A taylor series approach to survival analysis

International Nuclear Information System (INIS)

Brodsky, J.B.; Groer, P.G.

1984-09-01

A method of survival analysis using hazard functions is developed. The method uses the well known mathematical theory for Taylor Series. Hypothesis tests of the adequacy of many statistical models, including proportional hazards and linear and/or quadratic dose responses, are obtained. A partial analysis of leukemia mortality in the Life Span Study cohort is used as an example. Furthermore, a relatively robust estimation procedure for the proportional hazards model is proposed. (author)

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

Statistical and biophysical aspects of survival curve

International Nuclear Information System (INIS)

Kellerer, A.M.

1980-01-01

Statistic fluctuation in a series of consequently taken survival curves of asynchronous cells of a hamster of the V79 line during X-ray irradiation, are considered. In each of the experiments fluctuations are close to those expected on the basis of the Poisson distribution. The fluctuation of cell sensitivity in different experiments of one series can reach 10%. The normalization of each experiment in mean values permits to obtain the ''idealized'' survival curve. The survival logarithm in this curve is proportional to the absorbed dose and its square only at low radiation doses. Such proportionality in V lab 79 cells in the late S-phase is observed at all doses. Using the microdosimetric approach, the distance where the interaction of radiolysis products or subinjury takes place to make the dependence of injury on the dose non-linear, is determined. In the case of interaction distances of 10-100 nm, the linear component is shown to become comparable in value with the linear injury component at doses of the order of several hundred rad only in the case, when the interaction distance is close to micrometre [ru

Application of survival analysis methodology to the quantitative analysis of LC-MS proteomics data

KAUST Repository

Tekwe, C. D.; Carroll, R. J.; Dabney, A. R.

2012-01-01

positive, skewed and often left-censored, we propose using survival methodology to carry out differential expression analysis of proteins. Various standard statistical techniques including non-parametric tests such as the Kolmogorov-Smirnov and Wilcoxon

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

Association between obesity with disease-free survival and overall survival in triple-negative breast cancer: A meta-analysis.

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Mei, Lin; He, Lin; Song, Yuhua; Lv, Yang; Zhang, Lijiu; Hao, Fengxi; Xu, Mengmeng

2018-05-01

To investigate the relationship between obesity and disease-free survival (DFS) and overall survival (OS) of triple-negative breast cancer. Citations were searched in PubMed, Cochrane Library, and Web of Science. Random effect model meta-analysis was conducted by using Revman software version 5.0, and publication bias was evaluated by creating Egger regression with STATA software version 12. Nine studies (4412 patients) were included for DFS meta-analysis, 8 studies (4392 patients) include for OS meta-analysis. There were no statistical significances between obesity with DFS (P = .60) and OS (P = .71) in triple-negative breast cancer (TNBC) patients. Obesity has no impact on DFS and OS in patients with TNBC.

CFAssay: statistical analysis of the colony formation assay

International Nuclear Information System (INIS)

Braselmann, Herbert; Michna, Agata; Heß, Julia; Unger, Kristian

2015-01-01

Colony formation assay is the gold standard to determine cell reproductive death after treatment with ionizing radiation, applied for different cell lines or in combination with other treatment modalities. Associated linear-quadratic cell survival curves can be calculated with different methods. For easy code exchange and methodological standardisation among collaborating laboratories a software package CFAssay for R (R Core Team, R: A Language and Environment for Statistical Computing, 2014) was established to perform thorough statistical analysis of linear-quadratic cell survival curves after treatment with ionizing radiation and of two-way designs of experiments with chemical treatments only. CFAssay offers maximum likelihood and related methods by default and the least squares or weighted least squares method can be optionally chosen. A test for comparision of cell survival curves and an ANOVA test for experimental two-way designs are provided. For the two presented examples estimated parameters do not differ much between maximum-likelihood and least squares. However the dispersion parameter of the quasi-likelihood method is much more sensitive for statistical variation in the data than the multiple R 2 coefficient of determination from the least squares method. The dispersion parameter for goodness of fit and different plot functions in CFAssay help to evaluate experimental data quality. As open source software interlaboratory code sharing between users is facilitated

Addressing issues associated with evaluating prediction models for survival endpoints based on the concordance statistic.

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Wang, Ming; Long, Qi

2016-09-01

Prediction models for disease risk and prognosis play an important role in biomedical research, and evaluating their predictive accuracy in the presence of censored data is of substantial interest. The standard concordance (c) statistic has been extended to provide a summary measure of predictive accuracy for survival models. Motivated by a prostate cancer study, we address several issues associated with evaluating survival prediction models based on c-statistic with a focus on estimators using the technique of inverse probability of censoring weighting (IPCW). Compared to the existing work, we provide complete results on the asymptotic properties of the IPCW estimators under the assumption of coarsening at random (CAR), and propose a sensitivity analysis under the mechanism of noncoarsening at random (NCAR). In addition, we extend the IPCW approach as well as the sensitivity analysis to high-dimensional settings. The predictive accuracy of prediction models for cancer recurrence after prostatectomy is assessed by applying the proposed approaches. We find that the estimated predictive accuracy for the models in consideration is sensitive to NCAR assumption, and thus identify the best predictive model. Finally, we further evaluate the performance of the proposed methods in both settings of low-dimensional and high-dimensional data under CAR and NCAR through simulations. © 2016, The International Biometric Society.

Application of survival analysis methodology to the quantitative analysis of LC-MS proteomics data.

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Tekwe, Carmen D; Carroll, Raymond J; Dabney, Alan R

2012-08-01

Protein abundance in quantitative proteomics is often based on observed spectral features derived from liquid chromatography mass spectrometry (LC-MS) or LC-MS/MS experiments. Peak intensities are largely non-normal in distribution. Furthermore, LC-MS-based proteomics data frequently have large proportions of missing peak intensities due to censoring mechanisms on low-abundance spectral features. Recognizing that the observed peak intensities detected with the LC-MS method are all positive, skewed and often left-censored, we propose using survival methodology to carry out differential expression analysis of proteins. Various standard statistical techniques including non-parametric tests such as the Kolmogorov-Smirnov and Wilcoxon-Mann-Whitney rank sum tests, and the parametric survival model and accelerated failure time-model with log-normal, log-logistic and Weibull distributions were used to detect any differentially expressed proteins. The statistical operating characteristics of each method are explored using both real and simulated datasets. Survival methods generally have greater statistical power than standard differential expression methods when the proportion of missing protein level data is 5% or more. In particular, the AFT models we consider consistently achieve greater statistical power than standard testing procedures, with the discrepancy widening with increasing missingness in the proportions. The testing procedures discussed in this article can all be performed using readily available software such as R. The R codes are provided as supplemental materials. ctekwe@stat.tamu.edu.

Bernstein - Von Mises theorem and its application in survival analysis

Czech Academy of Sciences Publication Activity Database

Timková, Jana

2010-01-01

Roč. 22, č. 3 (2010), s. 115-122 ISSN 1210-8022. [16. letní škola JČMF Robust 2010. Králíky, 30.01.2010-05.02.2010] R&D Projects: GA AV ČR(CZ) IAA101120604 Institutional research plan: CEZ:AV0Z10750506 Keywords : Cox model * bayesian asymptotics * survival function Subject RIV: BB - Applied Statistics, Operational Research http://library.utia.cas.cz/separaty/2010/SI/timkova-bernstein - von mises theorem and its application in survival analysis.pdf

Breast cancer data analysis for survivability studies and prediction.

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Shukla, Nagesh; Hagenbuchner, Markus; Win, Khin Than; Yang, Jack

2018-03-01

Breast cancer is the most common cancer affecting females worldwide. Breast cancer survivability prediction is challenging and a complex research task. Existing approaches engage statistical methods or supervised machine learning to assess/predict the survival prospects of patients. The main objectives of this paper is to develop a robust data analytical model which can assist in (i) a better understanding of breast cancer survivability in presence of missing data, (ii) providing better insights into factors associated with patient survivability, and (iii) establishing cohorts of patients that share similar properties. Unsupervised data mining methods viz. the self-organising map (SOM) and density-based spatial clustering of applications with noise (DBSCAN) is used to create patient cohort clusters. These clusters, with associated patterns, were used to train multilayer perceptron (MLP) model for improved patient survivability analysis. A large dataset available from SEER program is used in this study to identify patterns associated with the survivability of breast cancer patients. Information gain was computed for the purpose of variable selection. All of these methods are data-driven and require little (if any) input from users or experts. SOM consolidated patients into cohorts of patients with similar properties. From this, DBSCAN identified and extracted nine cohorts (clusters). It is found that patients in each of the nine clusters have different survivability time. The separation of patients into clusters improved the overall survival prediction accuracy based on MLP and revealed intricate conditions that affect the accuracy of a prediction. A new, entirely data driven approach based on unsupervised learning methods improves understanding and helps identify patterns associated with the survivability of patient. The results of the analysis can be used to segment the historical patient data into clusters or subsets, which share common variable values and

Re-analysis of survival data of cancer patients utilizing additive homeopathy.

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Gleiss, Andreas; Frass, Michael; Gaertner, Katharina

2016-08-01

In this short communication we present a re-analysis of homeopathic patient data in comparison to control patient data from the same Outpatient´s Unit "Homeopathy in malignant diseases" of the Medical University of Vienna. In this analysis we took account of a probable immortal time bias. For patients suffering from advanced stages of cancer and surviving the first 6 or 12 months after diagnosis, respectively, the results show that utilizing homeopathy gives a statistically significant (p<0.001) advantage over control patients regarding survival time. In conclusion, bearing in mind all limitations, the results of this retrospective study suggest that patients with advanced stages of cancer might benefit from additional homeopathic treatment until a survival time of up to 12 months after diagnosis. Copyright © 2016 Elsevier Ltd. All rights reserved.

Outcome predictors in the management of intramedullary classic ependymoma: An integrative survival analysis.

Science.gov (United States)

Wang, Yinqing; Cai, Ranze; Wang, Rui; Wang, Chunhua; Chen, Chunmei

2018-06-01

This is a retrospective study.The aim of this study was to illustrate the survival outcomes of patients with classic ependymoma (CE) and identify potential prognostic factors.CE is the most common category of spinal ependymomas, but few published studies have discussed predictors of the survival outcome.A Boolean search of the PubMed, Embase, and OVID databases was conducted by 2 investigators independently. The objects were intramedullary grade II ependymoma according to 2007 WHO classification. Univariate Kaplan-Meier analysis and Log-Rank tests were performed to identify variables associated with progression-free survival (PFS) or overall survival (OS). Multivariate Cox regression was performed to assess hazard ratios (HRs) with 95% confidence intervals (95% CIs). Statistical analysis was performed by SPSS version 23.0 (IBM Corp.) with statistical significance defined as P analysis showed that patients who had undergone total resection (TR) had better PFS and OS than those with subtotal resection (STR) and biopsy (P = .002, P = .004, respectively). Within either univariate or multivariate analysis (P = .000, P = .07, respectively), histological type was an independent prognostic factor for PFS of CE [papillary type: HR 0.002, 95% CI (0.000-0.073), P = .001, tanycytic type: HR 0.010, 95% CI (0.000-0.218), P = .003].It was the first integrative analysis of CE to elucidate the correlation between kinds of factors and prognostic outcomes. Definite histological type and safely TR were foundation of CE's management. 4.

Application of survival analysis methodology to the quantitative analysis of LC-MS proteomics data

KAUST Repository

Tekwe, C. D.

2012-05-24

MOTIVATION: Protein abundance in quantitative proteomics is often based on observed spectral features derived from liquid chromatography mass spectrometry (LC-MS) or LC-MS/MS experiments. Peak intensities are largely non-normal in distribution. Furthermore, LC-MS-based proteomics data frequently have large proportions of missing peak intensities due to censoring mechanisms on low-abundance spectral features. Recognizing that the observed peak intensities detected with the LC-MS method are all positive, skewed and often left-censored, we propose using survival methodology to carry out differential expression analysis of proteins. Various standard statistical techniques including non-parametric tests such as the Kolmogorov-Smirnov and Wilcoxon-Mann-Whitney rank sum tests, and the parametric survival model and accelerated failure time-model with log-normal, log-logistic and Weibull distributions were used to detect any differentially expressed proteins. The statistical operating characteristics of each method are explored using both real and simulated datasets. RESULTS: Survival methods generally have greater statistical power than standard differential expression methods when the proportion of missing protein level data is 5% or more. In particular, the AFT models we consider consistently achieve greater statistical power than standard testing procedures, with the discrepancy widening with increasing missingness in the proportions. AVAILABILITY: The testing procedures discussed in this article can all be performed using readily available software such as R. The R codes are provided as supplemental materials. CONTACT: ctekwe@stat.tamu.edu.

On Statistical Analysis of Competing Risks with Application to the Time of First Goal

Czech Academy of Sciences Publication Activity Database

Volf, Petr

2016-01-01

Roč. 2, č. 10 (2016), s. 606-623, č. článku 2. ISSN 2411-2518 R&D Projects: GA ČR GA13-14445S Institutional support: RVO:67985556 Keywords : survival analysis * competing risks * sports statistics Subject RIV: BB - Applied Statistics, Operational Research http://library.utia.cas.cz/separaty/2016/SI/volf-0466157.pdf

Evaluating disease management program effectiveness: an introduction to survival analysis.

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Linden, Ariel; Adams, John L; Roberts, Nancy

2004-01-01

Currently, the most widely used method in the disease management industry for evaluating program effectiveness is the "total population approach." This model is a pretest-posttest design, with the most basic limitation being that without a control group, there may be sources of bias and/or competing extraneous confounding factors that offer plausible rationale explaining the change from baseline. Survival analysis allows for the inclusion of data from censored cases, those subjects who either "survived" the program without experiencing the event (e.g., achievement of target clinical levels, hospitalization) or left the program prematurely, due to disenrollement from the health plan or program, or were lost to follow-up. Additionally, independent variables may be included in the model to help explain the variability in the outcome measure. In order to maximize the potential of this statistical method, validity of the model and research design must be assured. This paper reviews survival analysis as an alternative, and more appropriate, approach to evaluating DM program effectiveness than the current total population approach.

Statistical study of clone survival curves after irradiation in one or two stages. Comparison and generalization of different models

International Nuclear Information System (INIS)

Lachet, Bernard.

1975-01-01

A statistical study was carried out on 208 survival curves for chlorella subjected to γ or particle radiations. The computing programmes used were written in Fortran. The different experimental causes contributing to the variance of a survival rate are analyzed and consequently the experiments can be planned. Each curve was fitted to four models by the weighted least squares method applied to non-linear functions. The validity of the fits obtained can be checked by the F test. It was possible to define the confidence and prediction zones around an adjusted curve by weighting of the residual variance, in spite of error on the doses delivered; the confidence limits can them be fixed for a dose estimated from an exact or measured survival. The four models adopted were compared for the precision of their fit (by a non-parametric simultaneous comparison test) and the scattering of their adjusted parameters: Wideroe's model gives a very good fit with the experimental points in return for a scattering of its parameters, which robs them of their presumed meaning. The principal component analysis showed the statistical equivalence of the 1 and 2 hit target models. Division of the irradiation into two doses, the first fixed by the investigator, leads to families of curves for which the equation was established from that of any basic model expressing the dose survival relationship in one-stage irradiation [fr

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.

Revealing the equivalence of two clonal survival models by principal component analysis

International Nuclear Information System (INIS)

Lachet, Bernard; Dufour, Jacques

1976-01-01

The principal component analysis of 21 chlorella cell survival curves, adjusted by one-hit and two-hit target models, lead to quite similar projections on the principal plan: the homologous parameters of these models are linearly correlated; the reason for the statistical equivalence of these two models, in the present state of experimental inaccuracy, is revealed [fr

Meta-analysis of single-arm survival studies: a distribution-free approach for estimating summary survival curves with random effects.

Science.gov (United States)

Combescure, Christophe; Foucher, Yohann; Jackson, Daniel

2014-07-10

In epidemiologic studies and clinical trials with time-dependent outcome (for instance death or disease progression), survival curves are used to describe the risk of the event over time. In meta-analyses of studies reporting a survival curve, the most informative finding is a summary survival curve. In this paper, we propose a method to obtain a distribution-free summary survival curve by expanding the product-limit estimator of survival for aggregated survival data. The extension of DerSimonian and Laird's methodology for multiple outcomes is applied to account for the between-study heterogeneity. Statistics I(2)  and H(2) are used to quantify the impact of the heterogeneity in the published survival curves. A statistical test for between-strata comparison is proposed, with the aim to explore study-level factors potentially associated with survival. The performance of the proposed approach is evaluated in a simulation study. Our approach is also applied to synthesize the survival of untreated patients with hepatocellular carcinoma from aggregate data of 27 studies and synthesize the graft survival of kidney transplant recipients from individual data from six hospitals. Copyright © 2014 John Wiley & Sons, Ltd.

Survival after radiotherapy in gastric cancer: Systematic review and meta-analysis

International Nuclear Information System (INIS)

Valentini, Vincenzo; Cellini, Francesco; Minsky, Bruce D.; Mattiucci, Gian Carlo; Balducci, Mario; D'Agostino, Giuseppe; D'Angelo, Elisa; Dinapoli, Nicola; Nicolotti, Nicola; Valentini, Chiara; La Torre, Giuseppe

2009-01-01

Background and purpose: A systematic review and meta-analysis was performed to assess the impact of radiotherapy on both 3- and 5-year survival in patients with resectable gastric cancer. Methods: Randomized Clinical Trials (RCTs) in which radiotherapy, (preoperative, postoperative and/or intraoperative), was compared with surgery alone or surgery plus chemotherapy in resectable gastric cancer were identified by searching web-based databases and supplemented by manual examination of reference lists. Meta-analysis was performed using Risk Ratios (RRs). Random or fixed effects models were used to combine data. The methodological quality was evaluated by Chalmers' score. Results: Radiotherapy had a significant impact on 5-year survival. Using an intent to treat (ITT) and a Per Protocol (PP) analysis, the overall 5-year RR was 1.26 (95% CI: 1.08-1.48; NNT = 17) and 1.31 (95% CI: 1.04-1.66; NNT = 13), respectively. Although the quality of the studies was variable, the data were consistent and no clear publication bias was found. Conclusion: This meta-analysis showed a statistically significant 5-year survival benefit with the addition of radiotherapy in patients with resectable gastric cancer. Radiotherapy remains a standard component in the treatment of resectable gastric cancer and new RCTs need to address the impact of new conformal radiotherapy technologies.

Limitations of Using Microsoft Excel Version 2016 (MS Excel 2016) for Statistical Analysis for Medical Research.

Science.gov (United States)

Tanavalee, Chotetawan; Luksanapruksa, Panya; Singhatanadgige, Weerasak

2016-06-01

Microsoft Excel (MS Excel) is a commonly used program for data collection and statistical analysis in biomedical research. However, this program has many limitations, including fewer functions that can be used for analysis and a limited number of total cells compared with dedicated statistical programs. MS Excel cannot complete analyses with blank cells, and cells must be selected manually for analysis. In addition, it requires multiple steps of data transformation and formulas to plot survival analysis graphs, among others. The Megastat add-on program, which will be supported by MS Excel 2016 soon, would eliminate some limitations of using statistic formulas within MS Excel.

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)

Covariate analysis of bivariate survival data

Energy Technology Data Exchange (ETDEWEB)

Bennett, L.E.

1992-01-01

The methods developed are used to analyze the effects of covariates on bivariate survival data when censoring and ties are present. The proposed method provides models for bivariate survival data that include differential covariate effects and censored observations. The proposed models are based on an extension of the univariate Buckley-James estimators which replace censored data points by their expected values, conditional on the censoring time and the covariates. For the bivariate situation, it is necessary to determine the expectation of the failure times for one component conditional on the failure or censoring time of the other component. Two different methods have been developed to estimate these expectations. In the semiparametric approach these expectations are determined from a modification of Burke's estimate of the bivariate empirical survival function. In the parametric approach censored data points are also replaced by their conditional expected values where the expected values are determined from a specified parametric distribution. The model estimation will be based on the revised data set, comprised of uncensored components and expected values for the censored components. The variance-covariance matrix for the estimated covariate parameters has also been derived for both the semiparametric and parametric methods. Data from the Demographic and Health Survey was analyzed by these methods. The two outcome variables are post-partum amenorrhea and breastfeeding; education and parity were used as the covariates. Both the covariate parameter estimates and the variance-covariance estimates for the semiparametric and parametric models will be compared. In addition, a multivariate test statistic was used in the semiparametric model to examine contrasts. The significance of the statistic was determined from a bootstrap distribution of the test statistic.

Statistical data analysis using SAS intermediate statistical methods

CERN Document Server

Marasinghe, Mervyn G

2018-01-01

The aim of this textbook (previously titled SAS for Data Analytics) is to teach the use of SAS for statistical analysis of data for advanced undergraduate and graduate students in statistics, data science, and disciplines involving analyzing data. The book begins with an introduction beyond the basics of SAS, illustrated with non-trivial, real-world, worked examples. It proceeds to SAS programming and applications, SAS graphics, statistical analysis of regression models, analysis of variance models, analysis of variance with random and mixed effects models, and then takes the discussion beyond regression and analysis of variance to conclude. Pedagogically, the authors introduce theory and methodological basis topic by topic, present a problem as an application, followed by a SAS analysis of the data provided and a discussion of results. The text focuses on applied statistical problems and methods. Key features include: end of chapter exercises, downloadable SAS code and data sets, and advanced material suitab...

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

Introduction to SURPH.1 analysis of release-recapture data for survival studies

International Nuclear Information System (INIS)

Smith, S.G.; Skalski, J.R.; Schlechte, J.W.; Hoffmann, A.; Cassen, V.

1994-12-01

Program SURPH is the culmination of several years of research to develop a comprehensive computer program to analyze survival studies of fish and wildlife populations. Development of this software was motivated by the advent of the PIT-tag (Passive Integrated Transponder) technology that permits the detection of salmonid smolt as they pass through hydroelectric facilities on the Snake and Columbia Rivers in the Pacific Northwest. Repeated detections of individually tagged smolt and analysis of their capture-histories permits estimates of downriver survival probabilities. Eventual installation of detection facilities at adult fish ladders will also permit estimation of ocean survival and upstream survival of returning salmon using the statistical methods incorporated in SURPH.1. However, the utility of SURPH.1 far exceeds solely the analysis of salmonid tagging studies. Release-recapture and radiotelemetry studies from a wide range of terrestrial and aquatic species have been analyzed using SURPH.1 to estimate discrete time survival probabilities and investigate survival relationships. The interactive computing environment of SURPH.1 was specifically developed to allow researchers to investigate the relationship between survival and capture processes and environmental, experimental and individual-based covariates. Program SURPH.1 represents a significant advancement in the ability of ecologists to investigate the interplay between morphologic, genetic, environmental and anthropogenic factors on the survival of wild species. It is hoped that this better understanding of risk factors affecting survival will lead to greater appreciation of the intricacies of nature and to improvements in the management of wild resources. This technical report is an introduction to SURPH.1 and provides a user guide for both the UNIX and MS-Windows reg-sign applications of the SURPH software

Survival analysis of colorectal cancer patients with tumor recurrence using global score test methodology

Energy Technology Data Exchange (ETDEWEB)

Zain, Zakiyah, E-mail: zac@uum.edu.my; Ahmad, Yuhaniz, E-mail: yuhaniz@uum.edu.my [School of Quantitative Sciences, Universiti Utara Malaysia, UUM Sintok 06010, Kedah (Malaysia); Azwan, Zairul, E-mail: zairulazwan@gmail.com, E-mail: farhanaraduan@gmail.com, E-mail: drisagap@yahoo.com; Raduan, Farhana, E-mail: zairulazwan@gmail.com, E-mail: farhanaraduan@gmail.com, E-mail: drisagap@yahoo.com; Sagap, Ismail, E-mail: zairulazwan@gmail.com, E-mail: farhanaraduan@gmail.com, E-mail: drisagap@yahoo.com [Surgery Department, Universiti Kebangsaan Malaysia Medical Centre, Jalan Yaacob Latif, 56000 Bandar Tun Razak, Kuala Lumpur (Malaysia); Aziz, Nazrina, E-mail: nazrina@uum.edu.my

2014-12-04

Colorectal cancer is the third and the second most common cancer worldwide in men and women respectively, and the second in Malaysia for both genders. Surgery, chemotherapy and radiotherapy are among the options available for treatment of patients with colorectal cancer. In clinical trials, the main purpose is often to compare efficacy between experimental and control treatments. Treatment comparisons often involve several responses or endpoints, and this situation complicates the analysis. In the case of colorectal cancer, sets of responses concerned with survival times include: times from tumor removal until the first, the second and the third tumor recurrences, and time to death. For a patient, the time to recurrence is correlated to the overall survival. In this study, global score test methodology is used in combining the univariate score statistics for comparing treatments with respect to each survival endpoint into a single statistic. The data of tumor recurrence and overall survival of colorectal cancer patients are taken from a Malaysian hospital. The results are found to be similar to those computed using the established Wei, Lin and Weissfeld method. Key factors such as ethnic, gender, age and stage at diagnose are also reported.

Statistical Models and Methods for Lifetime Data

CERN Document Server

Lawless, Jerald F

2011-01-01

Praise for the First Edition"An indispensable addition to any serious collection on lifetime data analysis and . . . a valuable contribution to the statistical literature. Highly recommended . . ."-Choice"This is an important book, which will appeal to statisticians working on survival analysis problems."-Biometrics"A thorough, unified treatment of statistical models and methods used in the analysis of lifetime data . . . this is a highly competent and agreeable statistical textbook."-Statistics in MedicineThe statistical analysis of lifetime or response time data is a key tool in engineering,

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

Two-stage meta-analysis of survival data from individual participants using percentile ratios

Science.gov (United States)

Barrett, Jessica K; Farewell, Vern T; Siannis, Fotios; Tierney, Jayne; Higgins, Julian P T

2012-01-01

Methods for individual participant data meta-analysis of survival outcomes commonly focus on the hazard ratio as a measure of treatment effect. Recently, Siannis et al. (2010, Statistics in Medicine 29:3030–3045) proposed the use of percentile ratios as an alternative to hazard ratios. We describe a novel two-stage method for the meta-analysis of percentile ratios that avoids distributional assumptions at the study level. Copyright © 2012 John Wiley & Sons, Ltd. PMID:22825835

Survival Analysis and its Associated Factors of Beta Thalassemia Major in Hamadan Province

Directory of Open Access Journals (Sweden)

Reza Zamani

2015-05-01

Full Text Available Background: There currently is a lack of knowledge about the long-term survival of patients with beta thalassemia (BT, particularly in regions with low incidence of the disease. The aim of the present study was to determine the survival rate of the patients with BT major and the factors associated with the survival time. Methods: This retrospective cohort study was performed in Hamadan province, located in the west of Iran. The study included patients that referred to the provincial hospitals during 16 year period from 1997 to 2013. The follow up of each subject was calculated from the date of birth to the date of death. Demographic and clinical data were extracted from patients’ medical records using a checklist. Statistical analysis included the Kaplan-Meier method to analyze survivals, log-rank to compare curves between groups, and Cox regression for multivariate prognostic analysis. Results: A total of 133 patients with BT major were enrolled, 54.9% of whom were male and 66.2% were urban. The 10-, 20- and 30-year survival rate for all patients were 98.3%, 88.4% and 80.5%, respectively. Based on hazard ratio (HR, we found that accompanied diseases (P=0.01, blood type (P=0.03 and residency status (P=0.01 were significant predictors for the survival time of patients. Conclusion: The survival rate of BT patients has improved. Future researches such as prospective designs are required for the estimation of survival rate and to find other prognostic factors, which have reliable sources of data.

KMWin--a convenient tool for graphical presentation of results from Kaplan-Meier survival time analysis.

Science.gov (United States)

Gross, Arnd; Ziepert, Marita; Scholz, Markus

2012-01-01

Analysis of clinical studies often necessitates multiple graphical representations of the results. Many professional software packages are available for this purpose. Most packages are either only commercially available or hard to use especially if one aims to generate or customize a huge number of similar graphical outputs. We developed a new, freely available software tool called KMWin (Kaplan-Meier for Windows) facilitating Kaplan-Meier survival time analysis. KMWin is based on the statistical software environment R and provides an easy to use graphical interface. Survival time data can be supplied as SPSS (sav), SAS export (xpt) or text file (dat), which is also a common export format of other applications such as Excel. Figures can directly be exported in any graphical file format supported by R. On the basis of a working example, we demonstrate how to use KMWin and present its main functions. We show how to control the interface, customize the graphical output, and analyse survival time data. A number of comparisons are performed between KMWin and SPSS regarding graphical output, statistical output, data management and development. Although the general functionality of SPSS is larger, KMWin comprises a number of features useful for survival time analysis in clinical trials and other applications. These are for example number of cases and number of cases under risk within the figure or provision of a queue system for repetitive analyses of updated data sets. Moreover, major adjustments of graphical settings can be performed easily on a single window. We conclude that our tool is well suited and convenient for repetitive analyses of survival time data. It can be used by non-statisticians and provides often used functions as well as functions which are not supplied by standard software packages. The software is routinely applied in several clinical study groups.

KMWin--a convenient tool for graphical presentation of results from Kaplan-Meier survival time analysis.

Directory of Open Access Journals (Sweden)

Arnd Gross

Full Text Available BACKGROUND: Analysis of clinical studies often necessitates multiple graphical representations of the results. Many professional software packages are available for this purpose. Most packages are either only commercially available or hard to use especially if one aims to generate or customize a huge number of similar graphical outputs. We developed a new, freely available software tool called KMWin (Kaplan-Meier for Windows facilitating Kaplan-Meier survival time analysis. KMWin is based on the statistical software environment R and provides an easy to use graphical interface. Survival time data can be supplied as SPSS (sav, SAS export (xpt or text file (dat, which is also a common export format of other applications such as Excel. Figures can directly be exported in any graphical file format supported by R. RESULTS: On the basis of a working example, we demonstrate how to use KMWin and present its main functions. We show how to control the interface, customize the graphical output, and analyse survival time data. A number of comparisons are performed between KMWin and SPSS regarding graphical output, statistical output, data management and development. Although the general functionality of SPSS is larger, KMWin comprises a number of features useful for survival time analysis in clinical trials and other applications. These are for example number of cases and number of cases under risk within the figure or provision of a queue system for repetitive analyses of updated data sets. Moreover, major adjustments of graphical settings can be performed easily on a single window. CONCLUSIONS: We conclude that our tool is well suited and convenient for repetitive analyses of survival time data. It can be used by non-statisticians and provides often used functions as well as functions which are not supplied by standard software packages. The software is routinely applied in several clinical study groups.

Applied Statistics Using SPSS, STATISTICA, MATLAB and R

CERN Document Server

De Sá, Joaquim P Marques

2007-01-01

This practical reference provides a comprehensive introduction and tutorial on the main statistical analysis topics, demonstrating their solution with the most common software package. Intended for anyone needing to apply statistical analysis to a large variety of science and enigineering problems, the book explains and shows how to use SPSS, MATLAB, STATISTICA and R for analysis such as data description, statistical inference, classification and regression, factor analysis, survival data and directional statistics. It concisely explains key concepts and methods, illustrated by practical examp

KMWin – A Convenient Tool for Graphical Presentation of Results from Kaplan-Meier Survival Time Analysis

Science.gov (United States)

Gross, Arnd; Ziepert, Marita; Scholz, Markus

2012-01-01

Background Analysis of clinical studies often necessitates multiple graphical representations of the results. Many professional software packages are available for this purpose. Most packages are either only commercially available or hard to use especially if one aims to generate or customize a huge number of similar graphical outputs. We developed a new, freely available software tool called KMWin (Kaplan-Meier for Windows) facilitating Kaplan-Meier survival time analysis. KMWin is based on the statistical software environment R and provides an easy to use graphical interface. Survival time data can be supplied as SPSS (sav), SAS export (xpt) or text file (dat), which is also a common export format of other applications such as Excel. Figures can directly be exported in any graphical file format supported by R. Results On the basis of a working example, we demonstrate how to use KMWin and present its main functions. We show how to control the interface, customize the graphical output, and analyse survival time data. A number of comparisons are performed between KMWin and SPSS regarding graphical output, statistical output, data management and development. Although the general functionality of SPSS is larger, KMWin comprises a number of features useful for survival time analysis in clinical trials and other applications. These are for example number of cases and number of cases under risk within the figure or provision of a queue system for repetitive analyses of updated data sets. Moreover, major adjustments of graphical settings can be performed easily on a single window. Conclusions We conclude that our tool is well suited and convenient for repetitive analyses of survival time data. It can be used by non-statisticians and provides often used functions as well as functions which are not supplied by standard software packages. The software is routinely applied in several clinical study groups. PMID:22723912

Understanding Statistics - Cancer Statistics

Science.gov (United States)

Annual reports of U.S. cancer statistics including new cases, deaths, trends, survival, prevalence, lifetime risk, and progress toward Healthy People targets, plus statistical summaries for a number of common cancer types.

Beginning statistics with data analysis

CERN Document Server

Mosteller, Frederick; Rourke, Robert EK

2013-01-01

This introduction to the world of statistics covers exploratory data analysis, methods for collecting data, formal statistical inference, and techniques of regression and analysis of variance. 1983 edition.

Statistical modelling in biostatistics and bioinformatics selected papers

CERN Document Server

Peng, Defen

2014-01-01

This book presents selected papers on statistical model development related mainly to the fields of Biostatistics and Bioinformatics. The coverage of the material falls squarely into the following categories: (a) Survival analysis and multivariate survival analysis, (b) Time series and longitudinal data analysis, (c) Statistical model development and (d) Applied statistical modelling. Innovations in statistical modelling are presented throughout each of the four areas, with some intriguing new ideas on hierarchical generalized non-linear models and on frailty models with structural dispersion, just to mention two examples. The contributors include distinguished international statisticians such as Philip Hougaard, John Hinde, Il Do Ha, Roger Payne and Alessandra Durio, among others, as well as promising newcomers. Some of the contributions have come from researchers working in the BIO-SI research programme on Biostatistics and Bioinformatics, centred on the Universities of Limerick and Galway in Ireland and fu...

Research design and statistical analysis

CERN Document Server

Myers, Jerome L; Lorch Jr, Robert F

2013-01-01

Research Design and Statistical Analysis provides comprehensive coverage of the design principles and statistical concepts necessary to make sense of real data.  The book's goal is to provide a strong conceptual foundation to enable readers to generalize concepts to new research situations.  Emphasis is placed on the underlying logic and assumptions of the analysis and what it tells the researcher, the limitations of the analysis, and the consequences of violating assumptions.  Sampling, design efficiency, and statistical models are emphasized throughout. As per APA recommendations

Advanced statistical methods in data science

CERN Document Server

Chen, Jiahua; Lu, Xuewen; Yi, Grace; Yu, Hao

2016-01-01

This book gathers invited presentations from the 2nd Symposium of the ICSA- CANADA Chapter held at the University of Calgary from August 4-6, 2015. The aim of this Symposium was to promote advanced statistical methods in big-data sciences and to allow researchers to exchange ideas on statistics and data science and to embraces the challenges and opportunities of statistics and data science in the modern world. It addresses diverse themes in advanced statistical analysis in big-data sciences, including methods for administrative data analysis, survival data analysis, missing data analysis, high-dimensional and genetic data analysis, longitudinal and functional data analysis, the design and analysis of studies with response-dependent and multi-phase designs, time series and robust statistics, statistical inference based on likelihood, empirical likelihood and estimating functions. The editorial group selected 14 high-quality presentations from this successful symposium and invited the presenters to prepare a fu...

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/.

Statistical modelling of survival data with random effects h-likelihood approach

CERN Document Server

Ha, Il Do; Lee, Youngjo

2017-01-01

This book provides a groundbreaking introduction to the likelihood inference for correlated survival data via the hierarchical (or h-) likelihood in order to obtain the (marginal) likelihood and to address the computational difficulties in inferences and extensions. The approach presented in the book overcomes shortcomings in the traditional likelihood-based methods for clustered survival data such as intractable integration. The text includes technical materials such as derivations and proofs in each chapter, as well as recently developed software programs in R (“frailtyHL”), while the real-world data examples together with an R package, “frailtyHL” in CRAN, provide readers with useful hands-on tools. Reviewing new developments since the introduction of the h-likelihood to survival analysis (methods for interval estimation of the individual frailty and for variable selection of the fixed effects in the general class of frailty models) and guiding future directions, the book is of interest to research...

[Analysis of clinicopathologic and survival characteristics in patients with right-or left-sided colon cancer].

Science.gov (United States)

Hu, Junjie; Zhou, Zhixiang; Liang, Jianwei; Zhou, Haitao; Wang, Zheng; Zhang, Xingmao; Zeng, Weigen

2015-07-28

This study aimed to clarify the clinical and histological parameters, and survival difference between right- and left-sided colon cancer. We retrospectively analyzed the medical records (2006.1-2009.12) of 1 088 consecutive colon cancer patients who received surgery at our hospital. Right- and left-sided colon cancers were compared regarding the clinical and histological parameters. The survival analysis was performed by the Kaplan-Meier method, and the log-rank test was used to determine the statistical significance of differences. Right-sided colon cancer was associated with older age, a more advanced state, and poorly differentiated and undifferentiated adenocarcinoma (25.2% vs 13.2%), mucinous adenocarcinoma (33.5% vs 17.3%) and vascular invasion (9.9% vs 3.9%) were more commonly seen in right-sided colon cancer compared with right-sided colon cancer, and all these differences were statistically significant. Median overall survival was right, 67 months; and left, 68 months. The five-years overall survival of right- and left-sided colon cancer was I/II stage, 91.4% vs 88.6% (P = 0.819); III stage, 66.1% vs 75.4% (P = 0.010); and IV stage, 27.8% vs 38.5% (P = 0.020) respectively. Right- and left-sided colon cancers are significantly different regarding clinical and histological parameters. Right-sided colon cancers in stage III and IV have a worse prognosis.

The statistical treatment of cell survival data

International Nuclear Information System (INIS)

Boag, J.W.

1975-01-01

The paper considers the sources of experimental error in cell survival experiments and discusses in simple terms how these combine to influence the accuracy of single points and the parameters of complete survival curves. Cell sampling and medium-dilution errors are discussed at length and one way of minimizing the former is examined. The Monte-Carlo method of estimating the distribution of derived parameters in small samples is recommended and illustrated. (author)

Statistical data analysis handbook

National Research Council Canada - National Science Library

Wall, Francis J

1986-01-01

It must be emphasized that this is not a text book on statistics. Instead it is a working tool that presents data analysis in clear, concise terms which can be readily understood even by those without formal training in statistics...

Mechanisms and mediation in survival analysis: towards an integrated analytical framework

Directory of Open Access Journals (Sweden)

Jonathan Pratschke

2016-02-01

Full Text Available Abstract Background A wide-ranging debate has taken place in recent years on mediation analysis and causal modelling, raising profound theoretical, philosophical and methodological questions. The authors build on the results of these discussions to work towards an integrated approach to the analysis of research questions that situate survival outcomes in relation to complex causal pathways with multiple mediators. The background to this contribution is the increasingly urgent need for policy-relevant research on the nature of inequalities in health and healthcare. Methods The authors begin by summarising debates on causal inference, mediated effects and statistical models, showing that these three strands of research have powerful synergies. They review a range of approaches which seek to extend existing survival models to obtain valid estimates of mediation effects. They then argue for an alternative strategy, which involves integrating survival outcomes within Structural Equation Models via the discrete-time survival model. This approach can provide an integrated framework for studying mediation effects in relation to survival outcomes, an issue of great relevance in applied health research. The authors provide an example of how these techniques can be used to explore whether the social class position of patients has a significant indirect effect on the hazard of death from colon cancer. Results The results suggest that the indirect effects of social class on survival are substantial and negative (-0.23 overall. In addition to the substantial direct effect of this variable (-0.60, its indirect effects account for more than one quarter of the total effect. The two main pathways for this indirect effect, via emergency admission (-0.12, on the one hand, and hospital caseload, on the other, (-0.10 are of similar size. Conclusions The discrete-time survival model provides an attractive way of integrating time-to-event data within the field of

Mechanisms and mediation in survival analysis: towards an integrated analytical framework.

Science.gov (United States)

Pratschke, Jonathan; Haase, Trutz; Comber, Harry; Sharp, Linda; de Camargo Cancela, Marianna; Johnson, Howard

2016-02-29

A wide-ranging debate has taken place in recent years on mediation analysis and causal modelling, raising profound theoretical, philosophical and methodological questions. The authors build on the results of these discussions to work towards an integrated approach to the analysis of research questions that situate survival outcomes in relation to complex causal pathways with multiple mediators. The background to this contribution is the increasingly urgent need for policy-relevant research on the nature of inequalities in health and healthcare. The authors begin by summarising debates on causal inference, mediated effects and statistical models, showing that these three strands of research have powerful synergies. They review a range of approaches which seek to extend existing survival models to obtain valid estimates of mediation effects. They then argue for an alternative strategy, which involves integrating survival outcomes within Structural Equation Models via the discrete-time survival model. This approach can provide an integrated framework for studying mediation effects in relation to survival outcomes, an issue of great relevance in applied health research. The authors provide an example of how these techniques can be used to explore whether the social class position of patients has a significant indirect effect on the hazard of death from colon cancer. The results suggest that the indirect effects of social class on survival are substantial and negative (-0.23 overall). In addition to the substantial direct effect of this variable (-0.60), its indirect effects account for more than one quarter of the total effect. The two main pathways for this indirect effect, via emergency admission (-0.12), on the one hand, and hospital caseload, on the other, (-0.10) are of similar size. The discrete-time survival model provides an attractive way of integrating time-to-event data within the field of Structural Equation Modelling. The authors demonstrate the efficacy

Cost-effectiveness Analysis in R Using a Multi-state Modeling Survival Analysis Framework: A Tutorial.

Science.gov (United States)

Williams, Claire; Lewsey, James D; Briggs, Andrew H; Mackay, Daniel F

2017-05-01

This tutorial provides a step-by-step guide to performing cost-effectiveness analysis using a multi-state modeling approach. Alongside the tutorial, we provide easy-to-use functions in the statistics package R. We argue that this multi-state modeling approach using a package such as R has advantages over approaches where models are built in a spreadsheet package. In particular, using a syntax-based approach means there is a written record of what was done and the calculations are transparent. Reproducing the analysis is straightforward as the syntax just needs to be run again. The approach can be thought of as an alternative way to build a Markov decision-analytic model, which also has the option to use a state-arrival extended approach. In the state-arrival extended multi-state model, a covariate that represents patients' history is included, allowing the Markov property to be tested. We illustrate the building of multi-state survival models, making predictions from the models and assessing fits. We then proceed to perform a cost-effectiveness analysis, including deterministic and probabilistic sensitivity analyses. Finally, we show how to create 2 common methods of visualizing the results-namely, cost-effectiveness planes and cost-effectiveness acceptability curves. The analysis is implemented entirely within R. It is based on adaptions to functions in the existing R package mstate to accommodate parametric multi-state modeling that facilitates extrapolation of survival curves.

Two-Sample Statistics for Testing the Equality of Survival Functions Against Improper Semi-parametric Accelerated Failure Time Alternatives: An Application to the Analysis of a Breast Cancer Clinical Trial

Science.gov (United States)

BROËT, PHILIPPE; TSODIKOV, ALEXANDER; DE RYCKE, YANN; MOREAU, THIERRY

2010-01-01

This paper presents two-sample statistics suited for testing equality of survival functions against improper semi-parametric accelerated failure time alternatives. These tests are designed for comparing either the short- or the long-term effect of a prognostic factor, or both. These statistics are obtained as partial likelihood score statistics from a time-dependent Cox model. As a consequence, the proposed tests can be very easily implemented using widely available software. A breast cancer clinical trial is presented as an example to demonstrate the utility of the proposed tests. PMID:15293627

Two-sample statistics for testing the equality of survival functions against improper semi-parametric accelerated failure time alternatives: an application to the analysis of a breast cancer clinical trial.

Science.gov (United States)

Broët, Philippe; Tsodikov, Alexander; De Rycke, Yann; Moreau, Thierry

2004-06-01

This paper presents two-sample statistics suited for testing equality of survival functions against improper semi-parametric accelerated failure time alternatives. These tests are designed for comparing either the short- or the long-term effect of a prognostic factor, or both. These statistics are obtained as partial likelihood score statistics from a time-dependent Cox model. As a consequence, the proposed tests can be very easily implemented using widely available software. A breast cancer clinical trial is presented as an example to demonstrate the utility of the proposed tests.

Statistical Power in Meta-Analysis

Science.gov (United States)

Liu, Jin

2015-01-01

Statistical power is important in a meta-analysis study, although few studies have examined the performance of simulated power in meta-analysis. The purpose of this study is to inform researchers about statistical power estimation on two sample mean difference test under different situations: (1) the discrepancy between the analytical power and…

Statistical analysis of fatigue crack growth behavior for grade B cast steel

International Nuclear Information System (INIS)

Li, W.; Sakai, T.; Li, Q.; Wang, P.

2011-01-01

Tests for fatigue crack growth rate (FCGR) and crack-tip opening displacement (CTOD) were performed to clarify the fatigue crack growth behavior of a railway grade B cast steel. The threshold values of this steel with specific survival probabilities are evaluated, in which the mean value is 8.3516 MPa m 1/2 , very similar to the experimental value, about 8.7279 MPa m 1/2 . Under the conditions of plane strain and small-scale yielding, the values of fracture toughness for this steel with specific survival probabilities are converted from the corresponding critical CTOD values, in which the mean value is about 138.4256 MPa m 1/2 . In consideration of the inherent variability of crack growth rates, six statistical models are proposed to represent the probabilistic FCGR curves of this steel in entire crack propagation region from the viewpoints of statistical evaluation on the number of cycles at a given crack size and the crack growth rate at a given stress intensity factor range, stochastic characteristic of crack growth as well as statistical analysis of coefficient and exponent in FCGR power law equation. Based on the model adequacy checking, result shows that all models are basically in good agreement with test data. Although the probabilistic damage-tolerant design based on some models may involve a certain amount of risk in stable crack propagation region, they just accord with the fact that the dispersion degree of test data in this region is relatively smaller.

Attributing death to cancer: cause-specific survival estimation.

Directory of Open Access Journals (Sweden)

Mathew A

2002-10-01

Full Text Available Cancer survival estimation is an important part of assessing the overall strength of cancer care in a region. Generally, the death of a patient is taken as the end point in estimation of overall survival. When calculating the overall survival, the cause of death is not taken into account. With increasing demand for better survival of cancer patients it is important for clinicians and researchers to know about survival statistics due to disease of interest, i.e. net survival. It is also important to choose the best method for estimating net survival. Increase in the use of computer programmes has made it possible to carry out statistical analysis without guidance from a bio-statistician. This is of prime importance in third- world countries as there are a few trained bio-statisticians to guide clinicians and researchers. The present communication describes current methods used to estimate net survival such as cause-specific survival and relative survival. The limitation of estimation of cause-specific survival particularly in India and the usefulness of relative survival are discussed. The various sources for estimating cancer survival are also discussed. As survival-estimates are to be projected on to the population at large, it becomes important to measure the variation of the estimates, and thus confidence intervals are used. Rothman′s confidence interval gives the most satisfactory result for survival estimate.

Maternal Risk Factors for Singleton Preterm Births and Survival at ...

African Journals Online (AJOL)

Context: Risk factors for and survival of singleton preterm births may vary ... factors and survival‑to‑discharge rate for singleton preterm births at the University of ... Statistical analysis involved descriptive and inferential statistics at 95% level of ...

A survival analysis on critical components of nuclear power plants

International Nuclear Information System (INIS)

Durbec, V.; Pitner, P.; Riffard, T.

1995-06-01

Some tubes of heat exchangers of nuclear power plants may be affected by Primary Water Stress Corrosion Cracking (PWSCC) in highly stressed areas. These defects can shorten the lifetime of the component and lead to its replacement. In order to reduce the risk of cracking, a preventive remedial operation called shot peening was applied on the French reactors between 1985 and 1988. To assess and investigate the effects of shot peening, a statistical analysis was carried on the tube degradation results obtained from in service inspection that are regularly conducted using non destructive tests. The statistical method used is based on the Cox proportional hazards model, a powerful tool in the analysis of survival data, implemented in PROC PHRED recently available in SAS/STAT. This technique has a number of major advantages including the ability to deal with censored failure times data and with the complication of time-dependant co-variables. The paper focus on the modelling and a presentation of the results given by SAS. They provide estimate of how the relative risk of degradation changes after peening and indicate for which values of the prognostic factors analyzed the treatment is likely to be most beneficial. (authors). 2 refs., 3 figs., 6 tabs

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.

Rweb:Web-based Statistical Analysis

Directory of Open Access Journals (Sweden)

Jeff Banfield

1999-03-01

Full Text Available Rweb is a freely accessible statistical analysis environment that is delivered through the World Wide Web (WWW. It is based on R, a well known statistical analysis package. The only requirement to run the basic Rweb interface is a WWW browser that supports forms. If you want graphical output you must, of course, have a browser that supports graphics. The interface provides access to WWW accessible data sets, so you may run Rweb on your own data. Rweb can provide a four window statistical computing environment (code input, text output, graphical output, and error information through browsers that support Javascript. There is also a set of point and click modules under development for use in introductory statistics courses.

