BOX-COX transformation and random regression models for fecal egg count data

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Marcos Vinicius Silva

2012-01-01

Full Text Available Accurate genetic evaluation of livestock is based on appropriate modeling of phenotypic measurements. In ruminants fecal egg count (FEC is commonly used to measure resistance to nematodes. FEC values are not normally distributed and logarithmic transformations have been used to achieve normality before analysis. However, the transformed data are often not normally distributed, especially when data are extremely skewed. A series of repeated FEC measurements may provide information about the population dynamics of a group or individual. A total of 6,375 FEC measures were obtained for 410 animals between 1992 and 2003 from the Beltsville Agricultural Research Center Angus herd. Original data were transformed using an extension of the Box-Cox transformation to approach normality and to estimate (covariance components. We also proposed using random regression models (RRM for genetic and non-genetic studies of FEC. Phenotypes were analyzed using RRM and restricted maximum likelihood. Within the different orders of Legendre polynomials used, those with more parameters (order 4 adjusted FEC data best. Results indicated that the transformation of FEC data utilizing the Box-Cox transformation family was effective in reducing the skewness and kurtosis, and dramatically increased estimates of heritability, and measurements of FEC obtained in the period between 12 and 26 weeks in a 26-week experimental challenge period are genetically correlated.

Box-Cox Transformation and Random Regression Models for Fecal egg Count Data.

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da Silva, Marcos Vinícius Gualberto Barbosa; Van Tassell, Curtis P; Sonstegard, Tad S; Cobuci, Jaime Araujo; Gasbarre, Louis C

2011-01-01

Accurate genetic evaluation of livestock is based on appropriate modeling of phenotypic measurements. In ruminants, fecal egg count (FEC) is commonly used to measure resistance to nematodes. FEC values are not normally distributed and logarithmic transformations have been used in an effort to achieve normality before analysis. However, the transformed data are often still not normally distributed, especially when data are extremely skewed. A series of repeated FEC measurements may provide information about the population dynamics of a group or individual. A total of 6375 FEC measures were obtained for 410 animals between 1992 and 2003 from the Beltsville Agricultural Research Center Angus herd. Original data were transformed using an extension of the Box-Cox transformation to approach normality and to estimate (co)variance components. We also proposed using random regression models (RRM) for genetic and non-genetic studies of FEC. Phenotypes were analyzed using RRM and restricted maximum likelihood. Within the different orders of Legendre polynomials used, those with more parameters (order 4) adjusted FEC data best. Results indicated that the transformation of FEC data utilizing the Box-Cox transformation family was effective in reducing the skewness and kurtosis, and dramatically increased estimates of heritability, and measurements of FEC obtained in the period between 12 and 26 weeks in a 26-week experimental challenge period are genetically correlated.

Predictors of unsuccessful outcome in cemented femoral revisions using bone impaction grafting; Cox regression analysis of 208 cases.

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Te Stroet, Martijn A J; Rijnen, Wim H C; Gardeniers, Jean W M; Schreurs, B Willem; Hannink, Gerjon

2016-09-29

Despite improvements in the technique of femoral impaction bone grafting, reconstruction failures still can occur. Therefore, the aim of our study was to determine risk factors for the endpoint re-revision for any reason. We used prospectively collected demographic, clinical and surgical data of all 202 patients who underwent 208 femoral revisions using the X-change Femoral Revision System (Stryker-Howmedica), fresh-frozen morcellised allograft and a cemented polished Exeter stem in our department from 1991 to 2007. Univariable and multivariable Cox regression analyses were performed to identify potential factors associated with re-revision. The mean follow-up was 10.6 (5-21) years. The cumulative re-revision rate was 6.3% (13/208). After univariable selection, sex, age, body mass index (BMI), American Association of Anesthesiologists (ASA) classification, type of removed femoral component, and mesh used for reconstruction were included in multivariable regression analysis.In the multivariable analysis, BMI was the only factor that was significantly associated with the risk of re-revision after bone impaction grafting (BMI ≥30 vs. BMI <30, HR = 6.54 [95% CI 1.89-22.65]; p = 0.003). BMI was the only factor associated with the risk of re-revision for any reason. Besides BMI also other factors, such as Endoklinik score and the type of removed femoral component, can provide guidance in the process of preclinical decision making. With the knowledge obtained from this study, preoperative patient selection, informed consent, and treatment protocols can be better adjusted to the individual patient who needs to undergo a femoral revision with impaction bone grafting.

BFLCRM: A BAYESIAN FUNCTIONAL LINEAR COX REGRESSION MODEL FOR PREDICTING TIME TO CONVERSION TO ALZHEIMER'S DISEASE.

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Lee, Eunjee; Zhu, Hongtu; Kong, Dehan; Wang, Yalin; Giovanello, Kelly Sullivan; Ibrahim, Joseph G

2015-12-01

The aim of this paper is to develop a Bayesian functional linear Cox regression model (BFLCRM) with both functional and scalar covariates. This new development is motivated by establishing the likelihood of conversion to Alzheimer's disease (AD) in 346 patients with mild cognitive impairment (MCI) enrolled in the Alzheimer's Disease Neuroimaging Initiative 1 (ADNI-1) and the early markers of conversion. These 346 MCI patients were followed over 48 months, with 161 MCI participants progressing to AD at 48 months. The functional linear Cox regression model was used to establish that functional covariates including hippocampus surface morphology and scalar covariates including brain MRI volumes, cognitive performance (ADAS-Cog), and APOE status can accurately predict time to onset of AD. Posterior computation proceeds via an efficient Markov chain Monte Carlo algorithm. A simulation study is performed to evaluate the finite sample performance of BFLCRM.

Methodological comparison of marginal structural model, time-varying Cox regression, and propensity score methods : the example of antidepressant use and the risk of hip fracture

NARCIS (Netherlands)

Ali, M Sanni; Groenwold, Rolf H H; Belitser, Svetlana V; Souverein, Patrick C; Martín, Elisa; Gatto, Nicolle M; Huerta, Consuelo; Gardarsdottir, Helga; Roes, Kit C B; Hoes, Arno W; de Boer, Antonius; Klungel, Olaf H

2016-01-01

BACKGROUND: Observational studies including time-varying treatments are prone to confounding. We compared time-varying Cox regression analysis, propensity score (PS) methods, and marginal structural models (MSMs) in a study of antidepressant [selective serotonin reuptake inhibitors (SSRIs)] use and

PERBANDINGAN TRANSFORMASI BOX-COX DAN REGRESI KUANTIL MEDIAN DALAM MENGATASI HETEROSKEDASTISITAS

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NI WAYAN YUNI CAHYANI

2015-01-01

Full Text Available Ordinary least square (OLS is a method that can be used to estimate the parameter in linear regression analysis. There are some assumption which should be satisfied on OLS, one of this assumption is homoscedasticity, that is the variance of error is constant. If variance of the error is unequal that so-called heteroscedasticity. The presence heteroscedasticity can cause estimation with OLS becomes inefficient. Therefore, heteroscedasticity shall be overcome. There are some method that can used to overcome heteroscedasticity, two among those are Box-Cox power transformation and median quantile regression. This research compared Box-Cox power transformation and median quantile regression to overcome heteroscedasticity. Applied Box-Cox power transformation on OLS result ????2point are greater, smaller RMSE point and confidencen interval more narrow, therefore can be concluded that applied of Box-Cox power transformation on OLS better of median quantile regression to overcome heteroscedasticity.

PERBANDINGAN TRANSFORMASI BOX-COX DAN REGRESI KUANTIL MEDIAN DALAM MENGATASI HETEROSKEDASTISITAS

Directory of Open Access Journals (Sweden)

NI WAYAN YUNI CAHYANI

2015-03-01

Full Text Available Ordinary least square (OLS is a method that can be used to estimate the parameter in linear regression analysis. There are some assumption which should be satisfied on OLS, one of this assumption is homoscedasticity, that is the variance of error is constant. If variance of the error is unequal that so-called heteroscedasticity. The presence heteroscedasticity can cause estimation with OLS becomes inefficient. Therefore, heteroscedasticity shall be overcome. There are some method that can used to overcome heteroscedasticity, two among those are Box-Cox power transformation and median quantile regression. This research compared Box-Cox power transformation and median quantile regression to overcome heteroscedasticity. Applied Box-Cox power transformation on OLS result ????2point are greater, smaller RMSE point and confidencen interval more narrow, therefore can be concluded that applied of Box-Cox power transformation on OLS better of median quantile regression to overcome heteroscedasticity.