Regularized Statistical Analysis of Anatomy

DEFF Research Database (Denmark)

Sjöstrand, Karl

2007-01-01

This thesis presents the application and development of regularized methods for the statistical analysis of anatomical structures. Focus is on structure-function relationships in the human brain, such as the connection between early onset of Alzheimer’s disease and shape changes of the corpus...... and mind. Statistics represents a quintessential part of such investigations as they are preluded by a clinical hypothesis that must be verified based on observed data. The massive amounts of image data produced in each examination pose an important and interesting statistical challenge...... efficient algorithms which make the analysis of large data sets feasible, and gives examples of applications....

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

[Survival analysis with competing risks: estimating failure probability].

Science.gov (United States)

Llorca, Javier; Delgado-Rodríguez, Miguel

2004-01-01

To show the impact of competing risks of death on survival analysis. We provide an example of survival time without chronic rejection after heart transplantation, where death before rejection acts as a competing risk. Using a computer simulation, we compare the Kaplan-Meier estimator and the multiple decrement model. The Kaplan-Meier method overestimated the probability of rejection. Next, we illustrate the use of the multiple decrement model to analyze secondary end points (in our example: death after rejection). Finally, we discuss Kaplan-Meier assumptions and why they fail in the presence of competing risks. Survival analysis should be adjusted for competing risks of death to avoid overestimation of the risk of rejection produced with the Kaplan-Meier method.

12th Workshop on Stochastic Models, Statistics and Their Applications

CERN Document Server

Rafajłowicz, Ewaryst; Szajowski, Krzysztof

2015-01-01

This volume presents the latest advances and trends in stochastic models and related statistical procedures. Selected peer-reviewed contributions focus on statistical inference, quality control, change-point analysis and detection, empirical processes, time series analysis, survival analysis and reliability, statistics for stochastic processes, big data in technology and the sciences, statistical genetics, experiment design, and stochastic models in engineering. Stochastic models and related statistical procedures play an important part in furthering our understanding of the challenging problems currently arising in areas of application such as the natural sciences, information technology, engineering, image analysis, genetics, energy and finance, to name but a few. This collection arises from the 12th Workshop on Stochastic Models, Statistics and Their Applications, Wroclaw, Poland.

Direct Survival Analysis: a new stock assessment method

Directory of Open Access Journals (Sweden)

Eduardo Ferrandis

2007-03-01

Full Text Available In this work, a new stock assessment method, Direct Survival Analysis, is proposed and described. The parameter estimation of the Weibull survival model proposed by Ferrandis (2007 is obtained using trawl survey data. This estimation is used to establish a baseline survival function, which is in turn used to estimate the specific survival functions in the different cohorts considered through an adaptation of the separable model of the fishing mortality rates introduced by Pope and Shepherd (1982. It is thus possible to test hypotheses on the evolution of survival during the period studied and to identify trends in recruitment. A link is established between the preceding analysis of trawl survey data and the commercial catch-at-age data that are generally obtained to evaluate the population using analytical models. The estimated baseline survival, with the proposed versions of the stock and catch equations and the adaptation of the Separable Model, may be applied to commercial catch-at-age data. This makes it possible to estimate the survival corresponding to the landing data, the initial size of the cohort and finally, an effective age of first capture, in order to complete the parameter model estimation and consequently the estimation of the whole survival and mortality, along with the reference parameters that are useful for management purposes. Alternatively, this estimation of an effective age of first capture may be obtained by adapting the demographic structure of trawl survey data to that of the commercial fleet through suitable selectivity models of the commercial gears. The complete model provides the evaluation of the stock at any age. The coherence (and hence the mutual “calibration” between the two kinds of information may be analysed and compared with results obtained by other methods, such as virtual population analysis (VPA, in order to improve the diagnosis of the state of exploitation of the population. The model may be

Neyman, Markov processes and survival analysis.

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Yang, Grace

2013-07-01

J. Neyman used stochastic processes extensively in his applied work. One example is the Fix and Neyman (F-N) competing risks model (1951) that uses finite homogeneous Markov processes to analyse clinical trials with breast cancer patients. We revisit the F-N model, and compare it with the Kaplan-Meier (K-M) formulation for right censored data. The comparison offers a way to generalize the K-M formulation to include risks of recovery and relapses in the calculation of a patient's survival probability. The generalization is to extend the F-N model to a nonhomogeneous Markov process. Closed-form solutions of the survival probability are available in special cases of the nonhomogeneous processes, like the popular multiple decrement model (including the K-M model) and Chiang's staging model, but these models do not consider recovery and relapses while the F-N model does. An analysis of sero-epidemiology current status data with recurrent events is illustrated. Fix and Neyman used Neyman's RBAN (regular best asymptotic normal) estimates for the risks, and provided a numerical example showing the importance of considering both the survival probability and the length of time of a patient living a normal life in the evaluation of clinical trials. The said extension would result in a complicated model and it is unlikely to find analytical closed-form solutions for survival analysis. With ever increasing computing power, numerical methods offer a viable way of investigating the problem.

Statistical methods for astronomical data analysis

CERN Document Server

Chattopadhyay, Asis Kumar

2014-01-01

This book introduces “Astrostatistics” as a subject in its own right with rewarding examples, including work by the authors with galaxy and Gamma Ray Burst data to engage the reader. This includes a comprehensive blending of Astrophysics and Statistics. The first chapter’s coverage of preliminary concepts and terminologies for astronomical phenomenon will appeal to both Statistics and Astrophysics readers as helpful context. Statistics concepts covered in the book provide a methodological framework. A unique feature is the inclusion of different possible sources of astronomical data, as well as software packages for converting the raw data into appropriate forms for data analysis. Readers can then use the appropriate statistical packages for their particular data analysis needs. The ideas of statistical inference discussed in the book help readers determine how to apply statistical tests. The authors cover different applications of statistical techniques already developed or specifically introduced for ...

Statistical inference on residual life

CERN Document Server

Jeong, Jong-Hyeon

2014-01-01

This is a monograph on the concept of residual life, which is an alternative summary measure of time-to-event data, or survival data. The mean residual life has been used for many years under the name of life expectancy, so it is a natural concept for summarizing survival or reliability data. It is also more interpretable than the popular hazard function, especially for communications between patients and physicians regarding the efficacy of a new drug in the medical field. This book reviews existing statistical methods to infer the residual life distribution. The review and comparison includes existing inference methods for mean and median, or quantile, residual life analysis through medical data examples. The concept of the residual life is also extended to competing risks analysis. The targeted audience includes biostatisticians, graduate students, and PhD (bio)statisticians. Knowledge in survival analysis at an introductory graduate level is advisable prior to reading this book.

Advanced Online Survival Analysis Tool for Predictive Modelling in Clinical Data Science.

Science.gov (United States)

Montes-Torres, Julio; Subirats, José Luis; Ribelles, Nuria; Urda, Daniel; Franco, Leonardo; Alba, Emilio; Jerez, José Manuel

2016-01-01

One of the prevailing applications of machine learning is the use of predictive modelling in clinical survival analysis. In this work, we present our view of the current situation of computer tools for survival analysis, stressing the need of transferring the latest results in the field of machine learning to biomedical researchers. We propose a web based software for survival analysis called OSA (Online Survival Analysis), which has been developed as an open access and user friendly option to obtain discrete time, predictive survival models at individual level using machine learning techniques, and to perform standard survival analysis. OSA employs an Artificial Neural Network (ANN) based method to produce the predictive survival models. Additionally, the software can easily generate survival and hazard curves with multiple options to personalise the plots, obtain contingency tables from the uploaded data to perform different tests, and fit a Cox regression model from a number of predictor variables. In the Materials and Methods section, we depict the general architecture of the application and introduce the mathematical background of each of the implemented methods. The study concludes with examples of use showing the results obtained with public datasets.

ATM and p53 combined analysis predicts survival in glioblastoma multiforme patients: A clinicopathologic study.

Science.gov (United States)

Romano, Francesco Jacopo; Guadagno, Elia; Solari, Domenico; Borrelli, Giorgio; Pignatiello, Sara; Cappabianca, Paolo; Del Basso De Caro, Marialaura

2018-06-01

Glioblastoma is one of the most malignant cancers, with a distinguishing dismal prognosis: surgery followed by chemo- and radiotherapy represents the current standard of care, and chemo- and radioresistance underlie disease recurrence and short overall survival of patients suffering from this malignancy. ATM is a kinase activated by autophosphorylation upon DNA doublestrand breaks arising from errors during replication, byproducts of metabolism, chemotherapy or ionizing radiations; TP53 is one of the most popular tumor suppressor, with a preeminent role in DNA damage response and repair. To study the effects of the immunohistochemical expression of p-ATM and p53 in glioblastoma patients, 21 cases were retrospectively examined. In normal brain tissue, p-ATM was expressed only in neurons; conversely, in tumors cells, the protein showed a variable cytoplasmic expression (score: +,++,+++), with being completely undetectable in three cases. Statistical analysis revealed that high p-ATM score (++/+++) strongly correlated to shorter survival (P = 0.022). No difference in overall survival was registered between p53 normally expressed (NE) and overexpressed (OE) glioblastoma patients (P = 0.669). Survival analysis performed on the results from combined assessment of the two proteins showed that patients with NE p53 /low pATM score had longer overall survival than the NE p53/ high pATM score counterpart. Cox-regression analysis confirmed this finding (HR = 0.025; CI 95% = 0.002-0.284; P = 0.003). Our study outlined the immunohistochemical expression of p-ATM/p53 in glioblastomas and provided data on their possible prognostic/predictive of response role. A "non-oncogene addiction" to ATM for NEp53 glioblastoma could be postulated, strengthening the rationale for development of ATM inhibiting drugs. © 2018 Wiley Periodicals, Inc.

Mediation Analysis with Survival Outcomes: Accelerated Failure Time vs. Proportional Hazards Models.

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Gelfand, Lois A; MacKinnon, David P; DeRubeis, Robert J; Baraldi, Amanda N

2016-01-01

Survival time is an important type of outcome variable in treatment research. Currently, limited guidance is available regarding performing mediation analyses with survival outcomes, which generally do not have normally distributed errors, and contain unobserved (censored) events. We present considerations for choosing an approach, using a comparison of semi-parametric proportional hazards (PH) and fully parametric accelerated failure time (AFT) approaches for illustration. We compare PH and AFT models and procedures in their integration into mediation models and review their ability to produce coefficients that estimate causal effects. Using simulation studies modeling Weibull-distributed survival times, we compare statistical properties of mediation analyses incorporating PH and AFT approaches (employing SAS procedures PHREG and LIFEREG, respectively) under varied data conditions, some including censoring. A simulated data set illustrates the findings. AFT models integrate more easily than PH models into mediation models. Furthermore, mediation analyses incorporating LIFEREG produce coefficients that can estimate causal effects, and demonstrate superior statistical properties. Censoring introduces bias in the coefficient estimate representing the treatment effect on outcome-underestimation in LIFEREG, and overestimation in PHREG. With LIFEREG, this bias can be addressed using an alternative estimate obtained from combining other coefficients, whereas this is not possible with PHREG. When Weibull assumptions are not violated, there are compelling advantages to using LIFEREG over PHREG for mediation analyses involving survival-time outcomes. Irrespective of the procedures used, the interpretation of coefficients, effects of censoring on coefficient estimates, and statistical properties should be taken into account when reporting results.

Mediation Analysis with Survival Outcomes: Accelerated Failure Time vs. Proportional Hazards Models

Science.gov (United States)

Gelfand, Lois A.; MacKinnon, David P.; DeRubeis, Robert J.; Baraldi, Amanda N.

2016-01-01

Objective: Survival time is an important type of outcome variable in treatment research. Currently, limited guidance is available regarding performing mediation analyses with survival outcomes, which generally do not have normally distributed errors, and contain unobserved (censored) events. We present considerations for choosing an approach, using a comparison of semi-parametric proportional hazards (PH) and fully parametric accelerated failure time (AFT) approaches for illustration. Method: We compare PH and AFT models and procedures in their integration into mediation models and review their ability to produce coefficients that estimate causal effects. Using simulation studies modeling Weibull-distributed survival times, we compare statistical properties of mediation analyses incorporating PH and AFT approaches (employing SAS procedures PHREG and LIFEREG, respectively) under varied data conditions, some including censoring. A simulated data set illustrates the findings. Results: AFT models integrate more easily than PH models into mediation models. Furthermore, mediation analyses incorporating LIFEREG produce coefficients that can estimate causal effects, and demonstrate superior statistical properties. Censoring introduces bias in the coefficient estimate representing the treatment effect on outcome—underestimation in LIFEREG, and overestimation in PHREG. With LIFEREG, this bias can be addressed using an alternative estimate obtained from combining other coefficients, whereas this is not possible with PHREG. Conclusions: When Weibull assumptions are not violated, there are compelling advantages to using LIFEREG over PHREG for mediation analyses involving survival-time outcomes. Irrespective of the procedures used, the interpretation of coefficients, effects of censoring on coefficient estimates, and statistical properties should be taken into account when reporting results. PMID:27065906

Mediation Analysis with Survival Outcomes: Accelerated Failure Time Versus Proportional Hazards Models

Directory of Open Access Journals (Sweden)

Lois A Gelfand

2016-03-01

Full Text Available Objective: Survival time is an important type of outcome variable in treatment research. Currently, limited guidance is available regarding performing mediation analyses with survival outcomes, which generally do not have normally distributed errors, and contain unobserved (censored events. We present considerations for choosing an approach, using a comparison of semi-parametric proportional hazards (PH and fully parametric accelerated failure time (AFT approaches for illustration.Method: We compare PH and AFT models and procedures in their integration into mediation models and review their ability to produce coefficients that estimate causal effects. Using simulation studies modeling Weibull-distributed survival times, we compare statistical properties of mediation analyses incorporating PH and AFT approaches (employing SAS procedures PHREG and LIFEREG, respectively under varied data conditions, some including censoring. A simulated data set illustrates the findings.Results: AFT models integrate more easily than PH models into mediation models. Furthermore, mediation analyses incorporating LIFEREG produce coefficients that can estimate causal effects, and demonstrate superior statistical properties. Censoring introduces bias in the coefficient estimate representing the treatment effect on outcome – underestimation in LIFEREG, and overestimation in PHREG. With LIFEREG, this bias can be addressed using an alternative estimate obtained from combining other coefficients, whereas this is not possible with PHREG.Conclusions: When Weibull assumptions are not violated, there are compelling advantages to using LIFEREG over PHREG for mediation analyses involving survival-time outcomes. Irrespective of the procedures used, the interpretation of coefficients, effects of censoring on coefficient estimates, and statistical properties should be taken into account when reporting results.

Survival Analysis of Occipital Nerve Stimulator Leads Placed under Fluoroscopic Guidance with and without Ultrasonography.

Science.gov (United States)

Jones, James H; Brown, Alison; Moyse, Daniel; Qi, Wenjing; Roy, Lance

2017-11-01

Electrical stimulation of the greater occipital nerves is performed to treat pain secondary to chronic daily headaches and occipital neuralgia. The use of fluoroscopy alone to guide the surgical placement of electrodes near the greater occipital nerves disregards the impact of tissue planes on lead stability and stimulation efficacy. We hypothesized that occipital neurostimulator (ONS) leads placed with ultrasonography combined with fluoroscopy would demonstrate increased survival rates and times when compared to ONS leads placed with fluoroscopy alone. A 2-arm retrospective chart review. A single academic medical center. This retrospective chart review analyzed the procedure notes and demographic data of patients who underwent the permanent implant of an ONS lead between July 2012 and August 2015. Patient data included the diagnosis (reason for implant), smoking tobacco use, disability, and age. ONS lead data included the date of permanent implant, the imaging modality used during permanent implant (fluoroscopy with or without ultrasonography), and, if applicable, the date and reason for lead removal. A total of 21 patients (53 leads) were included for the review. Chi-squared tests, Fishers exact tests, 2-sample t-tests, and Wilcoxon rank-sum tests were used to compare fluoroscopy against combined fluoroscopy and ultrasonography as implant methods with respect to patient demographics. These tests were also used to evaluate the primary aim of this study, which was to compare the survival rates and times of ONS leads placed with combined ultrasonography and fluoroscopy versus those placed with fluoroscopy alone. Survival analysis was used to assess the effect of implant method, adjusted for patient demographics (age, smoking tobacco use, and disability), on the risk of lead explant. Data from 21 patients were collected, including a total of 53 ONS leads. There was no statistically significant difference in the lead survival rate or time, disability, or patient age

SURVIVAL ANALYSIS AND LENGTH-BIASED SAMPLING

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Masoud Asgharian

2010-12-01

Full Text Available When survival data are colleted as part of a prevalent cohort study, the recruited cases have already experienced their initiating event. These prevalent cases are then followed for a fixed period of time at the end of which the subjects will either have failed or have been censored. When interests lies in estimating the survival distribution, from onset, of subjects with the disease, one must take into account that the survival times of the cases in a prevalent cohort study are left truncated. When it is possible to assume that there has not been any epidemic of the disease over the past period of time that covers the onset times of the subjects, one may assume that the underlying incidence process that generates the initiating event times is a stationary Poisson process. Under such assumption, the survival times of the recruited subjects are called “lengthbiased”. I discuss the challenges one is faced with in analyzing these type of data. To address the theoretical aspects of the work, I present asymptotic results for the NPMLE of the length-biased as well as the unbiased survival distribution. I also discuss estimating the unbiased survival function using only the follow-up time. This addresses the case that the onset times are either unknown or known with uncertainty. Some of our most recent work and open questions will be presented. These include some aspects of analysis of covariates, strong approximation, functional LIL and density estimation under length-biased sampling with right censoring. The results will be illustrated with survival data from patients with dementia, collected as part of the Canadian Study of Health and Aging (CSHA.

Orphan caribou, Rangifer tarandus, calves: A re-evaluation of overwinter survival data

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Joly, Kyle

2000-01-01

Low sample size and high variation within populations reduce power of statistical tests. These aspects of statistical power appear to have affected an analysis comparing overwinter survival rates of non-orphan and orphan Caribou (Rangifer tarandus) calves by an earlier study for the Porcupine Caribou Herd. A re-evaluation of the data revealed that conclusions about a lack of significant difference in the overwinter survival rates between orphan and non-orphan calves were premature.

Reassessment of the relationship between M-protein decrement and survival in multiple myeloma.

OpenAIRE

Palmer, M.; Belch, A.; Hanson, J.; Brox, L.

1989-01-01

The relationship between percentage M-protein decrement and survival is assessed in 134 multiple myeloma patients. The correlation did not achieve statistical significance (P = 0.069). Multivariate analysis using the Cox proportional hazards model, including a number of previously recognised prognostic factors, showed only percentage M-protein decrement, creatinine and haemoglobin to be significantly correlated with survival. However, the R'-statistic for each of these variables was low, indi...

Statistical analysis of medical data using SAS

CERN Document Server

Der, Geoff

2005-01-01

An Introduction to SASDescribing and Summarizing DataBasic InferenceScatterplots Correlation: Simple Regression and SmoothingAnalysis of Variance and CovarianceMultiple RegressionLogistic RegressionThe Generalized Linear ModelGeneralized Additive ModelsNonlinear Regression ModelsThe Analysis of Longitudinal Data IThe Analysis of Longitudinal Data II: Models for Normal Response VariablesThe Analysis of Longitudinal Data III: Non-Normal ResponseSurvival AnalysisAnalysis Multivariate Date: Principal Components and Cluster AnalysisReferences

The role of river hydrology on Salix shoot and root survival statistics on the alluvial sediment of a restored river corridor

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Pasquale, Nicola; Perona, Paolo; Verones, Francesca; Francis, Robert; Burlando, Paolo

2010-05-01

In river restoration projects there is considerable interest in understanding the morphodynamics of river reaches in relation to the characteristics of vegetation that may colonize the bare alluvial sediment, and locally stabilize it by root anchoring. Vegetation interacts with river hydrology on multiple time scales, but such interactions are at present still poorly understood. In this contribution, we discuss both the above and below ground biomass growth dynamics of 1188 Salix cuttings (individual and group survival rate, growth of the longest shoots and number of branches and morphological root analysis) in relation to local river hydrodynamics. Cuttings were organized in square plots of different size and planted in spring 2009 on a gravel island of the restored river section of River Thur (Niederneunforn, Canton Thurgau, Switzerland). Cuttings in the plots were monitored regularly, from the beginning of the campaign (March) until the end of the growing season (October). We obtained a detailed and quite unique set of data, which includes, among others, root characteristic statistics obtained from image and high-resolution scanner analysis of carefully uprooted samples. Beyond describing the survival rate dynamics in relation to river hydrology, we show the nature and strength of correlations between island topography, cutting growth statistics and local reach morphodynamics (see also Pasquale et. al.3, session HS 3.1). In particular, by comparing empirical histograms of the vertical root distribution vs. those of the saturated water surface in the sediment, we show that main tropic responses are oxytropism, hydrotropism and thigmotropism. Moreover, by numerical modelling of the local hydrodynamics, we can also identify the spatial distribution of preferential locations of oxytropism and hydrotropism. As far as factors causing mortality are concerned, we also show that erosion by flood is responsible for influencing the spatial and temporal distribution of the

Neuroendocrine Tumor: Statistics

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... Tumor > Neuroendocrine Tumor: Statistics Request Permissions Neuroendocrine Tumor: Statistics Approved by the Cancer.Net Editorial Board , 01/ ... the body. It is important to remember that statistics on the survival rates for people with a ...

A Statistical Toolkit for Data Analysis

International Nuclear Information System (INIS)

Donadio, S.; Guatelli, S.; Mascialino, B.; Pfeiffer, A.; Pia, M.G.; Ribon, A.; Viarengo, P.

2006-01-01

The present project aims to develop an open-source and object-oriented software Toolkit for statistical data analysis. Its statistical testing component contains a variety of Goodness-of-Fit tests, from Chi-squared to Kolmogorov-Smirnov, to less known, but generally much more powerful tests such as Anderson-Darling, Goodman, Fisz-Cramer-von Mises, Kuiper, Tiku. Thanks to the component-based design and the usage of the standard abstract interfaces for data analysis, this tool can be used by other data analysis systems or integrated in experimental software frameworks. This Toolkit has been released and is downloadable from the web. In this paper we describe the statistical details of the algorithms, the computational features of the Toolkit and describe the code validation

Statistical considerations on safety analysis

International Nuclear Information System (INIS)

Pal, L.; Makai, M.

2004-01-01

The authors have investigated the statistical methods applied to safety analysis of nuclear reactors and arrived at alarming conclusions: a series of calculations with the generally appreciated safety code ATHLET were carried out to ascertain the stability of the results against input uncertainties in a simple experimental situation. Scrutinizing those calculations, we came to the conclusion that the ATHLET results may exhibit chaotic behavior. A further conclusion is that the technological limits are incorrectly set when the output variables are correlated. Another formerly unnoticed conclusion of the previous ATHLET calculations that certain innocent looking parameters (like wall roughness factor, the number of bubbles per unit volume, the number of droplets per unit volume) can influence considerably such output parameters as water levels. The authors are concerned with the statistical foundation of present day safety analysis practices and can only hope that their own misjudgment will be dispelled. Until then, the authors suggest applying correct statistical methods in safety analysis even if it makes the analysis more expensive. It would be desirable to continue exploring the role of internal parameters (wall roughness factor, steam-water surface in thermal hydraulics codes, homogenization methods in neutronics codes) in system safety codes and to study their effects on the analysis. In the validation and verification process of a code one carries out a series of computations. The input data are not precisely determined because measured data have an error, calculated data are often obtained from a more or less accurate model. Some users of large codes are content with comparing the nominal output obtained from the nominal input, whereas all the possible inputs should be taken into account when judging safety. At the same time, any statement concerning safety must be aleatory, and its merit can be judged only when the probability is known with which the

Statistical shape analysis with applications in R

CERN Document Server

Dryden, Ian L

2016-01-01

A thoroughly revised and updated edition of this introduction to modern statistical methods for shape analysis Shape analysis is an important tool in the many disciplines where objects are compared using geometrical features. Examples include comparing brain shape in schizophrenia; investigating protein molecules in bioinformatics; and describing growth of organisms in biology. This book is a significant update of the highly-regarded `Statistical Shape Analysis’ by the same authors. The new edition lays the foundations of landmark shape analysis, including geometrical concepts and statistical techniques, and extends to include analysis of curves, surfaces, images and other types of object data. Key definitions and concepts are discussed throughout, and the relative merits of different approaches are presented. The authors have included substantial new material on recent statistical developments and offer numerous examples throughout the text. Concepts are introduced in an accessible manner, while reta...

Spatial analysis statistics, visualization, and computational methods

CERN Document Server

Oyana, Tonny J

2015-01-01

An introductory text for the next generation of geospatial analysts and data scientists, Spatial Analysis: Statistics, Visualization, and Computational Methods focuses on the fundamentals of spatial analysis using traditional, contemporary, and computational methods. Outlining both non-spatial and spatial statistical concepts, the authors present practical applications of geospatial data tools, techniques, and strategies in geographic studies. They offer a problem-based learning (PBL) approach to spatial analysis-containing hands-on problem-sets that can be worked out in MS Excel or ArcGIS-as well as detailed illustrations and numerous case studies. The book enables readers to: Identify types and characterize non-spatial and spatial data Demonstrate their competence to explore, visualize, summarize, analyze, optimize, and clearly present statistical data and results Construct testable hypotheses that require inferential statistical analysis Process spatial data, extract explanatory variables, conduct statisti...

Association of phase angle on bioelectrical impedance analysis and dialysis frequency with survival of chronic hemodialysis patients

Science.gov (United States)

Muzasti, R. A.; Lubis, H. R.

2018-03-01

Phase angle, a parameter by Bioelectrical Impedance Analysis, can detect body composition changes, so it can be used as a prognostic indicator in some chronic conditions. This study was for determining the relationship between PhA and hemodiálisis frequency with the survival of chronic hemodiálisis patients. This longitudinal retrospective study involved 173 chronic hemodiálisis patients at Rasyida Renal Hospital. The Kaplan-Meier method is used to determine the survival. Cox proportional hazard analysis is used to determine which variables significantly increase mortality. During the study period, 89 patients underwent hemodiálysis 3x a week (4 hours/session), and 84 patients underwent HD 2x a week (5 hours/session). Demographic and clinical characteristics in both groups were similar. There was no difference in PhA value in groups of 3x a week and group 2x a week (4.02 ± 1.13 vs 4.25 ± 1.12). Patients with twice a week hemodiálisis had a shorter survival than the 3x week group (35.14 ± 2.76 vs 38.62 ± 3.03) although it was not statistically significant (p = 0.126).

Survival Rate and Associated Factors of Childhood Leukemia in Iran: A Systematic Review and Meta Analysis

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Yousef Veisani

2017-02-01

Full Text Available Context Resent reviews have shown that about 18% of all child cancers are leukemia. Track of the survival rate can help researchers improve quality of life of patients through improving screening or discovery of better treatments. Objectives This review aimed at estimating the 5-year survival rates and associated factors of childhood leukemia in Iran. Data Sources We carried out a systematic review through search of relevant studies published in English (PubMed, Scopus, Google scholar, and ISI and Persian databases (Magiran, Medlib, SID, and Iran Medex. Study Selection The study included all epidemiologic studies that estimated survival rate in children with leukemia in Iran during years 2002 to 2015, and a standardized manner was used for extraction of information. Data Extraction The entire text or summary of all searched articles was extracted and then, related articles were selected, and irrelevant ones were excluded. Fixed and random effects models were calculated by the STATA using standard meta-analysis methods. Heterogeneity was assessed by I² statistics. Results The overall 5-year survival rate in patients with childhood leukemia in Iran was 0.65 (95% CI, 0.62 to 0.67, 10 studies, in the acute lymphoblastic leukemia (ALL subtype was 71.0% (95% CI: 68.0 to 74.0, and in the acute myeloid leukemia (AML subtype was 46.0%. Results of the meta analysis showed significant poor survival with relapse (heart rate (HR 1.59, 95% confidence interval (CI 1.27 to 1.98 and white blood count (WBC counts ≥ 50,000 (HR 2.92, 95% CI 1.23 to 4.60. Conclusions The results showed that 5-year survival rates in patients with AML were lower than patients with ALL. The results of this meta analysis strongly support the need for future research, action, and guidance for clinicians to improve health-related quality of life and outcomes for children with leukemia.

Application of descriptive statistics in analysis of experimental data

OpenAIRE

Mirilović Milorad; Pejin Ivana

2008-01-01

Statistics today represent a group of scientific methods for the quantitative and qualitative investigation of variations in mass appearances. In fact, statistics present a group of methods that are used for the accumulation, analysis, presentation and interpretation of data necessary for reaching certain conclusions. Statistical analysis is divided into descriptive statistical analysis and inferential statistics. The values which represent the results of an experiment, and which are the subj...

Statistical Analysis of Research Data | Center for Cancer Research

Science.gov (United States)

Recent advances in cancer biology have resulted in the need for increased statistical analysis of research data. The Statistical Analysis of Research Data (SARD) course will be held on April 5-6, 2018 from 9 a.m.-5 p.m. at the National Institutes of Health's Natcher Conference Center, Balcony C on the Bethesda Campus. SARD is designed to provide an overview on the general principles of statistical analysis of research data.  The first day will feature univariate data analysis, including descriptive statistics, probability distributions, one- and two-sample inferential statistics.

PROGNOSTIC FACTORS OF SURVIVAL IN RENAL CANCER

Directory of Open Access Journals (Sweden)

A. V. Seriogin

2014-08-01

Full Text Available The purpose of the study was to reveal the independent anatomic, histological, and clinical factors of cancer-specific survival in patients with renal-cell carcinoma (RCC. For this, the authors retrospectively analyzed their experience with radical surgical treatments in 73 RCC patients operated on at the Department of Urology and Surgical Andrology, Russian Medical Academy of Postgraduate Education, from January 1, 1999 to December 31, 2004; their outcomes have become known by the present time. There was a statistically significant correlation of cancer-specific survival with its parameters, such as pathological stage of a tumor, its maximum pathological size, differentiation grade, involvement of regional lymph nodes, venous tumor thrombosis, level of thrombocytosis, and degree of the clinical symptoms of the disease. Multivariate analysis of survival in RCC in relation to the prognostic factors could reveal odd ratios for the limit values of significant prognostic factors. The statistically significant prognostic values established in the present study, as well as the molecular factors the implication of which is being now investigated can become in future an effective addition to the TNM staging system to define indications for certain treatments and to predict survival in RCC  

PROGNOSTIC FACTORS OF SURVIVAL IN RENAL CANCER

Directory of Open Access Journals (Sweden)

A. V. Seriogin

2009-01-01

Full Text Available The purpose of the study was to reveal the independent anatomic, histological, and clinical factors of cancer-specific survival in patients with renal-cell carcinoma (RCC. For this, the authors retrospectively analyzed their experience with radical surgical treatments in 73 RCC patients operated on at the Department of Urology and Surgical Andrology, Russian Medical Academy of Postgraduate Education, from January 1, 1999 to December 31, 2004; their outcomes have become known by the present time. There was a statistically significant correlation of cancer-specific survival with its parameters, such as pathological stage of a tumor, its maximum pathological size, differentiation grade, involvement of regional lymph nodes, venous tumor thrombosis, level of thrombocytosis, and degree of the clinical symptoms of the disease. Multivariate analysis of survival in RCC in relation to the prognostic factors could reveal odd ratios for the limit values of significant prognostic factors. The statistically significant prognostic values established in the present study, as well as the molecular factors the implication of which is being now investigated can become in future an effective addition to the TNM staging system to define indications for certain treatments and to predict survival in RCC  

Statistical analysis with Excel for dummies

CERN Document Server

Schmuller, Joseph

2013-01-01

Take the mystery out of statistical terms and put Excel to work! If you need to create and interpret statistics in business or classroom settings, this easy-to-use guide is just what you need. It shows you how to use Excel's powerful tools for statistical analysis, even if you've never taken a course in statistics. Learn the meaning of terms like mean and median, margin of error, standard deviation, and permutations, and discover how to interpret the statistics of everyday life. You'll learn to use Excel formulas, charts, PivotTables, and other tools to make sense of everything fro

Survival analysis for customer satisfaction: A case study

Science.gov (United States)

Hadiyat, M. A.; Wahyudi, R. D.; Sari, Y.

2017-11-01

Most customer satisfaction surveys are conducted periodically to track their dynamics. One of the goals of this survey was to evaluate the service design by recognizing the trend of satisfaction score. Many researchers recommended in redesigning the service when the satisfaction scores were decreasing, so that the service life cycle could be predicted qualitatively. However, these scores were usually set in Likert scale and had quantitative properties. Thus, they should also be analyzed in quantitative model so that the predicted service life cycle would be done by applying the survival analysis. This paper discussed a starting point for customer satisfaction survival analysis with a case study in healthcare service.

Lamb survival analysis from birth to weaning in Iranian Kermani sheep.

Science.gov (United States)

Barazandeh, Arsalan; Moghbeli, Sadrollah Molaei; Vatankhah, Mahmood; Hossein-Zadeh, Navid Ghavi

2012-04-01

Survival records from 1,763 Kermani lambs born between 1996 and 2004 from 294 ewes and 81 rams were used to determine genetic and non-genetic factors affecting lamb survival. Traits included were lamb survival across five periods from birth to 7, 14, 56, 70, and 90 days of age. Traits were analyzed under Weibull proportional hazard sire models. Several binary analyses were also conducted using animal models. Statistical models included the fixed class effects of sex of lamb, month and year of birth, a covariate effect of birth weight, and random genetic effects of both sire (in survival analyses) and animal (in binary analyses). The average survival to 90 days of age was 94.8%. Hazard rates ranged from 1.00 (birth to 90 days of age) to 1.73 (birth to 7 days of age) between the two sexes indicating that male lambs were at higher risk of mortality than females (P lamb survival and lamb birth weight, suggesting that viability and birth weight could be considered simultaneously in the selection programs to obtain optimal birth weight in Kermani lambs. Estimates of heritabilities from survival analyses were medium and ranged from 0.23 to 0.29. In addition, heritability estimates obtained from binary analyses were low and varied from 0.04 to 0.09. The results of this study suggest that progress in survival traits could be possible through managerial strategies and genetic selection.

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....

Population-based cancer survival in the United States: Data, quality control, and statistical methods.

Science.gov (United States)

Allemani, Claudia; Harewood, Rhea; Johnson, Christopher J; Carreira, Helena; Spika, Devon; Bonaventure, Audrey; Ward, Kevin; Weir, Hannah K; Coleman, Michel P

2017-12-15

Robust comparisons of population-based cancer survival estimates require tight adherence to the study protocol, standardized quality control, appropriate life tables of background mortality, and centralized analysis. The CONCORD program established worldwide surveillance of population-based cancer survival in 2015, analyzing individual data on 26 million patients (including 10 million US patients) diagnosed between 1995 and 2009 with 1 of 10 common malignancies. In this Cancer supplement, we analyzed data from 37 state cancer registries that participated in the second cycle of the CONCORD program (CONCORD-2), covering approximately 80% of the US population. Data quality checks were performed in 3 consecutive phases: protocol adherence, exclusions, and editorial checks. One-, 3-, and 5-year age-standardized net survival was estimated using the Pohar Perme estimator and state- and race-specific life tables of all-cause mortality for each year. The cohort approach was adopted for patients diagnosed between 2001 and 2003, and the complete approach for patients diagnosed between 2004 and 2009. Articles in this supplement report population coverage, data quality indicators, and age-standardized 5-year net survival by state, race, and stage at diagnosis. Examples of tables, bar charts, and funnel plots are provided in this article. Population-based cancer survival is a key measure of the overall effectiveness of services in providing equitable health care. The high quality of US cancer registry data, 80% population coverage, and use of an unbiased net survival estimator ensure that the survival trends reported in this supplement are robustly comparable by race and state. The results can be used by policymakers to identify and address inequities in cancer survival in each state and for the United States nationally. Cancer 2017;123:4982-93. Published 2017. This article is a U.S. Government work and is in the public domain in the USA. Published 2017. This article is a U

Data-Driven Lead-Acid Battery Prognostics Using Random Survival Forests

Science.gov (United States)

2014-10-02

Kogalur, Blackstone , & Lauer, 2008; Ishwaran & Kogalur, 2010). Random survival forest is a sur- vival analysis extension of Random Forests (Breiman, 2001...Statistics & probability letters, 80(13), 1056–1064. Ishwaran, H., Kogalur, U. B., Blackstone , E. H., & Lauer, M. S. (2008). Random survival forests. The...and environment for sta- tistical computing [Computer software manual]. Vienna, Austria. Retrieved from http://www.R-project .org/ Wager, S., Hastie, T

Statistical analysis of dynamic parameters of the core

International Nuclear Information System (INIS)

Ionov, V.S.

2007-01-01

The transients of various types were investigated for the cores of zero power critical facilities in RRC KI and NPP. Dynamic parameters of neutron transients were explored by tool statistical analysis. Its have sufficient duration, few channels for currents of chambers and reactivity and also some channels for technological parameters. On these values the inverse period. reactivity, lifetime of neutrons, reactivity coefficients and some effects of a reactivity are determinate, and on the values were restored values of measured dynamic parameters as result of the analysis. The mathematical means of statistical analysis were used: approximation(A), filtration (F), rejection (R), estimation of parameters of descriptive statistic (DSP), correlation performances (kk), regression analysis(KP), the prognosis (P), statistician criteria (SC). The calculation procedures were realized by computer language MATLAB. The reasons of methodical and statistical errors are submitted: inadequacy of model operation, precision neutron-physical parameters, features of registered processes, used mathematical model in reactivity meters, technique of processing for registered data etc. Examples of results of statistical analysis. Problems of validity of the methods used for definition and certification of values of statistical parameters and dynamic characteristics are considered (Authors)

Statistical Analysis of Competing Risks: Overall Survival in a Group of Chronic Myeloid Leukemia Patients

Czech Academy of Sciences Publication Activity Database

Fürstová, Jana; Valenta, Zdeněk

2011-01-01

Roč. 7, č. 1 (2011), s. 2-10 ISSN 1801-5603 Institutional research plan: CEZ:AV0Z10300504 Keywords : competing risks * chronic myeloid leukemia (CML) * overall survival * cause-specific hazard * cumulative incidence function Subject RIV: IN - Informatics, Computer Science http://www.ejbi.eu/images/2011-1/Furstova_en.pdf

CONFIDENCE LEVELS AND/VS. STATISTICAL HYPOTHESIS TESTING IN STATISTICAL ANALYSIS. CASE STUDY

Directory of Open Access Journals (Sweden)

ILEANA BRUDIU

2009-05-01

Full Text Available Estimated parameters with confidence intervals and testing statistical assumptions used in statistical analysis to obtain conclusions on research from a sample extracted from the population. Paper to the case study presented aims to highlight the importance of volume of sample taken in the study and how this reflects on the results obtained when using confidence intervals and testing for pregnant. If statistical testing hypotheses not only give an answer "yes" or "no" to some questions of statistical estimation using statistical confidence intervals provides more information than a test statistic, show high degree of uncertainty arising from small samples and findings build in the "marginally significant" or "almost significant (p very close to 0.05.

Collecting operational event data for statistical analysis

International Nuclear Information System (INIS)

Atwood, C.L.

1994-09-01

This report gives guidance for collecting operational data to be used for statistical analysis, especially analysis of event counts. It discusses how to define the purpose of the study, the unit (system, component, etc.) to be studied, events to be counted, and demand or exposure time. Examples are given of classification systems for events in the data sources. A checklist summarizes the essential steps in data collection for statistical analysis

Survival benefit of radiotherapy to patients with small cell esophagus carcinoma: an analysis of Surveillance Epidemiology and End Results (SEER) data.

Science.gov (United States)

Song, Yaqi; Wang, Wanwei; Tao, Guangzhou; Zhu, Weiguo; Zhou, Xilei; Pan, Peng

2016-03-29

Small cell esophageal carcinoma (SCEC) is a rare malignant tumor. So far, few studies are found to research the effect of radiotherapy (RT) to it. This study is designed to explore the prognostic factors, and analyze survival benefit of RT to patients with SCEC. Patients with SCEC were more likely to be in female, older, higher disease stage than those with non-small cell esophageal carcinoma. RT was used in more than 50% SCEC patients. RT tended be reduced as the disease stage raise in SCEC. Univariate and multivariate analysis showed that age, year, disease stage, and RT were the prognostic factors of survival (P 0.05) and nearly 30% risks of death in distant stage (P > 0.05). SCEC patients between 1973 and 2012 were searched from the Surveillance Epidemiology and End Results (SEER) data. Clinical factors including age, year, sex, race, stage, surgery, and RT were summarized. Univariate and multivariate analysis were performed to explore the independent prognostic factors of SCEC. Cox regression survival analysis was performed to evaluate the effect of RT to SCEC based on different stages. Stage, age, year, and RT are independent prognostic factors of SCEC. Survival benefit of RT exists in any disease stage, but is only statistically significant in localized stage of SCEC.

Statistics and analysis of scientific data

CERN Document Server

Bonamente, Massimiliano

2013-01-01

Statistics and Analysis of Scientific Data covers the foundations of probability theory and statistics, and a number of numerical and analytical methods that are essential for the present-day analyst of scientific data. Topics covered include probability theory, distribution functions of statistics, fits to two-dimensional datasheets and parameter estimation, Monte Carlo methods and Markov chains. Equal attention is paid to the theory and its practical application, and results from classic experiments in various fields are used to illustrate the importance of statistics in the analysis of scientific data. The main pedagogical method is a theory-then-application approach, where emphasis is placed first on a sound understanding of the underlying theory of a topic, which becomes the basis for an efficient and proactive use of the material for practical applications. The level is appropriate for undergraduates and beginning graduate students, and as a reference for the experienced researcher. Basic calculus is us...

Association of body mass index and survival in pediatric leukemia: a meta-analysis.

Science.gov (United States)

Orgel, Etan; Genkinger, Jeanine M; Aggarwal, Divya; Sung, Lillian; Nieder, Michael; Ladas, Elena J

2016-03-01

Obesity is a worldwide epidemic in children and adolescents. Adult cohort studies have reported an association between higher body mass index (BMI) and increased leukemia-related mortality; whether a similar effect exists in childhood leukemia remains controversial. We conducted a meta-analysis to determine whether a higher BMI at diagnosis of pediatric acute lymphoblastic leukemia (ALL) or acute myeloid leukemia (AML) is associated with worse event-free survival (EFS), overall survival (OS), and cumulative incidence of relapse (CIR). We searched 4 electronic databases from inception through March 2015 without language restriction and included studies in pediatric ALL or AML (0-21 y of age) reporting BMI as a predictor of survival or relapse. Higher BMI, defined as obese (≥95%) or overweight/obese (≥85%), was compared with lower BMI [nonoverweight/obese (children with a higher BMI (RR: 1.35; 95% CI: 1.20, 1.51) than in those at a lower BMI. A higher BMI was associated with significantly increased mortality (RR: 1.31; 95% CI: 1.09, 1.58) and a statistically nonsignificant trend toward greater risk of relapse (RR: 1.17; 95% CI: 0.99, 1.38) compared with a lower BMI. In AML, a higher BMI was significantly associated with poorer EFS and OS (RR: 1.36; 95% CI: 1.16, 1.60 and RR: 1.56; 95% CI: 1.32, 1.86, respectively) than was a lower BMI. Higher BMI at diagnosis is associated with poorer survival in children with pediatric ALL or AML. © 2016 American Society for Nutrition.

Method for statistical data analysis of multivariate observations

CERN Document Server

Gnanadesikan, R

1997-01-01

A practical guide for multivariate statistical techniques-- now updated and revised In recent years, innovations in computer technology and statistical methodologies have dramatically altered the landscape of multivariate data analysis. This new edition of Methods for Statistical Data Analysis of Multivariate Observations explores current multivariate concepts and techniques while retaining the same practical focus of its predecessor. It integrates methods and data-based interpretations relevant to multivariate analysis in a way that addresses real-world problems arising in many areas of inte

Advances in statistical models for data analysis

CERN Document Server

Minerva, Tommaso; Vichi, Maurizio

2015-01-01

This edited volume focuses on recent research results in classification, multivariate statistics and machine learning and highlights advances in statistical models for data analysis. The volume provides both methodological developments and contributions to a wide range of application areas such as economics, marketing, education, social sciences and environment. The papers in this volume were first presented at the 9th biannual meeting of the Classification and Data Analysis Group (CLADAG) of the Italian Statistical Society, held in September 2013 at the University of Modena and Reggio Emilia, Italy.

Causal inference in survival analysis using pseudo-observations.

Science.gov (United States)

Andersen, Per K; Syriopoulou, Elisavet; Parner, Erik T

2017-07-30

Causal inference for non-censored response variables, such as binary or quantitative outcomes, is often based on either (1) direct standardization ('G-formula') or (2) inverse probability of treatment assignment weights ('propensity score'). To do causal inference in survival analysis, one needs to address right-censoring, and often, special techniques are required for that purpose. We will show how censoring can be dealt with 'once and for all' by means of so-called pseudo-observations when doing causal inference in survival analysis. The pseudo-observations can be used as a replacement of the outcomes without censoring when applying 'standard' causal inference methods, such as (1) or (2) earlier. We study this idea for estimating the average causal effect of a binary treatment on the survival probability, the restricted mean lifetime, and the cumulative incidence in a competing risks situation. The methods will be illustrated in a small simulation study and via a study of patients with acute myeloid leukemia who received either myeloablative or non-myeloablative conditioning before allogeneic hematopoetic cell transplantation. We will estimate the average causal effect of the conditioning regime on outcomes such as the 3-year overall survival probability and the 3-year risk of chronic graft-versus-host disease. Copyright © 2017 John Wiley & Sons, Ltd. Copyright © 2017 John Wiley & Sons, Ltd.

Survival analysis of a treatment data for cancer of the larynx

International Nuclear Information System (INIS)

Khan, K.

2002-01-01

In this paper a survival analysis of the survival time is done. The Cox regression model is fitted to the survival time with the assumption of proportional hazard. A model is selected after inclusion and exclusion of factors and variables as explanatory variables. The assumption of proportional hazards is tested in the manner suggested by Harrell (1986). The assumption of proportional hazards is supported by these tests. However the plot of Schoenfeld residuals against dose gave a little evidence of non validity of the proportional hazard assumption. The assumption seems to be satisfied for variable time. The martingale residuals suggest no pattern for variable age. The functional form of dose is not linear. Hence the quadratic dose is used as an explanatory variable. A comparison of logistic regression analysis and survival analysis is also made in this paper. It can be concluded that Cox proportional hazards model is a better model than the logistic model as it is more parsimonious and utilizes more information. (author)

An introduction to statistics with Python with applications in the life sciences

CERN Document Server

Haslwanter, Thomas

2016-01-01

This textbook provides an introduction to the free software Python and its use for statistical data analysis. It covers common statistical tests for continuous, discrete and categorical data, as well as linear regression analysis and topics from survival analysis and Bayesian statistics. Working code and data for Python solutions for each test, together with easy-to-follow Python examples, can be reproduced by the reader and reinforce their immediate understanding of the topic. With recent advances in the Python ecosystem, Python has become a popular language for scientific computing, offering a powerful environment for statistical data analysis and an interesting alternative to R. The book is intended for master and PhD students, mainly from the life and medical sciences, with a basic knowledge of statistics. As it also provides some statistics background, the book can be used by anyone who wants to perform a statistical data analysis. .

Classification, (big) data analysis and statistical learning

CERN Document Server

Conversano, Claudio; Vichi, Maurizio

2018-01-01

This edited book focuses on the latest developments in classification, statistical learning, data analysis and related areas of data science, including statistical analysis of large datasets, big data analytics, time series clustering, integration of data from different sources, as well as social networks. It covers both methodological aspects as well as applications to a wide range of areas such as economics, marketing, education, social sciences, medicine, environmental sciences and the pharmaceutical industry. In addition, it describes the basic features of the software behind the data analysis results, and provides links to the corresponding codes and data sets where necessary. This book is intended for researchers and practitioners who are interested in the latest developments and applications in the field. The peer-reviewed contributions were presented at the 10th Scientific Meeting of the Classification and Data Analysis Group (CLADAG) of the Italian Statistical Society, held in Santa Margherita di Pul...

Statistical hot spot analysis of reactor cores

International Nuclear Information System (INIS)

Schaefer, H.

1974-05-01

This report is an introduction into statistical hot spot analysis. After the definition of the term 'hot spot' a statistical analysis is outlined. The mathematical method is presented, especially the formula concerning the probability of no hot spots in a reactor core is evaluated. A discussion with the boundary conditions of a statistical hot spot analysis is given (technological limits, nominal situation, uncertainties). The application of the hot spot analysis to the linear power of pellets and the temperature rise in cooling channels is demonstrated with respect to the test zone of KNK II. Basic values, such as probability of no hot spots, hot spot potential, expected hot spot diagram and cumulative distribution function of hot spots, are discussed. It is shown, that the risk of hot channels can be dispersed equally over all subassemblies by an adequate choice of the nominal temperature distribution in the core

The statistical analysis of anisotropies

International Nuclear Information System (INIS)

Webster, A.