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

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

2006-07-01

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

Accounting for covariate measurement error in a Cox model analysis of recurrence of depression.

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Liu, K; Mazumdar, S; Stone, R A; Dew, M A; Houck, P R; Reynolds, C F

2001-01-01

When a covariate measured with error is used as a predictor in a survival analysis using the Cox model, the parameter estimate is usually biased. In clinical research, covariates measured without error such as treatment procedure or sex are often used in conjunction with a covariate measured with error. In a randomized clinical trial of two types of treatments, we account for the measurement error in the covariate, log-transformed total rapid eye movement (REM) activity counts, in a Cox model analysis of the time to recurrence of major depression in an elderly population. Regression calibration and two variants of a likelihood-based approach are used to account for measurement error. The likelihood-based approach is extended to account for the correlation between replicate measures of the covariate. Using the replicate data decreases the standard error of the parameter estimate for log(total REM) counts while maintaining the bias reduction of the estimate. We conclude that covariate measurement error and the correlation between replicates can affect results in a Cox model analysis and should be accounted for. In the depression data, these methods render comparable results that have less bias than the results when measurement error is ignored.

Application and validation of Cox regression models in a single-center series of double kidney transplantation.

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Santori, G; Fontana, I; Bertocchi, M; Gasloli, G; Magoni Rossi, A; Tagliamacco, A; Barocci, S; Nocera, A; Valente, U

2010-05-01

A useful approach to reduce the number of discarded marginal kidneys and to increase the nephron mass is double kidney transplantation (DKT). In this study, we retrospectively evaluated the potential predictors for patient and graft survival in a single-center series of 59 DKT procedures performed between April 21, 1999, and September 21, 2008. The kidney recipients of mean age 63.27 +/- 5.17 years included 16 women (27%) and 43 men (73%). The donors of mean age 69.54 +/- 7.48 years included 32 women (54%) and 27 men (46%). The mean posttransplant dialysis time was 2.37 +/- 3.61 days. The mean hospitalization was 20.12 +/- 13.65 days. Average serum creatinine (SCr) at discharge was 1.5 +/- 0.59 mg/dL. In view of the limited numbers of recipient deaths (n = 4) and graft losses (n = 8) that occurred in our series, the proportional hazards assumption for each Cox regression model with P DKT (P = .043), and SCr 6 months post-DKT (P = .017). All significant univariate models for graft survival passed the Schoenfeld test. A final multivariate model retained SCr at 6 months (beta = 1.746, P = .042) and donor SCr (beta = .767, P = .090). In our analysis, SCr at 6 months seemed to emerge from both univariate and multivariate Cox models as a potential predictor of graft survival among DKT. Multicenter studies with larger recipient populations and more graft losses should be performed to confirm our findings. Copyright (c) 2010 Elsevier Inc. All rights reserved.

Bayesian inference for multivariate meta-analysis Box-Cox transformation models for individual patient data with applications to evaluation of cholesterol-lowering drugs.

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Kim, Sungduk; Chen, Ming-Hui; Ibrahim, Joseph G; Shah, Arvind K; Lin, Jianxin

2013-10-15

In this paper, we propose a class of Box-Cox transformation regression models with multidimensional random effects for analyzing multivariate responses for individual patient data in meta-analysis. Our modeling formulation uses a multivariate normal response meta-analysis model with multivariate random effects, in which each response is allowed to have its own Box-Cox transformation. Prior distributions are specified for the Box-Cox transformation parameters as well as the regression coefficients in this complex model, and the deviance information criterion is used to select the best transformation model. Because the model is quite complex, we develop a novel Monte Carlo Markov chain sampling scheme to sample from the joint posterior of the parameters. This model is motivated by a very rich dataset comprising 26 clinical trials involving cholesterol-lowering drugs where the goal is to jointly model the three-dimensional response consisting of low density lipoprotein cholesterol (LDL-C), high density lipoprotein cholesterol (HDL-C), and triglycerides (TG) (LDL-C, HDL-C, TG). Because the joint distribution of (LDL-C, HDL-C, TG) is not multivariate normal and in fact quite skewed, a Box-Cox transformation is needed to achieve normality. In the clinical literature, these three variables are usually analyzed univariately; however, a multivariate approach would be more appropriate because these variables are correlated with each other. We carry out a detailed analysis of these data by using the proposed methodology. Copyright © 2013 John Wiley & Sons, Ltd.