1977-01-01

One of the many uses to which a radio survey may be put is an analysis of the distribution of the radio sources on the celestial sphere to find out whether they are bunched into clusters or lie in preferred regions of space. There are many methods of testing for clustering in point processes and since they are not all equally good this contribution is presented as a brief guide to what seems to be the best of them. The radio sources certainly do not show very strong clusering and may well be entirely unclustered so if a statistical method is to be useful it must be both powerful and flexible. A statistic is powerful in this context if it can efficiently distinguish a weakly clustered distribution of sources from an unclustered one, and it is flexible if it can be applied in a way which avoids mistaking defects in the survey for true peculiarities in the distribution of sources. The paper divides clustering statistics into two classes: number density statistics and log N/log S statistics. (Auth.)

Reporting and methodological quality of survival analysis in articles published in Chinese oncology journals.

Science.gov (United States)

Zhu, Xiaoyan; Zhou, Xiaobin; Zhang, Yuan; Sun, Xiao; Liu, Haihua; Zhang, Yingying

2017-12-01

Survival analysis methods have gained widespread use in the filed of oncology. For achievement of reliable results, the methodological process and report quality is crucial. This review provides the first examination of methodological characteristics and reporting quality of survival analysis in articles published in leading Chinese oncology journals.To examine methodological and reporting quality of survival analysis, to identify some common deficiencies, to desirable precautions in the analysis, and relate advice for authors, readers, and editors.A total of 242 survival analysis articles were included to be evaluated from 1492 articles published in 4 leading Chinese oncology journals in 2013. Articles were evaluated according to 16 established items for proper use and reporting of survival analysis.The application rates of Kaplan-Meier, life table, log-rank test, Breslow test, and Cox proportional hazards model (Cox model) were 91.74%, 3.72%, 78.51%, 0.41%, and 46.28%, respectively, no article used the parametric method for survival analysis. Multivariate Cox model was conducted in 112 articles (46.28%). Follow-up rates were mentioned in 155 articles (64.05%), of which 4 articles were under 80% and the lowest was 75.25%, 55 articles were100%. The report rates of all types of survival endpoint were lower than 10%. Eleven of 100 articles which reported a loss to follow-up had stated how to treat it in the analysis. One hundred thirty articles (53.72%) did not perform multivariate analysis. One hundred thirty-nine articles (57.44%) did not define the survival time. Violations and omissions of methodological guidelines included no mention of pertinent checks for proportional hazard assumption; no report of testing for interactions and collinearity between independent variables; no report of calculation method of sample size. Thirty-six articles (32.74%) reported the methods of independent variable selection. The above defects could make potentially inaccurate

Somatic mutation load of estrogen receptor-positive breast tumors predicts overall survival: an analysis of genome sequence data.

Science.gov (United States)

Haricharan, Svasti; Bainbridge, Matthew N; Scheet, Paul; Brown, Powel H

2014-07-01

Breast cancer is one of the most commonly diagnosed cancers in women. While there are several effective therapies for breast cancer and important single gene prognostic/predictive markers, more than 40,000 women die from this disease every year. The increasing availability of large-scale genomic datasets provides opportunities for identifying factors that influence breast cancer survival in smaller, well-defined subsets. The purpose of this study was to investigate the genomic landscape of various breast cancer subtypes and its potential associations with clinical outcomes. We used statistical analysis of sequence data generated by the Cancer Genome Atlas initiative including somatic mutation load (SML) analysis, Kaplan-Meier survival curves, gene mutational frequency, and mutational enrichment evaluation to study the genomic landscape of breast cancer. We show that ER(+), but not ER(-), tumors with high SML associate with poor overall survival (HR = 2.02). Further, these high mutation load tumors are enriched for coincident mutations in both DNA damage repair and ER signature genes. While it is known that somatic mutations in specific genes affect breast cancer survival, this study is the first to identify that SML may constitute an important global signature for a subset of ER(+) tumors prone to high mortality. Moreover, although somatic mutations in individual DNA damage genes affect clinical outcome, our results indicate that coincident mutations in DNA damage response and signature ER genes may prove more informative for ER(+) breast cancer survival. Next generation sequencing may prove an essential tool for identifying pathways underlying poor outcomes and for tailoring therapeutic strategies.

Reassessment of the relationship between M-protein decrement and survival in multiple myeloma.

Science.gov (United States)

Palmer, M; Belch, A; Hanson, J; Brox, L

1989-01-01

The relationship between percentage M-protein decrement and survival is assessed in 134 multiple myeloma patients. The correlation did not achieve statistical significance (P = 0.069). Multivariate analysis using the Cox proportional hazards model, including a number of previously recognised prognostic factors, showed only percentage M-protein decrement, creatinine and haemoglobin to be significantly correlated with survival. However, the R'-statistic for each of these variables was low, indicating that their prognostic power is weak. We conclude that neither the percentage M-protein decrement nor the response derived from it can be used as an accurate means of assessing the efficacy of treatment in myeloma. Mature survival data alone should be used for this purpose.

Reassessment of the relationship between M-protein decrement and survival in multiple myeloma.

Science.gov (United States)

Palmer, M.; Belch, A.; Hanson, J.; Brox, L.

1989-01-01

The relationship between percentage M-protein decrement and survival is assessed in 134 multiple myeloma patients. The correlation did not achieve statistical significance (P = 0.069). Multivariate analysis using the Cox proportional hazards model, including a number of previously recognised prognostic factors, showed only percentage M-protein decrement, creatinine and haemoglobin to be significantly correlated with survival. However, the R'-statistic for each of these variables was low, indicating that their prognostic power is weak. We conclude that neither the percentage M-protein decrement nor the response derived from it can be used as an accurate means of assessing the efficacy of treatment in myeloma. Mature survival data alone should be used for this purpose. PMID:2757916

Basic statistical tools in research and data analysis

Directory of Open Access Journals (Sweden)

Zulfiqar Ali

2016-01-01

Full Text Available Statistical methods involved in carrying out a study include planning, designing, collecting data, analysing, drawing meaningful interpretation and reporting of the research findings. The statistical analysis gives meaning to the meaningless numbers, thereby breathing life into a lifeless data. The results and inferences are precise only if proper statistical tests are used. This article will try to acquaint the reader with the basic research tools that are utilised while conducting various studies. The article covers a brief outline of the variables, an understanding of quantitative and qualitative variables and the measures of central tendency. An idea of the sample size estimation, power analysis and the statistical errors is given. Finally, there is a summary of parametric and non-parametric tests used for data analysis.

A Framework for RFID Survivability Requirement Analysis and Specification

Science.gov (United States)

Zuo, Yanjun; Pimple, Malvika; Lande, Suhas

Many industries are becoming dependent on Radio Frequency Identification (RFID) technology for inventory management and asset tracking. The data collected about tagged objects though RFID is used in various high level business operations. The RFID system should hence be highly available, reliable, and dependable and secure. In addition, this system should be able to resist attacks and perform recovery in case of security incidents. Together these requirements give rise to the notion of a survivable RFID system. The main goal of this paper is to analyze and specify the requirements for an RFID system to become survivable. These requirements, if utilized, can assist the system in resisting against devastating attacks and recovering quickly from damages. This paper proposes the techniques and approaches for RFID survivability requirements analysis and specification. From the perspective of system acquisition and engineering, survivability requirement is the important first step in survivability specification, compliance formulation, and proof verification.

Reproducible statistical analysis with multiple languages

DEFF Research Database (Denmark)

Lenth, Russell; Højsgaard, Søren

2011-01-01

This paper describes the system for making reproducible statistical analyses. differs from other systems for reproducible analysis in several ways. The two main differences are: (1) Several statistics programs can be in used in the same document. (2) Documents can be prepared using OpenOffice or ......Office or \\LaTeX. The main part of this paper is an example showing how to use and together in an OpenOffice text document. The paper also contains some practical considerations on the use of literate programming in statistics....

Survival benefit of TIPS versus serial paracentesis in patients with refractory ascites: a single institution case-control propensity score analysis

International Nuclear Information System (INIS)

Gaba, R.C.; Parvinian, A.; Casadaban, L.C.; Couture, P.M.; Zivin, S.P.; Lakhoo, J.; Minocha, J.; Ray, C.E.; Knuttinen, M.G.; Bui, J.T.

2015-01-01

Aim: To compare the impact of covered stent-graft transjugular intrahepatic portosystemic shunt (TIPS) versus serial paracentesis on survival of patients with medically refractory ascites. Materials and methods: In this retrospective study, cirrhotic patients who underwent covered stent-graft TIPS for refractory ascites from 2003–2013 were compared with similar patients who underwent serial paracentesis during 2009–2013. Demographic and liver disease data, Model for End-Stage Liver Disease (MELD) scores, and survival outcomes were obtained from hospital electronic medical records and the social security death index. After propensity score weighting to match study group characteristics, survival outcomes were compared using Kaplan–Meier statistics with log-rank analysis. Results: Seventy TIPS (70% men, mean age 55.7 years, mean MELD 15.1) and 80 paracentesis (58% men, mean age 53.5 years, mean MELD 22.5) patients were compared. The TIPS haemodynamic success rate was 100% (mean portosystemic pressure gradient reduction 13 mmHg). Paracentesis patients underwent a mean of 7.9 procedures. After propensity score weighting to balance group features, TIPS patients showed a trend toward enhanced survival compared with paracentesis patients (median survival 1037 versus 262 days, p = 0.074). TIPS conferred a significant increase or trend toward improved survival compared with paracentesis at 1 (66% versus 44%, p = 0.018), 2 (56% versus 38%, p = 0.057), and 3 year (49% versus 32%, p = 0.077) time points. Thirty and 90 day mortality rates were not statistically increased by TIPS. Conclusion: Covered stent-graft TIPS improves intermediate- to long-term survival without significantly increasing short-term mortality of ascites patients, and suggests a greater potential role for TIPS in properly selected ascitic patients when medical management fails. - Highlights: • The survival benefit of TIPS for patients with refractory ascites remains unproven. • A case

Common pitfalls in statistical analysis: "P" values, statistical significance and confidence intervals

Directory of Open Access Journals (Sweden)

Priya Ranganathan

2015-01-01

Full Text Available In the second part of a series on pitfalls in statistical analysis, we look at various ways in which a statistically significant study result can be expressed. We debunk some of the myths regarding the ′P′ value, explain the importance of ′confidence intervals′ and clarify the importance of including both values in a paper

A STATISTICAL ANALYSIS OF LARYNGEAL MALIGNANCIES AT OUR INSTITUTION

Directory of Open Access Journals (Sweden)

Bharathi Mohan Mathan

2017-03-01

Full Text Available BACKGROUND Malignancies of larynx are an increasing global burden with a distribution of approximately 2-5% of all malignancies with an incidence of 3.6/1,00,000 for men and 1.3/1,00,000 for women with a male-to-female ratio of 4:1. Smoking and alcohol are major established risk factors. More than 90-95% of all malignancies are squamous cell type. Three main subsite of laryngeal malignancies are glottis, supraglottis and subglottis. Improved surgical techniques and advanced chemoradiotherapy has increased the overall 5 year survival rate. The above study is statistical analysis of laryngeal malignancies at our institution for a period of one year and analysis of pattern of distribution, aetiology, sites and subsites and causes for recurrence. MATERIALS AND METHODS Based on the statistical data available in the institution for the period of one year from January 2016-December 2016, all laryngeal malignancies were analysed with respect to demographic pattern, age, gender, site, subsite, aetiology, staging, treatment received and probable cause for failure of treatment. Patients were followed up for 12 months period during the study. RESULTS Total number of cases studied are 27 (twenty seven. Male cases are 23 and female cases are 4, male-to-female ratio is 5.7:1, most common age is above 60 years, most common site is supraglottis, most common type is moderately-differentiated squamous cell carcinoma, most common cause for relapse or recurrence is advanced stage of disease and poor differentiation. CONCLUSION The commonest age occurrence at the end of the study is above 60 years and male-to-female ratio is 5.7:1, which is slightly above the international standards. Most common site is supraglottis and not glottis. The relapse and recurrences are higher compared to the international standards.

Statistics and analysis of scientific data

CERN Document Server

Bonamente, Massimiliano

2017-01-01

The revised second edition of this textbook provides the reader with a solid foundation in probability theory and statistics as applied to the physical sciences, engineering and related fields. It covers a broad range of numerical and analytical methods that are essential for the correct analysis of scientific data, including probability theory, distribution functions of statistics, fits to two-dimensional data and parameter estimation, Monte Carlo methods and Markov chains. Features new to this edition include: • a discussion of statistical techniques employed in business science, such as multiple regression analysis of multivariate datasets. • a new chapter on the various measures of the mean including logarithmic averages. • new chapters on systematic errors and intrinsic scatter, and on the fitting of data with bivariate errors. • a new case study and additional worked examples. • mathematical derivations and theoretical background material have been appropriately marked,to improve the readabili...

Statistical evaluation of diagnostic performance topics in ROC analysis

CERN Document Server

Zou, Kelly H; Bandos, Andriy I; Ohno-Machado, Lucila; Rockette, Howard E

2016-01-01

Statistical evaluation of diagnostic performance in general and Receiver Operating Characteristic (ROC) analysis in particular are important for assessing the performance of medical tests and statistical classifiers, as well as for evaluating predictive models or algorithms. This book presents innovative approaches in ROC analysis, which are relevant to a wide variety of applications, including medical imaging, cancer research, epidemiology, and bioinformatics. Statistical Evaluation of Diagnostic Performance: Topics in ROC Analysis covers areas including monotone-transformation techniques in parametric ROC analysis, ROC methods for combined and pooled biomarkers, Bayesian hierarchical transformation models, sequential designs and inferences in the ROC setting, predictive modeling, multireader ROC analysis, and free-response ROC (FROC) methodology. The book is suitable for graduate-level students and researchers in statistics, biostatistics, epidemiology, public health, biomedical engineering, radiology, medi...

Bayesian Inference in Statistical Analysis

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Box, George E P

2011-01-01

The Wiley Classics Library consists of selected books that have become recognized classics in their respective fields. With these new unabridged and inexpensive editions, Wiley hopes to extend the life of these important works by making them available to future generations of mathematicians and scientists. Currently available in the Series: T. W. Anderson The Statistical Analysis of Time Series T. S. Arthanari & Yadolah Dodge Mathematical Programming in Statistics Emil Artin Geometric Algebra Norman T. J. Bailey The Elements of Stochastic Processes with Applications to the Natural Sciences Rob

Prognostic classification index in Iranian colorectal cancer patients: Survival tree analysis

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Amal Saki Malehi

2016-01-01

Full Text Available Aims: The aim of this study was to determine the prognostic index for separating homogenous subgroups in colorectal cancer (CRC patients based on clinicopathological characteristics using survival tree analysis. Methods: The current study was conducted at the Research Center of Gastroenterology and Liver Disease, Shahid Beheshti Medical University in Tehran, between January 2004 and January 2009. A total of 739 patients who already have been diagnosed with CRC based on pathologic report were enrolled. The data included demographic and clinical-pathological characteristic of patients. Tree-structured survival analysis based on a recursive partitioning algorithm was implemented to evaluate prognostic factors. The probability curves were calculated according to the Kaplan-Meier method, and the hazard ratio was estimated as an interest effect size. Result: There were 526 males (71.2% of these patients. The mean survival time (from diagnosis time was 42.46± (3.4. Survival tree identified three variables as main prognostic factors and based on their four prognostic subgroups was constructed. The log-rank test showed good separation of survival curves. Patients with Stage I-IIIA and treated with surgery as the first treatment showed low risk (median = 34 months whereas patients with stage IIIB, IV, and more than 68 years have the worse survival outcome (median = 9.5 months. Conclusion: Constructing the prognostic classification index via survival tree can aid the researchers to assess interaction between clinical variables and determining the cumulative effect of these variables on survival outcome.

Analysis of Variance: What Is Your Statistical Software Actually Doing?

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Li, Jian; Lomax, Richard G.

2011-01-01

Users assume statistical software packages produce accurate results. In this article, the authors systematically examined Statistical Package for the Social Sciences (SPSS) and Statistical Analysis System (SAS) for 3 analysis of variance (ANOVA) designs, mixed-effects ANOVA, fixed-effects analysis of covariance (ANCOVA), and nested ANOVA. For each…

Survival of dental implants placed in sites of previously failed implants.

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Chrcanovic, Bruno R; Kisch, Jenö; Albrektsson, Tomas; Wennerberg, Ann

2017-11-01

To assess the survival of dental implants placed in sites of previously failed implants and to explore the possible factors that might affect the outcome of this reimplantation procedure. Patients that had failed dental implants, which were replaced with the same implant type at the same site, were included. Descriptive statistics were used to describe the patients and implants; survival analysis was also performed. The effect of systemic, environmental, and local factors on the survival of the reoperated implants was evaluated. 175 of 10,096 implants in 98 patients were replaced by another implant at the same location (159, 14, and 2 implants at second, third, and fourth surgeries, respectively). Newly replaced implants were generally of similar diameter but of shorter length compared to the previously placed fixtures. A statistically significant greater percentage of lost implants were placed in sites with low bone quantity. There was a statistically significant difference (P = 0.032) in the survival rates between implants that were inserted for the first time (94%) and implants that replaced the ones lost (73%). There was a statistically higher failure rate of the reoperated implants for patients taking antidepressants and antithrombotic agents. Dental implants replacing failed implants had lower survival rates than the rates reported for the previous attempts of implant placement. It is suggested that a site-specific negative effect may possibly be associated with this phenomenon, as well as the intake of antidepressants and antithrombotic agents. © 2016 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Comparing Visual and Statistical Analysis of Multiple Baseline Design Graphs.

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Wolfe, Katie; Dickenson, Tammiee S; Miller, Bridget; McGrath, Kathleen V

2018-04-01

A growing number of statistical analyses are being developed for single-case research. One important factor in evaluating these methods is the extent to which each corresponds to visual analysis. Few studies have compared statistical and visual analysis, and information about more recently developed statistics is scarce. Therefore, our purpose was to evaluate the agreement between visual analysis and four statistical analyses: improvement rate difference (IRD); Tau-U; Hedges, Pustejovsky, Shadish (HPS) effect size; and between-case standardized mean difference (BC-SMD). Results indicate that IRD and BC-SMD had the strongest overall agreement with visual analysis. Although Tau-U had strong agreement with visual analysis on raw values, it had poorer agreement when those values were dichotomized to represent the presence or absence of a functional relation. Overall, visual analysis appeared to be more conservative than statistical analysis, but further research is needed to evaluate the nature of these disagreements.

Sensitivity analysis and related analysis : A survey of statistical techniques

NARCIS (Netherlands)

Kleijnen, J.P.C.

1995-01-01

This paper reviews the state of the art in five related types of analysis, namely (i) sensitivity or what-if analysis, (ii) uncertainty or risk analysis, (iii) screening, (iv) validation, and (v) optimization. The main question is: when should which type of analysis be applied; which statistical

Mediation analysis of the relationship between institutional research activity and patient survival

DEFF Research Database (Denmark)

Rochon, Justine; du Bois, Andreas; Lange, Theis

2014-01-01

BACKGROUND: Recent studies have suggested that patients treated in research-active institutions have better outcomes than patients treated in research-inactive institutions. However, little attention has been paid to explaining such effects, probably because techniques for mediation analysis...... existing so far have not been applicable to survival data. METHODS: We investigated the underlying mechanisms using a recently developed method for mediation analysis of survival data. Our analysis of the effect of research activity on patient survival was based on 352 patients who had been diagnosed...... mediated through either optimal surgery or chemotherapy. Taken together, about 26% of the beneficial effect of research activity was mediated through the proposed pathways. CONCLUSIONS: Mediation analysis allows proceeding from the question "Does it work?" to the question "How does it work?" In particular...

A Combinatory Approach for Selecting Prognostic Genes in Microarray Studies of Tumour Survivals

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Qihua Tan

2009-01-01

Full Text Available Different from significant gene expression analysis which looks for genes that are differentially regulated, feature selection in the microarray-based prognostic gene expression analysis aims at finding a subset of marker genes that are not only differentially expressed but also informative for prediction. Unfortunately feature selection in literature of microarray study is predominated by the simple heuristic univariate gene filter paradigm that selects differentially expressed genes according to their statistical significances. We introduce a combinatory feature selection strategy that integrates differential gene expression analysis with the Gram-Schmidt process to identify prognostic genes that are both statistically significant and highly informative for predicting tumour survival outcomes. Empirical application to leukemia and ovarian cancer survival data through-within- and cross-study validations shows that the feature space can be largely reduced while achieving improved testing performances.

Statistical analysis with measurement error or misclassification strategy, method and application

CERN Document Server

Yi, Grace Y

2017-01-01

This monograph on measurement error and misclassification covers a broad range of problems and emphasizes unique features in modeling and analyzing problems arising from medical research and epidemiological studies. Many measurement error and misclassification problems have been addressed in various fields over the years as well as with a wide spectrum of data, including event history data (such as survival data and recurrent event data), correlated data (such as longitudinal data and clustered data), multi-state event data, and data arising from case-control studies. Statistical Analysis with Measurement Error or Misclassification: Strategy, Method and Application brings together assorted methods in a single text and provides an update of recent developments for a variety of settings. Measurement error effects and strategies of handling mismeasurement for different models are closely examined in combination with applications to specific problems. Readers with diverse backgrounds and objectives can utilize th...

Survival Outcomes of Patients Treated with Hypofractionated Stereotactic Body Radiation Therapy for Parotid Gland Tumors: a Retrospective Analysis

International Nuclear Information System (INIS)

Karam, Sana D.; Snider, James W.; Wang, Hongkun; Wooster, Margaux; Lominska, Christopher; Deeken, John; Newkirk, Kenneth; Davidson, Bruce; Harter, K. William

2012-01-01

Background: to review a single-institution experience with the management of parotid malignancies treated by fractionated stereotactic body radiosurgery (SBRT). Findings: Between 2003 and 2011, 13 patients diagnosed with parotid malignancies were treated with adjuvant or definitive SBRT to a median dose of 33 Gy (range 25–40 Gy). There were 11 male and two female patients with a median age of 80. Ten patients declined conventional radiation treatment and three patients had received prior unrelated radiation therapy to neighboring structures with unavailable radiation records. Six patients were treated with definitive intent while seven patients were treated adjuvantly for adverse surgical or pathologic features. Five patients had clinical or pathologic evidence of lymph node disease. Conclusion: at a median follow-up of 14 months only one patient failed locally, and four failed distantly. The actuarial 2-year overall survival, progression-free survival, and local-regional control rates were 46, 84, and 47%, respectively. Statistical analysis revealed surgery as a positive predictor of overall survival while presence of gross disease was a negatively correlated factor (p < 0.05).

Statistical models for competing risk analysis

International Nuclear Information System (INIS)

Sather, H.N.

1976-08-01

Research results on three new models for potential applications in competing risks problems. One section covers the basic statistical relationships underlying the subsequent competing risks model development. Another discusses the problem of comparing cause-specific risk structure by competing risks theory in two homogeneous populations, P1 and P2. Weibull models which allow more generality than the Berkson and Elveback models are studied for the effect of time on the hazard function. The use of concomitant information for modeling single-risk survival is extended to the multiple failure mode domain of competing risks. The model used to illustrate the use of this methodology is a life table model which has constant hazards within pre-designated intervals of the time scale. Two parametric models for bivariate dependent competing risks, which provide interesting alternatives, are proposed and examined

Cancer Statistics Animator

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This tool allows users to animate cancer trends over time by cancer site and cause of death, race, and sex. Provides access to incidence, mortality, and survival. Select the type of statistic, variables, format, and then extract the statistics in a delimited format for further analyses.

Evaluation of the effects of red blood cell distribution width on survival in lung cancer patients.

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Kos, Mehmet; Hocazade, Cemil; Kos, F Tugba; Uncu, Dogan; Karakas, Esra; Dogan, Mutlu; Uncu, Hikmet G; Ozdemir, Nuriye; Zengin, Nurullah

2016-01-01

Data are available indicating that red blood cell distribution width (RDW) is higher in cancer patients compared to healthy individuals or benign events. In our study, we aimed to investigate the influence of different RDW levels on survival in lung cancer patients. Clinical and laboratory data from 146 patients with lung cancer and 40 healthy subjects were retrospectively studied. RDW was recorded before the application of any treatment. Patients were categorised according to four different RDW cut-off values (median RDW, RDW determined by ROC curve analysis, the upper limit at the automatic blood count device, and RDW cut of value which used in previous studies). Kaplan-Meier survival analysis was used to examine the effect of RDW on survival for each cut-off level. The median age of patients was 56.5 years (range: 26-83 years). The difference in median RDW between patients and the control group was statistically significant (14.0 and 13.8, respectively, p = 0.04). There was no difference with regard to overall survival when patients with RDW ≥ 14.0 were compared to those with RDW < 14.0 (p = 0.70); however, overall survival was 3.0 months shorter in low values of its own group in each of the following cut-off values: ≥ 14.2 (p = 0.34), ≥ 14.5 (p = 0.25), ≥ 15 (p = 0.59), although no results were statistically significant. We consider that the difference between low and high RDW values according to certain cut-off values may reflect the statistics of larger studies although there is a statistically negative correlation between RDW level and survival.

Causal inference in survival analysis using pseudo-observations

DEFF Research Database (Denmark)

Andersen, Per K; Syriopoulou, Elisavet; Parner, Erik T

2017-01-01

Causal inference for non-censored response variables, such as binary or quantitative outcomes, is often based on either (1) direct standardization ('G-formula') or (2) inverse probability of treatment assignment weights ('propensity score'). To do causal inference in survival analysis, one needs ...

Online Statistical Modeling (Regression Analysis) for Independent Responses

Science.gov (United States)

Made Tirta, I.; Anggraeni, Dian; Pandutama, Martinus

2017-06-01

Regression analysis (statistical analmodelling) are among statistical methods which are frequently needed in analyzing quantitative data, especially to model relationship between response and explanatory variables. Nowadays, statistical models have been developed into various directions to model various type and complex relationship of data. Rich varieties of advanced and recent statistical modelling are mostly available on open source software (one of them is R). However, these advanced statistical modelling, are not very friendly to novice R users, since they are based on programming script or command line interface. Our research aims to developed web interface (based on R and shiny), so that most recent and advanced statistical modelling are readily available, accessible and applicable on web. We have previously made interface in the form of e-tutorial for several modern and advanced statistical modelling on R especially for independent responses (including linear models/LM, generalized linier models/GLM, generalized additive model/GAM and generalized additive model for location scale and shape/GAMLSS). In this research we unified them in the form of data analysis, including model using Computer Intensive Statistics (Bootstrap and Markov Chain Monte Carlo/ MCMC). All are readily accessible on our online Virtual Statistics Laboratory. The web (interface) make the statistical modeling becomes easier to apply and easier to compare them in order to find the most appropriate model for the data.

DDX3X Biomarker Correlates with Poor Survival in Human Gliomas

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Dueng-Yuan Hueng

2015-07-01

Full Text Available Primary high-grade gliomas possess invasive growth and lead to unfavorable survival outcome. The investigation of biomarkers for prediction of survival outcome in patients with gliomas is important for clinical assessment. The DEAD (Asp-Glu-Ala-Asp box helicase 3, X-linked (DDX3X controls tumor migration, proliferation, and progression. However, the role of DDX3X in defining the pathological grading and survival outcome in patients with human gliomas is not yet clarified. We analyzed the DDX3X gene expression, WHO pathological grading, and overall survival from de-linked data. Further validation was done using quantitative RT-PCR of cDNA from normal brain and glioma, and immunohistochemical (IHC staining of tissue microarray. Statistical analysis of GEO datasets showed that DDX3X mRNA expression demonstrated statistically higher in WHO grade IV (n = 81 than in non-tumor controls (n = 23, p = 1.13 × 10−10. Moreover, DDX3X level was also higher in WHO grade III (n = 19 than in non-tumor controls (p = 2.43 × 10−5. Kaplan–Meier survival analysis showed poor survival in patients with high DDX3X mRNA levels (n = 24 than in those with low DDX3X expression (n = 53 (median survival, 115 vs. 58 weeks, p = 0.0009, by log-rank test, hazard ratio: 0.3507, 95% CI: 0.1893–0.6496. Furthermore, DDX3X mRNA expression and protein production significantly increased in glioma cells compared with normal brain tissue examined by quantitative RT-PCR, and Western blot. IHC staining showed highly staining of high-grade glioma in comparison with normal brain tissue. Taken together, DDX3X expression level positively correlates with WHO pathologic grading and poor survival outcome, indicating that DDX3X is a valuable biomarker in human gliomas.

Survival Analysis of Patients with End Stage Renal Disease

Science.gov (United States)

Urrutia, J. D.; Gayo, W. S.; Bautista, L. A.; Baccay, E. B.

2015-06-01

This paper provides a survival analysis of End Stage Renal Disease (ESRD) under Kaplan-Meier Estimates and Weibull Distribution. The data were obtained from the records of V. L. MakabaliMemorial Hospital with respect to time t (patient's age), covariates such as developed secondary disease (Pulmonary Congestion and Cardiovascular Disease), gender, and the event of interest: the death of ESRD patients. Survival and hazard rates were estimated using NCSS for Weibull Distribution and SPSS for Kaplan-Meier Estimates. These lead to the same conclusion that hazard rate increases and survival rate decreases of ESRD patient diagnosed with Pulmonary Congestion, Cardiovascular Disease and both diseases with respect to time. It also shows that female patients have a greater risk of death compared to males. The probability risk was given the equation R = 1 — e-H(t) where e-H(t) is the survival function, H(t) the cumulative hazard function which was created using Cox-Regression.

Application of Ontology Technology in Health Statistic Data Analysis.

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Guo, Minjiang; Hu, Hongpu; Lei, Xingyun

2017-01-01

Research Purpose: establish health management ontology for analysis of health statistic data. Proposed Methods: this paper established health management ontology based on the analysis of the concepts in China Health Statistics Yearbook, and used protégé to define the syntactic and semantic structure of health statistical data. six classes of top-level ontology concepts and their subclasses had been extracted and the object properties and data properties were defined to establish the construction of these classes. By ontology instantiation, we can integrate multi-source heterogeneous data and enable administrators to have an overall understanding and analysis of the health statistic data. ontology technology provides a comprehensive and unified information integration structure of the health management domain and lays a foundation for the efficient analysis of multi-source and heterogeneous health system management data and enhancement of the management efficiency.

Statistical considerations in the development of injury risk functions.

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McMurry, Timothy L; Poplin, Gerald S

2015-01-01

We address 4 frequently misunderstood and important statistical ideas in the construction of injury risk functions. These include the similarities of survival analysis and logistic regression, the correct scale on which to construct pointwise confidence intervals for injury risk, the ability to discern which form of injury risk function is optimal, and the handling of repeated tests on the same subject. The statistical models are explored through simulation and examination of the underlying mathematics. We provide recommendations for the statistically valid construction and correct interpretation of single-predictor injury risk functions. This article aims to provide useful and understandable statistical guidance to improve the practice in constructing injury risk functions.

Clinical performance of ART restorations in primary teeth: a survival analysis.

Science.gov (United States)

Faccin, Elise Sasso; Ferreira, Simone Helena; Kramer, Paulo Floriani; Ardenghi, Thiago Machado; Feldens, Carlos Alberto

2009-01-01

To assess the survival of Atraumatic Restorative Treatment (ART) restorations in primary teeth performed in a dental clinical setting. One hundred and five single-surface ART restorations placed in 56 preschool children (mean age 31 months) were included. Final-year dental students performed the restorations using standard ART procedures with hand instruments. A resin-modified glass ionomer cement (Vitremer 3M/ESPE) was used as a restorative material. Performances of the restorations were assessed directly by the ART evaluation criteria. Follow-up period ranged from 6 to 48 months. Survival estimates for restoration longevity were evaluated using the Kaplan-Meier method. Log-rank test (P ART restorations were 89%, 85% and 72% in 6 to 11, 12 to 24 and 25 to 48 months of evaluation respectively. Differences in success rates among demographic and clinical characteristics were not statistically significant. High survivals rates of the ART restorations found in this study seem to indicate the reliability of this approach as an appropriate treatment option for primary teeth in a clinical setting.

A track-event theory of cell survival

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Besserer, Juergen; Schneider, Uwe [Zuerich Univ. (Switzerland). Inst. of Physics; Radiotherapy Hirslanden, Zuerich (Switzerland)

2015-09-01

When fractionation schemes for hypofractionation and stereotactic body radiotherapy are considered, a reliable cell survival model at high dose is needed for calculating doses of similar biological effectiveness. In this work a simple model for cell survival which is valid also at high dose is developed from Poisson statistics. An event is defined by two double strand breaks (DSB) on the same or different chromosomes. An event is always lethal due to direct lethal damage or lethal binary misrepair by the formation of chromosome aberrations. Two different mechanisms can produce events: one-track events (OTE) or two-track-events (TTE). The target for an OTE is always a lethal event, the target for an TTE is one DSB. At least two TTEs on the same or different chromosomes are necessary to produce an event. Both, the OTE and the TTE are statistically independent. From the stochastic nature of cell kill which is described by the Poisson distribution the cell survival probability was derived. It was shown that a solution based on Poisson statistics exists for cell survival. It exhibits exponential cell survival at high dose and a finite gradient of cell survival at vanishing dose, which is in agreement with experimental cell studies. The model fits the experimental data nearly as well as the three-parameter formula of Hug-Kellerer and is only based on two free parameters. It is shown that the LQ formalism is an approximation of the model derived in this work. It could be also shown that the derived model predicts a fractionated cell survival experiment better than the LQ-model. It was shown that cell survival can be described with a simple analytical formula on the basis of Poisson statistics. This solution represents in the limit of large dose the typical exponential behavior and predicts cell survival after fractionated dose application better than the LQ-model.

A track-event theory of cell survival

International Nuclear Information System (INIS)

Besserer, Juergen; Schneider, Uwe

2015-01-01

When fractionation schemes for hypofractionation and stereotactic body radiotherapy are considered, a reliable cell survival model at high dose is needed for calculating doses of similar biological effectiveness. In this work a simple model for cell survival which is valid also at high dose is developed from Poisson statistics. An event is defined by two double strand breaks (DSB) on the same or different chromosomes. An event is always lethal due to direct lethal damage or lethal binary misrepair by the formation of chromosome aberrations. Two different mechanisms can produce events: one-track events (OTE) or two-track-events (TTE). The target for an OTE is always a lethal event, the target for an TTE is one DSB. At least two TTEs on the same or different chromosomes are necessary to produce an event. Both, the OTE and the TTE are statistically independent. From the stochastic nature of cell kill which is described by the Poisson distribution the cell survival probability was derived. It was shown that a solution based on Poisson statistics exists for cell survival. It exhibits exponential cell survival at high dose and a finite gradient of cell survival at vanishing dose, which is in agreement with experimental cell studies. The model fits the experimental data nearly as well as the three-parameter formula of Hug-Kellerer and is only based on two free parameters. It is shown that the LQ formalism is an approximation of the model derived in this work. It could be also shown that the derived model predicts a fractionated cell survival experiment better than the LQ-model. It was shown that cell survival can be described with a simple analytical formula on the basis of Poisson statistics. This solution represents in the limit of large dose the typical exponential behavior and predicts cell survival after fractionated dose application better than the LQ-model.

Explorations in Statistics: The Analysis of Change

Science.gov (United States)

Curran-Everett, Douglas; Williams, Calvin L.

2015-01-01

Learning about statistics is a lot like learning about science: the learning is more meaningful if you can actively explore. This tenth installment of "Explorations in Statistics" explores the analysis of a potential change in some physiological response. As researchers, we often express absolute change as percent change so we can…

Common pitfalls in statistical analysis: “P” values, statistical significance and confidence intervals

Science.gov (United States)

Ranganathan, Priya; Pramesh, C. S.; Buyse, Marc

2015-01-01

In the second part of a series on pitfalls in statistical analysis, we look at various ways in which a statistically significant study result can be expressed. We debunk some of the myths regarding the ‘P’ value, explain the importance of ‘confidence intervals’ and clarify the importance of including both values in a paper PMID:25878958

Survival of patients with non-small cell lung cancer without treatment: a systematic review and meta-analysis

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Wao Hesborn

2013-02-01

Full Text Available Abstract Background Lung cancer is considered a terminal illness with a five-year survival rate of about 16%. Informed decision-making related to the management of a disease requires accurate prognosis of the disease with or without treatment. Despite the significance of disease prognosis in clinical decision-making, systematic assessment of prognosis in patients with lung cancer without treatment has not been performed. We conducted a systematic review and meta-analysis of the natural history of patients with confirmed diagnosis of lung cancer without active treatment, to provide evidence-based recommendations for practitioners on management decisions related to the disease. Specifically, we estimated overall survival when no anticancer therapy is provided. Methods Relevant studies were identified by search of electronic databases and abstract proceedings, review of bibliographies of included articles, and contacting experts in the field. All prospective or retrospective studies assessing prognosis of lung cancer patients without treatment were eligible for inclusion. Data on mortality was extracted from all included studies. Pooled proportion of mortality was calculated as a back-transform of the weighted mean of the transformed proportions using the random-effects model. To perform meta-analysis of median survival, published methods were used to pool the estimates as mean and standard error under the random-effects model. Methodological quality of the studies was examined. Results Seven cohort studies (4,418 patients and 15 randomized controlled trials (1,031 patients were included in the meta-analysis. All studies assessed mortality without treatment in patients with non-small cell lung cancer (NSCLC. The pooled proportion of mortality without treatment in cohort studies was 0.97 (95% CI: 0.96 to 0.99 and 0.96 in randomized controlled trials (95% CI: 0.94 to 0.98 over median study periods of eight and three years, respectively. When data

Identification of novel genetic markers of breast cancer survival

DEFF Research Database (Denmark)

Guo, Qi; Schmidt, Marjanka K; Kraft, Peter

2015-01-01

BACKGROUND: Survival after a diagnosis of breast cancer varies considerably between patients, and some of this variation may be because of germline genetic variation. We aimed to identify genetic markers associated with breast cancer-specific survival. METHODS: We conducted a large meta-analysis ......BACKGROUND: Survival after a diagnosis of breast cancer varies considerably between patients, and some of this variation may be because of germline genetic variation. We aimed to identify genetic markers associated with breast cancer-specific survival. METHODS: We conducted a large meta......-analysis of studies in populations of European ancestry, including 37954 patients with 2900 deaths from breast cancer. Each study had been genotyped for between 200000 and 900000 single nucleotide polymorphisms (SNPs) across the genome; genotypes for nine million common variants were imputed using a common reference...... panel from the 1000 Genomes Project. We also carried out subtype-specific analyses based on 6881 estrogen receptor (ER)-negative patients (920 events) and 23059 ER-positive patients (1333 events). All statistical tests were two-sided. RESULTS: We identified one new locus (rs2059614 at 11q24...

Immune phenotypes predict survival in patients with glioblastoma multiforme

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Haouraa Mostafa

2016-09-01

Full Text Available Abstract Background Glioblastoma multiforme (GBM, a common primary malignant brain tumor, rarely disseminates beyond the central nervous system and has a very bad prognosis. The current study aimed at the analysis of immunological control in individual patients with GBM. Methods Immune phenotypes and plasma biomarkers of GBM patients were determined at the time of diagnosis using flow cytometry and ELISA, respectively. Results Using descriptive statistics, we found that immune anomalies were distinct in individual patients. Defined marker profiles proved highly relevant for survival. A remarkable relation between activated NK cells and improved survival in GBM patients was in contrast to increased CD39 and IL-10 in patients with a detrimental course and very short survival. Recursive partitioning analysis (RPA and Cox proportional hazards models substantiated the relevance of absolute numbers of CD8 cells and low numbers of CD39 cells for better survival. Conclusions Defined alterations of the immune system may guide the course of disease in patients with GBM and may be prognostically valuable for longitudinal studies or can be applied for immune intervention.

Meta-analysis of racial disparities in survival in association with socioeconomic status among men and women with colon cancer.

Science.gov (United States)

Du, Xianglin L; Meyer, Tamra E; Franzini, Luisa

2007-06-01

Few studies have addressed racial disparities in survival for colon cancer by adequately incorporating both treatment and socioeconomic factors, and the findings from those studies have been inconsistent. The objectives of the current study were to systematically review the existing literature and provide a more stable estimate of the measures of association between socioeconomic status and racial disparities in survival for colon cancer by undertaking a meta-analysis. For this meta-analysis, the authors searched the MEDLINE database to identify articles published in English from 1966 to August 2006 that met the following inclusion criteria: original research articles that addressed the association between race/ethnicity and survival in patients with colon or colorectal cancer after adjusting for socioeconomic status. In total, 66 full articles were reviewed, and 56 of those articles were excluded, which left 10 studies for the final analysis. The pooled hazard ratio (HR) for African Americans compared with Caucasians was 1.14 (95% confidence interval [95% CI], 1.00-1.29) for all-cause mortality and 1.13 (95% CI, 1.01-1.28) for colon cancer-specific mortality. The test for homogeneity of the HR was statistically significant across the studies for all-cause mortality (Q=31.69; Pcolon cancer-specific mortality (Q=7.45; P=.114). Racial disparities in survival for colon cancer between African Americans and Caucasians were only marginally significant after adjusting for socioeconomic factors and treatment. Attempts to modify treatment and socioeconomic factors with the objective of reducing racial disparities in health outcomes may have important clinical and public health implications. (c) 2007 American Cancer Society.

To improve the quality of the statistical analysis of papers published in the Journal of the Korean Society for Therapeutic Radiology and Oncology

International Nuclear Information System (INIS)

Park, Hee Chul; Choi, Doo Ho; Ahn, Song Vogue

2008-01-01

To improve the quality of the statistical analysis of papers published in the Journal of the Korean Society for Therapeutic Radiology and Oncology (JKOSTRO) by evaluating commonly encountered errors. Materials and Methods: Papers published in the JKOSTRO from January 2006 to December 2007 were reviewed for methodological and statistical validity using a modified version of Ahn's checklist. A statistician reviewed individual papers and evaluated the list items in the checklist for each paper. To avoid the potential assessment error by the statistician who lacks expertise in the field of radiation oncology; the editorial board of the JKOSTRO reviewed each checklist for individual articles. A frequency analysis of the list items was performed using SAS (version 9.0, SAS Institute, NC, USA) software. Results: A total of 73 papers including 5 case reports and 68 original articles were reviewed. Inferential statistics was used in 46 papers. The most commonly adopted statistical methodology was a survival analysis (58.7%). Only 19% of papers were free of statistical errors. Errors of omission were encountered in 34 (50.0%) papers. Errors of commission were encountered in 35 (51.5%) papers. Twenty-one papers (30.9%) had both errors of omission and commission. Conclusion: A variety of statistical errors were encountered in papers published in the JKOSTRO. The current study suggests that a more thorough review of the statistical analysis is needed for manuscripts submitted in the JKOSTRO

TECHNIQUE OF THE STATISTICAL ANALYSIS OF INVESTMENT APPEAL OF THE REGION

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А. А. Vershinina

2014-01-01

Full Text Available The technique of the statistical analysis of investment appeal of the region is given in scientific article for direct foreign investments. Definition of a technique of the statistical analysis is given, analysis stages reveal, the mathematico-statistical tools are considered.

Statistical analysis of network data with R

CERN Document Server

Kolaczyk, Eric D

2014-01-01

Networks have permeated everyday life through everyday realities like the Internet, social networks, and viral marketing. As such, network analysis is an important growth area in the quantitative sciences, with roots in social network analysis going back to the 1930s and graph theory going back centuries. Measurement and analysis are integral components of network research. As a result, statistical methods play a critical role in network analysis. This book is the first of its kind in network research. It can be used as a stand-alone resource in which multiple R packages are used to illustrate how to conduct a wide range of network analyses, from basic manipulation and visualization, to summary and characterization, to modeling of network data. The central package is igraph, which provides extensive capabilities for studying network graphs in R. This text builds on Eric D. Kolaczyk’s book Statistical Analysis of Network Data (Springer, 2009).

General statistical data structure for epidemiologic studies of DOE workers

International Nuclear Information System (INIS)

Frome, E.L.; Hudson, D.R.

1981-01-01

Epidemiologic studies to evaluate the occupational risks associated with employment in the nuclear industry are currently being conducted by the Department of Energy. Data that have potential value in evaluating any long-term health effects of occupational exposure to low levels of radiation are obtained for each individual at a given facility. We propose a general data structure for statistical analysis that is used to define transformations from the data management system into the data analysis system. Statistical methods of interest in epidemiologic studies include contingency table analysis and survival analysis procedures that can be used to evaluate potential associations between occupational radiation exposure and mortality. The purposes of this paper are to discuss (1) the adequacy of this data structure for single- and multiple-facility analysis and (2) the statistical computing problems encountered in dealing with large populations over extended periods of time

Semiclassical analysis, Witten Laplacians, and statistical mechanis

CERN Document Server

Helffer, Bernard

2002-01-01

This important book explains how the technique of Witten Laplacians may be useful in statistical mechanics. It considers the problem of analyzing the decay of correlations, after presenting its origin in statistical mechanics. In addition, it compares the Witten Laplacian approach with other techniques, such as the transfer matrix approach and its semiclassical analysis. The author concludes by providing a complete proof of the uniform Log-Sobolev inequality. Contents: Witten Laplacians Approach; Problems in Statistical Mechanics with Discrete Spins; Laplace Integrals and Transfer Operators; S

A novel statistic for genome-wide interaction analysis.

Directory of Open Access Journals (Sweden)

Xuesen Wu

2010-09-01

Full Text Available Although great progress in genome-wide association studies (GWAS has been made, the significant SNP associations identified by GWAS account for only a few percent of the genetic variance, leading many to question where and how we can find the missing heritability. There is increasing interest in genome-wide interaction analysis as a possible source of finding heritability unexplained by current GWAS. However, the existing statistics for testing interaction have low power for genome-wide interaction analysis. To meet challenges raised by genome-wide interactional analysis, we have developed a novel statistic for testing interaction between two loci (either linked or unlinked. The null distribution and the type I error rates of the new statistic for testing interaction are validated using simulations. Extensive power studies show that the developed statistic has much higher power to detect interaction than classical logistic regression. The results identified 44 and 211 pairs of SNPs showing significant evidence of interactions with FDR<0.001 and 0.001analysis is a valuable tool for finding remaining missing heritability unexplained by the current GWAS, and the developed novel statistic is able to search significant interaction between SNPs across the genome. Real data analysis showed that the results of genome-wide interaction analysis can be replicated in two independent studies.

Evaluation of the effects of red blood cell distribution width on survival in lung cancer patients

Directory of Open Access Journals (Sweden)

Mehmet Kos

2016-06-01

Full Text Available Aim of the study : Data are available indicating that red blood cell distribution width (RDW is higher in cancer patients compared to healthy individuals or benign events. In our study, we aimed to investigate the influence of different RDW levels on survival in lung cancer patients. Material and methods: Clinical and laboratory data from 146 patients with lung cancer and 40 healthy subjects were retrospectively studied. RDW was recorded before the application of any treatment. Patients were categorised according to four different RDW cut-off values (median RDW, RDW determined by ROC curve analysis, the upper limit at the automatic blood count device, and RDW cut of value which used in previous studies. Kaplan-Meier survival analysis was used to examine the effect of RDW on survival for each cut-off level. Results : The median age of patients was 56.5 years (range: 26–83 years. The difference in median RDW between patients and the control group was statistically significant (14.0 and 13.8, respectively, p = 0.04. There was no difference with regard to overall survival when patients with RDW ≥ 14.0 were compared to those with RDW < 14.0 (p = 0.70; however, overall survival was 3.0 months shorter in low values of its own group in each of the following cut-off values: ≥ 14.2 (p = 0.34, ≥ 14.5 (p = 0.25, ≥ 15 (p = 0.59, although no results were statistically significant. Discussion : We consider that the difference between low and high RDW values according to certain cut-off values may reflect the statistics of larger studies although there is a statistically negative correlation between RDW level and survival.

Survival analysis approach to account for non-exponential decay rate effects in lifetime experiments

International Nuclear Information System (INIS)

Coakley, K.J.; Dewey, M.S.; Huber, M.G.; Huffer, C.R.; Huffman, P.R.; Marley, D.E.; Mumm, H.P.; O'Shaughnessy, C.M.; Schelhammer, K.W.; Thompson, A.K.; Yue, A.T.

2016-01-01

In experiments that measure the lifetime of trapped particles, in addition to loss mechanisms with exponential survival probability functions, particles can be lost by mechanisms with non-exponential survival probability functions. Failure to account for such loss mechanisms produces systematic measurement error and associated systematic uncertainties in these measurements. In this work, we develop a general competing risks survival analysis method to account for the joint effect of loss mechanisms with either exponential or non-exponential survival probability functions, and a method to quantify the size of systematic effects and associated uncertainties for lifetime estimates. As a case study, we apply our survival analysis formalism and method to the Ultra Cold Neutron lifetime experiment at NIST. In this experiment, neutrons can escape a magnetic trap before they decay due to a wall loss mechanism with an associated non-exponential survival probability function.

Survival analysis approach to account for non-exponential decay rate effects in lifetime experiments

Energy Technology Data Exchange (ETDEWEB)

Coakley, K.J., E-mail: kevincoakley@nist.gov [National Institute of Standards and Technology, 325 Broadway, Boulder, CO 80305 (United States); Dewey, M.S.; Huber, M.G. [National Institute of Standards and Technology, 100 Bureau Drive, Stop 8461, Gaithersburg, MD 20899 (United States); Huffer, C.R.; Huffman, P.R. [North Carolina State University, 2401 Stinson Drive, Box 8202, Raleigh, NC 27695 (United States); Triangle Universities Nuclear Laboratory, 116 Science Drive, Box 90308, Durham, NC 27708 (United States); Marley, D.E. [National Institute of Standards and Technology, 100 Bureau Drive, Stop 8461, Gaithersburg, MD 20899 (United States); North Carolina State University, 2401 Stinson Drive, Box 8202, Raleigh, NC 27695 (United States); Mumm, H.P. [National Institute of Standards and Technology, 100 Bureau Drive, Stop 8461, Gaithersburg, MD 20899 (United States); O' Shaughnessy, C.M. [University of North Carolina at Chapel Hill, 120 E. Cameron Ave., CB #3255, Chapel Hill, NC 27599 (United States); Triangle Universities Nuclear Laboratory, 116 Science Drive, Box 90308, Durham, NC 27708 (United States); Schelhammer, K.W. [North Carolina State University, 2401 Stinson Drive, Box 8202, Raleigh, NC 27695 (United States); Triangle Universities Nuclear Laboratory, 116 Science Drive, Box 90308, Durham, NC 27708 (United States); Thompson, A.K.; Yue, A.T. [National Institute of Standards and Technology, 100 Bureau Drive, Stop 8461, Gaithersburg, MD 20899 (United States)

2016-03-21

In experiments that measure the lifetime of trapped particles, in addition to loss mechanisms with exponential survival probability functions, particles can be lost by mechanisms with non-exponential survival probability functions. Failure to account for such loss mechanisms produces systematic measurement error and associated systematic uncertainties in these measurements. In this work, we develop a general competing risks survival analysis method to account for the joint effect of loss mechanisms with either exponential or non-exponential survival probability functions, and a method to quantify the size of systematic effects and associated uncertainties for lifetime estimates. As a case study, we apply our survival analysis formalism and method to the Ultra Cold Neutron lifetime experiment at NIST. In this experiment, neutrons can escape a magnetic trap before they decay due to a wall loss mechanism with an associated non-exponential survival probability function.

A statistical approach to plasma profile analysis

International Nuclear Information System (INIS)

Kardaun, O.J.W.F.; McCarthy, P.J.; Lackner, K.; Riedel, K.S.

1990-05-01

A general statistical approach to the parameterisation and analysis of tokamak profiles is presented. The modelling of the profile dependence on both the radius and the plasma parameters is discussed, and pertinent, classical as well as robust, methods of estimation are reviewed. Special attention is given to statistical tests for discriminating between the various models, and to the construction of confidence intervals for the parameterised profiles and the associated global quantities. The statistical approach is shown to provide a rigorous approach to the empirical testing of plasma profile invariance. (orig.)

Study designs, use of statistical tests, and statistical analysis software choice in 2015: Results from two Pakistani monthly Medline indexed journals.

Science.gov (United States)

Shaikh, Masood Ali

2017-09-01

Assessment of research articles in terms of study designs used, statistical tests applied and the use of statistical analysis programmes help determine research activity profile and trends in the country. In this descriptive study, all original articles published by Journal of Pakistan Medical Association (JPMA) and Journal of the College of Physicians and Surgeons Pakistan (JCPSP), in the year 2015 were reviewed in terms of study designs used, application of statistical tests, and the use of statistical analysis programmes. JPMA and JCPSP published 192 and 128 original articles, respectively, in the year 2015. Results of this study indicate that cross-sectional study design, bivariate inferential statistical analysis entailing comparison between two variables/groups, and use of statistical software programme SPSS to be the most common study design, inferential statistical analysis, and statistical analysis software programmes, respectively. These results echo previously published assessment of these two journals for the year 2014.

Statistical analysis of brake squeal noise

Science.gov (United States)

Oberst, S.; Lai, J. C. S.

2011-06-01

Despite substantial research efforts applied to the prediction of brake squeal noise since the early 20th century, the mechanisms behind its generation are still not fully understood. Squealing brakes are of significant concern to the automobile industry, mainly because of the costs associated with warranty claims. In order to remedy the problems inherent in designing quieter brakes and, therefore, to understand the mechanisms, a design of experiments study, using a noise dynamometer, was performed by a brake system manufacturer to determine the influence of geometrical parameters (namely, the number and location of slots) of brake pads on brake squeal noise. The experimental results were evaluated with a noise index and ranked for warm and cold brake stops. These data are analysed here using statistical descriptors based on population distributions, and a correlation analysis, to gain greater insight into the functional dependency between the time-averaged friction coefficient as the input and the peak sound pressure level data as the output quantity. The correlation analysis between the time-averaged friction coefficient and peak sound pressure data is performed by applying a semblance analysis and a joint recurrence quantification analysis. Linear measures are compared with complexity measures (nonlinear) based on statistics from the underlying joint recurrence plots. Results show that linear measures cannot be used to rank the noise performance of the four test pad configurations. On the other hand, the ranking of the noise performance of the test pad configurations based on the noise index agrees with that based on nonlinear measures: the higher the nonlinearity between the time-averaged friction coefficient and peak sound pressure, the worse the squeal. These results highlight the nonlinear character of brake squeal and indicate the potential of using nonlinear statistical analysis tools to analyse disc brake squeal.

The Statistical Analysis of Time Series

CERN Document Server

Anderson, T W

2011-01-01

The Wiley Classics Library consists of selected books that have become recognized classics in their respective fields. With these new unabridged and inexpensive editions, Wiley hopes to extend the life of these important works by making them available to future generations of mathematicians and scientists. Currently available in the Series: T. W. Anderson Statistical Analysis of Time Series T. S. Arthanari & Yadolah Dodge Mathematical Programming in Statistics Emil Artin Geometric Algebra Norman T. J. Bailey The Elements of Stochastic Processes with Applications to the Natural Sciences George

Analysis of room transfer function and reverberant signal statistics

DEFF Research Database (Denmark)

Georganti, Eleftheria; Mourjopoulos, John; Jacobsen, Finn

2008-01-01

For some time now, statistical analysis has been a valuable tool in analyzing room transfer functions (RTFs). This work examines existing statistical time-frequency models and techniques for RTF analysis (e.g., Schroeder's stochastic model and the standard deviation over frequency bands for the RTF...... magnitude and phase). RTF fractional octave smoothing, as with 1-slash 3 octave analysis, may lead to RTF simplifications that can be useful for several audio applications, like room compensation, room modeling, auralisation purposes. The aim of this work is to identify the relationship of optimal response...... and the corresponding ratio of the direct and reverberant signal. In addition, this work examines the statistical quantities for speech and audio signals prior to their reproduction within rooms and when recorded in rooms. Histograms and other statistical distributions are used to compare RTF minima of typical...

Survival analysis in patients with metastatic spinal disease: the influence of surgery, histology, clinical and neurologic status

Directory of Open Access Journals (Sweden)

Matheus Fernandes de Oliveira

2015-04-01

Full Text Available Spine is the most common site for skeletal metastasis in patients with malignancy. Vertebral involvement quantification, neurological status, general health status and primary tumor histology are factors to set surgical planning and therapeutic targets. We evaluated the impact of general clinical and neurological status, histologic type and surgery in survival. Method : The study sample consisted of consecutive patients admitted from July 2010 to January 2013 for treatment. Results : Sixty eight patients were evaluated. 23 were female and 45 were male. Main primary neoplasic sites were: breast, prostate, lung/pleura and linfoproliferative. Thirty three out of 68 received surgical treatment, 2 received percutaneous biopsy and 33 had nonsurgical treatment. Survival : Log Rank curves revealed no statistical significant difference according to histological type, surgical approach and Frankel Score. Karnofsky Score was statistically different. Conclusion : Histological type and clinical status were statistically associated with life expectancy in vertebral metastatic disease.

Statistical considerations of graphite strength for assessing design allowable stresses

International Nuclear Information System (INIS)

Ishihara, M.; Mogi, H.; Ioka, I.; Arai, T.; Oku, T.

1987-01-01

Several aspects of statistics need to be considered to determine design allowable stresses for graphite structures. These include: 1) Statistical variation of graphite material strength. 2) Uncertainty of calculated stress. 3) Reliability (survival probability) required from operational and safety performance of graphite structures. This paper deals with some statistical considerations of structural graphite for assessing design allowable stress. Firstly, probability distribution functions of tensile and compressive strengths are investigated on experimental Very High Temperature candidated graphites. Normal, logarithmic normal and Weibull distribution functions are compared in terms of coefficient of correlation to measured strength data. This leads to the adaptation of normal distribution function. Then, the relation between factor of safety and fracture probability is discussed on the following items: 1) As the graphite strength is more variable than metalic material's strength, the effect of strength variation to the fracture probability is evaluated. 2) Fracture probability depending on survival probability of 99 ∼ 99.9 (%) with confidence level of 90 ∼ 95 (%) is discussed. 3) As the material properties used in the design analysis are usually the mean values of their variation, the additional effect of these variations on the fracture probability is discussed. Finally, the way to assure the minimum ultimate strength with required survival probability with confidence level is discussed in view of statistical treatment of the strength data from varying sample numbers in a material acceptance test. (author)

Survival after Second and Subsequent Recurrences in Osteosarcoma: A Retrospective Multicenter Analysis.

Science.gov (United States)

Tirtei, Elisa; Asaftei, Sebastian D; Manicone, Rosaria; Cesari, Marilena; Paioli, Anna; Rocca, Michele; Ferrari, Stefano; Fagioli, Franca

2017-05-01

Purpose Osteosarcoma (OS) is the most common primary bone tumor. Despite complete surgical removal and intensive chemotherapeutic treatment, 30%-35% of patients with OS have local or systemic recurrence. Some patients survive multiple recurrences, but overall survival after OS recurrence is poor. This analysis aims to describe and identify factors influencing post-relapse survival (PRS) after a second OS relapse. Methods This is a retrospective analysis of 60 patients with a second relapse of OS of the extremities in 2 Italian centers between 2003 and 2013. Results Treatment for first and subsequent relapses was planned according to institutional guidelines. After complete surgical remission (CSR) following the first recurrence, patients experienced a second OS relapse with a median disease-free interval (DFI) of 6 months. Lung disease was prevalent: 44 patients (76%) had pulmonary metastases. Survival after the second relapse was 22% at 5 years. Lung disease only correlated with better survival at 5 years (33.6%) compared with other sites of recurrence (5%; p = 0.008). Patients with a single pulmonary lesion had a better 5-year second PRS (42%; p = 0.02). Patients who achieved a second CSR had a 5-year second PRS of 33.4%. Chemotherapy (p<0.001) benefited patients without a third CSR. Conclusions This analysis confirms the importance of an aggressive, repeated surgical approach. Lung metastases only, the number of lesions, DFI and CSR influenced survival. It also confirms the importance of chemotherapy in patients in whom surgical treatment is not feasible.

New applications of statistical tools in plant pathology.

Science.gov (United States)

Garrett, K A; Madden, L V; Hughes, G; Pfender, W F

2004-09-01

ABSTRACT The series of papers introduced by this one address a range of statistical applications in plant pathology, including survival analysis, nonparametric analysis of disease associations, multivariate analyses, neural networks, meta-analysis, and Bayesian statistics. Here we present an overview of additional applications of statistics in plant pathology. An analysis of variance based on the assumption of normally distributed responses with equal variances has been a standard approach in biology for decades. Advances in statistical theory and computation now make it convenient to appropriately deal with discrete responses using generalized linear models, with adjustments for overdispersion as needed. New nonparametric approaches are available for analysis of ordinal data such as disease ratings. Many experiments require the use of models with fixed and random effects for data analysis. New or expanded computing packages, such as SAS PROC MIXED, coupled with extensive advances in statistical theory, allow for appropriate analyses of normally distributed data using linear mixed models, and discrete data with generalized linear mixed models. Decision theory offers a framework in plant pathology for contexts such as the decision about whether to apply or withhold a treatment. Model selection can be performed using Akaike's information criterion. Plant pathologists studying pathogens at the population level have traditionally been the main consumers of statistical approaches in plant pathology, but new technologies such as microarrays supply estimates of gene expression for thousands of genes simultaneously and present challenges for statistical analysis. Applications to the study of the landscape of the field and of the genome share the risk of pseudoreplication, the problem of determining the appropriate scale of the experimental unit and of obtaining sufficient replication at that scale.

Advanced statistical methods to study the effects of gastric tube and non-invasive ventilation on functional decline and survival in amyotrophic lateral sclerosis.

Science.gov (United States)

Atassi, Nazem; Cudkowicz, Merit E; Schoenfeld, David A

2011-07-01

A few studies suggest that non-invasive ventilation (1) and gastric tube (G-tube) may have a positive impact on survival but the effect on functional decline is unclear. Confounding by indication may have produced biased estimates of the benefit seen in some of these retrospective studies. The objective of this study was to evaluate the effects of G-tube and NIV on survival and functional decline using advanced statistical models that adjust for confounding by indications. A database of 331 subjects enrolled in previous clinical trials in ALS was available for analysis. Marginal structural models (MSM) were used to compare the mortality hazards and ALSFRS-R slopes between treatment and non-treatment groups, after adjusting for confounding by indication. Results showed that the placement of a G-tube was associated with an additional 1.42 units/month decline in the ALSFRS-R slope (p NIV had no significant effect on ALSFRS-R decline or mortality. In conclusion, marginal structural models can be used to adjust for confounding by indication in retrospective ALS studies. G-tube placement could be followed by a faster rate of functional decline and increased mortality. Our results may suffer from some of the limitations of retrospective analyses.

Transit safety & security statistics & analysis 2002 annual report (formerly SAMIS)

Science.gov (United States)

2004-12-01

The Transit Safety & Security Statistics & Analysis 2002 Annual Report (formerly SAMIS) is a compilation and analysis of mass transit accident, casualty, and crime statistics reported under the Federal Transit Administrations (FTAs) National Tr...

Transit safety & security statistics & analysis 2003 annual report (formerly SAMIS)

Science.gov (United States)

2005-12-01

The Transit Safety & Security Statistics & Analysis 2003 Annual Report (formerly SAMIS) is a compilation and analysis of mass transit accident, casualty, and crime statistics reported under the Federal Transit Administrations (FTAs) National Tr...

A retrospective analysis of survival and prognostic factors after stereotactic radiosurgery for aggressive meningiomas

International Nuclear Information System (INIS)

Ferraro, Daniel J; Zoberi, Imran; Simpson, Joseph R; Jaboin, Jerry J; Funk, Ryan K; Blackett, John William; Ju, Michelle R; DeWees, Todd A; Chicoine, Michael R; Dowling, Joshua L; Rich, Keith M; Drzymala, Robert E

2014-01-01

While most meningiomas are benign, aggressive meningiomas are associated with high levels of recurrence and mortality. A single institution’s Gamma Knife radiosurgical experience with atypical and malignant meningiomas is presented, stratified by the most recent WHO classification. Thirty-one patients with atypical and 4 patients with malignant meningiomas treated with Gamma Knife radiosurgery between July 2000 and July 2011 were retrospectively reviewed. All patients underwent prior surgical resection. Overall survival was the primary endpoint and rate of disease recurrence in the brain was a secondary endpoint. Patients who had previous radiotherapy or prior surgical resection were included. Kaplan-Meier and Cox proportional hazards models were used to estimate survival and identify factors predictive of recurrence and survival. Post-Gamma Knife recurrence was identified in 11 patients (31.4%) with a median overall survival of 36 months and progression-free survival of 25.8 months. Nine patients (25.7%) had died. Three-year overall survival (OS) and progression-free survival (PFS) rates were 78.0% and 65.0%, respectively. WHO grade II 3-year OS and PFS were 83.4% and 70.1%, while WHO grade III 3-year OS and PFS were 33.3% and 0%. Recurrence rate was significantly higher in patients with a prior history of benign meningioma, nuclear atypia, high mitotic rate, spontaneous necrosis, and WHO grade III diagnosis on univariate analysis; only WHO grade III diagnosis was significant on multivariate analysis. Overall survival was adversely affected in patients with WHO grade III diagnosis, prior history of benign meningioma, prior fractionated radiotherapy, larger tumor volume, and higher isocenter number on univariate analysis; WHO grade III diagnosis and larger treated tumor volume were significant on multivariate analysis. Atypical and anaplastic meningiomas remain difficult tumors to treat. WHO grade III diagnosis and treated tumor volume were significantly

Statistical Modelling of Wind Proles - Data Analysis and Modelling

DEFF Research Database (Denmark)

Jónsson, Tryggvi; Pinson, Pierre

The aim of the analysis presented in this document is to investigate whether statistical models can be used to make very short-term predictions of wind profiles.......The aim of the analysis presented in this document is to investigate whether statistical models can be used to make very short-term predictions of wind profiles....

Statistical analysis of long term spatial and temporal trends of ...

Indian Academy of Sciences (India)

Statistical analysis of long term spatial and temporal trends of temperature ... CGCM3; HadCM3; modified Mann–Kendall test; statistical analysis; Sutlej basin. ... Water Resources Systems Division, National Institute of Hydrology, Roorkee 247 ...

Survival after elective surgery for colonic cancer in Denmark

DEFF Research Database (Denmark)

Perdawid, S K; Hemmingsen, L; Boesby, S

2012-01-01

AIM: Total mesorectal excision (TME) has been shown to improve the outcome for patients with rectal cancer. In contrast, there are fewer data on complete mesocolic excision (CME) for colonic cancer. METHOD: Data from the National Colorectal Cancer Database were analysed. This includes about 95......% of all patients with colorectal cancer in Denmark. Only patients having elective surgery for colonic cancer in the period 2001-2008 were included. Overall and relative survival analyses were carried out. The study period was divided into the periods 2001-2004 and 2005-2008. RESULTS: 9149 patients were...... included for the final analysis. The overall 5-year survival rates were 0.65 in 2001-2004 and 0.66 in 2005-2008. The relative 5-year survival rates were also within 1% of each other. None of these comparisons was statistically significant. CONCLUSION: Survival following elective colon cancer surgery has...

CORSSA: The Community Online Resource for Statistical Seismicity Analysis

Science.gov (United States)

Michael, Andrew J.; Wiemer, Stefan

2010-01-01

Statistical seismology is the application of rigorous statistical methods to earthquake science with the goal of improving our knowledge of how the earth works. Within statistical seismology there is a strong emphasis on the analysis of seismicity data in order to improve our scientific understanding of earthquakes and to improve the evaluation and testing of earthquake forecasts, earthquake early warning, and seismic hazards assessments. Given the societal importance of these applications, statistical seismology must be done well. Unfortunately, a lack of educational resources and available software tools make it difficult for students and new practitioners to learn about this discipline. The goal of the Community Online Resource for Statistical Seismicity Analysis (CORSSA) is to promote excellence in statistical seismology by providing the knowledge and resources necessary to understand and implement the best practices, so that the reader can apply these methods to their own research. This introduction describes the motivation for and vision of CORRSA. It also describes its structure and contents.

Multivariate statistical analysis a high-dimensional approach

CERN Document Server

Serdobolskii, V

2000-01-01

In the last few decades the accumulation of large amounts of in­ formation in numerous applications. has stimtllated an increased in­ terest in multivariate analysis. Computer technologies allow one to use multi-dimensional and multi-parametric models successfully. At the same time, an interest arose in statistical analysis with a de­ ficiency of sample data. Nevertheless, it is difficult to describe the recent state of affairs in applied multivariate methods as satisfactory. Unimprovable (dominating) statistical procedures are still unknown except for a few specific cases. The simplest problem of estimat­ ing the mean vector with minimum quadratic risk is unsolved, even for normal distributions. Commonly used standard linear multivari­ ate procedures based on the inversion of sample covariance matrices can lead to unstable results or provide no solution in dependence of data. Programs included in standard statistical packages cannot process 'multi-collinear data' and there are no theoretical recommen­ ...

Surrogacy of progression-free survival (PFS) for overall survival (OS) in esophageal cancer trials with preoperative therapy: Literature-based meta-analysis.

Science.gov (United States)

Kataoka, K; Nakamura, K; Mizusawa, J; Kato, K; Eba, J; Katayama, H; Shibata, T; Fukuda, H

2017-10-01

There have been no reports evaluating progression-free survival (PFS) as a surrogate endpoint in resectable esophageal cancer. This study was conducted to evaluate the trial level correlations between PFS and overall survival (OS) in resectable esophageal cancer with preoperative therapy and to explore the potential benefit of PFS as a surrogate endpoint for OS. A systematic literature search of randomized trials with preoperative chemotherapy or preoperative chemoradiotherapy for esophageal cancer reported from January 1990 to September 2014 was conducted using PubMed and the Cochrane Library. Weighted linear regression using sample size of each trial as a weight was used to estimate coefficient of determination (R 2 ) within PFS and OS. The primary analysis included trials in which the HR for both PFS and OS was reported. The sensitivity analysis included trials in which either HR or median survival time of PFS and OS was reported. In the sensitivity analysis, HR was estimated from the median survival time of PFS and OS, assuming exponential distribution. Of 614 articles, 10 trials were selected for the primary analysis and 15 for the sensitivity analysis. The primary analysis did not show a correlation between treatment effects on PFS and OS (R 2 0.283, 95% CI [0.00-0.90]). The sensitivity analysis did not show an association between PFS and OS (R 2 0.084, 95% CI [0.00-0.70]). Although the number of randomized controlled trials evaluating preoperative therapy for esophageal cancer is limited at the moment, PFS is not suitable for primary endpoint as a surrogate endpoint for OS. Copyright © 2017 Elsevier Ltd, BASO ~ The Association for Cancer Surgery, and the European Society of Surgical Oncology. All rights reserved.

Applied multivariate statistical analysis

CERN Document Server

Härdle, Wolfgang Karl

2015-01-01

Focusing on high-dimensional applications, this 4th edition presents the tools and concepts used in multivariate data analysis in a style that is also accessible for non-mathematicians and practitioners.  It surveys the basic principles and emphasizes both exploratory and inferential statistics; a new chapter on Variable Selection (Lasso, SCAD and Elastic Net) has also been added.  All chapters include practical exercises that highlight applications in different multivariate data analysis fields: in quantitative financial studies, where the joint dynamics of assets are observed; in medicine, where recorded observations of subjects in different locations form the basis for reliable diagnoses and medication; and in quantitative marketing, where consumers’ preferences are collected in order to construct models of consumer behavior.  All of these examples involve high to ultra-high dimensions and represent a number of major fields in big data analysis. The fourth edition of this book on Applied Multivariate ...

Prognostic factors in patients with advanced cancer: use of the patient-generated subjective global assessment in survival prediction.

Science.gov (United States)

Martin, Lisa; Watanabe, Sharon; Fainsinger, Robin; Lau, Francis; Ghosh, Sunita; Quan, Hue; Atkins, Marlis; Fassbender, Konrad; Downing, G Michael; Baracos, Vickie

2010-10-01

To determine whether elements of a standard nutritional screening assessment are independently prognostic of survival in patients with advanced cancer. A prospective nested cohort of patients with metastatic cancer were accrued from different units of a Regional Palliative Care Program. Patients completed a nutritional screen on admission. Data included age, sex, cancer site, height, weight history, dietary intake, 13 nutrition impact symptoms, and patient- and physician-reported performance status (PS). Univariate and multivariate survival analyses were conducted. Concordance statistics (c-statistics) were used to test the predictive accuracy of models based on training and validation sets; a c-statistic of 0.5 indicates the model predicts the outcome as well as chance; perfect prediction has a c-statistic of 1.0. A training set of patients in palliative home care (n = 1,164) was used to identify prognostic variables. Primary disease site, PS, short-term weight change (either gain or loss), dietary intake, and dysphagia predicted survival in multivariate analysis (P statistics between predicted and observed responses for survival in the training set (0.90) and validation set (0.88; n = 603). The addition of weight change, dietary intake, and dysphagia did not further improve the c-statistic of the model. The c-statistic was also not altered by substituting physician-rated palliative PS for patient-reported PS. We demonstrate a high probability of concordance between predicted and observed survival for patients in distinct palliative care settings (home care, tertiary inpatient, ambulatory outpatient) based on patient-reported information.

[Comparative evaluation of survival prognosis using MELD or Child-Pugh scores in patients with liver cirrhosis in Chile].

Science.gov (United States)

Sanhueza, Edgar; Contreras, Jorge; Zapata, Rodrigo; Sanhueza, Matías; Elgueta, Fabián; López, Constanza; Jerez, Sigrid; Jerez, Verónica; Delgado, Iris

2017-01-01

Currently, most liver units use the Child-Pugh (CP) or the Model for End-Stage Liver Disease (MELD) scores to establish survival prognosis among patients with liver cirrhosis. Which classification is superior, is not well defined. To compare CP and MELD classification scores to predict survival among adult patients with liver cirrhosis in Chile. Follow-up of 137 consecutive adult patients with liver cirrhosis aged 59 ± 12 years (55% women). The diagnosis was reached by clinical, laboratory and image studies at three different centers of Santiago. Patients were staged with CP and MELD classification scores at baseline and followed over a period of 12 months. The predictive capacity of the scores for survival was analyzed using a multivariate statistical analysis (Kaplan-Meier curves). The most common etiology was alcohol (37.9%). The actuarial survival rate was 79.6% at 12 months of follow-up. When comparing groups with areas under curve of receiver operating characteristic curves (AUROC), there was no statistically significant difference in survival between less severe and advanced disease, assessed with both survival scales. The AUROC for MELD and CP were 0.80 and 0.81, respectively. This clinical study did not find a statistically significant difference between the two classifications for the prediction of 12 months survival in patients with cirrhosis.

Statistical evaluation of vibration analysis techniques

Science.gov (United States)

Milner, G. Martin; Miller, Patrice S.

1987-01-01

An evaluation methodology is presented for a selection of candidate vibration analysis techniques applicable to machinery representative of the environmental control and life support system of advanced spacecraft; illustrative results are given. Attention is given to the statistical analysis of small sample experiments, the quantification of detection performance for diverse techniques through the computation of probability of detection versus probability of false alarm, and the quantification of diagnostic performance.

HistFitter software framework for statistical data analysis

CERN Document Server

Baak, M.; Côte, D.; Koutsman, A.; Lorenz, J.; Short, D.

2015-01-01

We present a software framework for statistical data analysis, called HistFitter, that has been used extensively by the ATLAS Collaboration to analyze big datasets originating from proton-proton collisions at the Large Hadron Collider at CERN. Since 2012 HistFitter has been the standard statistical tool in searches for supersymmetric particles performed by ATLAS. HistFitter is a programmable and flexible framework to build, book-keep, fit, interpret and present results of data models of nearly arbitrary complexity. Starting from an object-oriented configuration, defined by users, the framework builds probability density functions that are automatically fitted to data and interpreted with statistical tests. A key innovation of HistFitter is its design, which is rooted in core analysis strategies of particle physics. The concepts of control, signal and validation regions are woven into its very fabric. These are progressively treated with statistically rigorous built-in methods. Being capable of working with mu...

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.

Survival Prediction in Pancreatic Ductal Adenocarcinoma by Quantitative Computed Tomography Image Analysis.

Science.gov (United States)

Attiyeh, Marc A; Chakraborty, Jayasree; Doussot, Alexandre; Langdon-Embry, Liana; Mainarich, Shiana; Gönen, Mithat; Balachandran, Vinod P; D'Angelica, Michael I; DeMatteo, Ronald P; Jarnagin, William R; Kingham, T Peter; Allen, Peter J; Simpson, Amber L; Do, Richard K

2018-04-01

Pancreatic cancer is a highly lethal cancer with no established a priori markers of survival. Existing nomograms rely mainly on post-resection data and are of limited utility in directing surgical management. This study investigated the use of quantitative computed tomography (CT) features to preoperatively assess survival for pancreatic ductal adenocarcinoma (PDAC) patients. A prospectively maintained database identified consecutive chemotherapy-naive patients with CT angiography and resected PDAC between 2009 and 2012. Variation in CT enhancement patterns was extracted from the tumor region using texture analysis, a quantitative image analysis tool previously described in the literature. Two continuous survival models were constructed, with 70% of the data (training set) using Cox regression, first based only on preoperative serum cancer antigen (CA) 19-9 levels and image features (model A), and then on CA19-9, image features, and the Brennan score (composite pathology score; model B). The remaining 30% of the data (test set) were reserved for independent validation. A total of 161 patients were included in the analysis. Training and test sets contained 113 and 48 patients, respectively. Quantitative image features combined with CA19-9 achieved a c-index of 0.69 [integrated Brier score (IBS) 0.224] on the test data, while combining CA19-9, imaging, and the Brennan score achieved a c-index of 0.74 (IBS 0.200) on the test data. We present two continuous survival prediction models for resected PDAC patients. Quantitative analysis of CT texture features is associated with overall survival. Further work includes applying the model to an external dataset to increase the sample size for training and to determine its applicability.

Lung Shunt Fraction prior to Yttrium-90 Radioembolization Predicts Survival in Patients with Neuroendocrine Liver Metastases: Single-Center Prospective Analysis

Energy Technology Data Exchange (ETDEWEB)

Ludwig, Johannes M. [Yale University, Division of Interventional Radiology, Department of Radiology and Biomedical Imaging (United States); Ambinder, Emily McIntosh [John Hopkins University School of Medicine, Department of Diagnostic Radiology (United States); Ghodadra, Anish [University of Pittsburgh School of Medicine, Interventional Radiology, Department of Radiology (United States); Xing, Minzhi [Yale University, Division of Interventional Radiology, Department of Radiology and Biomedical Imaging (United States); Prajapati, Hasmukh J. [The University of Tennessee Health Science Center, Division of Interventional Radiology, Department of Radiology (United States); Kim, Hyun S., E-mail: kevin.kim@yale.edu [Yale University, Division of Interventional Radiology, Department of Radiology and Biomedical Imaging (United States)

2016-07-15

ObjectiveTo investigate survival outcomes following radioembolization with Yttrium-90 (Y90) for neuroendocrine tumor liver metastases (NETLMs). This study was designed to assess the efficacy of Y90 radioembolization and to evaluate lung shunt fraction (LSF) as a predictor for survival.MethodsA single-center, prospective study of 44 consecutive patients (median age: 58.5 years, 29.5 % male) diagnosed with pancreatic (52.3 %) or carcinoid (47.7 %) NETLMs from 2006 to 2012 who underwent Y90 radioembolization was performed. Patients’ baseline characteristics, including LSF and median overall survival (OS) from first Y90 radioembolization, were recorded and compared between patients with high (≥10 %) and low (<10 %) LSF. Baseline comparisons were performed using Fisher’s exact tests for categorical and Mann–Whitney U test for continuous variables. Survival was calculated using the Kaplan–Meier method. Univariate (Wilcoxon rank-sum test) and multivariate analyses (Cox Proportional Hazard Model) for risk factor analysis were performed.ResultsThere was no statistically significant difference in age, gender, race, tumor properties, or previous treatments between patients with high (n = 15) and low (n = 29) LSF. The median OS was 27.4 months (95 %CI 12.73–55.23), with 4.77 months (95 %CI 2.87–26.73) for high and 42.77 months (95 %CI 18.47–59.73) for low LSF (p = 0.003). Multivariate analysis identified high LSF (p = 0.001), total serum bilirubin >1.2 mg (p = 0.016), and lack of pretreatment with octreotide (p = 0.01) as independent prognostic factors for poorer survival. Tumor type and total radiation dose did not predict survival.ConclusionsLSF ≥10 %, elevated bilirubin levels, and lack of pretreatment with octreotide were found to be independent prognostic factors for poorer survival in patients with NETLMs.

Statistical analysis on extreme wave height

Digital Repository Service at National Institute of Oceanography (India)

Teena, N.V.; SanilKumar, V.; Sudheesh, K.; Sajeev, R.

-294. • WAFO (2000) – A MATLAB toolbox for analysis of random waves and loads, Lund University, Sweden, homepage http://www.maths.lth.se/matstat/wafo/,2000. 15    Table 1: Statistical results of data and fitted distribution for cumulative distribution...

The prognostic factors affecting survival in muscle invasive bladder cancer treated with radiotherapy

International Nuclear Information System (INIS)

Chung, Woong Ki; Oh, Bong Ryoul; Ahn, Sung Ja; Nah, Byung Sik; Kwon, Dong Deuk; Park, Kwang Sung; Ryu, Soo Bang; Park, Yang Il

2002-01-01

This study analyzed the prognostic factors affecting the survival rate and evaluated the role of radiation therapy in muscle-invading bladder cancer. Twenty eight patient with bladder cancer who completed planned definitive radiotherapy in the Departments of Therapeutic Radiology and Urology, Chonnam National University Hospital between Jan. 1986 to Dec. 1998 were retrospectively analyzed. The reviews were performed based on the patients' medical records. There were 21 males and 7 females in this study. The median of age was 72 years old ranging from 49 to 84 years. All patients were confirmed as having transitional cell carcinoma with histological grade 1 in one patient, grade 2 in 15, grade 3 in 9, and uniformed in 3. Radiation therapy was performed using a linear accelerator with 6 or 10 MV X-rays. Radiation was delivered daily with a 1.8 or 2.0 Gy fraction size by 4 ports (anterior-posterior, both lateral, alternatively) or 3 ports (Anterior and both lateral). The median radiation dose delivered to the isocenter of the target volume was 61.24 Gy ranging from 59 to 66.6 Gy. The survival rate was calculated by the Kaplan-Meier method. Multivariate analysis was performed on the prognostic factors affecting the survival rate. The survival rate was 76%, 46%, 33%, 33% at 1, 2, 3, 5 years, respectively, with 19 months of median survival. The potential factors of age (less than 70 years vs above 70), sex, diabetes mellitus, hypertension, hydronephrosis, T-stage (T3a vs T3b), TUR, chemotherapy, total duration of radiotherapy, radiation dose (less than 60 Gy vs above 60 Gy), and the treatment response were investigated with uni- and multivariate analysis. In univariate analysis, the T-stage (ρ 0.078) and radiation dose (ρ = 0.051) were marginally significant, and the treatment response (ρ = 0.011) was a statistically significant factor on the survival rate. Multivariate analysis showed there were no significant prognostic factors affecting the survival rate. The

The prognostic factors affecting survival in muscle invasive bladder cancer treated with radiotherapy

Energy Technology Data Exchange (ETDEWEB)

Chung, Woong Ki; Oh, Bong Ryoul; Ahn, Sung Ja; Nah, Byung Sik; Kwon, Dong Deuk; Park, Kwang Sung; Ryu, Soo Bang; Park, Yang Il [Chonnam National University Medical School, Chonnam National University Hospital, Kwangju (Korea, Republic of)

2002-06-15

This study analyzed the prognostic factors affecting the survival rate and evaluated the role of radiation therapy in muscle-invading bladder cancer. Twenty eight patient with bladder cancer who completed planned definitive radiotherapy in the Departments of Therapeutic Radiology and Urology, Chonnam National University Hospital between Jan. 1986 to Dec. 1998 were retrospectively analyzed. The reviews were performed based on the patients' medical records. There were 21 males and 7 females in this study. The median of age was 72 years old ranging from 49 to 84 years. All patients were confirmed as having transitional cell carcinoma with histological grade 1 in one patient, grade 2 in 15, grade 3 in 9, and uniformed in 3. Radiation therapy was performed using a linear accelerator with 6 or 10 MV X-rays. Radiation was delivered daily with a 1.8 or 2.0 Gy fraction size by 4 ports (anterior-posterior, both lateral, alternatively) or 3 ports (Anterior and both lateral). The median radiation dose delivered to the isocenter of the target volume was 61.24 Gy ranging from 59 to 66.6 Gy. The survival rate was calculated by the Kaplan-Meier method. Multivariate analysis was performed on the prognostic factors affecting the survival rate. The survival rate was 76%, 46%, 33%, 33% at 1, 2, 3, 5 years, respectively, with 19 months of median survival. The potential factors of age (less than 70 years vs above 70), sex, diabetes mellitus, hypertension, hydronephrosis, T-stage (T3a vs T3b), TUR, chemotherapy, total duration of radiotherapy, radiation dose (less than 60 Gy vs above 60 Gy), and the treatment response were investigated with uni- and multivariate analysis. In univariate analysis, the T-stage ({rho} 0.078) and radiation dose ({rho} = 0.051) were marginally significant, and the treatment response ({rho} = 0.011) was a statistically significant factor on the survival rate. Multivariate analysis showed there were no significant prognostic factors affecting the survival

Statistical Analysis of Zebrafish Locomotor Response.

Science.gov (United States)

Liu, Yiwen; Carmer, Robert; Zhang, Gaonan; Venkatraman, Prahatha; Brown, Skye Ashton; Pang, Chi-Pui; Zhang, Mingzhi; Ma, Ping; Leung, Yuk Fai

2015-01-01

Zebrafish larvae display rich locomotor behaviour upon external stimulation. The movement can be simultaneously tracked from many larvae arranged in multi-well plates. The resulting time-series locomotor data have been used to reveal new insights into neurobiology and pharmacology. However, the data are of large scale, and the corresponding locomotor behavior is affected by multiple factors. These issues pose a statistical challenge for comparing larval activities. To address this gap, this study has analyzed a visually-driven locomotor behaviour named the visual motor response (VMR) by the Hotelling's T-squared test. This test is congruent with comparing locomotor profiles from a time period. Different wild-type (WT) strains were compared using the test, which shows that they responded differently to light change at different developmental stages. The performance of this test was evaluated by a power analysis, which shows that the test was sensitive for detecting differences between experimental groups with sample numbers that were commonly used in various studies. In addition, this study investigated the effects of various factors that might affect the VMR by multivariate analysis of variance (MANOVA). The results indicate that the larval activity was generally affected by stage, light stimulus, their interaction, and location in the plate. Nonetheless, different factors affected larval activity differently over time, as indicated by a dynamical analysis of the activity at each second. Intriguingly, this analysis also shows that biological and technical repeats had negligible effect on larval activity. This finding is consistent with that from the Hotelling's T-squared test, and suggests that experimental repeats can be combined to enhance statistical power. Together, these investigations have established a statistical framework for analyzing VMR data, a framework that should be generally applicable to other locomotor data with similar structure.

Main Clinical Outcomes of Feldspathic Porcelain and Glass-Ceramic Laminate Veneers: A Systematic Review and Meta-Analysis of Survival and Complication Rates.

Science.gov (United States)

Morimoto, Susana; Albanesi, Rafael Borges; Sesma, Newton; Agra, Carlos Martins; Braga, Mariana Minatel

2016-01-01

The aim of this study was to perform a systematic review and meta-analysis based on clinical trials that evaluated the main outcomes of glass-ceramic and feldspathic porcelain laminate veneers. A systematic search was carried out in Cochrane and PubMed databases. From the selected studies, the survival rates for porcelain and glass-ceramic veneers were extracted, as were complication rates of clinical outcomes: debonding, fracture/chipping, secondary caries, endodontic problems, severe marginal discoloration, and influence of incisal coverage and enamel/dentin preparation. The Cochran Q test and the I(2) statistic were used to evaluate heterogeneity. Out of the 899 articles initially identified, 13 were included for analysis. Metaregression analysis showed that the types of ceramics and follow-up periods had no influence on failure rate. The estimated overall cumulative survival rate was 89% (95% CI: 84% to 94%) in a median follow-up period of 9 years. The estimated survival for glass-ceramic was 94% (95% CI: 87% to 100%), and for feldspathic porcelain veneers, 87% (95% CI: 82% to 93%). The meta-analysis showed rates for the following events: debonding: 2% (95% CI: 1% to 4%); fracture/chipping: 4% (95% CI: 3% to 6%); secondary caries: 1% (95% CI: 0% to 3%); severe marginal discoloration: 2% (95% CI: 1% to 10%); endodontic problems: 2% (95% CI: 1% to 3%); and incisal coverage odds ratio: 1.25 (95% CI: 0.33 to 4.73). It was not possible to perform meta-analysis of the influence of enamel/dentin preparation on failure rates. Glass-ceramic and porcelain laminate veneers have high survival rates. Fracture/ chipping was the most frequent complication, providing evidence that ceramic veneers are a safe treatment option that preserve tooth structure.

Molecular Infectious Disease Epidemiology: Survival Analysis and Algorithms Linking Phylogenies to Transmission Trees

Science.gov (United States)

Kenah, Eben; Britton, Tom; Halloran, M. Elizabeth; Longini, Ira M.

2016-01-01

Recent work has attempted to use whole-genome sequence data from pathogens to reconstruct the transmission trees linking infectors and infectees in outbreaks. However, transmission trees from one outbreak do not generalize to future outbreaks. Reconstruction of transmission trees is most useful to public health if it leads to generalizable scientific insights about disease transmission. In a survival analysis framework, estimation of transmission parameters is based on sums or averages over the possible transmission trees. A phylogeny can increase the precision of these estimates by providing partial information about who infected whom. The leaves of the phylogeny represent sampled pathogens, which have known hosts. The interior nodes represent common ancestors of sampled pathogens, which have unknown hosts. Starting from assumptions about disease biology and epidemiologic study design, we prove that there is a one-to-one correspondence between the possible assignments of interior node hosts and the transmission trees simultaneously consistent with the phylogeny and the epidemiologic data on person, place, and time. We develop algorithms to enumerate these transmission trees and show these can be used to calculate likelihoods that incorporate both epidemiologic data and a phylogeny. A simulation study confirms that this leads to more efficient estimates of hazard ratios for infectiousness and baseline hazards of infectious contact, and we use these methods to analyze data from a foot-and-mouth disease virus outbreak in the United Kingdom in 2001. These results demonstrate the importance of data on individuals who escape infection, which is often overlooked. The combination of survival analysis and algorithms linking phylogenies to transmission trees is a rigorous but flexible statistical foundation for molecular infectious disease epidemiology. PMID:27070316

Time Series Analysis Based on Running Mann Whitney Z Statistics

Science.gov (United States)

A sensitive and objective time series analysis method based on the calculation of Mann Whitney U statistics is described. This method samples data rankings over moving time windows, converts those samples to Mann-Whitney U statistics, and then normalizes the U statistics to Z statistics using Monte-...

Sensitivity analysis of ranked data: from order statistics to quantiles

NARCIS (Netherlands)

Heidergott, B.F.; Volk-Makarewicz, W.

2015-01-01

In this paper we provide the mathematical theory for sensitivity analysis of order statistics of continuous random variables, where the sensitivity is with respect to a distributional parameter. Sensitivity analysis of order statistics over a finite number of observations is discussed before

Applied statistical methods in agriculture, health and life sciences

CERN Document Server

Lawal, Bayo

2014-01-01

This textbook teaches crucial statistical methods to answer research questions using a unique range of statistical software programs, including MINITAB and R. This textbook is developed for undergraduate students in agriculture, nursing, biology and biomedical research. Graduate students will also find it to be a useful way to refresh their statistics skills and to reference software options. The unique combination of examples is approached using MINITAB and R for their individual strengths. Subjects covered include among others data description, probability distributions, experimental design, regression analysis, randomized design and biological assay. Unlike other biostatistics textbooks, this text also includes outliers, influential observations in regression and an introduction to survival analysis. Material is taken from the author's extensive teaching and research in Africa, USA and the UK. Sample problems, references and electronic supplementary material accompany each chapter.

Epidermal Growth Factor Receptor Is Related to Poor Survival in Glioblastomas: Single-Institution Experience

Science.gov (United States)

Choi, Youngmin; Lee, Hyung-Sik; Hur, Won-Joo; Sung, Ki-Han; Kim, Ki-Uk; Choi, Sun-Seob; Kim, Su-Jin; Kim, Dae-Cheol

2013-01-01

Purpose There are conflicting results surrounding the prognostic significance of epidermal growth factor receptor (EGFR) status in glioblastoma (GBM) patients. Accordingly, we attempted to assess the influence of EGFR expression on the survival of GBM patients receiving postoperative radiotherapy. Materials and Methods Thirty three GBM patients who had received surgery and postoperative radiotherapy at our institute, between March 1997 and February 2006, were included. The evaluation of EGFR expression with immunohistochemistry was available for 30 patients. Kaplan-Meier survival analysis and Cox regression were used for statistical analysis. Results EGFR was expressed in 23 patients (76.7%), and not expressed in seven (23.3%). Survival in EGFR expressing GBM patients was significantly less than that in non-expressing patients (median survival: 12.5 versus 17.5 months, p=0.013). Patients who received more than 60 Gy showed improved survival over those who received up to 60 Gy (median survival: 17.0 versus 9.0 months, p=0.000). Negative EGFR expression and a higher radiation dose were significantly correlated with improved survival on multivariate analysis. Survival rates showed no differences according to age, sex, and surgical extent. Conclusion The expression of EGFR demonstrated a significantly deleterious effect on the survival of GBM patients. Therefore, approaches targeting EGFR should be considered in potential treatment methods for GBM patients, in addition to current management strategies. PMID:23225805

Survival Function Analysis of Planet Size Distribution

OpenAIRE

Zeng, Li; Jacobsen, Stein B.; Sasselov, Dimitar D.; Vanderburg, Andrew

2018-01-01

Applying the survival function analysis to the planet radius distribution of the Kepler exoplanet candidates, we have identified two natural divisions of planet radius at 4 Earth radii and 10 Earth radii. These divisions place constraints on planet formation and interior structure model. The division at 4 Earth radii separates small exoplanets from large exoplanets above. When combined with the recently-discovered radius gap at 2 Earth radii, it supports the treatment of planets 2-4 Earth rad...

Survival analysis with functional covariates for partial follow-up studies.

Science.gov (United States)

Fang, Hong-Bin; Wu, Tong Tong; Rapoport, Aaron P; Tan, Ming

2016-12-01

Predictive or prognostic analysis plays an increasingly important role in the era of personalized medicine to identify subsets of patients whom the treatment may benefit the most. Although various time-dependent covariate models are available, such models require that covariates be followed in the whole follow-up period. This article studies a new class of functional survival models where the covariates are only monitored in a time interval that is shorter than the whole follow-up period. This paper is motivated by the analysis of a longitudinal study on advanced myeloma patients who received stem cell transplants and T cell infusions after the transplants. The absolute lymphocyte cell counts were collected serially during hospitalization. Those patients are still followed up if they are alive after hospitalization, while their absolute lymphocyte cell counts cannot be measured after that. Another complication is that absolute lymphocyte cell counts are sparsely and irregularly measured. The conventional method using Cox model with time-varying covariates is not applicable because of the different lengths of observation periods. Analysis based on each single observation obviously underutilizes available information and, more seriously, may yield misleading results. This so-called partial follow-up study design represents increasingly common predictive modeling problem where we have serial multiple biomarkers up to a certain time point, which is shorter than the total length of follow-up. We therefore propose a solution to the partial follow-up design. The new method combines functional principal components analysis and survival analysis with selection of those functional covariates. It also has the advantage of handling sparse and irregularly measured longitudinal observations of covariates and measurement errors. Our analysis based on functional principal components reveals that it is the patterns of the trajectories of absolute lymphocyte cell counts, instead of

Survival analysis of heart failure patients: A case study.

Science.gov (United States)

Ahmad, Tanvir; Munir, Assia; Bhatti, Sajjad Haider; Aftab, Muhammad; Raza, Muhammad Ali

2017-01-01

This study was focused on survival analysis of heart failure patients who were admitted to Institute of Cardiology and Allied hospital Faisalabad-Pakistan during April-December (2015). All the patients were aged 40 years or above, having left ventricular systolic dysfunction, belonging to NYHA class III and IV. Cox regression was used to model mortality considering age, ejection fraction, serum creatinine, serum sodium, anemia, platelets, creatinine phosphokinase, blood pressure, gender, diabetes and smoking status as potentially contributing for mortality. Kaplan Meier plot was used to study the general pattern of survival which showed high intensity of mortality in the initial days and then a gradual increase up to the end of study. Martingale residuals were used to assess functional form of variables. Results were validated computing calibration slope and discrimination ability of model via bootstrapping. For graphical prediction of survival probability, a nomogram was constructed. Age, renal dysfunction, blood pressure, ejection fraction and anemia were found as significant risk factors for mortality among heart failure patients.