Bayesian inference for multivariate meta-analysis Box-Cox transformation models for individual patient data with applications to evaluation of cholesterol lowering drugs

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Kim, Sungduk; Chen, Ming-Hui; Ibrahim, Joseph G.; Shah, Arvind K.; Lin, Jianxin

2013-01-01

In this paper, we propose a class of Box-Cox transformation regression models with multidimensional random effects for analyzing multivariate responses for individual patient data (IPD) in meta-analysis. Our modeling formulation uses a multivariate normal response meta-analysis model with multivariate random effects, in which each response is allowed to have its own Box-Cox transformation. Prior distributions are specified for the Box-Cox transformation parameters as well as the regression coefficients in this complex model, and the Deviance Information Criterion (DIC) is used to select the best transformation model. Since the model is quite complex, a novel Monte Carlo Markov chain (MCMC) sampling scheme is developed to sample from the joint posterior of the parameters. This model is motivated by a very rich dataset comprising 26 clinical trials involving cholesterol lowering drugs where the goal is to jointly model the three dimensional response consisting of Low Density Lipoprotein Cholesterol (LDL-C), High Density Lipoprotein Cholesterol (HDL-C), and Triglycerides (TG) (LDL-C, HDL-C, TG). Since the joint distribution of (LDL-C, HDL-C, TG) is not multivariate normal and in fact quite skewed, a Box-Cox transformation is needed to achieve normality. In the clinical literature, these three variables are usually analyzed univariately: however, a multivariate approach would be more appropriate since these variables are correlated with each other. A detailed analysis of these data is carried out using the proposed methodology. PMID:23580436

A Comparative Study of Cox Regression vs. Log-Logistic ...

African Journals Online (AJOL)

Colorectal cancer is common and lethal disease with different incidence rate in different parts of the world which is taken into account as the third cause of cancer-related deaths. In the present study, using non-parametric Cox model and parametric Log-logistic model, factors influencing survival of patients with colorectal ...

Immunohistochemical and morphometric evaluation of COX 1 and COX-2 in the remodeled lung in idiopathic pulmonary fibrosis and systemic sclerosis

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Edwin Roger Parra

2013-12-01

Full Text Available OBJECTIVE: To study the expression of COX-1 and COX-2 in the remodeled lung in systemic sclerosis (SSc and idiopathic pulmonary fibrosis (IPF patients, correlating that expression with patient survival.METHODS: We examined open lung biopsy specimens from 24 SSc patients and 30 IPF patients, using normal lung tissue as a control. The histological patterns included fibrotic nonspecific interstitial pneumonia (NSIP in SSc patients and usual interstitial pneumonia (UIP in IPF patients. We used immunohistochemistry and histomorphometry to evaluate the expression of COX-1 and COX-2 in alveolar septa, vessels, and bronchioles. We then correlated that expression with pulmonary function test results and evaluated its impact on patient survival.RESULTS: The expression of COX-1 and COX-2 in alveolar septa was significantly higher in IPF-UIP and SSc-NSIP lung tissue than in the control tissue. No difference was found between IPF-UIP and SSc-NSIP tissue regarding COX-1 and COX-2 expression. Multivariate analysis based on the Cox regression model showed that the factors associated with a low risk of death were younger age, high DLCO/alveolar volume, IPF, and high COX-1 expression in alveolar septa, whereas those associated with a high risk of death were advanced age, low DLCO/alveolar volume, SSc (with NSIP, and low COX-1 expression in alveolar septa.CONCLUSIONS: Our findings suggest that strategies aimed at preventing low COX-1 synthesis will have a greater impact on SSc, whereas those aimed at preventing high COX-2 synthesis will have a greater impact on IPF. However, prospective randomized clinical trials are needed in order to confirm that.

Exploring QSAR with E-state index: selectivity requirements for COX-2 versus COX-1 binding of terphenyl methyl sulfones and sulfonamides.