Feature-Based Statistical Analysis of Combustion Simulation Data

Energy Technology Data Exchange (ETDEWEB)

Bennett, J; Krishnamoorthy, V; Liu, S; Grout, R; Hawkes, E; Chen, J; Pascucci, V; Bremer, P T

2011-11-18

We present a new framework for feature-based statistical analysis of large-scale scientific data and demonstrate its effectiveness by analyzing features from Direct Numerical Simulations (DNS) of turbulent combustion. Turbulent flows are ubiquitous and account for transport and mixing processes in combustion, astrophysics, fusion, and climate modeling among other disciplines. They are also characterized by coherent structure or organized motion, i.e. nonlocal entities whose geometrical features can directly impact molecular mixing and reactive processes. While traditional multi-point statistics provide correlative information, they lack nonlocal structural information, and hence, fail to provide mechanistic causality information between organized fluid motion and mixing and reactive processes. Hence, it is of great interest to capture and track flow features and their statistics together with their correlation with relevant scalar quantities, e.g. temperature or species concentrations. In our approach we encode the set of all possible flow features by pre-computing merge trees augmented with attributes, such as statistical moments of various scalar fields, e.g. temperature, as well as length-scales computed via spectral analysis. The computation is performed in an efficient streaming manner in a pre-processing step and results in a collection of meta-data that is orders of magnitude smaller than the original simulation data. This meta-data is sufficient to support a fully flexible and interactive analysis of the features, allowing for arbitrary thresholds, providing per-feature statistics, and creating various global diagnostics such as Cumulative Density Functions (CDFs), histograms, or time-series. We combine the analysis with a rendering of the features in a linked-view browser that enables scientists to interactively explore, visualize, and analyze the equivalent of one terabyte of simulation data. We highlight the utility of this new framework for combustion

Statistical learning methods in high-energy and astrophysics analysis

Energy Technology Data Exchange (ETDEWEB)

Zimmermann, J. [Forschungszentrum Juelich GmbH, Zentrallabor fuer Elektronik, 52425 Juelich (Germany) and Max-Planck-Institut fuer Physik, Foehringer Ring 6, 80805 Munich (Germany)]. E-mail: zimmerm@mppmu.mpg.de; Kiesling, C. [Max-Planck-Institut fuer Physik, Foehringer Ring 6, 80805 Munich (Germany)

2004-11-21

We discuss several popular statistical learning methods used in high-energy- and astro-physics analysis. After a short motivation for statistical learning we present the most popular algorithms and discuss several examples from current research in particle- and astro-physics. The statistical learning methods are compared with each other and with standard methods for the respective application.

Statistical learning methods in high-energy and astrophysics analysis

International Nuclear Information System (INIS)

Zimmermann, J.; Kiesling, C.

2004-01-01

We discuss several popular statistical learning methods used in high-energy- and astro-physics analysis. After a short motivation for statistical learning we present the most popular algorithms and discuss several examples from current research in particle- and astro-physics. The statistical learning methods are compared with each other and with standard methods for the respective application

The fuzzy approach to statistical analysis

NARCIS (Netherlands)

Coppi, Renato; Gil, Maria A.; Kiers, Henk A. L.

2006-01-01

For the last decades, research studies have been developed in which a coalition of Fuzzy Sets Theory and Statistics has been established with different purposes. These namely are: (i) to introduce new data analysis problems in which the objective involves either fuzzy relationships or fuzzy terms;

Statistical analysis applied to safety culture self-assessment

International Nuclear Information System (INIS)

Macedo Soares, P.P.

2002-01-01

Interviews and opinion surveys are instruments used to assess the safety culture in an organization as part of the Safety Culture Enhancement Programme. Specific statistical tools are used to analyse the survey results. This paper presents an example of an opinion survey with the corresponding application of the statistical analysis and the conclusions obtained. Survey validation, Frequency statistics, Kolmogorov-Smirnov non-parametric test, Student (T-test) and ANOVA means comparison tests and LSD post-hoc multiple comparison test, are discussed. (author)

The survival analysis on localized prostate cancer treated with neoadjuvant endocrine therapy followed by intensity modulated radiation therapy

International Nuclear Information System (INIS)

Gao Hong; Li Gaofeng; Wu Qinhong; Li Xuenan; Zhong Qiuzi; Xu Yonggang

2010-01-01

Objective: To retrospectively investigate clinical outcomes and prognostic factors in localized prostate cancer treated with neoadjuvant endocrine therapy followed by intensity modulated radiotherapy (IMRT). Methods: Between March 2003 and October 2008, 54 localized prostate cancer treated by IMRT were recruited. All patients had received endocrine therapy before IMRT. The endocrine therapy included surgical castration or medical castration in combination with antiandrogens. The target of IMRT was the prostate and seminal vesicles with or without pelvis. The biochemical failure was defined according to the phoenix definition. By using the risk grouping standard proposed by D'Amico, patients were divided into three groups: low-risk group (n = 5), intermediate-risk group (n = 12), and high-risk group (n = 37). Kaplan-Meier method was used to calculate the overall survival rate. Prognostic factors were analyzed by univariate and multiple Cox regression analysis. Results: The follow-up rate was 98%. The number of patients under follow-up was 39 at 3 years and 25 at 5 years. Potential prognostic factors, including risk groups, mode of endocrine therapy, time of endocrine therapy, phoenix grouping before IMRT, the prostate specific antigen doubling time (PSADT) before radiotherapy, PSA value before IMRT, interval of endocrine therapy and IMRT, irradiation region, and irradiation dose were analyzed by survival analysis. In univariate analysis, time of endocrine therapy (75 % vs 95 %, χ 2 = 6. 45, P = 0. 011), phoenix grouping before IMRT (87% vs 96%, χ 2 = 4. 36, P = 0. 037), interval of endocrine therapy and IMRT (80% vs 95%, χ 2 = 11.60, P= 0. 001), irradiation dose (75% vs 91%, χ 2 =5.92, P= 0. 015) were statistically significant prognostic factors for 3 - year overall survival , and risk groups (85 vs 53 vs 29, χ 2 = 6. 40, P =0. 041) and PSADT before IMRT (62 vs 120, U =24. 50, P =0. 003) were significant factors for the median survival time. In the multiple Cox

Cancer survival for Aboriginal and Torres Strait Islander Australians: a national study of survival rates and excess mortality.

Science.gov (United States)

Condon, John R; Zhang, Xiaohua; Baade, Peter; Griffiths, Kalinda; Cunningham, Joan; Roder, David M; Coory, Michael; Jelfs, Paul L; Threlfall, Tim

2014-01-31

National cancer survival statistics are available for the total Australian population but not Indigenous Australians, although their cancer mortality rates are known to be higher than those of other Australians. We aimed to validate analysis methods and report cancer survival rates for Indigenous Australians as the basis for regular national reporting. We used national cancer registrations data to calculate all-cancer and site-specific relative survival for Indigenous Australians (compared with non-Indigenous Australians) diagnosed in 2001-2005. Because of limited availability of Indigenous life tables, we validated and used cause-specific survival (rather than relative survival) for proportional hazards regression to analyze time trends and regional variation in all-cancer survival between 1991 and 2005. Survival was lower for Indigenous than non-Indigenous Australians for all cancers combined and for many cancer sites. The excess mortality of Indigenous people with cancer was restricted to the first three years after diagnosis, and greatest in the first year. Survival was lower for rural and remote than urban residents; this disparity was much greater for Indigenous people. Survival improved between 1991 and 2005 for non-Indigenous people (mortality decreased by 28%), but to a much lesser extent for Indigenous people (11%) and only for those in remote areas; cancer survival did not improve for urban Indigenous residents. Cancer survival is lower for Indigenous than other Australians, for all cancers combined and many individual cancer sites, although more accurate recording of Indigenous status by cancer registers is required before the extent of this disadvantage can be known with certainty. Cancer care for Indigenous Australians needs to be considerably improved; cancer diagnosis, treatment, and support services need to be redesigned specifically to be accessible and acceptable to Indigenous people.

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.

Foundation of statistical energy analysis in vibroacoustics

CERN Document Server

Le Bot, A

2015-01-01

This title deals with the statistical theory of sound and vibration. The foundation of statistical energy analysis is presented in great detail. In the modal approach, an introduction to random vibration with application to complex systems having a large number of modes is provided. For the wave approach, the phenomena of propagation, group speed, and energy transport are extensively discussed. Particular emphasis is given to the emergence of diffuse field, the central concept of the theory.

Statistical Analysis of Big Data on Pharmacogenomics

Science.gov (United States)

Fan, Jianqing; Liu, Han

2013-01-01

This paper discusses statistical methods for estimating complex correlation structure from large pharmacogenomic datasets. We selectively review several prominent statistical methods for estimating large covariance matrix for understanding correlation structure, inverse covariance matrix for network modeling, large-scale simultaneous tests for selecting significantly differently expressed genes and proteins and genetic markers for complex diseases, and high dimensional variable selection for identifying important molecules for understanding molecule mechanisms in pharmacogenomics. Their applications to gene network estimation and biomarker selection are used to illustrate the methodological power. Several new challenges of Big data analysis, including complex data distribution, missing data, measurement error, spurious correlation, endogeneity, and the need for robust statistical methods, are also discussed. PMID:23602905

HistFitter software framework for statistical data analysis

Energy Technology Data Exchange (ETDEWEB)

Baak, M. [CERN, Geneva (Switzerland); Besjes, G.J. [Radboud University Nijmegen, Nijmegen (Netherlands); Nikhef, Amsterdam (Netherlands); Cote, D. [University of Texas, Arlington (United States); Koutsman, A. [TRIUMF, Vancouver (Canada); Lorenz, J. [Ludwig-Maximilians-Universitaet Muenchen, Munich (Germany); Excellence Cluster Universe, Garching (Germany); Short, D. [University of Oxford, Oxford (United Kingdom)

2015-04-15

We present a software framework for statistical data analysis, called HistFitter, that has been used extensively by the ATLAS Collaboration to analyze big datasets originating from proton-proton collisions at the Large Hadron Collider at CERN. Since 2012 HistFitter has been the standard statistical tool in searches for supersymmetric particles performed by ATLAS. HistFitter is a programmable and flexible framework to build, book-keep, fit, interpret and present results of data models of nearly arbitrary complexity. Starting from an object-oriented configuration, defined by users, the framework builds probability density functions that are automatically fit to data and interpreted with statistical tests. Internally HistFitter uses the statistics packages RooStats and HistFactory. A key innovation of HistFitter is its design, which is rooted in analysis strategies of particle physics. The concepts of control, signal and validation regions are woven into its fabric. These are progressively treated with statistically rigorous built-in methods. Being capable of working with multiple models at once that describe the data, HistFitter introduces an additional level of abstraction that allows for easy bookkeeping, manipulation and testing of large collections of signal hypotheses. Finally, HistFitter provides a collection of tools to present results with publication quality style through a simple command-line interface. (orig.)

HistFitter software framework for statistical data analysis

International Nuclear Information System (INIS)

Baak, M.; Besjes, G.J.; Cote, D.; Koutsman, A.; Lorenz, J.; Short, D.

2015-01-01

We present a software framework for statistical data analysis, called HistFitter, that has been used extensively by the ATLAS Collaboration to analyze big datasets originating from proton-proton collisions at the Large Hadron Collider at CERN. Since 2012 HistFitter has been the standard statistical tool in searches for supersymmetric particles performed by ATLAS. HistFitter is a programmable and flexible framework to build, book-keep, fit, interpret and present results of data models of nearly arbitrary complexity. Starting from an object-oriented configuration, defined by users, the framework builds probability density functions that are automatically fit to data and interpreted with statistical tests. Internally HistFitter uses the statistics packages RooStats and HistFactory. A key innovation of HistFitter is its design, which is rooted in analysis strategies of particle physics. The concepts of control, signal and validation regions are woven into its fabric. These are progressively treated with statistically rigorous built-in methods. Being capable of working with multiple models at once that describe the data, HistFitter introduces an additional level of abstraction that allows for easy bookkeeping, manipulation and testing of large collections of signal hypotheses. Finally, HistFitter provides a collection of tools to present results with publication quality style through a simple command-line interface. (orig.)

Robust statistics and geochemical data analysis

International Nuclear Information System (INIS)

Di, Z.

1987-01-01

Advantages of robust procedures over ordinary least-squares procedures in geochemical data analysis is demonstrated using NURE data from the Hot Springs Quadrangle, South Dakota, USA. Robust principal components analysis with 5% multivariate trimming successfully guarded the analysis against perturbations by outliers and increased the number of interpretable factors. Regression with SINE estimates significantly increased the goodness-of-fit of the regression and improved the correspondence of delineated anomalies with known uranium prospects. Because of the ubiquitous existence of outliers in geochemical data, robust statistical procedures are suggested as routine procedures to replace ordinary least-squares procedures

Factors predicting survival in amyotrophic lateral sclerosis patients on non-invasive ventilation.

Science.gov (United States)

Gonzalez Calzada, Nuria; Prats Soro, Enric; Mateu Gomez, Lluis; Giro Bulta, Esther; Cordoba Izquierdo, Ana; Povedano Panades, Monica; Dorca Sargatal, Jordi; Farrero Muñoz, Eva

2016-01-01

Non invasive ventilation (NIV) improves quality of life and extends survival in amyotrophic lateral sclerosis (ALS) patients. However, few data exist about the factors related to survival. We intended to assess the predictive factors that influence survival in patients after NIV initiation. Patients who started NIV from 2000 to 2014 and were tolerant (compliance ≥ 4 hours) were included; demographic, disease related and respiratory variables at NIV initiation were analysed. Statistical analysis was performed using the Kaplan-Meier test and Cox proportional hazard models. 213 patients were included with median survival from NIV initiation of 13.5 months. In univariate analysis, the identified risk factors for mortality were severity of bulbar involvement (HR 2), Forced Vital Capacity (FVC) % (HR 0.99) and ALSFRS-R (HR 0.97). Multivariate analysis showed that bulbar involvement (HR 1.92) and ALSFRS-R (HR 0.97) were independent predictive factors of survival in patients on NIV. In our study, the two prognostic factors in ALS patients following NIV were the severity of bulbar involvement and ALSFRS-R at the time on NIV initiation. A better assessment of bulbar involvement, including evaluation of the upper airway, and a careful titration on NIV are necessary to optimize treatment efficacy.

Using Pre-Statistical Analysis to Streamline Monitoring Assessments

International Nuclear Information System (INIS)

Reed, J.K.

1999-01-01

A variety of statistical methods exist to aid evaluation of groundwater quality and subsequent decision making in regulatory programs. These methods are applied because of large temporal and spatial extrapolations commonly applied to these data. In short, statistical conclusions often serve as a surrogate for knowledge. However, facilities with mature monitoring programs that have generated abundant data have inherently less uncertainty because of the sheer quantity of analytical results. In these cases, statistical tests can be less important, and ''expert'' data analysis should assume an important screening role.The WSRC Environmental Protection Department, working with the General Separations Area BSRI Environmental Restoration project team has developed a method for an Integrated Hydrogeological Analysis (IHA) of historical water quality data from the F and H Seepage Basins groundwater remediation project. The IHA combines common sense analytical techniques and a GIS presentation that force direct interactive evaluation of the data. The IHA can perform multiple data analysis tasks required by the RCRA permit. These include: (1) Development of a groundwater quality baseline prior to remediation startup, (2) Targeting of constituents for removal from RCRA GWPS, (3) Targeting of constituents for removal from UIC, permit, (4) Targeting of constituents for reduced, (5)Targeting of monitoring wells not producing representative samples, (6) Reduction in statistical evaluation, and (7) Identification of contamination from other facilities

Survival after Liver Transplantation in the United States: A Disease-Specific Analysis of the UNOS database

Czech Academy of Sciences Publication Activity Database

Roberts, M.S.; Angus, D.C.; Bryce, C.L.; Valenta, Zdeněk; Weissfeld, L.

2004-01-01

Roč. 10, č. 7 (2004), s. 886-897 ISSN 1527-6465 Source of funding: V - iné verejné zdroje Keywords : disease-specific survival * liver transplantation * cox PH model Subject RIV: BB - Applied Statistics, Operational Research Impact factor: 3.984, year: 2004

Trends in Testicular Cancer Survival: A Large Population-based Analysis.

Science.gov (United States)

Sui, Wilson; Morrow, David C; Bermejo, Carlos E; Hellenthal, Nicholas J

2015-06-01

To determine whether discrepancies in testicular cancer outcomes between Caucasians and non-Caucasians are changing over time. Although testicular cancer is more common in Caucasians, studies have shown that other races have worse outcomes. Using the Surveillance, Epidemiology, and End Results registry, we identified 29,803 patients diagnosed with histologically confirmed testicular cancer between 1983 and 2011. Of these, 12,650 patients (42%) had 10-year follow-up data. We stratified the patients by age group, stage, race, and year of diagnosis and assessed 10-year overall and cancer-specific survival in each cohort. Cox proportional hazard models were used to determine the relative contributions of each stratum to cancer-specific survival. Predicted overall 10-year survival of Caucasian patients with testicular cancer increased slightly from 88% to 89% over the period studied, whereas predicted cancer-specific 10-year survival dropped slightly from 94% to 93%. In contrast, non-Caucasian men demonstrated larger changes in 10-year overall (84%-86%) and cancer-specific (88%-91%) survival. On univariate analysis, race was significantly associated with testicular cancer death, with non-Caucasian men being 1.69 times more likely to die of testicular cancer than Caucasians (hazard ratio, 1.33-2.16; 95% confidence interval, testicular cancer. These data show a convergence in cancer-specific survival between racial groups over time, suggesting that diagnostic and treatment discrepancies may be improving for non-Caucasians. Copyright © 2015 Elsevier Inc. All rights reserved.

Conjunction analysis and propositional logic in fMRI data analysis using Bayesian statistics.

Science.gov (United States)

Rudert, Thomas; Lohmann, Gabriele

2008-12-01

To evaluate logical expressions over different effects in data analyses using the general linear model (GLM) and to evaluate logical expressions over different posterior probability maps (PPMs). In functional magnetic resonance imaging (fMRI) data analysis, the GLM was applied to estimate unknown regression parameters. Based on the GLM, Bayesian statistics can be used to determine the probability of conjunction, disjunction, implication, or any other arbitrary logical expression over different effects or contrast. For second-level inferences, PPMs from individual sessions or subjects are utilized. These PPMs can be combined to a logical expression and its probability can be computed. The methods proposed in this article are applied to data from a STROOP experiment and the methods are compared to conjunction analysis approaches for test-statistics. The combination of Bayesian statistics with propositional logic provides a new approach for data analyses in fMRI. Two different methods are introduced for propositional logic: the first for analyses using the GLM and the second for common inferences about different probability maps. The methods introduced extend the idea of conjunction analysis to a full propositional logic and adapt it from test-statistics to Bayesian statistics. The new approaches allow inferences that are not possible with known standard methods in fMRI. (c) 2008 Wiley-Liss, Inc.

Progesterone receptor levels independently predict survival in endometrial adenocarcinoma

DEFF Research Database (Denmark)

Nyholm, H C; Christensen, Ib Jarle; Nielsen, Anette Lynge

1995-01-01

to correlations to cancer-specific survival in a multivariate analysis including histopathological characteristics. Median patient follow-up time was 67 months with 18 cancer deaths. The PR-DCC and ER-DCC values were dichotomized according to levels previously found by us to correspond to the best agreement...... between receptor status as determined by the DCC and ICA methods (130 fmol/mg cytosol protein for ER, 114 fmol/mg for PR). Using these thresholds, we found by multivariate analysis that "high" PR-DCC levels (> 114 fmol/mg) correlated significantly (P = 0.004) with survival, independent of stage risk group...... could not be statistically evaluated due to the number of cases with eligible ICA values. However, we suggest that owing to a close correlation between DCC and ICA results, PR-ICA status may provide significant prognostic information when DCC measurements are not available....

The impact of metformin use on survival in kidney cancer patients with diabetes: a meta-analysis.

Science.gov (United States)

Li, Yang; Hu, Liyi; Xia, Qinghong; Yuan, Yongqiang; Mi, Yonghua

2017-06-01

The effects of metformin on the prognosis of kidney cancer patients with diabetes are in controversial. The present study is conducted to classify the association of metformin use with the survival of patients with kidney cancer. Electronic databases, namely PubMed and Web of Science, were used to search the eligible studies up to December, 2016. Pooled hazard ratio (HR) and its corresponding 95% confidence interval (95% CI) were calculated. It was considered as statistically significant when P value was kidney cancer patients. The combined HR suggested that the use of metformin could improve the overall survival (OS) (HR 0.643, 95% CI 0.520-0.795, P cancer-specific survival (CSS) (HR 0.618, 95% CI 0.446-0.858, P = 0.004) in kidney cancer patients. In subgroup analysis, positive associations were found between metformin use and OS/CSS of localized renal cell carcinoma patients (OS: HR 0.634, 95% CI 0.440-0.913, P = 0.014; CSS: HR 0.476, 95% CI 0.295-0.768, P = 0.002). Moreover, we also found that the use of metformin could reduce the risk of death in kidney cancer patients (HR 0.711, 95% CI 0.562-0.899, P = 0.004). Our findings suggest that the use of metformin is in favor of the prognosis of patients with kidney cancers. Further investigations are needed to evaluate the prognostic value of metformin on kidney cancer patients.

Analysis of survival in breast cancer patients by using different parametric models

Science.gov (United States)

Enera Amran, Syahila; Asrul Afendi Abdullah, M.; Kek, Sie Long; Afiqah Muhamad Jamil, Siti

2017-09-01

In biomedical applications or clinical trials, right censoring was often arising when studying the time to event data. In this case, some individuals are still alive at the end of the study or lost to follow up at a certain time. It is an important issue to handle the censoring data in order to prevent any bias information in the analysis. Therefore, this study was carried out to analyze the right censoring data with three different parametric models; exponential model, Weibull model and log-logistic models. Data of breast cancer patients from Hospital Sultan Ismail, Johor Bahru from 30 December 2008 until 15 February 2017 was used in this study to illustrate the right censoring data. Besides, the covariates included in this study are the time of breast cancer infection patients survive t, age of each patients X1 and treatment given to the patients X2 . In order to determine the best parametric models in analysing survival of breast cancer patients, the performance of each model was compare based on Akaike Information Criterion (AIC), Bayesian Information Criterion (BIC) and log-likelihood value using statistical software R. When analysing the breast cancer data, all three distributions were shown consistency of data with the line graph of cumulative hazard function resembles a straight line going through the origin. As the result, log-logistic model was the best fitted parametric model compared with exponential and Weibull model since it has the smallest value in AIC and BIC, also the biggest value in log-likelihood.

Effectiveness of surgery and individualized high-dose hyperfractionated accelerated radiotherapy on survival in clinical stage I non-small cell lung cancer. A propensity score matched analysis

International Nuclear Information System (INIS)

Jimenez, Marcelo F.; Baardwijk, Angela van; Aerts, Hugo J.W.L.; De Ruysscher, Dirk; Novoa, Nuria M.; Varela, Gonzalo; Lambin, Philippe

2010-01-01

Background and purpose: Surgery is considered the treatment of choice for early-stage non-small cell lung cancer (NSCLC). Patients with poor pulmonary function or other comorbidities are treated with radiotherapy. The objective of this investigation is to compare the 3-year survival of two early-stage NSCLC populations treated in two different hospitals, either by surgical resection (lobectomy) or by individualized high-dose accelerated radiotherapy, after matching patients by propensity scoring analysis. Methods: A retrospective comparative study has been performed on two series of consecutive patients with cytohistological diagnosis of NSCLC, clinically staged IA by means of PET-scan (radiotherapy group) and pathologically staged IA (surgery group). Results: A total of 157 cases were initially selected for the analysis (110 operated and 47 treated by radiotherapy). Patients in the radiotherapy group were older, with higher comorbidity and lower FEV1% with 3-years probability of survival for operated patients higher than that found for patients treated by radiotherapy. After matching by propensity scoring (using age and FEV1%), differences disappear and 3-years probability of survival had no statistical differences. Conclusions: Although this is a non-randomized retrospective analysis, we have not found 3-years survival differences after matching cases between surgery and radiotherapy. Nevertheless, data presented here support the continuous investigation for non-surgical alternatives in this disease.

A nomogram for predicting survival in patients with breast cancer brain metastasis.

Science.gov (United States)

Huang, Zhou; Sun, Bing; Wu, Shikai; Meng, Xiangying; Cong, Yang; Shen, Ge; Song, Santai

2018-05-01

Brain metastasis (BM) is common in patients with breast cancer. Predicting patient survival is critical for the clinical management of breast cancer brain metastasis (BCBM). The present study was designed to develop and evaluate a prognostic model for patients with newly diagnosed BCBM. Based on the clinical data of patients with BCBM treated in the Affiliated Hospital of Academy of Military Medical Sciences (Beijing, China) between 2002 and 2014, a nomogram was developed to predict survival using proportional hazards regression analysis. The model was validated internally by bootstrapping, and the concordance index (c-index) was calculated. A calibration curve and c-index were used to evaluate discriminatory and predictive ability, in order to compare the nomogram with widely used models, including recursive partitioning analysis (RPA), graded prognostic assessment (GPA) and breast-graded prognostic assessment (Breast-GPA). A total of 411 patients with BCBM were included in the development of this predictive model. The median overall survival time was 14.1 months. Statistically significant predictors for patient survival included biological subtype, Karnofsky performance score, leptomeningeal metastasis, extracranial metastasis, the number of brain metastases and disease-free survival. A nomogram for predicting 1- and 2-year overall survival rates was constructed, which exhibited good accuracy in predicting overall survival with a concordance index of 0.735. This model outperformed RPA, GPA and Breast-GPA, based on the comparisons of the c-indexes. The nomogram constructed based on a multiple factor analysis was able to more accurately predict the individual survival probability of patients with BCBM, compared with existing models.

Mathematical and statistical applications in life sciences and engineering

CERN Document Server

Adhikari, Mahima; Chaubey, Yogendra

2017-01-01

The book includes articles from eminent international scientists discussing a wide spectrum of topics of current importance in mathematics and statistics and their applications. It presents state-of-the-art material along with a clear and detailed review of the relevant topics and issues concerned. The topics discussed include message transmission, colouring problem, control of stochastic structures and information dynamics, image denoising, life testing and reliability, survival and frailty models, analysis of drought periods, prediction of genomic profiles, competing risks, environmental applications and chronic disease control. It is a valuable resource for researchers and practitioners in the relevant areas of mathematics and statistics.

Multilevel survival analysis of health inequalities in life expectancy

Directory of Open Access Journals (Sweden)

Merlo Juan

2009-08-01

Full Text Available Abstract Background The health status of individuals is determined by multiple factors operating at both micro and macro levels and the interactive effects of them. Measures of health inequalities should reflect such determinants explicitly through sources of levels and combining mean differences at group levels and the variation of individuals, for the benefits of decision making and intervention planning. Measures derived recently from marginal models such as beta-binomial and frailty survival, address this issue to some extent, but are limited in handling data with complex structures. Beta-binomial models were also limited in relation to measuring inequalities of life expectancy (LE directly. Methods We propose a multilevel survival model analysis that estimates life expectancy based on survival time with censored data. The model explicitly disentangles total health inequalities in terms of variance components of life expectancy compared to the source of variation at the level of individuals in households and parishes and so on, and estimates group differences of inequalities at the same time. Adjusted distributions of life expectancy by gender and by household socioeconomic level are calculated. Relative and absolute health inequality indices are derived based on model estimates. The model based analysis is illustrated on a large Swedish cohort of 22,680 men and 26,474 women aged 65–69 in 1970 and followed up for 30 years. Model based inequality measures are compared to the conventional calculations. Results Much variation of life expectancy is observed at individual and household levels. Contextual effects at Parish and Municipality level are negligible. Women have longer life expectancy than men and lower inequality. There is marked inequality by the level of household socioeconomic status measured by the median life expectancy in each socio-economic group and the variation in life expectancy within each group. Conclusion Multilevel

Sensitivity analysis and optimization of system dynamics models : Regression analysis and statistical design of experiments

NARCIS (Netherlands)

Kleijnen, J.P.C.

1995-01-01

This tutorial discusses what-if analysis and optimization of System Dynamics models. These problems are solved, using the statistical techniques of regression analysis and design of experiments (DOE). These issues are illustrated by applying the statistical techniques to a System Dynamics model for

Multivariate Statistical Methods as a Tool of Financial Analysis of Farm Business

Czech Academy of Sciences Publication Activity Database

Novák, J.; Sůvová, H.; Vondráček, Jiří

2002-01-01

Roč. 48, č. 1 (2002), s. 9-12 ISSN 0139-570X Institutional research plan: AV0Z1030915 Keywords : financial analysis * financial ratios * multivariate statistical methods * correlation analysis * discriminant analysis * cluster analysis Subject RIV: BB - Applied Statistics, Operational Research

Survival analysis of heart failure patients: A case study.

Directory of Open Access Journals (Sweden)

Tanvir Ahmad

Full Text Available This study was focused on survival analysis of heart failure patients who were admitted to Institute of Cardiology and Allied hospital Faisalabad-Pakistan during April-December (2015. All the patients were aged 40 years or above, having left ventricular systolic dysfunction, belonging to NYHA class III and IV. Cox regression was used to model mortality considering age, ejection fraction, serum creatinine, serum sodium, anemia, platelets, creatinine phosphokinase, blood pressure, gender, diabetes and smoking status as potentially contributing for mortality. Kaplan Meier plot was used to study the general pattern of survival which showed high intensity of mortality in the initial days and then a gradual increase up to the end of study. Martingale residuals were used to assess functional form of variables. Results were validated computing calibration slope and discrimination ability of model via bootstrapping. For graphical prediction of survival probability, a nomogram was constructed. Age, renal dysfunction, blood pressure, ejection fraction and anemia were found as significant risk factors for mortality among heart failure patients.

Marital status independently predicts testis cancer survival--an analysis of the SEER database.

Science.gov (United States)

Abern, Michael R; Dude, Annie M; Coogan, Christopher L

2012-01-01

Previous reports have shown that married men with malignancies have improved 10-year survival over unmarried men. We sought to investigate the effect of marital status on 10-year survival in a U.S. population-based cohort of men with testis cancer. We examined 30,789 cases of testis cancer reported to the Surveillance, Epidemiology, and End Results (SEER 17) database between 1973 and 2005. All staging were converted to the 1997 AJCC TNM system. Patients less than 18 years of age at time of diagnosis were excluded. A subgroup analysis of patients with stages I or II non-seminomatous germ cell tumors (NSGCT) was performed. Univariate analysis using t-tests and χ(2) tests compared characteristics of patients separated by marital status. Multivariate analysis was performed using a Cox proportional hazard model to generate Kaplan-Meier survival curves, with all-cause and cancer-specific mortality as the primary endpoints. 20,245 cases met the inclusion criteria. Married men were more likely to be older (38.9 vs. 31.4 years), Caucasian (94.4% vs. 92.1%), stage I (73.1% vs. 61.4%), and have seminoma as the tumor histology (57.3% vs. 43.4%). On multivariate analysis, married status (HR 0.58, P married status (HR 0.60, P married and unmarried men (44.8% vs. 43.4%, P = 0.33). Marital status is an independent predictor of improved overall and cancer-specific survival in men with testis cancer. In men with stages I or II NSGCT, RPLND is an additional predictor of improved overall survival. Marital status does not appear to influence whether men undergo RPLND. Copyright © 2012 Elsevier Inc. All rights reserved.

Statistical analysis and interpretation of prenatal diagnostic imaging studies, Part 2: descriptive and inferential statistical methods.

Science.gov (United States)

Tuuli, Methodius G; Odibo, Anthony O

2011-08-01

The objective of this article is to discuss the rationale for common statistical tests used for the analysis and interpretation of prenatal diagnostic imaging studies. Examples from the literature are used to illustrate descriptive and inferential statistics. The uses and limitations of linear and logistic regression analyses are discussed in detail.

Factors affecting the survival of the “at risk” newborn at Korle Bu ...

African Journals Online (AJOL)

The type of delivery other than the spontaneous vaginal route also affects the outcome, though the relationship was not statistically significant. Logistic regression analysis showed that maturity, birthweight and time from birth to admission to NICU were the most significant factors associated with the survival of the neonate.

Clinical Predictors of Survival for Patients with Stage IV Cancer Referred to Radiation Oncology.

Directory of Open Access Journals (Sweden)

Johnny Kao

Full Text Available There is an urgent need for a robust, clinically useful predictive model for survival in a heterogeneous group of patients with metastatic cancer referred to radiation oncology.From May 2012 to August 2013, 143 consecutive patients with stage IV cancer were prospectively evaluated by a single radiation oncologist. We retrospectively analyzed the effect of 29 patient, laboratory and tumor-related prognostic factors on overall survival using univariate analysis. Variables that were statistically significant on univariate analysis were entered into a multivariable Cox regression to identify independent predictors of overall survival.The median overall survival was 5.5 months. Four prognostic factors significantly predicted survival on multivariable analysis including ECOG performance status (0-1 vs. 2 vs. 3-4, number of active tumors (1 to 5 vs. ≥ 6, albumin levels (≥ 3.4 vs. 2.4 to 3.3 vs. 31.4 months for very low risk patients compared to 14.5 months for low risk, 4.1 months for intermediate risk and 1.2 months for high risk (p < 0.001.These data suggest that a model that considers performance status, extent of disease, primary tumor site and serum albumin represents a simple model to accurately predict survival for patients with stage IV cancer who are potential candidates for radiation therapy.

Statistical analysis of environmental data

International Nuclear Information System (INIS)

Beauchamp, J.J.; Bowman, K.O.; Miller, F.L. Jr.

1975-10-01

This report summarizes the analyses of data obtained by the Radiological Hygiene Branch of the Tennessee Valley Authority from samples taken around the Browns Ferry Nuclear Plant located in Northern Alabama. The data collection was begun in 1968 and a wide variety of types of samples have been gathered on a regular basis. The statistical analysis of environmental data involving very low-levels of radioactivity is discussed. Applications of computer calculations for data processing are described

The comparison of proportional hazards and accelerated failure time models in analyzing the first birth interval survival data

Science.gov (United States)

Faruk, Alfensi

2018-03-01

Survival analysis is a branch of statistics, which is focussed on the analysis of time- to-event data. In multivariate survival analysis, the proportional hazards (PH) is the most popular model in order to analyze the effects of several covariates on the survival time. However, the assumption of constant hazards in PH model is not always satisfied by the data. The violation of the PH assumption leads to the misinterpretation of the estimation results and decreasing the power of the related statistical tests. On the other hand, the accelerated failure time (AFT) models do not assume the constant hazards in the survival data as in PH model. The AFT models, moreover, can be used as the alternative to PH model if the constant hazards assumption is violated. The objective of this research was to compare the performance of PH model and the AFT models in analyzing the significant factors affecting the first birth interval (FBI) data in Indonesia. In this work, the discussion was limited to three AFT models which were based on Weibull, exponential, and log-normal distribution. The analysis by using graphical approach and a statistical test showed that the non-proportional hazards exist in the FBI data set. Based on the Akaike information criterion (AIC), the log-normal AFT model was the most appropriate model among the other considered models. Results of the best fitted model (log-normal AFT model) showed that the covariates such as women’s educational level, husband’s educational level, contraceptive knowledge, access to mass media, wealth index, and employment status were among factors affecting the FBI in Indonesia.

The effect of melatonin on mouse jejunal crypt cell survival and apoptosis

International Nuclear Information System (INIS)

Kang, Jin Oh; Ha, Eun Young; Baik, Hyung Hwan; Cho, Yong Ho; Hong, Seong Eon

2000-01-01

To evaluate protective mechanism of melatonin against radiation damage and its relationship with apoptosis in mouse jejunum. 168 mice were divided into 28 groups according to radiation dose and melatonin treatment. To analysis crypt survival, microcolony survival assay was done according to Withers and Elkind's method. To analysis apoptosis, TUNEL assay was done according to Labet-Moleur's method. Radiation protection effect of melatonin was demonstrated by crypt survival assay and its effect was stronger in high radiation dose area. Apoptosis index with 8 Gy irradiation was 18.4% in control group and 16.5% in melatonin treated group. After 18 Gy, apoptosis index was 17.2%in control group and 15.4% in melatonin treated group. Apoptosis index did not show statistically significant difference between melatonin shows clear protective effect in mouse jejunum against radiation damage but its protective effect seems not to be related with apoptosis protection effect

Volumetric and MGMT parameters in glioblastoma patients: Survival analysis

International Nuclear Information System (INIS)

Iliadis, Georgios; Kotoula, Vassiliki; Chatzisotiriou, Athanasios; Televantou, Despina; Eleftheraki, Anastasia G; Lambaki, Sofia; Misailidou, Despina; Selviaridis, Panagiotis; Fountzilas, George

2012-01-01

In this study several tumor-related volumes were assessed by means of a computer-based application and a survival analysis was conducted to evaluate the prognostic significance of pre- and postoperative volumetric data in patients harboring glioblastomas. In addition, MGMT (O 6 -methylguanine methyltransferase) related parameters were compared with those of volumetry in order to observe possible relevance of this molecule in tumor development. We prospectively analyzed 65 patients suffering from glioblastoma (GBM) who underwent radiotherapy with concomitant adjuvant temozolomide. For the purpose of volumetry T1 and T2-weighted magnetic resonance (MR) sequences were used, acquired both pre- and postoperatively (pre-radiochemotherapy). The volumes measured on preoperative MR images were necrosis, enhancing tumor and edema (including the tumor) and on postoperative ones, net-enhancing tumor. Age, sex, performance status (PS) and type of operation were also included in the multivariate analysis. MGMT was assessed for promoter methylation with Multiplex Ligation-dependent Probe Amplification (MLPA), for RNA expression with real time PCR, and for protein expression with immunohistochemistry in a total of 44 cases with available histologic material. In the multivariate analysis a negative impact was shown for pre-radiochemotherapy net-enhancing tumor on the overall survival (OS) (p = 0.023) and for preoperative necrosis on progression-free survival (PFS) (p = 0.030). Furthermore, the multivariate analysis confirmed the importance of PS in PFS and OS of patients. MGMT promoter methylation was observed in 13/23 (43.5%) evaluable tumors; complete methylation was observed in 3/13 methylated tumors only. High rate of MGMT protein positivity (> 20% positive neoplastic nuclei) was inversely associated with pre-operative tumor necrosis (p = 0.021). Our findings implicate that volumetric parameters may have a significant role in the prognosis of GBM patients. Furthermore

Highly Robust Statistical Methods in Medical Image Analysis

Czech Academy of Sciences Publication Activity Database

Kalina, Jan

2012-01-01

Roč. 32, č. 2 (2012), s. 3-16 ISSN 0208-5216 R&D Projects: GA MŠk(CZ) 1M06014 Institutional research plan: CEZ:AV0Z10300504 Keywords : robust statistics * classification * faces * robust image analysis * forensic science Subject RIV: BB - Applied Statistics, Operational Research Impact factor: 0.208, year: 2012 http://www.ibib.waw.pl/bbe/bbefulltext/BBE_32_2_003_FT.pdf

Statistical Power Analysis with Missing Data A Structural Equation Modeling Approach

CERN Document Server

Davey, Adam

2009-01-01

Statistical power analysis has revolutionized the ways in which we conduct and evaluate research.  Similar developments in the statistical analysis of incomplete (missing) data are gaining more widespread applications. This volume brings statistical power and incomplete data together under a common framework, in a way that is readily accessible to those with only an introductory familiarity with structural equation modeling.  It answers many practical questions such as: How missing data affects the statistical power in a study How much power is likely with different amounts and types

Parametric and semiparametric models with applications to reliability, survival analysis, and quality of life

CERN Document Server

Nikulin, M; Mesbah, M; Limnios, N

2004-01-01

Parametric and semiparametric models are tools with a wide range of applications to reliability, survival analysis, and quality of life. This self-contained volume examines these tools in survey articles written by experts currently working on the development and evaluation of models and methods. While a number of chapters deal with general theory, several explore more specific connections and recent results in "real-world" reliability theory, survival analysis, and related fields.

Breastfeeding practices in a public health field practice area in Sri Lanka: a survival analysis

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Agampodi Thilini C

2007-10-01

Full Text Available Abstract Background Exclusive breastfeeding up to the completion of the sixth month of age is the national infant feeding recommendation for Sri Lanka. The objective of the present study was to collect data on exclusive breastfeeding up to six months and to describe the association between exclusive breastfeeding and selected socio-demographic factors. Methods A clinic based cross-sectional study was conducted in the Medical Officer of Health area, Beruwala, Sri Lanka in June 2006. Mothers with infants aged 4 to 12 months, attending the 19 child welfare clinics in the area were included in the study. Infants with specific feeding problems (cleft lip and palate and primary lactose intolerance were excluded. Cluster sampling technique was used and consecutive infants fulfilling the inclusion criteria were enrolled. A total of 219 mothers participated in the study. The statistical tests used were survival analysis (Kaplan-Meier survival curves and Cox proportional Hazard model. Results All 219 mothers had initiated breastfeeding. The median duration of exclusive breastfeeding was four months (95% CI 3.75, 4.25. The rates of exclusive breastfeeding at 4 and 6 months were 61.6% (135/219 and 15.5% (24/155 respectively. Bivariate analysis showed that the Muslim ethnicity (p = 0.004, lower levels of parental education (p Conclusion The rate of breastfeeding initiation and exclusive breastfeeding up to the fourth month is very high in Medical Officer of Health area, Beruwala, Sri Lanka. However exclusive breastfeeding up to six months is still low and the prevalence of inappropriate feeding practices is high.

Statistical Analysis of Data for Timber Strengths

DEFF Research Database (Denmark)

Sørensen, John Dalsgaard

2003-01-01

Statistical analyses are performed for material strength parameters from a large number of specimens of structural timber. Non-parametric statistical analysis and fits have been investigated for the following distribution types: Normal, Lognormal, 2 parameter Weibull and 3-parameter Weibull...... fits to the data available, especially if tail fits are used whereas the Log Normal distribution generally gives a poor fit and larger coefficients of variation, especially if tail fits are used. The implications on the reliability level of typical structural elements and on partial safety factors...... for timber are investigated....

Numeric computation and statistical data analysis on the Java platform

CERN Document Server

Chekanov, Sergei V

2016-01-01

Numerical computation, knowledge discovery and statistical data analysis integrated with powerful 2D and 3D graphics for visualization are the key topics of this book. The Python code examples powered by the Java platform can easily be transformed to other programming languages, such as Java, Groovy, Ruby and BeanShell. This book equips the reader with a computational platform which, unlike other statistical programs, is not limited by a single programming language. The author focuses on practical programming aspects and covers a broad range of topics, from basic introduction to the Python language on the Java platform (Jython), to descriptive statistics, symbolic calculations, neural networks, non-linear regression analysis and many other data-mining topics. He discusses how to find regularities in real-world data, how to classify data, and how to process data for knowledge discoveries. The code snippets are so short that they easily fit into single pages. Numeric Computation and Statistical Data Analysis ...

Survival after stereotactic biopsy of malignant gliomas

International Nuclear Information System (INIS)

Coffey, R.J.; Lunsford, L.D.; Taylor, F.H.

1988-01-01

For many patients with malignant gliomas in inaccessible or functionally important locations, stereotactic biopsy followed by radiation therapy (RT) may be a more appropriate initial treatment than craniotomy and tumor resection. We studied the long term survival in 91 consecutive patients with malignant gliomas diagnosed by stereotactic biopsy: 64 had glioblastoma multiforme (GBM) and 27 had anaplastic astrocytoma (AA). Sixty-four per cent of the GBMs and 33% of the AAs involved deep or midline cerebral structures. The treatment prescribed after biopsy, the tumor location, the histological findings, and the patient's age at presentation (for AAs) were statistically important factors determining patient survival. If adequate RT (tumor dose of 5000 to 6000 cGy) was not prescribed, the median survival was less than or equal to 11 weeks regardless of tumor histology or location. The median survival for patients with deep or midline tumors who completed RT was similar in AA (19.4 weeks) and GBM (27 weeks) cases. Histology was an important predictor of survival only for patients with adequately treated lobar tumors. The median survival in lobar GBM patients who completed RT was 46.9 weeks, and that in lobar AA patients who completed RT was 129 weeks. Cytoreductive surgery had no statistically significant effect on survival. Among the clinical factors examined, age of less than 40 years at presentation was associated with prolonged survival only in AA patients. Constellations of clinical features, tumor location, histological diagnosis, and treatment prescribed were related to survival time

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.

System-level analysis of genes and functions affecting survival during nutrient starvation in Saccharomyces cerevisiae.

Science.gov (United States)

Gresham, David; Boer, Viktor M; Caudy, Amy; Ziv, Naomi; Brandt, Nathan J; Storey, John D; Botstein, David

2011-01-01

An essential property of all cells is the ability to exit from active cell division and persist in a quiescent state. For single-celled microbes this primarily occurs in response to nutrient deprivation. We studied the genetic requirements for survival of Saccharomyces cerevisiae when starved for either of two nutrients: phosphate or leucine. We measured the survival of nearly all nonessential haploid null yeast mutants in mixed populations using a quantitative sequencing method that estimates the abundance of each mutant on the basis of frequency of unique molecular barcodes. Starvation for phosphate results in a population half-life of 337 hr whereas starvation for leucine results in a half-life of 27.7 hr. To measure survival of individual mutants in each population we developed a statistical framework that accounts for the multiple sources of experimental variation. From the identities of the genes in which mutations strongly affect survival, we identify genetic evidence for several cellular processes affecting survival during nutrient starvation, including autophagy, chromatin remodeling, mRNA processing, and cytoskeleton function. In addition, we found evidence that mitochondrial and peroxisome function is required for survival. Our experimental and analytical methods represent an efficient and quantitative approach to characterizing genetic functions and networks with unprecedented resolution and identified genotype-by-environment interactions that have important implications for interpretation of studies of aging and quiescence in yeast.

A Divergence Statistics Extension to VTK for Performance Analysis

Energy Technology Data Exchange (ETDEWEB)

Pebay, Philippe Pierre [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Bennett, Janine Camille [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)

2015-02-01

This report follows the series of previous documents ([PT08, BPRT09b, PT09, BPT09, PT10, PB13], where we presented the parallel descriptive, correlative, multi-correlative, principal component analysis, contingency, k -means, order and auto-correlative statistics engines which we developed within the Visualization Tool Kit ( VTK ) as a scalable, parallel and versatile statistics package. We now report on a new engine which we developed for the calculation of divergence statistics, a concept which we hereafter explain and whose main goal is to quantify the discrepancy, in a stasticial manner akin to measuring a distance, between an observed empirical distribution and a theoretical, "ideal" one. The ease of use of the new diverence statistics engine is illustrated by the means of C++ code snippets. Although this new engine does not yet have a parallel implementation, it has already been applied to HPC performance analysis, of which we provide an example.

Developments in statistical analysis in quantitative genetics

DEFF Research Database (Denmark)

Sorensen, Daniel

2009-01-01

of genetic means and variances, models for the analysis of categorical and count data, the statistical genetics of a model postulating that environmental variance is partly under genetic control, and a short discussion of models that incorporate massive genetic marker information. We provide an overview......A remarkable research impetus has taken place in statistical genetics since the last World Conference. This has been stimulated by breakthroughs in molecular genetics, automated data-recording devices and computer-intensive statistical methods. The latter were revolutionized by the bootstrap...... and by Markov chain Monte Carlo (McMC). In this overview a number of specific areas are chosen to illustrate the enormous flexibility that McMC has provided for fitting models and exploring features of data that were previously inaccessible. The selected areas are inferences of the trajectories over time...

On the Statistical Validation of Technical Analysis

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Rosane Riera Freire

2007-06-01

Full Text Available Technical analysis, or charting, aims on visually identifying geometrical patterns in price charts in order to antecipate price "trends". In this paper we revisit the issue of thecnical analysis validation which has been tackled in the literature without taking care for (i the presence of heterogeneity and (ii statistical dependence in the analyzed data - various agglutinated return time series from distinct financial securities. The main purpose here is to address the first cited problem by suggesting a validation methodology that also "homogenizes" the securities according to the finite dimensional probability distribution of their return series. The general steps go through the identification of the stochastic processes for the securities returns, the clustering of similar securities and, finally, the identification of presence, or absence, of informatinal content obtained from those price patterns. We illustrate the proposed methodology with a real data exercise including several securities of the global market. Our investigation shows that there is a statistically significant informational content in two out of three common patterns usually found through technical analysis, namely: triangle, rectangle and head and shoulders.

Histopathological analysis of pre-implantation donor kidney biopsies: association with graft survival and function in one year post-transplantation

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Karla Lais Pêgas

2014-04-01

Full Text Available Introduction: Pre-implantation kidney biopsy is a decision-making tool when considering the use of grafts from deceased donors with expanded criteria, implanting one or two kidneys and comparing this to post-transplantation biopsies. The role of histopathological alterations in kidney compartments as a prognostic factor in graft survival and function has had conflicting results. Objective: This study evaluated the prevalence of chronic alterations in pre-implant biopsies of kidney grafts and the association of findings with graft function and survival in one year post-transplant. Methods: 110 biopsies were analyzed between 2006 and 2009 at Santa Casa de Porto Alegre, including live donors, ideal deceased donors and those with expanded criteria. The score was computed according to criteria suggested by Remuzzi. The glomerular filtration rate (GFR was calculated using the abbreviated MDRD formula. Results: No statistical difference was found in the survival of donors stratified according to Remuzzi criteria. The GFR was significantly associated with the total scores in the groups with mild and moderate alterations, and in the kidney compartments alone, by univariate analysis. The multivariate model found an association with the presence of arteriosclerosis, glomerulosclerosis, acute rejection and delayed graft function. Conclusion: Pre-transplant chronic kidney alterations did not influence the post-transplantation one-year graft survival, but arteriosclerosis and glomerulosclerosis is predictive of a worse GFR. Delayed graft function and acute rejection are independent prognostic factors.

Analysis of single nucleotide variants of HFE gene and association to survival in The Cancer Genome Atlas GBM data.

Science.gov (United States)

Lee, Sang Y; Zhu, Junjia; Salzberg, Anna C; Zhang, Bo; Liu, Dajiang J; Muscat, Joshua E; Langan, Sara T; Connor, James R

2017-01-01

Human hemochromatosis protein (HFE) is involved in iron metabolism. Two major HFE polymorphisms, H63D and C282Y, have been associated with an increased risk of cancers. Previously, we reported decreased gender effects in overall survival based on H63D or C282Y HFE polymorphisms patients with glioblastoma multiforme (GBM). However, the effect of other single nucleotide variation (SNV) in the HFE gene on the cancer development and progression has not been systematically studied. To expand our finding in a larger sample, and to identify other HFE SNV, we analyzed the frequency of somatic SNV in HFE gene and its relationship to survival in GBM patients using The Cancer Genome Atlas (TCGA) GBM (Caucasian only) database. We found 9 SNVs with increased frequency in blood normal of TCGA GBM patients compared to the 1000Genome. Among 9 SNVs, 7 SNVs were located in the intron and 2 SNVs (i.e., H63D, C282Y) in the exon of HFE gene. The statistical analysis demonstrated that blood normal samples of TCGA GBM have more H63D (p = 0.0002, 95% Confidence interval (CI): 0.2119-0.3223) or C282Y (p = 0.0129, 95% CI: 0.0474-0.1159) HFE polymorphisms than 1000Genome. The Kaplan-Meier survival curve for the 264 GBM samples revealed no difference between wild type (WT) HFE and H63D, and WT HFE and C282Y GBM patients. In addition, there was no difference in the survival of male/female GBM patients based on HFE genotype. There was no correlation between HFE expression and survival. In conclusion, the current results suggest that somatic HFE polymorphisms do not impact GBM patients' survival in the TCGA data set of GBM.

Analysis of single nucleotide variants of HFE gene and association to survival in The Cancer Genome Atlas GBM data.

Directory of Open Access Journals (Sweden)

Sang Y Lee

Full Text Available Human hemochromatosis protein (HFE is involved in iron metabolism. Two major HFE polymorphisms, H63D and C282Y, have been associated with an increased risk of cancers. Previously, we reported decreased gender effects in overall survival based on H63D or C282Y HFE polymorphisms patients with glioblastoma multiforme (GBM. However, the effect of other single nucleotide variation (SNV in the HFE gene on the cancer development and progression has not been systematically studied. To expand our finding in a larger sample, and to identify other HFE SNV, we analyzed the frequency of somatic SNV in HFE gene and its relationship to survival in GBM patients using The Cancer Genome Atlas (TCGA GBM (Caucasian only database. We found 9 SNVs with increased frequency in blood normal of TCGA GBM patients compared to the 1000Genome. Among 9 SNVs, 7 SNVs were located in the intron and 2 SNVs (i.e., H63D, C282Y in the exon of HFE gene. The statistical analysis demonstrated that blood normal samples of TCGA GBM have more H63D (p = 0.0002, 95% Confidence interval (CI: 0.2119-0.3223 or C282Y (p = 0.0129, 95% CI: 0.0474-0.1159 HFE polymorphisms than 1000Genome. The Kaplan-Meier survival curve for the 264 GBM samples revealed no difference between wild type (WT HFE and H63D, and WT HFE and C282Y GBM patients. In addition, there was no difference in the survival of male/female GBM patients based on HFE genotype. There was no correlation between HFE expression and survival. In conclusion, the current results suggest that somatic HFE polymorphisms do not impact GBM patients' survival in the TCGA data set of GBM.

Detecting small-study effects and funnel plot asymmetry in meta-analysis of survival data: A comparison of new and existing tests.

Science.gov (United States)

Debray, Thomas P A; Moons, Karel G M; Riley, Richard D

2018-03-01

Small-study effects are a common threat in systematic reviews and may indicate publication bias. Their existence is often verified by visual inspection of the funnel plot. Formal tests to assess the presence of funnel plot asymmetry typically estimate the association between the reported effect size and their standard error, the total sample size, or the inverse of the total sample size. In this paper, we demonstrate that the application of these tests may be less appropriate in meta-analysis of survival data, where censoring influences statistical significance of the hazard ratio. We subsequently propose 2 new tests that are based on the total number of observed events and adopt a multiplicative variance component. We compare the performance of the various funnel plot asymmetry tests in an extensive simulation study where we varied the true hazard ratio (0.5 to 1), the number of published trials (N=10 to 100), the degree of censoring within trials (0% to 90%), and the mechanism leading to participant dropout (noninformative versus informative). Results demonstrate that previous well-known tests for detecting funnel plot asymmetry suffer from low power or excessive type-I error rates in meta-analysis of survival data, particularly when trials are affected by participant dropout. Because our novel test (adopting estimates of the asymptotic precision as study weights) yields reasonable power and maintains appropriate type-I error rates, we recommend its use to evaluate funnel plot asymmetry in meta-analysis of survival data. The use of funnel plot asymmetry tests should, however, be avoided when there are few trials available for any meta-analysis. © 2017 The Authors. Research Synthesis Methods Published by John Wiley & Sons, Ltd.

Factors of influence upon overall survival in the treatment of intracranial MPNSTs. Review of the literature and report of a case

International Nuclear Information System (INIS)

Gousias, Konstantinos; Boström, Jan; Kovacs, Attila; Niehusmann, Pitt; Wagner, Ingo; Kristof, Rudolf

2010-01-01

Intracranial malignant peripheral nerve sheath tumors are rare entities that carry a poor prognosis. To date, there are no established therapeutic strategies for these tumors. We review the present treatment modalities and present the current therapeutic dilemmas. We perform a statistical analysis to evaluate the prognostic factors for Overall Survival of these patients. Additionally, we present our experience with a 64-year-old man with a MPNST of the left cerebellopontine angle. To our best knowledge, forty three patients with intracranial MPNSTs, including our case, have been published in the international literature. Our analysis showed gross total resection, radiotherapy and female gender to be beneficial prognostic factors of survival in the univariate analysis. Gross total resection was recognized as the only independent predictor of prolonged Overall Survival. In our case, we performed a gross total resection followed for the first time by stereotactically guided radiotherapy. Considering the results of the statistical analysis and the known advantages of the stereotaxy, we suggest aggressive surgery followed by stereotactically guided radiotherapy as therapy of choice

Models for probability and statistical inference theory and applications

CERN Document Server

Stapleton, James H

2007-01-01

This concise, yet thorough, book is enhanced with simulations and graphs to build the intuition of readersModels for Probability and Statistical Inference was written over a five-year period and serves as a comprehensive treatment of the fundamentals of probability and statistical inference. With detailed theoretical coverage found throughout the book, readers acquire the fundamentals needed to advance to more specialized topics, such as sampling, linear models, design of experiments, statistical computing, survival analysis, and bootstrapping.Ideal as a textbook for a two-semester sequence on probability and statistical inference, early chapters provide coverage on probability and include discussions of: discrete models and random variables; discrete distributions including binomial, hypergeometric, geometric, and Poisson; continuous, normal, gamma, and conditional distributions; and limit theory. Since limit theory is usually the most difficult topic for readers to master, the author thoroughly discusses mo...

Data management and statistical analysis for environmental assessment

International Nuclear Information System (INIS)

Wendelberger, J.R.; McVittie, T.I.

1995-01-01

Data management and statistical analysis for environmental assessment are important issues on the interface of computer science and statistics. Data collection for environmental decision making can generate large quantities of various types of data. A database/GIS system developed is described which provides efficient data storage as well as visualization tools which may be integrated into the data analysis process. FIMAD is a living database and GIS system. The system has changed and developed over time to meet the needs of the Los Alamos National Laboratory Restoration Program. The system provides a repository for data which may be accessed by different individuals for different purposes. The database structure is driven by the large amount and varied types of data required for environmental assessment. The integration of the database with the GIS system provides the foundation for powerful visualization and analysis capabilities

Compliance strategy for statistically based neutron overpower protection safety analysis methodology

International Nuclear Information System (INIS)

Holliday, E.; Phan, B.; Nainer, O.

2009-01-01

The methodology employed in the safety analysis of the slow Loss of Regulation (LOR) event in the OPG and Bruce Power CANDU reactors, referred to as Neutron Overpower Protection (NOP) analysis, is a statistically based methodology. Further enhancement to this methodology includes the use of Extreme Value Statistics (EVS) for the explicit treatment of aleatory and epistemic uncertainties, and probabilistic weighting of the initial core states. A key aspect of this enhanced NOP methodology is to demonstrate adherence, or compliance, with the analysis basis. This paper outlines a compliance strategy capable of accounting for the statistical nature of the enhanced NOP methodology. (author)

Bayesian Analysis for Dynamic Generalized Linear Latent Model with Application to Tree Survival Rate

Directory of Open Access Journals (Sweden)

Yu-sheng Cheng

2014-01-01

Full Text Available Logistic regression model is the most popular regression technique, available for modeling categorical data especially for dichotomous variables. Classic logistic regression model is typically used to interpret relationship between response variables and explanatory variables. However, in real applications, most data sets are collected in follow-up, which leads to the temporal correlation among the data. In order to characterize the different variables correlations, a new method about the latent variables is introduced in this study. At the same time, the latent variables about AR (1 model are used to depict time dependence. In the framework of Bayesian analysis, parameters estimates and statistical inferences are carried out via Gibbs sampler with Metropolis-Hastings (MH algorithm. Model comparison, based on the Bayes factor, and forecasting/smoothing of the survival rate of the tree are established. A simulation study is conducted to assess the performance of the proposed method and a pika data set is analyzed to illustrate the real application. Since Bayes factor approaches vary significantly, efficiency tests have been performed in order to decide which solution provides a better tool for the analysis of real relational data sets.

Factors predicting survival following noninvasive ventilation in amyotrophic lateral sclerosis.

Science.gov (United States)

Peysson, S; Vandenberghe, N; Philit, F; Vial, C; Petitjean, T; Bouhour, F; Bayle, J Y; Broussolle, E

2008-01-01

The involvement of respiratory muscles is a major predicting factor for survival in amyotrophic lateral sclerosis (ALS). Recent studies show that noninvasive ventilation (NIV) can relieve symptoms of alveolar hypoventilation. However, factors predicting survival in ALS patients when treated with NIV need to be clarified. We conducted a retrospective study of 33 consecutive ALS patients receiving NIV. Ten patients had bulbar onset. We determined the median survivals from onset, diagnosis and initiation of NIV and factors predicting survival. Statistical analysis was performed using the Kaplan-Meier test and Cox proportional hazard models. The median initial and maximal total uses of NIV were 10 and 14 h/24h. The overall median survival from ALS onset was 34.2 months and worsened with increasing age and bulbar onset of the disease. The median survival from initiation of NIV was 8.4 months and was significantly poorer in patients with advanced age or with airway mucus accumulation. Survival from initiation of NIV was not influenced by respiratory parameters or bulbar symptoms. Advanced age at diagnosis and airway mucus accumulation represent poorer prognostic factors of ALS patients treated with NIV. NIV is a helpful treatment of sleep-disordered breathing, including patients with bulbar involvement. Copyright 2008 S. Karger AG, Basel.

Robust inference from multiple test statistics via permutations: a better alternative to the single test statistic approach for randomized trials.

Science.gov (United States)

Ganju, Jitendra; Yu, Xinxin; Ma, Guoguang Julie

2013-01-01

Formal inference in randomized clinical trials is based on controlling the type I error rate associated with a single pre-specified statistic. The deficiency of using just one method of analysis is that it depends on assumptions that may not be met. For robust inference, we propose pre-specifying multiple test statistics and relying on the minimum p-value for testing the null hypothesis of no treatment effect. The null hypothesis associated with the various test statistics is that the treatment groups are indistinguishable. The critical value for hypothesis testing comes from permutation distributions. Rejection of the null hypothesis when the smallest p-value is less than the critical value controls the type I error rate at its designated value. Even if one of the candidate test statistics has low power, the adverse effect on the power of the minimum p-value statistic is not much. Its use is illustrated with examples. We conclude that it is better to rely on the minimum p-value rather than a single statistic particularly when that single statistic is the logrank test, because of the cost and complexity of many survival trials. Copyright © 2013 John Wiley & Sons, Ltd.

Metformin Use and Endometrial Cancer Survival

Science.gov (United States)

Nevadunsky, Nicole S.; Van Arsdale, Anne; Strickler, Howard D.; Moadel, Alyson; Kaur, Gurpreet; Frimer, Marina; Conroy, Erin; Goldberg, Gary L.; Einstein, Mark H.

2013-01-01

Objective Impaired glucose tolerance and diabetes are risk factors for the development of uterine cancer. Although greater progression free survival among diabetic patients with ovarian and breast cancer using metformin have been reported, no studies have assessed the association of metformin use with survival in women with endometrial cancer (EC). Methods We conducted a single-institution retrospective cohort study of all patients treated for uterine cancer from January 1999 through December 2009. Demographic, medical, social, and survival data were abstracted from medical records and the national death registry. Overall survival (OS) was estimated using Kaplan-Meier methods. Cox models were utilized for multivariate analysis. All statistical tests were two-sided. Results Of 985 patients, 114 (12%) had diabetes and were treated with metformin, 136 (14%) were diabetic but did not use metformin, and 735 (74%) had not been diagnosed with diabetes. Greater OS was observed in diabetics with non-endometrioid EC who used metformin than in diabetic cases not using metformin and non-endometrioid EC cases without diabetes (log rank test (p=0.02)). This association remained significant (hazard ratio = 0.54, 95% CI: 0.30–0.97, p<0.04) after adjusting for age, clinical stage, grade, chemotherapy treatment, radiation treatment and presence of hyperlipidemia in multivariate analysis. No association between metformin use and OS in diabetics with endometrioid histology was observed. Conclusion Diabetic EC patients with non-endometrioid tumors who used metformin had lower risk of death than women with EC who did not use metformin. These data suggest that metformin might be useful as adjuvant therapy for non-endometrioid EC. PMID:24189334

Diagnosis checking of statistical analysis in RCTs indexed in PubMed.

Science.gov (United States)

Lee, Paul H; Tse, Andy C Y

2017-11-01

Statistical analysis is essential for reporting of the results of randomized controlled trials (RCTs), as well as evaluating their effectiveness. However, the validity of a statistical analysis also depends on whether the assumptions of that analysis are valid. To review all RCTs published in journals indexed in PubMed during December 2014 to provide a complete picture of how RCTs handle assumptions of statistical analysis. We reviewed all RCTs published in December 2014 that appeared in journals indexed in PubMed using the Cochrane highly sensitive search strategy. The 2014 impact factors of the journals were used as proxies for their quality. The type of statistical analysis used and whether the assumptions of the analysis were tested were reviewed. In total, 451 papers were included. Of the 278 papers that reported a crude analysis for the primary outcomes, 31 (27·2%) reported whether the outcome was normally distributed. Of the 172 papers that reported an adjusted analysis for the primary outcomes, diagnosis checking was rarely conducted, with only 20%, 8·6% and 7% checked for generalized linear model, Cox proportional hazard model and multilevel model, respectively. Study characteristics (study type, drug trial, funding sources, journal type and endorsement of CONSORT guidelines) were not associated with the reporting of diagnosis checking. The diagnosis of statistical analyses in RCTs published in PubMed-indexed journals was usually absent. Journals should provide guidelines about the reporting of a diagnosis of assumptions. © 2017 Stichting European Society for Clinical Investigation Journal Foundation.

Analysis of audiometric relapse-free survival in patients with immune-mediated hearing loss exclusively treated with corticosteroids.

Science.gov (United States)

Mata-Castro, Nieves; García-Chilleron, Raimon; Gavilanes-Plasencia, Javier; Ramírez-Camacho, Rafael; García-Fernández, Alfredo; García-Berrocal, José Ramón

2017-10-12

To describe the results in terms of audiometric relapse-free survival and relapse rate in immunomediated hearing loss patients treated exclusively with corticosteroids. Retrospective study of patients with audiometric relapses, monitored from 1995 to 2014, in two centres of the Community of Madrid. We evaluated 31 patients with a mean age of 48.52 years (14.67 SD), of which 61.3% were women. Most hearing loss was fluctuating (48.4%). Only 16.1% of patients had systemic autoimmune disease. There is a moderate positive correlation between the sex variable and the systemic involvement variable (Spearman's correlation coefficient=0.356): specifically, between being female and systemic disease. The relative incidence rate of relapse in the first year was 2.01 relapses/year with a 95% CI (1.32 to 2.92). The mean survival time of the event (audiometric relapse) was 5.25 months (SD 0.756). With multivariate analysis, the only variable that achieved statistical significance was age, with a hazard ratio of 1.032 (95% CI; 1.001-1.063, P=.043). Immune-mediated disease of the inner ear is a chronic disease with relapses. Half of the patients with immunomediated hearing loss treated exclusively with corticosteroids relapse before 6 months of follow-up. In addition, if a patient has not relapsed, they are more likely to relapse as each year passes. Analysis of the of audiometric relapse- free survival will enable the effect of future treatments to be compared and their capacity to reduce the rhythm of relapses. Copyright © 2017 Elsevier España, S.L.U. and Sociedad Española de Otorrinolaringología y Cirugía de Cabeza y Cuello. All rights reserved.

A κ-generalized statistical mechanics approach to income analysis

Science.gov (United States)

Clementi, F.; Gallegati, M.; Kaniadakis, G.

2009-02-01

This paper proposes a statistical mechanics approach to the analysis of income distribution and inequality. A new distribution function, having its roots in the framework of κ-generalized statistics, is derived that is particularly suitable for describing the whole spectrum of incomes, from the low-middle income region up to the high income Pareto power-law regime. Analytical expressions for the shape, moments and some other basic statistical properties are given. Furthermore, several well-known econometric tools for measuring inequality, which all exist in a closed form, are considered. A method for parameter estimation is also discussed. The model is shown to fit remarkably well the data on personal income for the United States, and the analysis of inequality performed in terms of its parameters is revealed as very powerful.

A κ-generalized statistical mechanics approach to income analysis

International Nuclear Information System (INIS)

Clementi, F; Gallegati, M; Kaniadakis, G

2009-01-01

This paper proposes a statistical mechanics approach to the analysis of income distribution and inequality. A new distribution function, having its roots in the framework of κ-generalized statistics, is derived that is particularly suitable for describing the whole spectrum of incomes, from the low–middle income region up to the high income Pareto power-law regime. Analytical expressions for the shape, moments and some other basic statistical properties are given. Furthermore, several well-known econometric tools for measuring inequality, which all exist in a closed form, are considered. A method for parameter estimation is also discussed. The model is shown to fit remarkably well the data on personal income for the United States, and the analysis of inequality performed in terms of its parameters is revealed as very powerful

Normality Tests for Statistical Analysis: A Guide for Non-Statisticians

Science.gov (United States)

Ghasemi, Asghar; Zahediasl, Saleh

2012-01-01

Statistical errors are common in scientific literature and about 50% of the published articles have at least one error. The assumption of normality needs to be checked for many statistical procedures, namely parametric tests, because their validity depends on it. The aim of this commentary is to overview checking for normality in statistical analysis using SPSS. PMID:23843808

Development of computer-assisted instruction application for statistical data analysis android platform as learning resource

Science.gov (United States)

Hendikawati, P.; Arifudin, R.; Zahid, M. Z.

2018-03-01

This study aims to design an android Statistics Data Analysis application that can be accessed through mobile devices to making it easier for users to access. The Statistics Data Analysis application includes various topics of basic statistical along with a parametric statistics data analysis application. The output of this application system is parametric statistics data analysis that can be used for students, lecturers, and users who need the results of statistical calculations quickly and easily understood. Android application development is created using Java programming language. The server programming language uses PHP with the Code Igniter framework, and the database used MySQL. The system development methodology used is the Waterfall methodology with the stages of analysis, design, coding, testing, and implementation and system maintenance. This statistical data analysis application is expected to support statistical lecturing activities and make students easier to understand the statistical analysis of mobile devices.

Risk Prediction of One-Year Mortality in Patients with Cardiac Arrhythmias Using Random Survival Forest

Directory of Open Access Journals (Sweden)

Fen Miao

2015-01-01

Full Text Available Existing models for predicting mortality based on traditional Cox proportional hazard approach (CPH often have low prediction accuracy. This paper aims to develop a clinical risk model with good accuracy for predicting 1-year mortality in cardiac arrhythmias patients using random survival forest (RSF, a robust approach for survival analysis. 10,488 cardiac arrhythmias patients available in the public MIMIC II clinical database were investigated, with 3,452 deaths occurring within 1-year followups. Forty risk factors including demographics and clinical and laboratory information and antiarrhythmic agents were analyzed as potential predictors of all-cause mortality. RSF was adopted to build a comprehensive survival model and a simplified risk model composed of 14 top risk factors. The built comprehensive model achieved a prediction accuracy of 0.81 measured by c-statistic with 10-fold cross validation. The simplified risk model also achieved a good accuracy of 0.799. Both results outperformed traditional CPH (which achieved a c-statistic of 0.733 for the comprehensive model and 0.718 for the simplified model. Moreover, various factors are observed to have nonlinear impact on cardiac arrhythmias prognosis. As a result, RSF based model which took nonlinearity into account significantly outperformed traditional Cox proportional hazard model and has great potential to be a more effective approach for survival analysis.

Statistical analysis of metallicity in spiral galaxies

Energy Technology Data Exchange (ETDEWEB)

Galeotti, P [Consiglio Nazionale delle Ricerche, Turin (Italy). Lab. di Cosmo-Geofisica; Turin Univ. (Italy). Ist. di Fisica Generale)

1981-04-01

A principal component analysis of metallicity and other integral properties of 33 spiral galaxies is presented; the involved parameters are: morphological type, diameter, luminosity and metallicity. From the statistical analysis it is concluded that the sample has only two significant dimensions and additonal tests, involving different parameters, show similar results. Thus it seems that only type and luminosity are independent variables, being the other integral properties of spiral galaxies correlated with them.

Biochemical Control With Radiotherapy Improves Overall Survival in Intermediate and High-Risk Prostate Cancer Patients Who Have an Estimated 10-Year Overall Survival of >90%

International Nuclear Information System (INIS)

Herbert, Christopher; Liu, Mitchell; Tyldesley, Scott; Morris, W. James; Joffres, Michel; Khaira, Mandip; Kwan, Winkle; Moiseenko, Vitali; Pickles, Thomas

2012-01-01

Purpose: To identify subgroups of patients with carcinoma of the prostate treated with radical radiotherapy that have improved overall survival when disease is biochemically controlled. Methods and Materials: A cohort of 1,060 prostate cancer patients treated with radical radiotherapy was divided into nine subgroups based on National Comprehensive Cancer Network risk category and estimated 10-year overall survival (eOS 10y) derived from the age adjusted Charlson Comorbidity Index. Patients with and without biochemical control were compared with respect to overall survival. Actuarial estimates of overall survival were calculated using the Kaplan-Meier method. Univariate and multivariate Cox proportional hazards models were used for analysis of overall survival. Results: Median follow-up was 125 months (range, 51–176 months). Only the subgroups with high or intermediate risk disease and an eOS 10y of >90% had a statistically significantly improved overall survival when prostate cancer was biochemically controlled. In all other groups, biochemical control made no significant difference to overall survival. In the subgroup with high-risk disease and eOS 10y >90%, actuarial overall survival was 86.3% (95% confidence interval [CI] 78.5%–94.1%) and 62.1% (95% CI 52.9%–71.3%) for patients with biochemical control and biochemical relapse respectively (p = 0.002). In the intermediate risk group with eOS >90%, actuarial overall survival was 95.3% (95% CI 89.0%–100%) and 79.8% (95% CI 68.0%–91.6%) for biochemically controlled and biochemically relapsed patients (p = 0.033). On multivariate analysis, National Comprehensive Cancer Network risk group (p = 0.005), biochemical control (p = 0.033) and eOS 10y (p 90%.

Statistical Analysis of Protein Ensembles

Science.gov (United States)

Máté, Gabriell; Heermann, Dieter

2014-04-01

As 3D protein-configuration data is piling up, there is an ever-increasing need for well-defined, mathematically rigorous analysis approaches, especially that the vast majority of the currently available methods rely heavily on heuristics. We propose an analysis framework which stems from topology, the field of mathematics which studies properties preserved under continuous deformations. First, we calculate a barcode representation of the molecules employing computational topology algorithms. Bars in this barcode represent different topological features. Molecules are compared through their barcodes by statistically determining the difference in the set of their topological features. As a proof-of-principle application, we analyze a dataset compiled of ensembles of different proteins, obtained from the Ensemble Protein Database. We demonstrate that our approach correctly detects the different protein groupings.

State analysis of BOP using statistical and heuristic methods

International Nuclear Information System (INIS)

Heo, Gyun Young; Chang, Soon Heung

2003-01-01

Under the deregulation environment, the performance enhancement of BOP in nuclear power plants is being highlighted. To analyze performance level of BOP, we use the performance test procedures provided from an authorized institution such as ASME. However, through plant investigation, it was proved that the requirements of the performance test procedures about the reliability and quantity of sensors was difficult to be satisfied. As a solution of this, state analysis method that are the expanded concept of signal validation, was proposed on the basis of the statistical and heuristic approaches. Authors recommended the statistical linear regression model by analyzing correlation among BOP parameters as a reference state analysis method. Its advantage is that its derivation is not heuristic, it is possible to calculate model uncertainty, and it is easy to apply to an actual plant. The error of the statistical linear regression model is below 3% under normal as well as abnormal system states. Additionally a neural network model was recommended since the statistical model is impossible to apply to the validation of all of the sensors and is sensitive to the outlier that is the signal located out of a statistical distribution. Because there are a lot of sensors need to be validated in BOP, wavelet analysis (WA) were applied as a pre-processor for the reduction of input dimension and for the enhancement of training accuracy. The outlier localization capability of WA enhanced the robustness of the neural network. The trained neural network restored the degraded signals to the values within ±3% of the true signals

The influence of design characteristics on statistical inference in nonlinear estimation: A simulation study based on survival data and hazard modeling

DEFF Research Database (Denmark)

Andersen, J.S.; Bedaux, J.J.M.; Kooijman, S.A.L.M.

2000-01-01

This paper describes the influence of design characteristics on the statistical inference for an ecotoxicological hazard-based model using simulated survival data. The design characteristics of interest are the number and spacing of observations (counts) in time, the number and spacing of exposure...... concentrations (within c(min) and c(max)), and the initial number of individuals at time 0 in each concentration. A comparison of the coverage probabilities for confidence limits arising from the profile-likelihood approach and the Wald-based approach is carried out. The Wald-based approach is very sensitive...

Precision Statistical Analysis of Images Based on Brightness Distribution

Directory of Open Access Journals (Sweden)

Muzhir Shaban Al-Ani

2017-07-01

Full Text Available Study the content of images is considered an important topic in which reasonable and accurate analysis of images are generated. Recently image analysis becomes a vital field because of huge number of images transferred via transmission media in our daily life. These crowded media with images lead to highlight in research area of image analysis. In this paper, the implemented system is passed into many steps to perform the statistical measures of standard deviation and mean values of both color and grey images. Whereas the last step of the proposed method concerns to compare the obtained results in different cases of the test phase. In this paper, the statistical parameters are implemented to characterize the content of an image and its texture. Standard deviation, mean and correlation values are used to study the intensity distribution of the tested images. Reasonable results are obtained for both standard deviation and mean value via the implementation of the system. The major issue addressed in the work is concentrated on brightness distribution via statistical measures applying different types of lighting.

Analysis of the Indicence and Survival of Female Breast Cancer Patients in Beijing Over a 20-Year Period

Institute of Scientific and Technical Information of China (English)

Qijun Wang; Weixing Zhu; Xiumei Xing; Chenxu Qu

2006-01-01

OBJECTIVE To provide evidence for breast cancer prevention and control through epidemiological analysis of the incidence, mortality and survival rate of female breast cancer patients in Beijing.METHODS The female registration data in the Beijing urban area from 1982 to 2001 were retrospectively reviewed. The incidence, mortality and survival rate of female breast cancer patients were analyzed using routine and life-table statistical methods.RESULTS During the period of 1982 to 2001, there was a trend of an average annual increase of female breast cancer incidence of 4.6% in urban Beijing, and of 4.9% in the world-population standardized incidence.The epidemiological features of urban Beijing female breast cancer showed:(1)The incidence distribution of different age groups from 25 to 80 years elevated with two peaks at ages of 45～ and 70～ years; (2)There was an elevation in each age group over the last 20 years; (3)The incidence rate at ages of 35 to 64 reached 95.3/105, causing breast cancer to become the number one cancer in females. The changes in the survival rate showed the following: the 5-year observed survival rate (OSR)increased from 62.0% in 1982～1983 to 68.7% in 1987～1988, and the relative-survival rate (RSR) increased from 66.3% to 74.2%. The 10-year OSR and RSR in 1987～1988 were 60.3% and 65.1%, and at 15 years 57.5% and 61.3%, respectively. The mortality rate of breast cancer patients fluctuated from 8 to 10 per 105 population over the 20 years of study.CONCLUSION There is a trend of an annual increase in female breast cancer in Beijing. The 5-year survival is being improved gradually while the mortality remains stable. The results demonstrate that the principles of "early prevention, diagnosis and treatment" for breast cancer are effective in Beijing.

Influence of prognostic factors to the survival of lung cancer patients

International Nuclear Information System (INIS)

Plieskiene, A.; Juozaityte, E.; Inciura, A. and others; Sakalauskas, R.

2003-01-01

This study presents the results of analysis of 134 lung cancer patients treated with radiotherapy in 1999-2002. The objective of the paper was to evaluate the importance of some prognostic factors on survival of lung cancer patients. We have analyzed influence of patient's age, stage of the disease, tumor size, lymphnodes status, histological type and radiotherapy dose to the survival of lung cancer patients. Among analyzed patients 87% were males and 73.9% were more than 60 years old. Locally advanced lung cancer was diagnosed in 65.6% of cases. The non-small cell lung cancer was diagnosed in 83.8% of cases. During the study period 58.2% of patients died. Statistically significant prognostic factors in our study were: stage, locally advanced lung cancer, involvement of the lymphnodes, III B and IV of the disease. The survival of the patients depends on the radiotherapy dose in our study. The better survival was associated with the bigger than 50 Gy dose (p<0.001). (author)

Relation between delay and survival in 596 patients with breast cancer.

Science.gov (United States)

Machiavelli, M; Leone, B; Romero, A; Perez, J; Vallejo, C; Bianco, A; Rodriguez, R; Estevez, R; Chacon, R; Dansky, C

1989-01-01

To evaluate the influence of delay between first symptom and first treatment upon survival the medical records of 596 patients with breast cancer were reviewed. The following intervals were considered: less than 3 months; 3-6 months and greater than 6 months. Patients in the less than 3 months delay group had a better distribution by clinical stages and a 10-year survival rate higher than those in the longer delay groups (p = 0.034). However, within each stage no statistically significant difference in survival according to delay was observed. A Cox multivariate analysis revealed that performance status and stage of disease were independent predictors of survival, but not delay. Assuming the best prognosis for patients with clinical stages I and II and less than 3 months delay, the group with longer delay times had 15 deaths over what would have been predicted. This adverse effect was observed almost exclusively among patients over age 50 (14/15).

Fisher statistics for analysis of diffusion tensor directional information.

Science.gov (United States)

Hutchinson, Elizabeth B; Rutecki, Paul A; Alexander, Andrew L; Sutula, Thomas P

2012-04-30

A statistical approach is presented for the quantitative analysis of diffusion tensor imaging (DTI) directional information using Fisher statistics, which were originally developed for the analysis of vectors in the field of paleomagnetism. In this framework, descriptive and inferential statistics have been formulated based on the Fisher probability density function, a spherical analogue of the normal distribution. The Fisher approach was evaluated for investigation of rat brain DTI maps to characterize tissue orientation in the corpus callosum, fornix, and hilus of the dorsal hippocampal dentate gyrus, and to compare directional properties in these regions following status epilepticus (SE) or traumatic brain injury (TBI) with values in healthy brains. Direction vectors were determined for each region of interest (ROI) for each brain sample and Fisher statistics were applied to calculate the mean direction vector and variance parameters in the corpus callosum, fornix, and dentate gyrus of normal rats and rats that experienced TBI or SE. Hypothesis testing was performed by calculation of Watson's F-statistic and associated p-value giving the likelihood that grouped observations were from the same directional distribution. In the fornix and midline corpus callosum, no directional differences were detected between groups, however in the hilus, significant (pstatistical comparison of tissue structural orientation. Copyright © 2012 Elsevier B.V. All rights reserved.

Statistical analysis of RHIC beam position monitors performance

Science.gov (United States)

Calaga, R.; Tomás, R.

2004-04-01

A detailed statistical analysis of beam position monitors (BPM) performance at RHIC is a critical factor in improving regular operations and future runs. Robust identification of malfunctioning BPMs plays an important role in any orbit or turn-by-turn analysis. Singular value decomposition and Fourier transform methods, which have evolved as powerful numerical techniques in signal processing, will aid in such identification from BPM data. This is the first attempt at RHIC to use a large set of data to statistically enhance the capability of these two techniques and determine BPM performance. A comparison from run 2003 data shows striking agreement between the two methods and hence can be used to improve BPM functioning at RHIC and possibly other accelerators.

Statistical analysis of RHIC beam position monitors performance

Directory of Open Access Journals (Sweden)

R. Calaga

2004-04-01

Full Text Available A detailed statistical analysis of beam position monitors (BPM performance at RHIC is a critical factor in improving regular operations and future runs. Robust identification of malfunctioning BPMs plays an important role in any orbit or turn-by-turn analysis. Singular value decomposition and Fourier transform methods, which have evolved as powerful numerical techniques in signal processing, will aid in such identification from BPM data. This is the first attempt at RHIC to use a large set of data to statistically enhance the capability of these two techniques and determine BPM performance. A comparison from run 2003 data shows striking agreement between the two methods and hence can be used to improve BPM functioning at RHIC and possibly other accelerators.

Statistics Education Research in Malaysia and the Philippines: A Comparative Analysis

Science.gov (United States)

Reston, Enriqueta; Krishnan, Saras; Idris, Noraini

2014-01-01

This paper presents a comparative analysis of statistics education research in Malaysia and the Philippines by modes of dissemination, research areas, and trends. An electronic search for published research papers in the area of statistics education from 2000-2012 yielded 20 for Malaysia and 19 for the Philippines. Analysis of these papers showed…

Common errors in statistics (and how to avoid them)

CERN Document Server

Good, Phillip I

2012-01-01

The Fourth Edition of this tried-and-true book elaborates on many key topics such as epidemiological studies, distribution of data; baseline data incorporation; case control studies; simulations; statistical theory publication; biplots; instrumental variables; ecological regression; result reporting, survival analysis; etc. Including new modifications and figures, the book also covers such topics as research plan creation; data collection; hypothesis formulation and testing; coefficient estimates; sample size specifications; assumption checking; p-values interpretations and confidence interval

Statistical analysis of next generation sequencing data

CERN Document Server

Nettleton, Dan

2014-01-01

Next Generation Sequencing (NGS) is the latest high throughput technology to revolutionize genomic research. NGS generates massive genomic datasets that play a key role in the big data phenomenon that surrounds us today. To extract signals from high-dimensional NGS data and make valid statistical inferences and predictions, novel data analytic and statistical techniques are needed. This book contains 20 chapters written by prominent statisticians working with NGS data. The topics range from basic preprocessing and analysis with NGS data to more complex genomic applications such as copy number variation and isoform expression detection. Research statisticians who want to learn about this growing and exciting area will find this book useful. In addition, many chapters from this book could be included in graduate-level classes in statistical bioinformatics for training future biostatisticians who will be expected to deal with genomic data in basic biomedical research, genomic clinical trials and personalized med...

Selected papers on analysis, probability, and statistics

CERN Document Server

Nomizu, Katsumi

1994-01-01

This book presents papers that originally appeared in the Japanese journal Sugaku. The papers fall into the general area of mathematical analysis as it pertains to probability and statistics, dynamical systems, differential equations and analytic function theory. Among the topics discussed are: stochastic differential equations, spectra of the Laplacian and Schrödinger operators, nonlinear partial differential equations which generate dissipative dynamical systems, fractal analysis on self-similar sets and the global structure of analytic functions.

Analysis of statistical misconception in terms of statistical reasoning

Science.gov (United States)

Maryati, I.; Priatna, N.

2018-05-01

Reasoning skill is needed for everyone to face globalization era, because every person have to be able to manage and use information from all over the world which can be obtained easily. Statistical reasoning skill is the ability to collect, group, process, interpret, and draw conclusion of information. Developing this skill can be done through various levels of education. However, the skill is low because many people assume that statistics is just the ability to count and using formulas and so do students. Students still have negative attitude toward course which is related to research. The purpose of this research is analyzing students’ misconception in descriptive statistic course toward the statistical reasoning skill. The observation was done by analyzing the misconception test result and statistical reasoning skill test; observing the students’ misconception effect toward statistical reasoning skill. The sample of this research was 32 students of math education department who had taken descriptive statistic course. The mean value of misconception test was 49,7 and standard deviation was 10,6 whereas the mean value of statistical reasoning skill test was 51,8 and standard deviation was 8,5. If the minimal value is 65 to state the standard achievement of a course competence, students’ mean value is lower than the standard competence. The result of students’ misconception study emphasized on which sub discussion that should be considered. Based on the assessment result, it was found that students’ misconception happen on this: 1) writing mathematical sentence and symbol well, 2) understanding basic definitions, 3) determining concept that will be used in solving problem. In statistical reasoning skill, the assessment was done to measure reasoning from: 1) data, 2) representation, 3) statistic format, 4) probability, 5) sample, and 6) association.

Comparative analysis of positive and negative attitudes toward statistics

Science.gov (United States)

Ghulami, Hassan Rahnaward; Ab Hamid, Mohd Rashid; Zakaria, Roslinazairimah

2015-02-01

Many statistics lecturers and statistics education researchers are interested to know the perception of their students' attitudes toward statistics during the statistics course. In statistics course, positive attitude toward statistics is a vital because it will be encourage students to get interested in the statistics course and in order to master the core content of the subject matters under study. Although, students who have negative attitudes toward statistics they will feel depressed especially in the given group assignment, at risk for failure, are often highly emotional, and could not move forward. Therefore, this study investigates the students' attitude towards learning statistics. Six latent constructs have been the measurement of students' attitudes toward learning statistic such as affect, cognitive competence, value, difficulty, interest, and effort. The questionnaire was adopted and adapted from the reliable and validate instrument of Survey of Attitudes towards Statistics (SATS). This study is conducted among engineering undergraduate engineering students in the university Malaysia Pahang (UMP). The respondents consist of students who were taking the applied statistics course from different faculties. From the analysis, it is found that the questionnaire is acceptable and the relationships among the constructs has been proposed and investigated. In this case, students show full effort to master the statistics course, feel statistics course enjoyable, have confidence that they have intellectual capacity, and they have more positive attitudes then negative attitudes towards statistics learning. In conclusion in terms of affect, cognitive competence, value, interest and effort construct the positive attitude towards statistics was mostly exhibited. While negative attitudes mostly exhibited by difficulty construct.

Survival of ceramic veneers made of different materials after a minimum follow-up period of five years: a systematic review and meta-analysis.

Science.gov (United States)

Petridis, Haralampos P; Zekeridou, Alkisti; Malliari, Maria; Tortopidis, Dimitrios; Koidis, Petros

2012-01-01

The purpose of this systematic review was to compare the survival and complication rates of ceramic veneers produced with different techniques and materials after a minimum follow-up time of 5 years. A literature search was conducted, using electronic databases, relevant references, citations and journal researching, for clinical studies reporting on the survival of ceramic veneers fabricated with different techniques and materials with a mean followup time of at least 5 years. The search period spanned from January 1980 up to October 2010. Event rates were calculated for the following complications associated with ceramic veneers: fracture, debonding, marginal discoloration, marginal integrity, and caries. Summary estimates, and 5-year event rates were reported. Comparison between subgroups of different materials, as well as statistical significance, was calculated using a mixed effects model. Nine studies were selected for final analysis over an initial yield of 409 titles. No study directly compared the incidence of complications between ceramic veneers fabricated from different materials. Four of the included studies reported on the survival of ceramic veneers made out of feldspathic ceramics; four studies were on glass-ceramic veneers and one study included veneers fabricated from both materials. The mean observation time ranged between 5 and 10 years. Overall, the 5-year complication rates were low, with the exception of studies reporting on extended ceramic veneers. The most frequent complication reported was marginal discoloration (9% at 5 years), followed by marginal integrity (3.9-7.7% at 5 years). There was no statistically significant difference in the event rates between the subgroups of different materials (feldspathic vs. glass-ceramic). The results of this systematic review showed that ceramic veneers fabricated from feldspathic or glass-ceramics have an adequate clinical survival for at least 5 years of clinical service, with very low complication

Prognostic and survival analysis of presbyopia: The healthy twin study

Science.gov (United States)

Lira, Adiyani; Sung, Joohon

2015-12-01

Presbyopia, a vision condition in which the eye loses its flexibility to focus on near objects, is part of ageing process which mostly perceptible in the early or mid 40s. It is well known that age is its major risk factor, while sex, alcohol, poor nutrition, ocular and systemic diseases are known as common risk factors. However, many other variables might influence the prognosis. Therefore in this paper we developed a prognostic model to estimate survival from presbyopia. 1645 participants which part of the Healthy Twin Study, a prospective cohort study that has recruited Korean adult twins and their family members based on a nation-wide registry at public health agencies since 2005, were collected and analyzed by univariate analysis as well as Cox proportional hazard model to reveal the prognostic factors for presbyopia while survival curves were calculated by Kaplan-Meier method. Besides age, sex, diabetes, and myopia; the proposed model shows that education level (especially engineering program) also contribute to the occurrence of presbyopia as well. Generally, at 47 years old, the chance of getting presbyopia becomes higher with the survival probability is less than 50%. Furthermore, our study shows that by stratifying the survival curve, MZ has shorter survival with average onset time about 45.8 compare to DZ and siblings with 47.5 years old. By providing factors that have more effects and mainly associate with presbyopia, we expect that we could help to design an intervention to control or delay its onset time.

Vapor Pressure Data Analysis and Statistics

Science.gov (United States)

2016-12-01

near 8, 2000, and 200, respectively. The A (or a) value is directly related to vapor pressure and will be greater for high vapor pressure materials...1, (10) where n is the number of data points, Yi is the natural logarithm of the i th experimental vapor pressure value, and Xi is the...VAPOR PRESSURE DATA ANALYSIS AND STATISTICS ECBC-TR-1422 Ann Brozena RESEARCH AND TECHNOLOGY DIRECTORATE

Statistical analysis of planktic foraminifera of the surface Continental ...

African Journals Online (AJOL)

Planktic foraminiferal assemblage recorded from selected samples obtained from shallow continental shelf sediments off southwestern Nigeria were subjected to statistical analysis. The Principal Component Analysis (PCA) was used to determine variants of planktic parameters. Values obtained for these parameters were ...

Imaging mass spectrometry statistical analysis.

Science.gov (United States)

Jones, Emrys A; Deininger, Sören-Oliver; Hogendoorn, Pancras C W; Deelder, André M; McDonnell, Liam A

2012-08-30

Imaging mass spectrometry is increasingly used to identify new candidate biomarkers. This clinical application of imaging mass spectrometry is highly multidisciplinary: expertise in mass spectrometry is necessary to acquire high quality data, histology is required to accurately label the origin of each pixel's mass spectrum, disease biology is necessary to understand the potential meaning of the imaging mass spectrometry results, and statistics to assess the confidence of any findings. Imaging mass spectrometry data analysis is further complicated because of the unique nature of the data (within the mass spectrometry field); several of the assumptions implicit in the analysis of LC-MS/profiling datasets are not applicable to imaging. The very large size of imaging datasets and the reporting of many data analysis routines, combined with inadequate training and accessible reviews, have exacerbated this problem. In this paper we provide an accessible review of the nature of imaging data and the different strategies by which the data may be analyzed. Particular attention is paid to the assumptions of the data analysis routines to ensure that the reader is apprised of their correct usage in imaging mass spectrometry research. Copyright © 2012 Elsevier B.V. All rights reserved.

Applied Behavior Analysis and Statistical Process Control?

Science.gov (United States)

Hopkins, B. L.

1995-01-01

Incorporating statistical process control (SPC) methods into applied behavior analysis is discussed. It is claimed that SPC methods would likely reduce applied behavior analysts' intimate contacts with problems and would likely yield poor treatment and research decisions. Cases and data presented by Pfadt and Wheeler (1995) are cited as examples.…

Ten-Year Experience of Renal Transplantation at the Northwest National Medical Center, Sonora Mexico: A Survival Study.

Science.gov (United States)

Ma, M A; Laguna-Teniente, I R

2016-03-01

To improve survival after kidney transplantation, it is important to identify the variables that affect it. The aim of this work was to determine the survival of renal grafts from living and cadaveric donors and the survival of patients with graft failure in a tertiary medical unit in northwest Mexico. We performed a retrospective cohort study of patients who received transplants since 2004 at the center. Database and medical records of patients were reviewed. The data were captured in a database previously designed in the SPSS v21.1 program for statistical processing. A descriptive analysis with frequencies and percentages and numeric variables measure of central tendency and dispersion was conducted. The survival analysis was made with the Kaplan-Meier method to estimate the graft survive. A total of 412 transplantations were performed during the 2004-2013 period. We analyzed 331 records, and the 10-year survival rates of donor allografts from living and cadaveric donors were 86.64% and 72.78%, respectively. Copyright © 2016 Elsevier Inc. All rights reserved.

Dedifferentiated chondrosarcoma: Radiological features, prognostic factors and survival statistics in 23 patients

Science.gov (United States)

Liu, Chenglei; Xi, Yan; Li, Mei; Jiao, Qiong; Zhang, Huizhen; Yang, Qingcheng; Yao, Weiwu

2017-01-01

Background Dedifferentiated chondrosarcoma is a rare, highly malignant tumor with a poor survival. There are many confusing issues concerning the imaging feature that can facilitate early diagnosis and the factors that might be related to outcomes. Methods Twenty-three patients with dedifferentiated chondrosarcoma confirmed by pathology were retrospectively reviewed from 2008 to 2015. The patients’ clinical information, images from radiographs (n = 17), CT (n = 19), and MRI (n = 17), histological features, treatment and prognosis were analyzed. Results There were 12 males and 11 females, and the mean age was 50.39 years old. Fourteen cases affected the axial bone (pelvis, spine), and 9 cases involved the appendicular bone. Seven (41.17%), 9 (47.36), and 12 (66.66%) lesions showed a biphasic nature on radiograph, CT and MRI, respectively. Of the lesions, 17.39% (4/23) were accompanied by pathological fractures. Histologically, the cartilage component was considered histological Grade1 in 12 patients and Grade 2 in 11 patients. The dedifferentiated component showed features of osteosarcoma in 8 cases, malignant fibrous histiocytoma in3 cases, myofibroblastic sarcoma in 1 case and spindle cell sarcoma in 11cases. Twenty-two cases were treated with surgical resection, and 17 cases achieved adequate (wide or radical) surgical margin. In 8 cases, surgery was combined with adjuvant chemotherapy. The overall median survival time was nine months; 17.4% of patients survived to five years. Conclusion Axial bone location, lung metastasis at diagnosis, inadequate surgical margin, incorrect diagnosis before surgery and pathological fractures was related to poorer outcome. Pre- or postoperative chemotherapy had no definitively effect on improved survival. PMID:28301537

Nonparametric Bayesian inference for mean residual life functions in survival analysis.

Science.gov (United States)

Poynor, Valerie; Kottas, Athanasios

2018-01-19

Modeling and inference for survival analysis problems typically revolves around different functions related to the survival distribution. Here, we focus on the mean residual life (MRL) function, which provides the expected remaining lifetime given that a subject has survived (i.e. is event-free) up to a particular time. This function is of direct interest in reliability, medical, and actuarial fields. In addition to its practical interpretation, the MRL function characterizes the survival distribution. We develop general Bayesian nonparametric inference for MRL functions built from a Dirichlet process mixture model for the associated survival distribution. The resulting model for the MRL function admits a representation as a mixture of the kernel MRL functions with time-dependent mixture weights. This model structure allows for a wide range of shapes for the MRL function. Particular emphasis is placed on the selection of the mixture kernel, taken to be a gamma distribution, to obtain desirable properties for the MRL function arising from the mixture model. The inference method is illustrated with a data set of two experimental groups and a data set involving right censoring. The supplementary material available at Biostatistics online provides further results on empirical performance of the model, using simulated data examples. © The Author 2018. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

The design and analysis of salmonid tagging studies in the Columbia Basin. Volume 2: Estimating salmonid survival with combined PIT-CWT tagging. Technical report

International Nuclear Information System (INIS)

Newman, K.