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Chakraborty, Santanu; Sengupta, Chandana; Roy, Kunal

2004-09-20

An attempt has been made to explore selectivity requirements for cyclooxygenase-2 (COX-2) versus cyclooxygenase-1 (COX-1) binding of terphenyl methyl sulfones and sulfonamides using electrotopological state (E-state) index and suitable indicator parameters. Multiple linear regression analyses produced statistically acceptable equations: the best relation based on 'all-possible-subsets regression' for COX-1 binding (n=18) showed predicted variance and explained variance of 0.675 and 0.777, respectively, while in case of the best equation for COX-2 binding (n=38), these values rose to 0.842 and 0.874, respectively. For the selectivity relation (n=17), predicted variance and explained variance values were 0.601 and 0.687, respectively. Based on the results of the analyses, three important sites have been suggested: sites A (methylsulfonyl or aminosulfonyl moiety), B (central phenyl ring), and C (terminal phenyl ring containing different substituents). All three sites are important for COX-2 binding while sites B and C are important for COX-1 binding. For COX-2 selectivity, only site C plays an important role. The study shows the utility of E-state index in developing statistically acceptable model having direct physicochemical significance.

Methodological comparison of marginal structural model, time-varying Cox regression, and propensity score methods: the example of antidepressant use and the risk of hip fracture.

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Ali, M Sanni; Groenwold, Rolf H H; Belitser, Svetlana V; Souverein, Patrick C; Martín, Elisa; Gatto, Nicolle M; Huerta, Consuelo; Gardarsdottir, Helga; Roes, Kit C B; Hoes, Arno W; de Boer, Antonius; Klungel, Olaf H

2016-03-01

Observational studies including time-varying treatments are prone to confounding. We compared time-varying Cox regression analysis, propensity score (PS) methods, and marginal structural models (MSMs) in a study of antidepressant [selective serotonin reuptake inhibitors (SSRIs)] use and the risk of hip fracture. A cohort of patients with a first prescription for antidepressants (SSRI or tricyclic antidepressants) was extracted from the Dutch Mondriaan and Spanish Base de datos para la Investigación Farmacoepidemiológica en Atención Primaria (BIFAP) general practice databases for the period 2001-2009. The net (total) effect of SSRI versus no SSRI on the risk of hip fracture was estimated using time-varying Cox regression, stratification and covariate adjustment using the PS, and MSM. In MSM, censoring was accounted for by inverse probability of censoring weights. The crude hazard ratio (HR) of SSRI use versus no SSRI use on hip fracture was 1.75 (95%CI: 1.12, 2.72) in Mondriaan and 2.09 (1.89, 2.32) in BIFAP. After confounding adjustment using time-varying Cox regression, stratification, and covariate adjustment using the PS, HRs increased in Mondriaan [2.59 (1.63, 4.12), 2.64 (1.63, 4.25), and 2.82 (1.63, 4.25), respectively] and decreased in BIFAP [1.56 (1.40, 1.73), 1.54 (1.39, 1.71), and 1.61 (1.45, 1.78), respectively]. MSMs with stabilized weights yielded HR 2.15 (1.30, 3.55) in Mondriaan and 1.63 (1.28, 2.07) in BIFAP when accounting for censoring and 2.13 (1.32, 3.45) in Mondriaan and 1.66 (1.30, 2.12) in BIFAP without accounting for censoring. In this empirical study, differences between the different methods to control for time-dependent confounding were small. The observed differences in treatment effect estimates between the databases are likely attributable to different confounding information in the datasets, illustrating that adequate information on (time-varying) confounding is crucial to prevent bias. Copyright © 2016 John Wiley & Sons, Ltd.

QSAR Modeling of COX -2 Inhibitory Activity of Some Dihydropyridine and Hydroquinoline Derivatives Using Multiple Linear Regression (MLR) Method.

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Akbari, Somaye; Zebardast, Tannaz; Zarghi, Afshin; Hajimahdi, Zahra

2017-01-01

COX-2 inhibitory activities of some 1,4-dihydropyridine and 5-oxo-1,4,5,6,7,8-hexahydroquinoline derivatives were modeled by quantitative structure-activity relationship (QSAR) using stepwise-multiple linear regression (SW-MLR) method. The built model was robust and predictive with correlation coefficient (R 2 ) of 0.972 and 0.531 for training and test groups, respectively. The quality of the model was evaluated by leave-one-out (LOO) cross validation (LOO correlation coefficient (Q 2 ) of 0.943) and Y-randomization. We also employed a leverage approach for the defining of applicability domain of model. Based on QSAR models results, COX-2 inhibitory activity of selected data set had correlation with BEHm6 (highest eigenvalue n. 6 of Burden matrix/weighted by atomic masses), Mor03u (signal 03/unweighted) and IVDE (Mean information content on the vertex degree equality) descriptors which derived from their structures.