1997-06-01

Passive Integrated Transponder (PIT) tags and Coded Wire Tags (CWTs) in combination can provide information about salmonid survival that single tag releases may not. The release and recapture protocol affects which survival and recapture rates can be estimated and the precision of the estimates. For the particular case of Columbia river salmonids tagged with both PIT tags and CWTs, three different release and recapture protocols were evaluated. This report addresses the need to study the fate of salmon smolt in-river and their subsequent return as adults. Double-tagging procedures are investigated where PIT-tags would be used to provide in-river survival data during smolt outmigrations and coded-wire tags (CWT) used to provide adult return information. This report provides statistical models for the analysis of the joint data as well as recommendations on optimal tagging studies. Study costs and stress on smolt can be reduced by only PIT-tagging a subset of all the fish coded-wire-tagged, while retaining the information content and sampling precision

Covariate-adjusted measures of discrimination for survival data

DEFF Research Database (Denmark)

White, Ian R; Rapsomaniki, Eleni; Frikke-Schmidt, Ruth

2015-01-01

by the study design (e.g. age and sex) influence discrimination and can make it difficult to compare model discrimination between studies. Although covariate adjustment is a standard procedure for quantifying disease-risk factor associations, there are no covariate adjustment methods for discrimination...... statistics in censored survival data. OBJECTIVE: To develop extensions of the C-index and D-index that describe the prognostic ability of a model adjusted for one or more covariate(s). METHOD: We define a covariate-adjusted C-index and D-index for censored survival data, propose several estimators......, and investigate their performance in simulation studies and in data from a large individual participant data meta-analysis, the Emerging Risk Factors Collaboration. RESULTS: The proposed methods perform well in simulations. In the Emerging Risk Factors Collaboration data, the age-adjusted C-index and D-index were...

Survival analysis of patients with uveal melanoma after organ preserving and liquidation treatment

Directory of Open Access Journals (Sweden)

E. E. Grishina

2018-01-01

Full Text Available Rationale: Uveal melanoma is the most common primary malignancy of the eye.Aim: To evaluate survival in patients with uveal melanoma stratified according to the type of treatment and to identify factors significantly associated with their survival.Materials and methods: The study was performed on the data extracted from medical files and follow-up forms of patients with uveal melanoma seen in the Ophthalmological Clinical Hospital of the Department of Healthcare, Moscow, from 1977 to 2012. Analysis of survival was used to assess the life longevity of patients with uveal melanoma. The analysis was censored at January 2013, when vital status (dead or alive of all patients was assessed. The factors included into the study analysis, were those taken from the follow-up forms. The incidence of uveal melanoma in Moscow (2012 was 0.9 per 100,000 of the population, whereas its prevalence was 11.1 per 100,000.Results: 698 patients with uveal melanoma were included into the study, among them 260 (37% men (aged from 19 to 87 years, median age 60 years and 438 (63% women (aged from 18 to 93 years, median age 63 years; therefore, the proportion of women under the follow-up monitoring was by 26% higher than that of men. The liquidation treatment (mostly enucleation was performed in 358 (51% of the patients, whereas the organ preserving treatment in 340 (49%. At 5, 7, and 10 years of the follow-up, the disease-specific survival of patients with uveal melanoma after the organ preserving treatment (median survival has not been reached and after the liquidation treatment (median, 88 months were 89 ± 2, 83 ± 3, and 75 ± 4% versus 63 ± 3, 52 ± 4, and 47 ± 5%, respectively (р = 0.001. Overall survival and disease-specific survival of the patients after the liquidation treatment were significantly lower than in the patients after the organ-preserving treatment. According to multiple regression analysis, this was associated not with the type of

Statistical analysis of JET disruptions

International Nuclear Information System (INIS)

Tanga, A.; Johnson, M.F.

1991-07-01

In the operation of JET and of any tokamak many discharges are terminated by a major disruption. The disruptive termination of a discharge is usually an unwanted event which may cause damage to the structure of the vessel. In a reactor disruptions are potentially a very serious problem, hence the importance of studying them and devising methods to avoid disruptions. Statistical information has been collected about the disruptions which have occurred at JET over a long span of operations. The analysis is focused on the operational aspects of the disruptions rather than on the underlining physics. (Author)

Immunotherapy for recurrent malignant glioma: an interim report on survival.

Science.gov (United States)

Ingram, M; Buckwalter, J G; Jacques, D B; Freshwater, D B; Abts, R M; Techy, G B; Miyagi, K; Shelden, C H; Rand, R W; English, L W

1990-12-01

We present interim survival data for a group of 83 adult patients with recurrent malignant glioma treated by implanting stimulated autologous lymphocytes into the tumour bed following surgical debulking. The patients were treated 6 months or more prior to data analysis. Fifty-nine patients were male and 24 female. The mean age for the entire group was 48.4 years and the mean Karnofsky rating (KR) was 67.2. Eight of the patients had grade II tumours, 33 had grade III tumours and 42 had grade IV tumours. Statistical analysis focuses on tumour grade, KR and patient age, factors that have been shown to affect survival in previous studies. Multifactorial analyses are employed to identify interrelationships among factors related to survival. Seven patients (8%) did not respond to immunotherapy, 76 (92%) had a good initial response. Twenty-five patients (30.1%) are living and 18 (22%) have shown no evidence of recurrence. Results are evaluated in the light of those obtained in trials of other experimental therapies for recurrent malignant gliomas. It is concluded that the present protocol offers a safe and comparatively effective treatment option.

The prognostic role of mTOR and p-mTOR for survival in non-small cell lung cancer: a systematic review and meta-analysis.

Directory of Open Access Journals (Sweden)

Lei Li

Full Text Available The mammalian target of rapamycin (mTOR and phosphorylated mTOR (p-mTOR are potential prognostic markers and therapeutic targets for non-small cell lung cancer (NSCLC. However, the association between mTOR/p-mTOR expression and NSCLC patients' prognosis remains controversial. Thus, a meta-analysis of existing studies evaluating the prognostic role of mTOR/p-mTOR expression for NSCLC was conducted.A systemically literature search was performed via Pubmed, Embase, Medline as well as CNKI (China National Knowledge Infrastructure. Studies were included that reported the hazard ratio (HR and 95%CI for the association between mTOR/p-mTOR expression and NSCLC patients' survival. Random-effects model was used to pool HRs.Ten eligible studies were included in this meta-analysis, with 4 about m-TOR and 7 about p-mTOR. For mTOR, the pooled HR of overall survival (OS was 1.00 (95%CI 0.5 to 1.99 by univariate analysis and 1.22 (95%CI 0.53 to 2.82 by multivariate analysis. For p-mTOR, the pooled HR was 1.39 (95%CI 0.97 to 1.98 by univariate analysis and 1.42 (95%CI 0.56 to 3.60 by multivariate analysis.The results indicated that no statistically significant association was found between mTOR/p-mTOR expression and NSCLC patients' prognosis.

Simulation Experiments in Practice : Statistical Design and Regression Analysis

NARCIS (Netherlands)

Kleijnen, J.P.C.

2007-01-01

In practice, simulation analysts often change only one factor at a time, and use graphical analysis of the resulting Input/Output (I/O) data. Statistical theory proves that more information is obtained when applying Design Of Experiments (DOE) and linear regression analysis. Unfortunately, classic

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

OpenAIRE

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...

Integrated survival analysis using an event-time approach in a Bayesian framework.

Science.gov (United States)

Walsh, Daniel P; Dreitz, Victoria J; Heisey, Dennis M

2015-02-01

Event-time or continuous-time statistical approaches have been applied throughout the biostatistical literature and have led to numerous scientific advances. However, these techniques have traditionally relied on knowing failure times. This has limited application of these analyses, particularly, within the ecological field where fates of marked animals may be unknown. To address these limitations, we developed an integrated approach within a Bayesian framework to estimate hazard rates in the face of unknown fates. We combine failure/survival times from individuals whose fates are known and times of which are interval-censored with information from those whose fates are unknown, and model the process of detecting animals with unknown fates. This provides the foundation for our integrated model and permits necessary parameter estimation. We provide the Bayesian model, its derivation, and use simulation techniques to investigate the properties and performance of our approach under several scenarios. Lastly, we apply our estimation technique using a piece-wise constant hazard function to investigate the effects of year, age, chick size and sex, sex of the tending adult, and nesting habitat on mortality hazard rates of the endangered mountain plover (Charadrius montanus) chicks. Traditional models were inappropriate for this analysis because fates of some individual chicks were unknown due to failed radio transmitters. Simulations revealed biases of posterior mean estimates were minimal (≤ 4.95%), and posterior distributions behaved as expected with RMSE of the estimates decreasing as sample sizes, detection probability, and survival increased. We determined mortality hazard rates for plover chicks were highest at birth weights and/or whose nest was within agricultural habitats. Based on its performance, our approach greatly expands the range of problems for which event-time analyses can be used by eliminating the need for having completely known fate data.

Integrated survival analysis using an event-time approach in a Bayesian framework

Science.gov (United States)

Walsh, Daniel P.; Dreitz, VJ; Heisey, Dennis M.

2015-01-01

Event-time or continuous-time statistical approaches have been applied throughout the biostatistical literature and have led to numerous scientific advances. However, these techniques have traditionally relied on knowing failure times. This has limited application of these analyses, particularly, within the ecological field where fates of marked animals may be unknown. To address these limitations, we developed an integrated approach within a Bayesian framework to estimate hazard rates in the face of unknown fates. We combine failure/survival times from individuals whose fates are known and times of which are interval-censored with information from those whose fates are unknown, and model the process of detecting animals with unknown fates. This provides the foundation for our integrated model and permits necessary parameter estimation. We provide the Bayesian model, its derivation, and use simulation techniques to investigate the properties and performance of our approach under several scenarios. Lastly, we apply our estimation technique using a piece-wise constant hazard function to investigate the effects of year, age, chick size and sex, sex of the tending adult, and nesting habitat on mortality hazard rates of the endangered mountain plover (Charadrius montanus) chicks. Traditional models were inappropriate for this analysis because fates of some individual chicks were unknown due to failed radio transmitters. Simulations revealed biases of posterior mean estimates were minimal (≤ 4.95%), and posterior distributions behaved as expected with RMSE of the estimates decreasing as sample sizes, detection probability, and survival increased. We determined mortality hazard rates for plover chicks were highest at birth weights and/or whose nest was within agricultural habitats. Based on its performance, our approach greatly expands the range of problems for which event-time analyses can be used by eliminating the need for having completely known fate data.

Fissure sealants in caries prevention:a practice-based study using survival analysis

OpenAIRE

Leskinen, K. (Kaja)

2010-01-01

Abstract The purpose of this study was to analyse the effectiveness and cost of fissure sealant treatment in preventing dental caries in children in a practice-based research network using survival analysis. The survival times of first permanent molars in children were analysed in three countries: in Finland (age cohorts 1970–1972 and 1980–1982), in Sweden (1980–1982) and in Greece (1980–1982), and additionally at two municipal health centres in Finland (age cohorts 1988–1990 in Kemi...

Statistical analysis of the Ft. Calhoun reactor coolant pump system

International Nuclear Information System (INIS)

Patel, Bimal; Heising, C.D.

1997-01-01

In engineering science, statistical quality control techniques have traditionally been applied to control manufacturing processes. An application to commercial nuclear power plant maintenance and control is presented that can greatly improve plant safety. As a demonstration of such an approach, a specific system is analyzed: the reactor coolant pumps (RCPs) of the Ft. Calhoun nuclear power plant. This research uses capability analysis, Shewhart X-bar, R charts, canonical correlation methods, and design of experiments to analyze the process for the state of statistical control. The results obtained show that six out of ten parameters are under control specification limits and four parameters are not in the state of statistical control. The analysis shows that statistical process control methods can be applied as an early warning system capable of identifying significant equipment problems well in advance of traditional control room alarm indicators. Such a system would provide operators with ample time to respond to possible emergency situations and thus improve plant safety and reliability. (Author)

Research and Development of Statistical Analysis Software System of Maize Seedling Experiment

OpenAIRE

Hui Cao

2014-01-01

In this study, software engineer measures were used to develop a set of software system for maize seedling experiments statistics and analysis works. During development works, B/S structure software design method was used and a set of statistics indicators for maize seedling evaluation were established. The experiments results indicated that this set of software system could finish quality statistics and analysis for maize seedling very well. The development of this software system explored a...

Survival Rate of Dental Implants in Patients with History of Periodontal Disease: A Retrospective Cohort Study.

Science.gov (United States)

Correia, Francisco; Gouveia, Sónia; Felino, António Campos; Costa, Ana Lemos; Almeida, Ricardo Faria

To evaluate the differences between the survival rates of implants placed in patients with no history of periodontal disease (NP) and in patients with a history of chronic periodontal disease (CP). A retrospective cohort study was conducted in which all consenting patients treated with dental implants in a private clinic in Oporto, Portugal, from November 2, 2002 through February 11, 2011 were included. All patients were treated consecutively by the same experimental operator. This study aimed to analyze how the primary outcomes (presence of disease, time of placement, and time of loading) and the secondary outcomes (severity-generalized periodontitis, brand, implant length, prosthesis type, prosthesis metal-ceramic extension) influence the survival rate of dental implants. The survival analysis was performed through the Kaplan-Meier method, and the equality of survival distributions for all groups was tested with the log-rank test with a significance level of .05 for all comparisons. The sample consisted of 202 patients (47% NP and 53% CP) and 689 implants (31% NP and 69% CP). The survival rate in the NP and CP groups showed no statistically significant differences (95.8% versus 93.1%; P ≥ .05). Implants were lost before loading in 54.9% of the cases. The majority of the implants were lost in the first year and stabilized after the second year. Survival rates in the NP and CP patients showed no statistically significant differences when comparing the following factors: subclassification of the disease, implant brands, implant length (short/standard), type of prosthesis, extension of the prosthesis metal-ceramic, and time of placement and loading (P ≥ .05). This work disclosed no statistically significant differences in terms of survival rates when compared with the control group. Placing implants in patients with a history of periodontal disease appears to be viable and safe.

Survival-related profile, pathways, and transcription factors in ovarian cancer.

Directory of Open Access Journals (Sweden)

Anne P G Crijns

2009-02-01

versus 41 mo, respectively; permutation p-value of log-rank statistic = 0.015 and maintained its independent prognostic value in multivariate analysis. Genes that composed the overall survival profile were also able to discriminate between the two risk groups in the independent dataset. In our dataset 17/167 pathways and 13/111 transcription factors were associated with overall survival, of which 16 and 12, respectively, were confirmed in the independent dataset. CONCLUSIONS: Our study provides new clues to genes, pathways, and transcription factors that contribute to the clinical outcome of serous ovarian cancer and might be exploited in designing new treatment strategies.

Statistical trend analysis methods for temporal phenomena

Energy Technology Data Exchange (ETDEWEB)

Lehtinen, E.; Pulkkinen, U. [VTT Automation, (Finland); Poern, K. [Poern Consulting, Nykoeping (Sweden)

1997-04-01

We consider point events occurring in a random way in time. In many applications the pattern of occurrence is of intrinsic interest as indicating a trend or some other systematic feature in the rate of occurrence. The purpose of this report is to survey briefly different statistical trend analysis methods and illustrate their applicability to temporal phenomena in particular. The trend testing of point events is usually seen as the testing of the hypotheses concerning the intensity of the occurrence of events. When the intensity function is parametrized, the testing of trend is a typical parametric testing problem. In industrial applications the operational experience generally does not suggest any specified model and method in advance. Therefore, and particularly, if the Poisson process assumption is very questionable, it is desirable to apply tests that are valid for a wide variety of possible processes. The alternative approach for trend testing is to use some non-parametric procedure. In this report we have presented four non-parametric tests: The Cox-Stuart test, the Wilcoxon signed ranks test, the Mann test, and the exponential ordered scores test. In addition to the classical parametric and non-parametric approaches we have also considered the Bayesian trend analysis. First we discuss a Bayesian model, which is based on a power law intensity model. The Bayesian statistical inferences are based on the analysis of the posterior distribution of the trend parameters, and the probability of trend is immediately seen from these distributions. We applied some of the methods discussed in an example case. It should be noted, that this report is a feasibility study rather than a scientific evaluation of statistical methods, and the examples can only be seen as demonstrations of the methods. 14 refs, 10 figs.

Statistical trend analysis methods for temporal phenomena

International Nuclear Information System (INIS)

Lehtinen, E.; Pulkkinen, U.; Poern, K.

1997-04-01

We consider point events occurring in a random way in time. In many applications the pattern of occurrence is of intrinsic interest as indicating a trend or some other systematic feature in the rate of occurrence. The purpose of this report is to survey briefly different statistical trend analysis methods and illustrate their applicability to temporal phenomena in particular. The trend testing of point events is usually seen as the testing of the hypotheses concerning the intensity of the occurrence of events. When the intensity function is parametrized, the testing of trend is a typical parametric testing problem. In industrial applications the operational experience generally does not suggest any specified model and method in advance. Therefore, and particularly, if the Poisson process assumption is very questionable, it is desirable to apply tests that are valid for a wide variety of possible processes. The alternative approach for trend testing is to use some non-parametric procedure. In this report we have presented four non-parametric tests: The Cox-Stuart test, the Wilcoxon signed ranks test, the Mann test, and the exponential ordered scores test. In addition to the classical parametric and non-parametric approaches we have also considered the Bayesian trend analysis. First we discuss a Bayesian model, which is based on a power law intensity model. The Bayesian statistical inferences are based on the analysis of the posterior distribution of the trend parameters, and the probability of trend is immediately seen from these distributions. We applied some of the methods discussed in an example case. It should be noted, that this report is a feasibility study rather than a scientific evaluation of statistical methods, and the examples can only be seen as demonstrations of the methods

3D Quantitative tumour burden analysis in patients with hepatocellular carcinoma before TACE: comparing single-lesion vs. multi-lesion imaging biomarkers as predictors of patient survival

International Nuclear Information System (INIS)

Fleckenstein, Florian N.; Schernthaner, Ruediger E.; Duran, Rafael; Sohn, Jae Ho; Sahu, Sonia; Zhao, Yan; Hamm, Bernd; Gebauer, Bernhard; Lin, MingDe; Geschwind, Jean-Francois; Chapiro, Julius

2016-01-01

To compare the ability of single- vs. multi-lesion assessment on baseline MRI using 1D- and 3D-based measurements to predict overall survival (OS) in patients with hepatocellular carcinoma (HCC) before transarterial chemoembolization (TACE). This retrospective analysis included 122 patients. A quantitative 3D analysis was performed on baseline MRI to calculate enhancing tumour volume (ETV [cm 3 ]) and enhancing tumour burden (ETB [%]) (ratio between ETV [cm 3 ] and liver volume). Furthermore, enhancing and overall tumour diameters were measured. Patients were stratified into two groups using thresholds derived from the BCLC staging system. Statistical analysis included Kaplan-Meier plots, uni- and multivariate cox proportional hazard ratios (HR) and concordances. All methods achieved good separation of the survival curves (p < 0.05). Multivariate analysis showed an HR of 5.2 (95 % CI 3.1-8.8, p < 0.001) for ETV [cm 3 ] and HR 6.6 (95 % CI 3.7-11.5, p < 0.001) for ETB [%] vs. HR 2.6 (95 % CI 1.2-5.6, p = 0.012) for overall diameter and HR 3.0 (95 % CI 1.5-6.3, p = 0.003) for enhancing diameter. Concordances were highest for ETB [%], with no added predictive power for multi-lesion assessment (difference between concordances not significant). 3D quantitative assessment is a stronger predictor of survival as compared to diameter-based measurements. Assessing multiple lesions provides no substantial improvement in predicting OS than evaluating the dominant lesion alone. (orig.)

StOCNET : Software for the statistical analysis of social networks

NARCIS (Netherlands)

Huisman, M.; van Duijn, M.A.J.

2003-01-01

StOCNET3 is an open software system in a Windows environment for the advanced statistical analysis of social networks. It provides a platform to make a number of recently developed and therefore not (yet) standard statistical methods available to a wider audience. A flexible user interface utilizing

Brachytherapy Improves Biochemical Failure–Free Survival in Low- and Intermediate-Risk Prostate Cancer Compared With Conventionally Fractionated External Beam Radiation Therapy: A Propensity Score Matched Analysis

International Nuclear Information System (INIS)

Smith, Graham D.; Pickles, Tom; Crook, Juanita; Martin, Andre-Guy; Vigneault, Eric; Cury, Fabio L.; Morris, Jim; Catton, Charles; Lukka, Himu; Warner, Andrew; Yang, Ying; Rodrigues, George

2015-01-01

Purpose: To compare, in a retrospective study, biochemical failure-free survival (bFFS) and overall survival (OS) in low-risk and intermediate-risk prostate cancer patients who received brachytherapy (BT) (either low-dose-rate brachytherapy [LDR-BT] or high-dose-rate brachytherapy with external beam radiation therapy [HDR-BT+EBRT]) versus external beam radiation therapy (EBRT) alone. Methods and Materials: Patient data were obtained from the ProCaRS database, which contains 7974 prostate cancer patients treated with primary radiation therapy at four Canadian cancer institutions from 1994 to 2010. Propensity score matching was used to obtain the following 3 matched cohorts with balanced baseline prognostic factors: (1) low-risk LDR-BT versus EBRT; (2) intermediate-risk LDR-BT versus EBRT; and (3) intermediate-risk HDR-BT+EBRT versus EBRT. Kaplan-Meier survival analysis was performed to compare differences in bFFS (primary endpoint) and OS in the 3 matched groups. Results: Propensity score matching created acceptable balance in the baseline prognostic factors in all matches. Final matches included 2 1:1 matches in the intermediate-risk cohorts, LDR-BT versus EBRT (total n=254) and HDR-BT+EBRT versus EBRT (total n=388), and one 4:1 match in the low-risk cohort (LDR-BT:EBRT, total n=400). Median follow-up ranged from 2.7 to 7.3 years for the 3 matched cohorts. Kaplan-Meier survival analysis showed that all BT treatment options were associated with statistically significant improvements in bFFS when compared with EBRT in all cohorts (intermediate-risk EBRT vs LDR-BT hazard ratio [HR] 4.58, P=.001; intermediate-risk EBRT vs HDR-BT+EBRT HR 2.08, P=.007; low-risk EBRT vs LDR-BT HR 2.90, P=.004). No significant difference in OS was found in all comparisons (intermediate-risk EBRT vs LDR-BT HR 1.27, P=.687; intermediate-risk EBRT vs HDR-BT+EBRT HR 1.55, P=.470; low-risk LDR-BT vs EBRT HR 1.41, P=.500). Conclusions: Propensity score matched analysis showed that BT options led

AutoBayes: A System for Generating Data Analysis Programs from Statistical Models

OpenAIRE

Fischer, Bernd; Schumann, Johann

2003-01-01

Data analysis is an important scientific task which is required whenever information needs to be extracted from raw data. Statistical approaches to data analysis, which use methods from probability theory and numerical analysis, are well-founded but dificult to implement: the development of a statistical data analysis program for any given application is time-consuming and requires substantial knowledge and experience in several areas. In this paper, we describe AutoBayes, a program synthesis...

[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.

Impact of anastomotic leak on recurrence and survival after colorectal cancer surgery: a BioGrid Australia analysis.

Science.gov (United States)

Sammour, Tarik; Hayes, Ian P; Jones, Ian T; Steel, Malcolm C; Faragher, Ian; Gibbs, Peter

2018-01-01

There is conflicting evidence regarding the oncological impact of anastomotic leak following colorectal cancer surgery. This study aims to test the hypothesis that anastomotic leak is independently associated with local recurrence and overall and cancer-specific survival. Analysis of prospectively collected data from multiple centres in Victoria between 1988 and 2015 including all patients who underwent colon or rectal resection for cancer with anastomosis was presented. Overall and cancer-specific survival rates and rates of local recurrence were compared using Cox regression analysis. A total of 4892 patients were included, of which 2856 had completed 5-year follow-up. The overall anastomotic leak rate was 4.0%. Cox regression analysis accounting for differences in age, sex, body mass index, American Society of Anesthesiologists score and tumour stage demonstrated that anastomotic leak was associated with significantly worse 5-year overall survival (χ 2 = 6.459, P = 0.011) for colon cancer, but only if early deaths were included. There was no difference in 5-year colon cancer-specific survival (χ 2 = 0.582, P = 0.446) or local recurrence (χ 2 = 0.735, P = 0.391). For rectal cancer, there was no difference in 5-year overall survival (χ 2 = 0.266, P = 0.606), cancer-specific survival (χ 2 = 0.008, P = 0.928) or local recurrence (χ 2 = 2.192, P = 0.139). Anastomotic leak may reduce 5-year overall survival in colon cancer patients but does not appear to influence the 5-year overall survival in rectal cancer patients. There was no effect on local recurrence or cancer-specific survival. © 2016 Royal Australasian College of Surgeons.

Summary curves for patients transplanted for chronic myeloid leukaemia salvaged by a donor lymphocyte infusion: the current leukaemia-free survival curve

DEFF Research Database (Denmark)

Klein, John P.; Keiding, Niels; Shu, Youyi

2000-01-01

CML, donor lymphocyte infusion, leukaemia-free survival, current leukaemia-free survival, statistical methods......CML, donor lymphocyte infusion, leukaemia-free survival, current leukaemia-free survival, statistical methods...

Network similarity and statistical analysis of earthquake seismic data

OpenAIRE

Deyasi, Krishanu; Chakraborty, Abhijit; Banerjee, Anirban

2016-01-01

We study the structural similarity of earthquake networks constructed from seismic catalogs of different geographical regions. A hierarchical clustering of underlying undirected earthquake networks is shown using Jensen-Shannon divergence in graph spectra. The directed nature of links indicates that each earthquake network is strongly connected, which motivates us to study the directed version statistically. Our statistical analysis of each earthquake region identifies the hub regions. We cal...

Statistical analysis and interpolation of compositional data in materials science.

Science.gov (United States)

Pesenson, Misha Z; Suram, Santosh K; Gregoire, John M

2015-02-09

Compositional data are ubiquitous in chemistry and materials science: analysis of elements in multicomponent systems, combinatorial problems, etc., lead to data that are non-negative and sum to a constant (for example, atomic concentrations). The constant sum constraint restricts the sampling space to a simplex instead of the usual Euclidean space. Since statistical measures such as mean and standard deviation are defined for the Euclidean space, traditional correlation studies, multivariate analysis, and hypothesis testing may lead to erroneous dependencies and incorrect inferences when applied to compositional data. Furthermore, composition measurements that are used for data analytics may not include all of the elements contained in the material; that is, the measurements may be subcompositions of a higher-dimensional parent composition. Physically meaningful statistical analysis must yield results that are invariant under the number of composition elements, requiring the application of specialized statistical tools. We present specifics and subtleties of compositional data processing through discussion of illustrative examples. We introduce basic concepts, terminology, and methods required for the analysis of compositional data and utilize them for the spatial interpolation of composition in a sputtered thin film. The results demonstrate the importance of this mathematical framework for compositional data analysis (CDA) in the fields of materials science and chemistry.

Introducing the new business demography statistics

OpenAIRE

Karen Grierson; Andrew Allen

2008-01-01

Introducing the new business demography statisticsA new National Statistics series waspublished on 28 November 2008 bythe Offi ce for National Statistics (ONS),providing data on business births,deaths and survival rates, called BusinessDemography: Enterprise Births andDeaths. The Department for Business,Enterprise & Regulatory Reform (BERR)also published its series Business start upsand closures: VAT registrations andde-registrations in 2007 on the sameday. The year 2008 is the final update t...

An Application of Multivariate Statistical Analysis for Query-Driven Visualization

Energy Technology Data Exchange (ETDEWEB)

Gosink, Luke J. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Garth, Christoph [Univ. of California, Davis, CA (United States); Anderson, John C. [Univ. of California, Davis, CA (United States); Bethel, E. Wes [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Joy, Kenneth I. [Univ. of California, Davis, CA (United States)

2011-03-01

Driven by the ability to generate ever-larger, increasingly complex data, there is an urgent need in the scientific community for scalable analysis methods that can rapidly identify salient trends in scientific data. Query-Driven Visualization (QDV) strategies are among the small subset of techniques that can address both large and highly complex datasets. This paper extends the utility of QDV strategies with a statistics-based framework that integrates non-parametric distribution estimation techniques with a new segmentation strategy to visually identify statistically significant trends and features within the solution space of a query. In this framework, query distribution estimates help users to interactively explore their query's solution and visually identify the regions where the combined behavior of constrained variables is most important, statistically, to their inquiry. Our new segmentation strategy extends the distribution estimation analysis by visually conveying the individual importance of each variable to these regions of high statistical significance. We demonstrate the analysis benefits these two strategies provide and show how they may be used to facilitate the refinement of constraints over variables expressed in a user's query. We apply our method to datasets from two different scientific domains to demonstrate its broad applicability.

Perioperative Blood Transfusion as a Significant Predictor of Biochemical Recurrence and Survival after Radical Prostatectomy in Patients with Prostate Cancer.

Directory of Open Access Journals (Sweden)

Jung Kwon Kim

Full Text Available There have been conflicting reports regarding the association of perioperative blood transfusion (PBT with oncologic outcomes including recurrence rates and survival outcomes in prostate cancer. We aimed to evaluate whether perioperative blood transfusion (PBT affects biochemical recurrence-free survival (BRFS, cancer-specific survival (CSS, and overall survival (OS following radical prostatectomy (RP for patients with prostate cancer.A total of 2,713 patients who underwent RP for clinically localized prostate cancer between 1993 and 2014 were retrospectively analyzed. We performed a comparative analysis based on receipt of transfusion (PBT group vs. no-PBT group and transfusion type (autologous PBT vs. allogeneic PBT. Univariate and multivariate Cox-proportional hazard regression analysis were performed to evaluate variables associated with BRFS, CSS, and OS. The Kaplan-Meier method was used to calculate survival estimates for BRFS, CSS, and OS, and log-rank test was used to conduct comparisons between the groups.The number of patients who received PBT was 440 (16.5%. Among these patients, 350 (79.5% received allogeneic transfusion and the other 90 (20.5% received autologous transfusion. In a multivariate analysis, allogeneic PBT was found to be statistically significant predictors of BRFS, CSS, and OS; conversely, autologous PBT was not. The Kaplan-Meier survival analysis showed significantly decreased 5-year BRFS (79.2% vs. 70.1%, log-rank, p = 0.001, CSS (98.5% vs. 96.7%, log-rank, p = 0.012, and OS (95.5% vs. 90.6%, log-rank, p < 0.001 in the allogeneic PBT group compared to the no-allogeneic PBT group. In the autologous PBT group, however, none of these were statistically significant compared to the no-autologous PBT group.We found that allogeneic PBT was significantly associated with decreased BRFS, CSS, and OS. This provides further support for the immunomodulation hypothesis for allogeneic PBT.

Integrative analysis of survival-associated gene sets in breast cancer.

Science.gov (United States)

Varn, Frederick S; Ung, Matthew H; Lou, Shao Ke; Cheng, Chao

2015-03-12

Patient gene expression information has recently become a clinical feature used to evaluate breast cancer prognosis. The emergence of prognostic gene sets that take advantage of these data has led to a rich library of information that can be used to characterize the molecular nature of a patient's cancer. Identifying robust gene sets that are consistently predictive of a patient's clinical outcome has become one of the main challenges in the field. We inputted our previously established BASE algorithm with patient gene expression data and gene sets from MSigDB to develop the gene set activity score (GSAS), a metric that quantitatively assesses a gene set's activity level in a given patient. We utilized this metric, along with patient time-to-event data, to perform survival analyses to identify the gene sets that were significantly correlated with patient survival. We then performed cross-dataset analyses to identify robust prognostic gene sets and to classify patients by metastasis status. Additionally, we created a gene set network based on component gene overlap to explore the relationship between gene sets derived from MSigDB. We developed a novel gene set based on this network's topology and applied the GSAS metric to characterize its role in patient survival. Using the GSAS metric, we identified 120 gene sets that were significantly associated with patient survival in all datasets tested. The gene overlap network analysis yielded a novel gene set enriched in genes shared by the robustly predictive gene sets. This gene set was highly correlated to patient survival when used alone. Most interestingly, removal of the genes in this gene set from the gene pool on MSigDB resulted in a large reduction in the number of predictive gene sets, suggesting a prominent role for these genes in breast cancer progression. The GSAS metric provided a useful medium by which we systematically investigated how gene sets from MSigDB relate to breast cancer patient survival. We used

Explorations in Statistics: The Analysis of Ratios and Normalized Data

Science.gov (United States)

Curran-Everett, Douglas

2013-01-01

Learning about statistics is a lot like learning about science: the learning is more meaningful if you can actively explore. This ninth installment of "Explorations in Statistics" explores the analysis of ratios and normalized--or standardized--data. As researchers, we compute a ratio--a numerator divided by a denominator--to compute a…

Statistical Energy Analysis (SEA) and Energy Finite Element Analysis (EFEA) Predictions for a Floor-Equipped Composite Cylinder

Science.gov (United States)

Grosveld, Ferdinand W.; Schiller, Noah H.; Cabell, Randolph H.

2011-01-01

Comet Enflow is a commercially available, high frequency vibroacoustic analysis software founded on Energy Finite Element Analysis (EFEA) and Energy Boundary Element Analysis (EBEA). Energy Finite Element Analysis (EFEA) was validated on a floor-equipped composite cylinder by comparing EFEA vibroacoustic response predictions with Statistical Energy Analysis (SEA) and experimental results. Statistical Energy Analysis (SEA) predictions were made using the commercial software program VA One 2009 from ESI Group. The frequency region of interest for this study covers the one-third octave bands with center frequencies from 100 Hz to 4000 Hz.

Simulation Experiments in Practice : Statistical Design and Regression Analysis

NARCIS (Netherlands)

Kleijnen, J.P.C.

2007-01-01

In practice, simulation analysts often change only one factor at a time, and use graphical analysis of the resulting Input/Output (I/O) data. The goal of this article is to change these traditional, naïve methods of design and analysis, because statistical theory proves that more information is

Statistical trend analysis methodology for rare failures in changing technical systems

International Nuclear Information System (INIS)

Ott, K.O.; Hoffmann, H.J.

1983-07-01

A methodology for a statistical trend analysis (STA) in failure rates is presented. It applies primarily to relatively rare events in changing technologies or components. The formulation is more general and the assumptions are less restrictive than in a previously published version. Relations of the statistical analysis and probabilistic assessment (PRA) are discussed in terms of categorization of decisions for action following particular failure events. The significance of tentatively identified trends is explored. In addition to statistical tests for trend significance, a combination of STA and PRA results quantifying the trend complement is proposed. The STA approach is compared with other concepts for trend characterization. (orig.)

Drawing Nomograms with R: applications to categorical outcome and survival data.

Science.gov (United States)

Zhang, Zhongheng; Kattan, Michael W

2017-05-01

Outcome prediction is a major task in clinical medicine. The standard approach to this work is to collect a variety of predictors and build a model of appropriate type. The model is a mathematical equation that connects the outcome of interest with the predictors. A new patient with given clinical characteristics can be predicted for outcome with this model. However, the equation describing the relationship between predictors and outcome is often complex and the computation requires software for practical use. There is another method called nomogram which is a graphical calculating device allowing an approximate graphical computation of a mathematical function. In this article, we describe how to draw nomograms for various outcomes with nomogram() function. Binary outcome is fit by logistic regression model and the outcome of interest is the probability of the event of interest. Ordinal outcome variable is also discussed. Survival analysis can be fit with parametric model to fully describe the distributions of survival time. Statistics such as the median survival time, survival probability up to a specific time point are taken as the outcome of interest.

Analysis of thrips distribution: application of spatial statistics and Kriging

Science.gov (United States)

John Aleong; Bruce L. Parker; Margaret Skinner; Diantha Howard

1991-01-01

Kriging is a statistical technique that provides predictions for spatially and temporally correlated data. Observations of thrips distribution and density in Vermont soils are made in both space and time. Traditional statistical analysis of such data assumes that the counts taken over space and time are independent, which is not necessarily true. Therefore, to analyze...

Statistical wind analysis for near-space applications

Science.gov (United States)

Roney, Jason A.

2007-09-01

Statistical wind models were developed based on the existing observational wind data for near-space altitudes between 60 000 and 100 000 ft (18 30 km) above ground level (AGL) at two locations, Akon, OH, USA, and White Sands, NM, USA. These two sites are envisioned as playing a crucial role in the first flights of high-altitude airships. The analysis shown in this paper has not been previously applied to this region of the stratosphere for such an application. Standard statistics were compiled for these data such as mean, median, maximum wind speed, and standard deviation, and the data were modeled with Weibull distributions. These statistics indicated, on a yearly average, there is a lull or a “knee” in the wind between 65 000 and 72 000 ft AGL (20 22 km). From the standard statistics, trends at both locations indicated substantial seasonal variation in the mean wind speed at these heights. The yearly and monthly statistical modeling indicated that Weibull distributions were a reasonable model for the data. Forecasts and hindcasts were done by using a Weibull model based on 2004 data and comparing the model with the 2003 and 2005 data. The 2004 distribution was also a reasonable model for these years. Lastly, the Weibull distribution and cumulative function were used to predict the 50%, 95%, and 99% winds, which are directly related to the expected power requirements of a near-space station-keeping airship. These values indicated that using only the standard deviation of the mean may underestimate the operational conditions.

Analysis of photon statistics with Silicon Photomultiplier

International Nuclear Information System (INIS)

D'Ascenzo, N.; Saveliev, V.; Wang, L.; Xie, Q.

2015-01-01

The Silicon Photomultiplier (SiPM) is a novel silicon-based photodetector, which represents the modern perspective of low photon flux detection. The aim of this paper is to provide an introduction on the statistical analysis methods needed to understand and estimate in quantitative way the correct features and description of the response of the SiPM to a coherent source of light

[Survival rate for breast cancer in Rabat (Morocco) 2005-2008].

Science.gov (United States)

Mechita, Nada Bennani; Tazi, Mohammed Adnane; Er-Raki, Abdelouahed; Mrabet, Mustapha; Saadi, Asma; Benjaafar, Noureddine; Razine, Rachid

2016-01-01

Breast cancer is a public health problem in Morocco. This study aims to estimate the survival rate for patients with breast cancer living in Rabat. We conducted a prognostic study of female patients with breast cancer diagnosed during 2005-2008, living in Rabat and whose data were recorded in the Rabat Cancer Registry. The date of inclusion in this study corresponded with the date on which cancer was histologically confirmed. Survival rate was estimated using the Kaplan-Meier method and the comparison between the different classes of a variable was made using the log rank test. The study of factors associated with survival was performed using the Cox model. During the study period 628 cases of breast cancer were collected. Mortality rate was 19.9%. Overall 1-year survival rate was 97.1%, 89.2% at 3 years and 80.6% at 5 years. In multivariate analysis, breast cancer survival was statistically lower in patients over 70 years of age (p <0.001) with large tumor size (p < 0.001), advanced-stage adenopathies (p = 0.007), metastases (p < 0.001) and not using hormone therapy (p = 0.002). Large tumor size and metastases are poor prognostic factors in breast cancer, hence the need to strengthen screening programs.

Development of statistical analysis code for meteorological data (W-View)

International Nuclear Information System (INIS)

Tachibana, Haruo; Sekita, Tsutomu; Yamaguchi, Takenori

2003-03-01

A computer code (W-View: Weather View) was developed to analyze the meteorological data statistically based on 'the guideline of meteorological statistics for the safety analysis of nuclear power reactor' (Nuclear Safety Commission on January 28, 1982; revised on March 29, 2001). The code gives statistical meteorological data to assess the public dose in case of normal operation and severe accident to get the license of nuclear reactor operation. This code was revised from the original code used in a large office computer code to enable a personal computer user to analyze the meteorological data simply and conveniently and to make the statistical data tables and figures of meteorology. (author)

Statistical analysis of the Ft. Calhoun reactor coolant pump system

International Nuclear Information System (INIS)

Heising, Carolyn D.

1998-01-01

In engineering science, statistical quality control techniques have traditionally been applied to control manufacturing processes. An application to commercial nuclear power plant maintenance and control is presented that can greatly improve plant safety. As a demonstration of such an approach to plant maintenance and control, a specific system is analyzed: the reactor coolant pumps (RCPs) of the Ft. Calhoun nuclear power plant. This research uses capability analysis, Shewhart X-bar, R-charts, canonical correlation methods, and design of experiments to analyze the process for the state of statistical control. The results obtained show that six out of ten parameters are under control specifications limits and four parameters are not in the state of statistical control. The analysis shows that statistical process control methods can be applied as an early warning system capable of identifying significant equipment problems well in advance of traditional control room alarm indicators Such a system would provide operators with ample time to respond to possible emergency situations and thus improve plant safety and reliability. (author)

Survival analysis of cancer risk reduction strategies for BRCA1/2 mutation carriers.

Science.gov (United States)

Kurian, Allison W; Sigal, Bronislava M; Plevritis, Sylvia K

2010-01-10

Women with BRCA1/2 mutations inherit high risks of breast and ovarian cancer; options to reduce cancer mortality include prophylactic surgery or breast screening, but their efficacy has never been empirically compared. We used decision analysis to simulate risk-reducing strategies in BRCA1/2 mutation carriers and to compare resulting survival probability and causes of death. We developed a Monte Carlo model of breast screening with annual mammography plus magnetic resonance imaging (MRI) from ages 25 to 69 years, prophylactic mastectomy (PM) at various ages, and/or prophylactic oophorectomy (PO) at ages 40 or 50 years in 25-year-old BRCA1/2 mutation carriers. With no intervention, survival probability by age 70 is 53% for BRCA1 and 71% for BRCA2 mutation carriers. The most effective single intervention for BRCA1 mutation carriers is PO at age 40, yielding a 15% absolute survival gain; for BRCA2 mutation carriers, the most effective single intervention is PM, yielding a 7% survival gain if performed at age 40 years. The combination of PM and PO at age 40 improves survival more than any single intervention, yielding 24% survival gain for BRCA1 and 11% for BRCA2 mutation carriers. PM at age 25 instead of age 40 offers minimal incremental benefit (1% to 2%); substituting screening for PM yields a similarly minimal decrement in survival (2% to 3%). Although PM at age 25 plus PO at age 40 years maximizes survival probability, substituting mammography plus MRI screening for PM seems to offer comparable survival. These results may guide women with BRCA1/2 mutations in their choices between prophylactic surgery and breast screening.

Pregnancy associated nasopharyngeal carcinoma: A retrospective case-control analysis of maternal survival outcomes

International Nuclear Information System (INIS)

Cheng, Yi-Kan; Zhang, Fan; Tang, Ling-Long; Chen, Lei; Zhou, Guan-Qun; Zeng, Mu-Sheng; Kang, Tie-Bang; Jia, Wei-Hua; Shao, Jian-Yong; Mai, Hai-Qiang; Guo, Ying; Ma, Jun

2015-01-01

Background: Pregnancy-associated nasopharyngeal carcinoma (PANPC) has been associated with poor survival. Recent advances in radiation technology and imaging techniques, and the introduction of chemotherapy have improved survival in nasopharyngeal carcinoma (NPC); however, it is not clear whether these changes have improved survival in PANPC. Therefore, the purpose of this study was to compare five-year maternal survival in patients with PANPC and non-pregnant patients with NPC. Methods: After adjusting for age, stage and chemotherapy mode, we conducted a retrospective case-control study among 36 non-metastatic PANPC patients and 36 non-pregnant NPC patients (control group) who were treated at our institution between 2000 and 2010. Results: The median age of both groups was 30 years (range, 23–35 years); median follow-up for all patients was 70 months. Locoregionally-advanced disease accounted for 83.3% of all patients with PANPC and 92.9% of patients who developed NPC during pregnancy. In both the PANPC and control groups, 31 patients (86.1%) received chemotherapy and all patients received definitive radiotherapy. The five-year rates for overall survival (70% vs. 78%, p = 0.72), distant metastasis-free survival (79% vs. 76%, p = 0.77), loco-regional relapse-free survival (97% vs. 91%, p = 0.69) and disease-free survival (69% vs. 74%, p = 0.98) were not significantly different between the PANPC and control groups. Multivariate analysis using a Cox proportional hazards model revealed that only N-classification was significantly associated with five-year OS. Conclusion: This study demonstrates that, in the modern treatment era, pregnancy itself may not negatively influence survival outcomes in patients with NPC; however, pregnancy may delay the diagnosis of NPC

Young patients with colorectal cancer have poor survival in the first twenty months after operation and predictable survival in the medium and long-term: Analysis of survival and prognostic markers

Directory of Open Access Journals (Sweden)

Wickramarachchi RE

2010-09-01

Full Text Available Abstract Objectives This study compares clinico-pathological features in young (50 years with colorectal cancer, survival in the young and the influence of pre-operative clinical and histological factors on survival. Materials and methods A twelve year prospective database of colorectal cancer was analysed. Fifty-three young patients were compared with forty seven consecutive older patients over fifty years old. An analysis of survival was undertaken in young patients using Kaplan Meier graphs, non parametric methods, Cox's Proportional Hazard Ratios and Weibull Hazard models. Results Young patients comprised 13.4 percent of 397 with colorectal cancer. Duration of symptoms and presentation in the young was similar to older patients (median, range; young patients; 6 months, 2 weeks to 2 years, older patients; 4 months, 4 weeks to 3 years, p > 0.05. In both groups, the majority presented without bowel obstruction (young - 81%, older - 94%. Cancer proximal to the splenic flexure was present more in young than in older patients. Synchronous cancers were found exclusively in the young. Mucinous tumours were seen in 16% of young and 4% of older patients (p Conclusion If patients, who are less than 40 years old with colorectal cancer, survive twenty months after operation, the prognosis improves and their survival becomes predictable.

Propensity Score Analysis: An Alternative Statistical Approach for HRD Researchers

Science.gov (United States)

Keiffer, Greggory L.; Lane, Forrest C.

2016-01-01

Purpose: This paper aims to introduce matching in propensity score analysis (PSA) as an alternative statistical approach for researchers looking to make causal inferences using intact groups. Design/methodology/approach: An illustrative example demonstrated the varying results of analysis of variance, analysis of covariance and PSA on a heuristic…

FORECASTING OF SURVIVAL OF CHILDREN WITH THE PRENATALLY DIAGNOSED PATHOLOGY OF THE CARDIOVASCULAR SYSTEM

Directory of Open Access Journals (Sweden)

Анна Валериевна Дубовая

2018-05-01

Full Text Available The development of effective methods for the analysis and prognosis of the survival of newborns with prenatally diagnosed congenital malformations of the cardiovascular system are the urgent task of modern medicine. Objective – a neural network model for predicting the survival of children with prenatally diagnosed congenital malformations of the cardiovascular system was developed. Materials and methods. To create the artificial neural networks, the method of constructing multifactor mathematical prediction models in the software package Statistica 6.0 was used. The significance level of the factors influencing the survival of children with prenatally diagnosed congenital malformations of the cardiovascular system was determined using Wald statistics. When checking statistical hypotheses, the critical level of significance was assumed to be 0,05. Results. A neural network model for the determination of the probability of survival of a child with prenatally diagnosed congenital malformations of the cardiovascular system, which has a high prognostic ability of 0,88, sensitivity of the model was 77,6 %, specificity 86,4 %. The value of prognostic survival probability is in the range from 0 to 100 %. With an indicator value of more than 80 %, the probability of survival of a child with prenatally diagnosed congenital malformations of the cardiovascular system is estimated as high, ranging from 20 % to 80 % – as an average and less than 20 % – as low. Conclusion. In the algorithm for predicting the survival of children with prenatally diagnosed congenital malformations of the cardiovascular system it is necessary to include a combination with other pathology of cardiovascular system, with other organs and systems, with chromosomal abnormalities, with microdeletion and monogenic syndromes.

Simulation Experiments in Practice: Statistical Design and Regression Analysis

OpenAIRE

Kleijnen, J.P.C.

2007-01-01

In practice, simulation analysts often change only one factor at a time, and use graphical analysis of the resulting Input/Output (I/O) data. The goal of this article is to change these traditional, naïve methods of design and analysis, because statistical theory proves that more information is obtained when applying Design Of Experiments (DOE) and linear regression analysis. Unfortunately, classic DOE and regression analysis assume a single simulation response that is normally and independen...

Statistical analysis of thermal conductivity of nanofluid containing ...

Indian Academy of Sciences (India)

Thermal conductivity measurements of nanofluids were analysed via two-factor completely randomized design and comparison of data means is carried out with Duncan's multiple-range test. Statistical analysis of experimental data show that temperature and weight fraction have a reasonable impact on the thermal ...