Cox-nnet: An artificial neural network method for prognosis prediction of high-throughput omics data.

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Ching, Travers; Zhu, Xun; Garmire, Lana X

2018-04-01

Artificial neural networks (ANN) are computing architectures with many interconnections of simple neural-inspired computing elements, and have been applied to biomedical fields such as imaging analysis and diagnosis. We have developed a new ANN framework called Cox-nnet to predict patient prognosis from high throughput transcriptomics data. In 10 TCGA RNA-Seq data sets, Cox-nnet achieves the same or better predictive accuracy compared to other methods, including Cox-proportional hazards regression (with LASSO, ridge, and mimimax concave penalty), Random Forests Survival and CoxBoost. Cox-nnet also reveals richer biological information, at both the pathway and gene levels. The outputs from the hidden layer node provide an alternative approach for survival-sensitive dimension reduction. In summary, we have developed a new method for accurate and efficient prognosis prediction on high throughput data, with functional biological insights. The source code is freely available at https://github.com/lanagarmire/cox-nnet.

Regression analysis by example

CERN Document Server

Chatterjee, Samprit

2012-01-01

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

Multiple Imputation of a Randomly Censored Covariate Improves Logistic Regression Analysis.

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Atem, Folefac D; Qian, Jing; Maye, Jacqueline E; Johnson, Keith A; Betensky, Rebecca A

2016-01-01

Randomly censored covariates arise frequently in epidemiologic studies. The most commonly used methods, including complete case and single imputation or substitution, suffer from inefficiency and bias. They make strong parametric assumptions or they consider limit of detection censoring only. We employ multiple imputation, in conjunction with semi-parametric modeling of the censored covariate, to overcome these shortcomings and to facilitate robust estimation. We develop a multiple imputation approach for randomly censored covariates within the framework of a logistic regression model. We use the non-parametric estimate of the covariate distribution or the semiparametric Cox model estimate in the presence of additional covariates in the model. We evaluate this procedure in simulations, and compare its operating characteristics to those from the complete case analysis and a survival regression approach. We apply the procedures to an Alzheimer's study of the association between amyloid positivity and maternal age of onset of dementia. Multiple imputation achieves lower standard errors and higher power than the complete case approach under heavy and moderate censoring and is comparable under light censoring. The survival regression approach achieves the highest power among all procedures, but does not produce interpretable estimates of association. Multiple imputation offers a favorable alternative to complete case analysis and ad hoc substitution methods in the presence of randomly censored covariates within the framework of logistic regression.

Replica analysis of overfitting in regression models for time-to-event data

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Coolen, A. C. C.; Barrett, J. E.; Paga, P.; Perez-Vicente, C. J.

2017-09-01

Overfitting, which happens when the number of parameters in a model is too large compared to the number of data points available for determining these parameters, is a serious and growing problem in survival analysis. While modern medicine presents us with data of unprecedented dimensionality, these data cannot yet be used effectively for clinical outcome prediction. Standard error measures in maximum likelihood regression, such as p-values and z-scores, are blind to overfitting, and even for Cox’s proportional hazards model (the main tool of medical statisticians), one finds in literature only rules of thumb on the number of samples required to avoid overfitting. In this paper we present a mathematical theory of overfitting in regression models for time-to-event data, which aims to increase our quantitative understanding of the problem and provide practical tools with which to correct regression outcomes for the impact of overfitting. It is based on the replica method, a statistical mechanical technique for the analysis of heterogeneous many-variable systems that has been used successfully for several decades in physics, biology, and computer science, but not yet in medical statistics. We develop the theory initially for arbitrary regression models for time-to-event data, and verify its predictions in detail for the popular Cox model.

Bayesian analysis of log Gaussian Cox processes for disease mapping

DEFF Research Database (Denmark)

Benes, Viktor; Bodlák, Karel; Møller, Jesper

We consider a data set of locations where people in Central Bohemia have been infected by tick-borne encephalitis, and where population census data and covariates concerning vegetation and altitude are available. The aims are to estimate the risk map of the disease and to study the dependence...... of the risk on the covariates. Instead of using the common area level approaches we consider a Bayesian analysis for a log Gaussian Cox point process with covariates. Posterior characteristics for a discretized version of the log Gaussian Cox process are computed using markov chain Monte Carlo methods...