Multiparametric analysis of magnetic resonance images for glioma grading and patient survival time prediction

International Nuclear Information System (INIS)

Garzon, Benjamin; Emblem, Kyrre E.; Mouridsen, Kim; Nedregaard, Baard; Due-Toennessen, Paulina; Nome, Terje; Hald, John K.; Bjoernerud, Atle; Haaberg, Asta K.; Kvinnsland, Yngve

2011-01-01

Background. A systematic comparison of magnetic resonance imaging (MRI) options for glioma diagnosis is lacking. Purpose. To investigate multiple MR-derived image features with respect to diagnostic accuracy in tumor grading and survival prediction in glioma patients. Material and Methods. T1 pre- and post-contrast, T2 and dynamic susceptibility contrast scans of 74 glioma patients with histologically confirmed grade were acquired. For each patient, a set of statistical features was obtained from the parametric maps derived from the original images, in a region-of-interest encompassing the tumor volume. A forward stepwise selection procedure was used to find the best combinations of features for grade prediction with a cross-validated logistic model and survival time prediction with a cox proportional-hazards regression. Results. Presence/absence of enhancement paired with kurtosis of the FM (first moment of the first-pass curve) was the feature combination that best predicted tumor grade (grade II vs. grade III-IV; median AUC 0.96), with the main contribution being due to the first of the features. A lower predictive value (median AUC = 0.82) was obtained when grade IV tumors were excluded. Presence/absence of enhancement alone was the best predictor for survival time, and the regression was significant (P < 0.0001). Conclusion. Presence/absence of enhancement, reflecting transendothelial leakage, was the feature with highest predictive value for grade and survival time in glioma patients

Multiparametric analysis of magnetic resonance images for glioma grading and patient survival time prediction

Energy Technology Data Exchange (ETDEWEB)

Garzon, Benjamin (Dept. of Circulation and Medical Imaging, NTNU, Trondheim (Norway)), email: benjamin.garzon@ntnu.no; Emblem, Kyrre E. (The Interventional Center, Rikshospitalet, Oslo Univ. Hospital, Oslo (Norway); Dept. of Radiology, MGH-HST AA Martinos Center for Biomedical Imaging, Massachusetts General Hospital and Harvard Medical School, Boston (United States)); Mouridsen, Kim (Center of Functionally Integrative Neuroscience, Aarhus Univ., Aarhus (Denmark)); Nedregaard, Baard; Due-Toennessen, Paulina; Nome, Terje; Hald, John K. (Dept. of Radiology and Nuclear Medicine, Rikshospitalet, Oslo Univ. Hospital, Oslo (Norway)); Bjoernerud, Atle (The Interventional Center, Rikshospitalet, Oslo Univ. Hospital, Oslo (Norway)); Haaberg, Asta K. (Dept. of Circulation and Medical Imaging, NTNU, Trondheim (Norway); Dept. of Medical Imaging, St Olav' s Hospital, Trondheim (Norway)); Kvinnsland, Yngve (NordicImagingLab, Bergen (Norway))

2011-11-15

Background. A systematic comparison of magnetic resonance imaging (MRI) options for glioma diagnosis is lacking. Purpose. To investigate multiple MR-derived image features with respect to diagnostic accuracy in tumor grading and survival prediction in glioma patients. Material and Methods. T1 pre- and post-contrast, T2 and dynamic susceptibility contrast scans of 74 glioma patients with histologically confirmed grade were acquired. For each patient, a set of statistical features was obtained from the parametric maps derived from the original images, in a region-of-interest encompassing the tumor volume. A forward stepwise selection procedure was used to find the best combinations of features for grade prediction with a cross-validated logistic model and survival time prediction with a cox proportional-hazards regression. Results. Presence/absence of enhancement paired with kurtosis of the FM (first moment of the first-pass curve) was the feature combination that best predicted tumor grade (grade II vs. grade III-IV; median AUC 0.96), with the main contribution being due to the first of the features. A lower predictive value (median AUC = 0.82) was obtained when grade IV tumors were excluded. Presence/absence of enhancement alone was the best predictor for survival time, and the regression was significant (P < 0.0001). Conclusion. Presence/absence of enhancement, reflecting transendothelial leakage, was the feature with highest predictive value for grade and survival time in glioma patients

Parameter resolution in two models for cell survival after radiation

International Nuclear Information System (INIS)

Di Cera, E.; Andreasi Bassi, F.; Arcovito, G.

1989-01-01

The resolvability of model parameters for the linear-quadratic and the repair-misrepair models for cell survival after radiation has been studied by Monte Carlo simulations as a function of the number of experimental data points collected in a given dose range and the experimental error. Statistical analysis of the results reveals the range of experimental conditions under which the model parameters can be resolved with sufficient accuracy, and points out some differences in the operational aspects of the two models. (orig.)

Longitudinal data analysis a handbook of modern statistical methods

CERN Document Server

Fitzmaurice, Garrett; Verbeke, Geert; Molenberghs, Geert

2008-01-01

Although many books currently available describe statistical models and methods for analyzing longitudinal data, they do not highlight connections between various research threads in the statistical literature. Responding to this void, Longitudinal Data Analysis provides a clear, comprehensive, and unified overview of state-of-the-art theory and applications. It also focuses on the assorted challenges that arise in analyzing longitudinal data. After discussing historical aspects, leading researchers explore four broad themes: parametric modeling, nonparametric and semiparametric methods, joint

Mathematical statistics

CERN Document Server

Pestman, Wiebe R

2009-01-01

This textbook provides a broad and solid introduction to mathematical statistics, including the classical subjects hypothesis testing, normal regression analysis, and normal analysis of variance. In addition, non-parametric statistics and vectorial statistics are considered, as well as applications of stochastic analysis in modern statistics, e.g., Kolmogorov-Smirnov testing, smoothing techniques, robustness and density estimation. For students with some elementary mathematical background. With many exercises. Prerequisites from measure theory and linear algebra are presented.

Bayesian Sensitivity Analysis of Statistical Models with Missing Data.

Science.gov (United States)

Zhu, Hongtu; Ibrahim, Joseph G; Tang, Niansheng

2014-04-01

Methods for handling missing data depend strongly on the mechanism that generated the missing values, such as missing completely at random (MCAR) or missing at random (MAR), as well as other distributional and modeling assumptions at various stages. It is well known that the resulting estimates and tests may be sensitive to these assumptions as well as to outlying observations. In this paper, we introduce various perturbations to modeling assumptions and individual observations, and then develop a formal sensitivity analysis to assess these perturbations in the Bayesian analysis of statistical models with missing data. We develop a geometric framework, called the Bayesian perturbation manifold, to characterize the intrinsic structure of these perturbations. We propose several intrinsic influence measures to perform sensitivity analysis and quantify the effect of various perturbations to statistical models. We use the proposed sensitivity analysis procedure to systematically investigate the tenability of the non-ignorable missing at random (NMAR) assumption. Simulation studies are conducted to evaluate our methods, and a dataset is analyzed to illustrate the use of our diagnostic measures.

Advanced data analysis in neuroscience integrating statistical and computational models

CERN Document Server

Durstewitz, Daniel

2017-01-01

This book is intended for use in advanced graduate courses in statistics / machine learning, as well as for all experimental neuroscientists seeking to understand statistical methods at a deeper level, and theoretical neuroscientists with a limited background in statistics. It reviews almost all areas of applied statistics, from basic statistical estimation and test theory, linear and nonlinear approaches for regression and classification, to model selection and methods for dimensionality reduction, density estimation and unsupervised clustering.  Its focus, however, is linear and nonlinear time series analysis from a dynamical systems perspective, based on which it aims to convey an understanding also of the dynamical mechanisms that could have generated observed time series. Further, it integrates computational modeling of behavioral and neural dynamics with statistical estimation and hypothesis testing. This way computational models in neuroscience are not only explanat ory frameworks, but become powerfu...

Quantitative analysis and IBM SPSS statistics a guide for business and finance

CERN Document Server

Aljandali, Abdulkader

2016-01-01

This guide is for practicing statisticians and data scientists who use IBM SPSS for statistical analysis of big data in business and finance. This is the first of a two-part guide to SPSS for Windows, introducing data entry into SPSS, along with elementary statistical and graphical methods for summarizing and presenting data. Part I also covers the rudiments of hypothesis testing and business forecasting while Part II will present multivariate statistical methods, more advanced forecasting methods, and multivariate methods. IBM SPSS Statistics offers a powerful set of statistical and information analysis systems that run on a wide variety of personal computers. The software is built around routines that have been developed, tested, and widely used for more than 20 years. As such, IBM SPSS Statistics is extensively used in industry, commerce, banking, local and national governments, and education. Just a small subset of users of the package include the major clearing banks, the BBC, British Gas, British Airway...

What type of statistical model to choose for the analysis of radioimmunoassays

International Nuclear Information System (INIS)

Huet, S.

1984-01-01

The current techniques used for statistical analysis of radioimmunoassays are not very satisfactory for either the statistician or the biologist. They are based on an attempt to make the response curve linear to avoid complicated computations. The present article shows that this practice has considerable effects (often neglected) on the statistical assumptions which must be formulated. A more strict analysis is proposed by applying the four-parameter logistic model. The advantages of this method are: the statistical assumptions formulated are based on observed data, and the model can be applied to almost all radioimmunoassays [fr

Computerized statistical analysis with bootstrap method in nuclear medicine

International Nuclear Information System (INIS)

Zoccarato, O.; Sardina, M.; Zatta, G.; De Agostini, A.; Barbesti, S.; Mana, O.; Tarolo, G.L.

1988-01-01

Statistical analysis of data samples involves some hypothesis about the features of data themselves. The accuracy of these hypotheses can influence the results of statistical inference. Among the new methods of computer-aided statistical analysis, the bootstrap method appears to be one of the most powerful, thanks to its ability to reproduce many artificial samples starting from a single original sample and because it works without hypothesis about data distribution. The authors applied the bootstrap method to two typical situation of Nuclear Medicine Department. The determination of the normal range of serum ferritin, as assessed by radioimmunoassay and defined by the mean value ±2 standard deviations, starting from an experimental sample of small dimension, shows an unacceptable lower limit (ferritin plasmatic levels below zero). On the contrary, the results obtained by elaborating 5000 bootstrap samples gives ans interval of values (10.95 ng/ml - 72.87 ng/ml) corresponding to the normal ranges commonly reported. Moreover the authors applied the bootstrap method in evaluating the possible error associated with the correlation coefficient determined between left ventricular ejection fraction (LVEF) values obtained by first pass radionuclide angiocardiography with 99m Tc and 195m Au. The results obtained indicate a high degree of statistical correlation and give the range of r 2 values to be considered acceptable for this type of studies

Software for statistical data analysis used in Higgs searches

International Nuclear Information System (INIS)

Gumpert, Christian; Moneta, Lorenzo; Cranmer, Kyle; Kreiss, Sven; Verkerke, Wouter

2014-01-01

The analysis and interpretation of data collected by the Large Hadron Collider (LHC) requires advanced statistical tools in order to quantify the agreement between observation and theoretical models. RooStats is a project providing a statistical framework for data analysis with the focus on discoveries, confidence intervals and combination of different measurements in both Bayesian and frequentist approaches. It employs the RooFit data modelling language where mathematical concepts such as variables, (probability density) functions and integrals are represented as C++ objects. RooStats and RooFit rely on the persistency technology of the ROOT framework. The usage of a common data format enables the concept of digital publishing of complicated likelihood functions. The statistical tools have been developed in close collaboration with the LHC experiments to ensure their applicability to real-life use cases. Numerous physics results have been produced using the RooStats tools, with the discovery of the Higgs boson by the ATLAS and CMS experiments being certainly the most popular among them. We will discuss tools currently used by LHC experiments to set exclusion limits, to derive confidence intervals and to estimate discovery significances based on frequentist statistics and the asymptotic behaviour of likelihood functions. Furthermore, new developments in RooStats and performance optimisation necessary to cope with complex models depending on more than 1000 variables will be reviewed

Preoperative diffusion-weighted imaging of single brain metastases correlates with patient survival times.

Directory of Open Access Journals (Sweden)

Anna Sophie Berghoff

Full Text Available BACKGROUND: MRI-based diffusion-weighted imaging (DWI visualizes the local differences in water diffusion in vivo. The prognostic value of DWI signal intensities on the source images and apparent diffusion coefficient (ADC maps respectively has not yet been studied in brain metastases (BM. METHODS: We included into this retrospective analysis all patients operated for single BM at our institution between 2002 and 2010, in whom presurgical DWI and BM tissue samples were available. We recorded relevant clinical data, assessed DWI signal intensity and apparent diffusion coefficient (ADC values and performed histopathological analysis of BM tissues. Statistical analyses including uni- and multivariate survival analyses were performed. RESULTS: 65 patients (34 female, 31 male with a median overall survival time (OS of 15 months (range 0-99 months were available for this study. 19 (29.2% patients presented with hyper-, 3 (4.6% with iso-, and 43 (66.2% with hypointense DWI. ADCmean values could be determined in 32 (49.2% patients, ranged from 456.4 to 1691.8*10⁻⁶ mm²/s (median 969.5 and showed a highly significant correlation with DWI signal intensity. DWI hyperintensity correlated significantly with high amount of interstitial reticulin deposition. In univariate analysis, patients with hyperintense DWI (5 months and low ADCmean values (7 months had significantly worse OS than patients with iso/hypointense DWI (16 months and high ADCmean values (30 months, respectively. In multivariate survival analysis, high ADCmean values retained independent statistical significance. CONCLUSIONS: Preoperative DWI findings strongly and independently correlate with OS in patients operated for single BM and are related to interstitial fibrosis. Inclusion of DWI parameters into established risk stratification scores for BM patients should be considered.

PRECISE - pregabalin in addition to usual care: Statistical analysis plan

NARCIS (Netherlands)

S. Mathieson (Stephanie); L. Billot (Laurent); C. Maher (Chris); A.J. McLachlan (Andrew J.); J. Latimer (Jane); B.W. Koes (Bart); M.J. Hancock (Mark J.); I. Harris (Ian); R.O. Day (Richard O.); J. Pik (Justin); S. Jan (Stephen); C.-W.C. Lin (Chung-Wei Christine)

2016-01-01

textabstractBackground: Sciatica is a severe, disabling condition that lacks high quality evidence for effective treatment strategies. This a priori statistical analysis plan describes the methodology of analysis for the PRECISE study. Methods/design: PRECISE is a prospectively registered, double

Statistical margin to DNB safety analysis approach for LOFT

International Nuclear Information System (INIS)

Atkinson, S.A.

1982-01-01

A method was developed and used for LOFT thermal safety analysis to estimate the statistical margin to DNB for the hot rod, and to base safety analysis on desired DNB probability limits. This method is an advanced approach using response surface analysis methods, a very efficient experimental design, and a 2nd-order response surface equation with a 2nd-order error propagation analysis to define the MDNBR probability density function. Calculations for limiting transients were used in the response surface analysis thereby including transient interactions and trip uncertainties in the MDNBR probability density

Nutritional factors as predictors of response to radio-chemotherapy and survival in unresectable squamous head and neck carcinoma

International Nuclear Information System (INIS)

Salas, Sebastien; Deville, Jean-Laurent; Giorgi, Roch; Pignon, Thierry; Bagarry, Danielle; Barrau, Karine; Zanaret, Michel; Giovanni, Antoine; Bourgeois, Aude; Favre, Roger; Duffaud, Florence

2008-01-01

Background and purpose: This study sought to evaluate nutritional prognostic factors before treatment in patients with unresectable head and neck cancer treated by concomitant radio-chemotherapy. Methods and materials: Seventy-two consecutive patients were treated. We studied the potential effects of CRP, Alb, preAlb, orosomucoid, weight, weight history, BMI, PINI, OPR and NRI on response to treatment, Event-Free Survival (EFS) and Overall Survival (OS). Effects of potential risk factors on OS and on EFS were analyzed by computing Kaplan-Meier estimates, and curves were compared using the log-rank test. Results: All biological nutritional factors were statistically correlated with the response to radio-chemotherapy. In multivariate analysis, only CRP (p = 0.004) remained statistically significant. A statistical correlation was found between Alb and EFS in multivariate analysis (p = 0.04). The factors influencing OS in univariate analysis were Alb (p = 0.008), CRP (p = 0.004), orosomucoid (p = 0.01) and NRI (p = 0.01), response to radio-chemotherapy (p < 0.001) and staging (p = 0.04). In multivariate analysis, only the response to radio-chemotherapy (p < 0.001) remained significant. Conclusions: This study illustrates the prognostic value of nutritional status. CRP and Alb may be useful in the assessment of advanced head and neck cancer patients at diagnosis and for stratifying patients taking part in randomized trials

Multivariate statistical analysis of atom probe tomography data

International Nuclear Information System (INIS)

Parish, Chad M.; Miller, Michael K.

2010-01-01

The application of spectrum imaging multivariate statistical analysis methods, specifically principal component analysis (PCA), to atom probe tomography (APT) data has been investigated. The mathematical method of analysis is described and the results for two example datasets are analyzed and presented. The first dataset is from the analysis of a PM 2000 Fe-Cr-Al-Ti steel containing two different ultrafine precipitate populations. PCA properly describes the matrix and precipitate phases in a simple and intuitive manner. A second APT example is from the analysis of an irradiated reactor pressure vessel steel. Fine, nm-scale Cu-enriched precipitates having a core-shell structure were identified and qualitatively described by PCA. Advantages, disadvantages, and future prospects for implementing these data analysis methodologies for APT datasets, particularly with regard to quantitative analysis, are also discussed.

Repair-dependent cell radiation survival and transformation: an integrated theory

International Nuclear Information System (INIS)

Sutherland, John C

2014-01-01

The repair-dependent model of cell radiation survival is extended to include radiation-induced transformations. The probability of transformation is presumed to scale with the number of potentially lethal damages that are repaired in a surviving cell or the interactions of such damages. The theory predicts that at doses corresponding to high survival, the transformation frequency is the sum of simple polynomial functions of dose; linear, quadratic, etc, essentially as described in widely used linear-quadratic expressions. At high doses, corresponding to low survival, the ratio of transformed to surviving cells asymptotically approaches an upper limit. The low dose fundamental- and high dose plateau domains are separated by a downwardly concave transition region. Published transformation data for mammalian cells show the high-dose plateaus predicted by the repair-dependent model for both ultraviolet and ionizing radiation. For the neoplastic transformation experiments that were analyzed, the data can be fit with only the repair-dependent quadratic function. At low doses, the transformation frequency is strictly quadratic, but becomes sigmodial over a wider range of doses. Inclusion of data from the transition region in a traditional linear-quadratic analysis of neoplastic transformation frequency data can exaggerate the magnitude of, or create the appearance of, a linear component. Quantitative analysis of survival and transformation data shows good agreement for ultraviolet radiation; the shapes of the transformation components can be predicted from survival data. For ionizing radiations, both neutrons and x-rays, survival data overestimate the transforming ability for low to moderate doses. The presumed cause of this difference is that, unlike UV photons, a single x-ray or neutron may generate more than one lethal damage in a cell, so the distribution of such damages in the population is not accurately described by Poisson statistics. However, the complete

Development of statistical analysis code for meteorological data (W-View)

Energy Technology Data Exchange (ETDEWEB)

Tachibana, Haruo; Sekita, Tsutomu; Yamaguchi, Takenori [Japan Atomic Energy Research Inst., Tokai, Ibaraki (Japan). Tokai Research Establishment

2003-03-01

A computer code (W-View: Weather View) was developed to analyze the meteorological data statistically based on 'the guideline of meteorological statistics for the safety analysis of nuclear power reactor' (Nuclear Safety Commission on January 28, 1982; revised on March 29, 2001). The code gives statistical meteorological data to assess the public dose in case of normal operation and severe accident to get the license of nuclear reactor operation. This code was revised from the original code used in a large office computer code to enable a personal computer user to analyze the meteorological data simply and conveniently and to make the statistical data tables and figures of meteorology. (author)

CORSSA: Community Online Resource for Statistical Seismicity Analysis

Science.gov (United States)

Zechar, J. D.; Hardebeck, J. L.; Michael, A. J.; Naylor, M.; Steacy, S.; Wiemer, S.; Zhuang, J.

2011-12-01

Statistical seismology is critical to the understanding of seismicity, the evaluation of proposed earthquake prediction and forecasting methods, and the assessment of seismic hazard. Unfortunately, despite its importance to seismology-especially to those aspects with great impact on public policy-statistical seismology is mostly ignored in the education of seismologists, and there is no central repository for the existing open-source software tools. To remedy these deficiencies, and with the broader goal to enhance the quality of statistical seismology research, we have begun building the Community Online Resource for Statistical Seismicity Analysis (CORSSA, www.corssa.org). We anticipate that the users of CORSSA will range from beginning graduate students to experienced researchers. More than 20 scientists from around the world met for a week in Zurich in May 2010 to kick-start the creation of CORSSA: the format and initial table of contents were defined; a governing structure was organized; and workshop participants began drafting articles. CORSSA materials are organized with respect to six themes, each will contain between four and eight articles. CORSSA now includes seven articles with an additional six in draft form along with forums for discussion, a glossary, and news about upcoming meetings, special issues, and recent papers. Each article is peer-reviewed and presents a balanced discussion, including illustrative examples and code snippets. Topics in the initial set of articles include: introductions to both CORSSA and statistical seismology, basic statistical tests and their role in seismology; understanding seismicity catalogs and their problems; basic techniques for modeling seismicity; and methods for testing earthquake predictability hypotheses. We have also begun curating a collection of statistical seismology software packages.

Association between pretreatment Glasgow prognostic score and gastric cancer survival and clinicopathological features: a meta-analysis

Directory of Open Access Journals (Sweden)

Zhang CX

2016-06-01

Full Text Available Chun-Xiao Zhang,* Shu-Yi Wang,* Shuang-Qian Chen, Shuai-Long Yang, Lu Wan, Bin Xiong Department of Oncology, Zhongnan Hospital of Wuhan University, Hubei Key Laboratory of Tumor Biological Behaviors and Hubei Cancer Clinical Study Center, Wuhan, Hubei, People’s Republic of China *These authors contributed equally to this work Background: Glasgow prognostic score (GPS is widely known as a systemic inflammatory-based marker. The relationship between pretreatment GPS and gastric cancer (GC survival and clinicopathological features remains controversial. The aim of the study was to conduct a meta-analysis of published studies to evaluate the association between pretreatment GPS and survival and clinicopathological features in GC patients. Methods: We searched PubMed, Embase, MEDLINE, and BioMed databases for relevant studies. Combined analyses were used to assess the association between pretreatment GPS and overall survival, disease-free survival, and clinicopathological parameters by Stata Version 12.0. Results: A total of 14 studies were included in this meta-analysis, including 5,579 GC patients. The results indicated that pretreatment high GPS (HGPS predicted poor overall survival (hazard ratio =1.51, 95% CI: 1.37–1.66, P<0.01 and disease-free survival (hazard ratio =1.45, 95% CI: 1.26–1.68, P<0.01 in GC patients. Pretreatment HGPS was also significantly associated with advanced tumor–node–metastasis stage (odds ratio [OR] =3.09, 95% CI: 2.11–4.53, P<0.01, lymph node metastasis (OR =4.60, 95% CI: 3.23–6.56, P<0.01, lymphatic invasion (OR =3.04, 95% CI: 2.00–4.62, P<0.01, and venous invasion (OR =3.56, 95% CI: 1.81–6.99, P<0.01. Conclusion: Our meta-analysis indicated that pretreatment HGPS could be a predicative factor of poor survival outcome and clinicopathological features for GC patients. Keywords: Glasgow prognostic score, gastric cancer, survival, clinicopathological feature

Recent advances in statistical energy analysis

Science.gov (United States)

Heron, K. H.

1992-01-01

Statistical Energy Analysis (SEA) has traditionally been developed using modal summation and averaging approach, and has led to the need for many restrictive SEA assumptions. The assumption of 'weak coupling' is particularly unacceptable when attempts are made to apply SEA to structural coupling. It is now believed that this assumption is more a function of the modal formulation rather than a necessary formulation of SEA. The present analysis ignores this restriction and describes a wave approach to the calculation of plate-plate coupling loss factors. Predictions based on this method are compared with results obtained from experiments using point excitation on one side of an irregular six-sided box structure. Conclusions show that the use and calculation of infinite transmission coefficients is the way forward for the development of a purely predictive SEA code.

The relationship between survival of Columbia River fall chinook salmon and in-river environmental factors -- Analysis of historic data for juvenile and adult salmonid production: Phase 2. Final report

International Nuclear Information System (INIS)

Skalski, J.R.; Townsend, R.L.; Donnelly, R.F.; Hilborn, R.W.

1996-12-01

This project analyzes in greater detail the coded-wire-tag (CWT) returns of Priest Rapids Hatchery fall chinook for the years 1976--1989 initially begun by Hilborn et al. (1993a). These additional analyses were prompted by suggestions made by peer reviews of the initial draft report. The initial draft and the peer review comments are included in this final report (Appendices A and B). The statistical analyses paired Priest Rapids stock with potential downriver reference stocks to isolate in-river survival rates. Thirty-three potential reference stocks were initially examined for similar ocean recovery rates; the five stocks with the most similar recovery patterns (i.e., Bonneville Brights, Cowlitz, Gray's River, Tanner Creek, and Washougal) to the Priest Rapids stock were used in the subsequent analysis of in-river survival. Three alternate forms of multiple regression models were used to investigate the relationship between predicted in-river survival and ambient conditions. Analyses were conducted with and without attempts to adjust for smolt transportation at McNary Dam. Independent variables examined in the analysis included river flows, temperature, turbidity, and spill along with the total biomass of hatchery releases in the Columbia-Snake River Basin

Statistical analysis of tourism destination competitiveness

Directory of Open Access Journals (Sweden)

Attilio Gardini

2013-05-01

Full Text Available The growing relevance of tourism industry for modern advanced economies has increased the interest among researchers and policy makers in the statistical analysis of destination competitiveness. In this paper we outline a new model of destination competitiveness based on sound theoretical grounds and we develop a statistical test of the model on sample data based on Italian tourist destination decisions and choices. Our model focuses on the tourism decision process which starts from the demand schedule for holidays and ends with the choice of a specific holiday destination. The demand schedule is a function of individual preferences and of destination positioning, while the final decision is a function of the initial demand schedule and the information concerning services for accommodation and recreation in the selected destinations. Moreover, we extend previous studies that focused on image or attributes (such as climate and scenery by paying more attention to the services for accommodation and recreation in the holiday destinations. We test the proposed model using empirical data collected from a sample of 1.200 Italian tourists interviewed in 2007 (October - December. Data analysis shows that the selection probability for the destination included in the consideration set is not proportional to the share of inclusion because the share of inclusion is determined by the brand image, while the selection of the effective holiday destination is influenced by the real supply conditions. The analysis of Italian tourists preferences underline the existence of a latent demand for foreign holidays which points out a risk of market share reduction for Italian tourism system in the global market. We also find a snow ball effect which helps the most popular destinations, mainly in the northern Italian regions.

Visual and statistical analysis of 18F-FDG PET in primary progressive aphasia

International Nuclear Information System (INIS)

Matias-Guiu, Jordi A.; Moreno-Ramos, Teresa; Garcia-Ramos, Rocio; Fernandez-Matarrubia, Marta; Oreja-Guevara, Celia; Matias-Guiu, Jorge; Cabrera-Martin, Maria Nieves; Perez-Castejon, Maria Jesus; Rodriguez-Rey, Cristina; Ortega-Candil, Aida; Carreras, Jose Luis

2015-01-01

Diagnosing progressive primary aphasia (PPA) and its variants is of great clinical importance, and fluorodeoxyglucose (FDG) positron emission tomography (PET) may be a useful diagnostic technique. The purpose of this study was to evaluate interobserver variability in the interpretation of FDG PET images in PPA as well as the diagnostic sensitivity and specificity of the technique. We also aimed to compare visual and statistical analyses of these images. There were 10 raters who analysed 44 FDG PET scans from 33 PPA patients and 11 controls. Five raters analysed the images visually, while the other five used maps created using Statistical Parametric Mapping software. Two spatial normalization procedures were performed: global mean normalization and cerebellar normalization. Clinical diagnosis was considered the gold standard. Inter-rater concordance was moderate for visual analysis (Fleiss' kappa 0.568) and substantial for statistical analysis (kappa 0.756-0.881). Agreement was good for all three variants of PPA except for the nonfluent/agrammatic variant studied with visual analysis. The sensitivity and specificity of each rater's diagnosis of PPA was high, averaging 87.8 and 89.9 % for visual analysis and 96.9 and 90.9 % for statistical analysis using global mean normalization, respectively. In cerebellar normalization, sensitivity was 88.9 % and specificity 100 %. FDG PET demonstrated high diagnostic accuracy for the diagnosis of PPA and its variants. Inter-rater concordance was higher for statistical analysis, especially for the nonfluent/agrammatic variant. These data support the use of FDG PET to evaluate patients with PPA and show that statistical analysis methods are particularly useful for identifying the nonfluent/agrammatic variant of PPA. (orig.)

From statistics to mathematical finance festschrift in honour of Winfried Stute

CERN Document Server

Manteiga, Wenceslao; Schmidt, Thorsten; Wang, Jane-Ling

2017-01-01

This book, dedicated to Winfried Stute on the occasion of his 70th birthday, presents a unique collection of contributions by leading experts in statistics, stochastic processes, mathematical finance and insurance. The individual chapters cover a wide variety of topics ranging from nonparametric estimation, regression modelling and asymptotic bounds for estimators, to shot-noise processes in finance, option pricing and volatility modelling. The book also features review articles, e.g. on survival analysis.

Restoration Survival: Revisiting Patients' Risk Factors Through a Systematic Literature Review.

Science.gov (United States)

van de Sande, F H; Collares, K; Correa, M B; Cenci, M S; Demarco, F F; Opdam, Njm

2016-09-01

A literature review was conducted to investigate the influence of patient-related factors on restoration survival in posterior permanent teeth as well as to report the methods used to collect these factors. The selection of articles on longitudinal clinical studies investigating the survival of posterior restorations (except full crowns and temporary fillings) and including patient-related factors was performed by applying predefined criteria. The review was organized into two parts, the first describing how patient factors were assessed in the studies (n=45) and the second presenting the statistical significance (n=27) and size of the effect (n=11) of these factors on restoration survival. Patient-related factors mentioned in the studies included age; gender; caries risk; caries activity/severity; decayed, missing, filled teeth; number of restorations; oral hygiene; and bruxism, among others. Sixteen studies included the patient age or age range in the analysis, which was found to be significant in 47% of the studies. Regarding gender, four of 17 reports found a significant effect on survival, showing more failures for men in three studies. The caries risk profile or related variables were included in the analysis of 15 studies, and a significant effect on survival was reported for high-caries-risk individuals (or related variables) in 67% of these studies. Bruxism was also found to influence restoration survival in three of six studies where this variable was investigated. Some issues were found regarding the reporting of methods used to classify patients according to risk and were thoroughly discussed. In view of the information gathered in this review, the assessment of patient factors along with other variables should become part of clinical studies investigating restoration survival, since several of these factors were shown to influence the failure of restorations, regardless of the material type.

Mechanisms and mediation in survival analysis: towards an integrated analytical framework.

LENUS (Irish Health Repository)

Haase, Trutz

2016-02-29

A wide-ranging debate has taken place in recent years on mediation analysis and causal modelling, raising profound theoretical, philosophical and methodological questions. The authors build on the results of these discussions to work towards an integrated approach to the analysis of research questions that situate survival outcomes in relation to complex causal pathways with multiple mediators. The background to this contribution is the increasingly urgent need for policy-relevant research on the nature of inequalities in health and healthcare.

Australasian Resuscitation In Sepsis Evaluation trial statistical analysis plan.

Science.gov (United States)

Delaney, Anthony; Peake, Sandra L; Bellomo, Rinaldo; Cameron, Peter; Holdgate, Anna; Howe, Belinda; Higgins, Alisa; Presneill, Jeffrey; Webb, Steve

2013-10-01

The Australasian Resuscitation In Sepsis Evaluation (ARISE) study is an international, multicentre, randomised, controlled trial designed to evaluate the effectiveness of early goal-directed therapy compared with standard care for patients presenting to the ED with severe sepsis. In keeping with current practice, and taking into considerations aspects of trial design and reporting specific to non-pharmacologic interventions, this document outlines the principles and methods for analysing and reporting the trial results. The document is prepared prior to completion of recruitment into the ARISE study, without knowledge of the results of the interim analysis conducted by the data safety and monitoring committee and prior to completion of the two related international studies. The statistical analysis plan was designed by the ARISE chief investigators, and reviewed and approved by the ARISE steering committee. The data collected by the research team as specified in the study protocol, and detailed in the study case report form were reviewed. Information related to baseline characteristics, characteristics of delivery of the trial interventions, details of resuscitation and other related therapies, and other relevant data are described with appropriate comparisons between groups. The primary, secondary and tertiary outcomes for the study are defined, with description of the planned statistical analyses. A statistical analysis plan was developed, along with a trial profile, mock-up tables and figures. A plan for presenting baseline characteristics, microbiological and antibiotic therapy, details of the interventions, processes of care and concomitant therapies, along with adverse events are described. The primary, secondary and tertiary outcomes are described along with identification of subgroups to be analysed. A statistical analysis plan for the ARISE study has been developed, and is available in the public domain, prior to the completion of recruitment into the

Measurement of temporal regional cerebral perfusion with single-photon emission tomography predicts rate of decline in language function and survival in early Alzheimer's disease

International Nuclear Information System (INIS)

Claus, J.J.; Walstra, G.J.M.; Hijdra, A.; Gool, W.A. van; Royen, E.A. van; Verbeeten, B. Jr.

1999-01-01

We determined the relationship between regional cerebral blood flow (rCBF) measured with single-photon emission tomography (SPET) and decline in cognitive function and survival in Alzheimer's disease. In a prospective follow-up study, 69 consecutively referred patients with early probable Alzheimer's disease (NINCDS/ADRDA criteria) underwent SPET performed at the time of initial diagnosis using technetium-99m-labelled hexamethylpropylene amine oxime. Neuropsychological function was assessed at baseline and after 6 months and survival data were available on all patients, extending to 5.5 years of follow-up. Lower left temporal (P<0.01) and lower left parietal (P<0.01) rCBF were statistically significantly related to decline in language function after 6 months. The association between left temporal rCBF and survival was also statistically significant (P<0.05) using Cox proportional hazards regression analysis. Performing analysis with quartiles of the distribution, we found a threshold effect for low left temporal rCBF (rCBF<73.7%, P<0.01) and high risk of mortality. In this lowest quartile, median survival time was 2.7 years (follow-up to 5.2 years), compared with 4.4 years in the other quartiles (follow-up to 5.5 years). Kaplan-Meier survival curves showed statistically significant (P<0.05, log rank test) survival curves for the lowest versus other quartiles of left temporal rCBF. All results were unaffected by adjustment for age, sex, dementia severity, duration of symptoms, education and ratings of local cortical atrophy. We conclude that left temporal rCBF predicts decline in language function and survival in patients with early probable Alzheimer's disease, with a threshold effect of low rCBF and high risk of mortality. (orig.)

Auto-SCT improves survival in systemic light chain amyloidosis: a retrospective analysis with 14-year follow-up.

Science.gov (United States)

Parmar, S; Kongtim, P; Champlin, R; Dinh, Y; Elgharably, Y; Wang, M; Bashir, Q; Shah, J J; Shah, N; Popat, U; Giralt, S A; Orlowski, R Z; Qazilbash, M H

2014-08-01

Optimal treatment approach continues to remain a challenge for systemic light chain amyloidosis (AL). So far, Auto-SCT is the only modality associated with long-term survival. However, failure to show survival benefit in randomized study raises questions regarding its efficacy. We present a comparative outcome analysis of Auto-SCT to conventional therapies (CTR) in AL patients treated over a 14-year period at our institution. Out of the 145 AL amyloidosis patients, Auto-SCT was performed in 80 patients with 1-year non-relapse mortality rate of 12.5%. Novel agents were used as part of induction therapy in 56% of transplant recipients vs 46% of CTR patients. Hematological and organ responses were seen in 74.6% and 39% in the Auto-SCT arm vs 53% and 12% in the CTR arm, respectively. The projected 5-year survival for Auto-SCT vs CTR was 63% vs 38%, respectively. Landmark analysis of patients alive at 1-year after diagnosis showed improved 5-year OS of 72% with Auto-SCT vs 65% in the CTR arm. In the multivariate analysis, age SCT were associated with improved survival. In conclusion, Auto-SCT is associated with long-term survival for patients with AL amyloidosis.

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.

Measuring the Success of an Academic Development Programme: A Statistical Analysis

Science.gov (United States)

Smith, L. C.

2009-01-01

This study uses statistical analysis to estimate the impact of first-year academic development courses in microeconomics, statistics, accountancy, and information systems, offered by the University of Cape Town's Commerce Academic Development Programme, on students' graduation performance relative to that achieved by mainstream students. The data…

Pyrotechnic Shock Analysis Using Statistical Energy Analysis

Science.gov (United States)

2015-10-23

SEA subsystems. A couple of validation examples are provided to demonstrate the new approach. KEY WORDS : Peak Ratio, phase perturbation...Ballistic Shock Prediction Models and Techniques for Use in the Crusader Combat Vehicle Program,” 11th Annual US Army Ground Vehicle Survivability

Does biological relatedness affect child survival?

Directory of Open Access Journals (Sweden)

2003-05-01

Full Text Available Objective: We studied child survival in Rakai, Uganda where many children are fostered out or orphaned. Methods: Biological relatedness is measured as the average of the Wright's coefficients between each household member and the child. Instrumental variables for fostering include proportion of adult males in household, age and gender of household head. Control variables include SES, religion, polygyny, household size, child age, child birth size, and child HIV status. Results: Presence of both parents in the household increased the odds of survival by 28%. After controlling for the endogeneity of child placement decisions in a multivariate model we found that lower biological relatedness of a child was associated with statistically significant reductions in child survival. The effects of biological relatedness on child survival tend to be stronger for both HIV- and HIV+ children of HIV+ mothers. Conclusions: Reductions in the numbers of close relatives caring for children of HIV+ mothers reduce child survival.

Bruxism and dental implant failures: a multilevel mixed effects parametric survival analysis approach.

Science.gov (United States)

Chrcanovic, B R; Kisch, J; Albrektsson, T; Wennerberg, A

2016-11-01

Recent studies have suggested that the insertion of dental implants in patients being diagnosed with bruxism negatively affected the implant failure rates. The aim of the present study was to investigate the association between the bruxism and the risk of dental implant failure. This retrospective study is based on 2670 patients who received 10 096 implants at one specialist clinic. Implant- and patient-related data were collected. Descriptive statistics were used to describe the patients and implants. Multilevel mixed effects parametric survival analysis was used to test the association between bruxism and risk of implant failure adjusting for several potential confounders. Criteria from a recent international consensus (Lobbezoo et al., J Oral Rehabil, 40, 2013, 2) and from the International Classification of Sleep Disorders (International classification of sleep disorders, revised: diagnostic and coding manual, American Academy of Sleep Medicine, Chicago, 2014) were used to define and diagnose the condition. The number of implants with information available for all variables totalled 3549, placed in 994 patients, with 179 implants reported as failures. The implant failure rates were 13·0% (24/185) for bruxers and 4·6% (155/3364) for non-bruxers (P bruxism was a statistically significantly risk factor to implant failure (HR 3·396; 95% CI 1·314, 8·777; P = 0·012), as well as implant length, implant diameter, implant surface, bone quantity D in relation to quantity A, bone quality 4 in relation to quality 1 (Lekholm and Zarb classification), smoking and the intake of proton pump inhibitors. It is suggested that the bruxism may be associated with an increased risk of dental implant failure. © 2016 John Wiley & Sons Ltd.

Survival benefits from follow-up of patients with lung cancer: a systematic review and meta-analysis.

Science.gov (United States)

Calman, Lynn; Beaver, Kinta; Hind, Daniel; Lorigan, Paul; Roberts, Chris; Lloyd-Jones, Myfanwy

2011-12-01

The burden of lung cancer is high for patients and carers. Care after treatment may have the potential to impact on this. We reviewed the published literature on follow-up strategies intended to improve survival and quality of life. We systematically reviewed studies comparing follow-up regimes in lung cancer. Primary outcomes were overall survival (comparing more intensive versus less intensive follow-up) and survival comparing symptomatic with asymptomatic recurrence. Quality of life was identified as a secondary outcome measure. Hazard ratios (HRs) and 95% confidence intervals from eligible studies were synthesized. Nine studies that examined the role of more intensive follow-up for patients with lung cancer were included (eight observational studies and one randomized controlled trial). The studies of curative resection included patients with non-small cell lung cancer Stages I to III disease, and studies of palliative treatment follow-up included limited and extensive stage patients with small cell lung cancer. A total of 1669 patients were included in the studies. Follow-up programs were heterogeneous and multifaceted. A nonsignificant trend for intensive follow-up to improve survival was identified, for the curative intent treatment subgroup (HR: 0.83; 95% confidence interval: 0.66-1.05). Asymptomatic recurrence was associated with increased survival, which was statistically significant HR: 0.61 (0.50-0.74) (p impact of follow-up regimes on living with lung cancer and psychosocial well-being.

Gene expression meta-analysis identifies chromosomal regions involved in ovarian cancer survival

DEFF Research Database (Denmark)

Thomassen, Mads; Jochumsen, Kirsten M; Mogensen, Ole

2009-01-01

the relation of gene expression and chromosomal position to identify chromosomal regions of importance for early recurrence of ovarian cancer. By use of *Gene Set Enrichment Analysis*, we have ranked chromosomal regions according to their association to survival. Over-representation analysis including 1...... using death (P = 0.015) and recurrence (P = 0.002) as outcome. The combined mutation score is strongly associated to upregulation of several growth factor pathways....

Analysis of Variance in Statistical Image Processing

Science.gov (United States)

Kurz, Ludwik; Hafed Benteftifa, M.

1997-04-01

A key problem in practical image processing is the detection of specific features in a noisy image. Analysis of variance (ANOVA) techniques can be very effective in such situations, and this book gives a detailed account of the use of ANOVA in statistical image processing. The book begins by describing the statistical representation of images in the various ANOVA models. The authors present a number of computationally efficient algorithms and techniques to deal with such problems as line, edge, and object detection, as well as image restoration and enhancement. By describing the basic principles of these techniques, and showing their use in specific situations, the book will facilitate the design of new algorithms for particular applications. It will be of great interest to graduate students and engineers in the field of image processing and pattern recognition.

Study of relationship between MUF correlation and detection sensitivity of statistical analysis

International Nuclear Information System (INIS)

Tamura, Toshiaki; Ihara, Hitoshi; Yamamoto, Yoichi; Ikawa, Koji

1989-11-01

Various kinds of statistical analysis are proposed to NRTA (Near Real Time Materials Accountancy) which was devised to satisfy the timeliness goal of one of the detection goals of IAEA. It will be presumed that different statistical analysis results will occur between the case of considered rigorous error propagation (with MUF correlation) and the case of simplified error propagation (without MUF correlation). Therefore, measurement simulation and decision analysis were done using flow simulation of 800 MTHM/Y model reprocessing plant, and relationship between MUF correlation and detection sensitivity and false alarm of statistical analysis was studied. Specific character of material accountancy for 800 MTHM/Y model reprocessing plant was grasped by this simulation. It also became clear that MUF correlation decreases not only false alarm but also detection probability for protracted loss in case of CUMUF test and Page's test applied to NRTA. (author)

The Survival of Morse Cone-Connection Implants with Platform Switch.

Science.gov (United States)

Cassetta, Michele; Di Mambro, Alfonso; Giansanti, Matteo; Brandetti, Giulia

2016-01-01

The aim of this prospective clinical study was to evaluate the survival up to 5 years of Morse cone-connection implants with platform switch considering the influence of biologically relevant, anatomical, and stress-related variables. STROBE guidelines were followed. Seven hundred forty-eight implants were inserted in 350 patients. Follow-up visits were scheduled at the time of stagetwo surgery (2 months later) and at 6, 12, 24, 36, and 60 months. All implants were initially loaded with a cemented provisional acrylic restoration. The definitive metal-ceramic restorations were cemented at the 6-month follow-up. Implant cumulative survival rates (CSRs) were calculated using life table actuarial method. Survival data were also analyzed by the log-rank test and Cox regression. The statistical analysis was conducted at the patient level. P ≤ .05 was considered as an indicator of statistical significance. During the follow-up (mean: 40 months; SD: 20.27), 28 patients were considered failed (8%). The CSR and its standard error (SE) was 92% ± 2.17%. Patients with implant-supported single crowns had a CSR of 90%, whereas those with implant-supported fixed dental prostheses had a CSR of 93%. The implant diameter (P = .0399) and implant length (P = .0441) were statistically significant. The probability of failure was almost 75% lower for patients with wide rather than standard implants, 91% lower for patients with long implants, and 69% lower for patients with standard implants compared with short implants. The use of Morse cone-connection implants with platform switch is a safe and reliable treatment method. Stress-related variables influence the risk of failure confirming the importance of biomechanical factors in the longevity of osseointegrated implants; thus, the clinician may obtain better results if attention is paid to these factors.

Determinants of survival after liver resection for metastatic colorectal carcinoma.

Science.gov (United States)

Parau, Angela; Todor, Nicolae; Vlad, Liviu

2015-01-01

Prognostic factors for survival after liver resection for metastatic colorectal cancer identified up to date are quite inconsistent with a great inter-study variability. In this study we aimed to identify predictors of outcome in our patient population. A series of 70 consecutive patients from the oncological hepatobiliary database, who had undergone curative hepatic surgical resection for hepatic metastases of colorectal origin, operated between 2006 and 2011, were identified. At 44.6 months (range 13.7-73), 30 of 70 patients (42.85%) were alive. Patient demographics, primary tumor and liver tumor factors, operative factors, pathologic findings, recurrence patterns, disease-free survival (DFS), overall survival (OS) and cancer-specific survival (CSS) were analyzed. Clinicopathologic variables were tested using univariate and multivariate analyses. The 3-year CSS after first hepatic resection was 54%. Median CSS survival after first hepatic resection was 40.2 months. Median CSS after second hepatic resection was 24.2 months. The 3-year DFS after first hepatic resection was 14%. Median disease free survival after first hepatic resection was 18 months. The 3-year DFS after second hepatic resection was 27% and median DFS after second hepatic resection 12 months. The 30-day mortality and morbidity rate after first hepatic resection was 5.71% and 12.78%, respectively. In univariate analysis CSS was significantly reduced for the following factors: age >53 years, advanced T stage of primary tumor, moderately- poorly differentiated tumor, positive and narrow resection margin, preoperative CEA level >30 ng/ml, DFS <18 months. Perioperative chemotherapy related to metastasectomy showed a trend in improving CSS (p=0.07). Perioperative chemotherapy improved DFS in a statistically significant way (p=0.03). Perioperative chemotherapy and achievement of resection margins beyond 1 mm were the major determinants of both CSS and DFS after first liver resection in multivariate

75 FR 24718 - Guidance for Industry on Documenting Statistical Analysis Programs and Data Files; Availability

Science.gov (United States)

2010-05-05

...] Guidance for Industry on Documenting Statistical Analysis Programs and Data Files; Availability AGENCY... documenting statistical analyses and data files submitted to the Center for Veterinary Medicine (CVM) for the... on Documenting Statistical Analysis Programs and Data Files; Availability'' giving interested persons...

Imaging Flow Cytometry Analysis to Identify Differences of Survival Motor Neuron Protein Expression in Patients With Spinal Muscular Atrophy.

Science.gov (United States)

Arakawa, Reiko; Arakawa, Masayuki; Kaneko, Kaori; Otsuki, Noriko; Aoki, Ryoko; Saito, Kayoko

2016-08-01

Spinal muscular atrophy is a neurodegenerative disorder caused by the deficient expression of survival motor neuron protein in motor neurons. A major goal of disease-modifying therapy is to increase survival motor neuron expression. Changes in survival motor neuron protein expression can be monitored via peripheral blood cells in patients; therefore we tested the sensitivity and utility of imaging flow cytometry for this purpose. After the immortalization of peripheral blood lymphocytes from a human healthy control subject and two patients with spinal muscular atrophy type 1 with two and three copies of SMN2 gene, respectively, we used imaging flow cytometry analysis to identify significant differences in survival motor neuron expression. A bright detail intensity analysis was used to investigate differences in the cellular localization of survival motor neuron protein. Survival motor neuron expression was significantly decreased in cells derived from patients with spinal muscular atrophy relative to those derived from a healthy control subject. Moreover, survival motor neuron expression correlated with the clinical severity of spinal muscular atrophy according to SMN2 copy number. The cellular accumulation of survival motor neuron protein was also significantly decreased in cells derived from patients with spinal muscular atrophy relative to those derived from a healthy control subject. The benefits of imaging flow cytometry for peripheral blood analysis include its capacities for analyzing heterogeneous cell populations; visualizing cell morphology; and evaluating the accumulation, localization, and expression of a target protein. Imaging flow cytometry analysis should be implemented in future studies to optimize its application as a tool for spinal muscular atrophy clinical trials. Copyright © 2016 Elsevier Inc. All rights reserved.

Chordoma: review of clinico radiological features and factors affecting survival

International Nuclear Information System (INIS)

Soo, M.Y.S.

2001-01-01

This study reviews the clinico radiological features of cranial and sacrospinal chordomas and identifies factors affecting survival. Nineteen patients seen between January 1980 and December 2000 with histopathological diagnosis of chordomas were retrospectively reviewed with reference to clinical presentation, imaging features, treatment modalities and post-therapy status. Eight had tumours in the skull base while 11 patients had spinal and sacro-coccygeal lesions. Surgical resection was performed in 16 patients whose subsequent natural history was used to identify clinical indicators that may influence survival. Completeness of resection, age, gender and postoperative irradiation were subjected to analysis using the Cox proportional hazard models. Kaplan-Meir survival curves illustrate the survival distributions. Diplopia and facial pain are prime clinical presentations in cranial lesions, while extremity weakness and a sacrogluteal mass are common complaints in the sacrospinal group. Lesional calcifications are present in 40% while an osteolytic soft tissue mass is detectable by CT in all cases. Heterogeneous signals and internal septations on T 2 -weighted MRI are predominant features. In sacrospinal tumours, complete excision with adjuvant radiotherapy achieves the best results with a disease-free survival of more than 5 years. The clinical and imaging findings in this study are in accordance with those of other series. Except for complete surgical excision followed by radiotherapy in the subset of patients with sacrospinal tumours, none of the other clinical indicators show a statistical significant influence on survival. Copyright (2001) Blackwell Science Pty Ltd

Point defect characterization in HAADF-STEM images using multivariate statistical analysis

International Nuclear Information System (INIS)