The Covariance Adjustment Approaches for Combining Incomparable Cox Regressions Caused by Unbalanced Covariates Adjustment: A Multivariate Meta-Analysis Study

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Tania Dehesh

2015-01-01

Full Text Available Background. Univariate meta-analysis (UM procedure, as a technique that provides a single overall result, has become increasingly popular. Neglecting the existence of other concomitant covariates in the models leads to loss of treatment efficiency. Our aim was proposing four new approximation approaches for the covariance matrix of the coefficients, which is not readily available for the multivariate generalized least square (MGLS method as a multivariate meta-analysis approach. Methods. We evaluated the efficiency of four new approaches including zero correlation (ZC, common correlation (CC, estimated correlation (EC, and multivariate multilevel correlation (MMC on the estimation bias, mean square error (MSE, and 95% probability coverage of the confidence interval (CI in the synthesis of Cox proportional hazard models coefficients in a simulation study. Result. Comparing the results of the simulation study on the MSE, bias, and CI of the estimated coefficients indicated that MMC approach was the most accurate procedure compared to EC, CC, and ZC procedures. The precision ranking of the four approaches according to all above settings was MMC ≥ EC ≥ CC ≥ ZC. Conclusion. This study highlights advantages of MGLS meta-analysis on UM approach. The results suggested the use of MMC procedure to overcome the lack of information for having a complete covariance matrix of the coefficients.

The Covariance Adjustment Approaches for Combining Incomparable Cox Regressions Caused by Unbalanced Covariates Adjustment: A Multivariate Meta-Analysis Study.

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Dehesh, Tania; Zare, Najaf; Ayatollahi, Seyyed Mohammad Taghi

2015-01-01

Univariate meta-analysis (UM) procedure, as a technique that provides a single overall result, has become increasingly popular. Neglecting the existence of other concomitant covariates in the models leads to loss of treatment efficiency. Our aim was proposing four new approximation approaches for the covariance matrix of the coefficients, which is not readily available for the multivariate generalized least square (MGLS) method as a multivariate meta-analysis approach. We evaluated the efficiency of four new approaches including zero correlation (ZC), common correlation (CC), estimated correlation (EC), and multivariate multilevel correlation (MMC) on the estimation bias, mean square error (MSE), and 95% probability coverage of the confidence interval (CI) in the synthesis of Cox proportional hazard models coefficients in a simulation study. Comparing the results of the simulation study on the MSE, bias, and CI of the estimated coefficients indicated that MMC approach was the most accurate procedure compared to EC, CC, and ZC procedures. The precision ranking of the four approaches according to all above settings was MMC ≥ EC ≥ CC ≥ ZC. This study highlights advantages of MGLS meta-analysis on UM approach. The results suggested the use of MMC procedure to overcome the lack of information for having a complete covariance matrix of the coefficients.

Maximum likelihood estimation for Cox's regression model under nested case-control sampling

DEFF Research Database (Denmark)

Scheike, Thomas; Juul, Anders

2004-01-01

Nested case-control sampling is designed to reduce the costs of large cohort studies. It is important to estimate the parameters of interest as efficiently as possible. We present a new maximum likelihood estimator (MLE) for nested case-control sampling in the context of Cox's proportional hazard...

Statistical power to detect violation of the proportional hazards assumption when using the Cox regression model.

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Austin, Peter C

2018-01-01

The use of the Cox proportional hazards regression model is widespread. A key assumption of the model is that of proportional hazards. Analysts frequently test the validity of this assumption using statistical significance testing. However, the statistical power of such assessments is frequently unknown. We used Monte Carlo simulations to estimate the statistical power of two different methods for detecting violations of this assumption. When the covariate was binary, we found that a model-based method had greater power than a method based on cumulative sums of martingale residuals. Furthermore, the parametric nature of the distribution of event times had an impact on power when the covariate was binary. Statistical power to detect a strong violation of the proportional hazards assumption was low to moderate even when the number of observed events was high. In many data sets, power to detect a violation of this assumption is likely to be low to modest.

The association of four common polymorphisms from four candidate genes (COX-1, COX-2, ITGA2B, ITGA2 with aspirin insensitivity: a meta-analysis.

Directory of Open Access Journals (Sweden)

Zhiyuan Weng

Full Text Available OBJECTIVE: Evidence is mounting suggesting that a strong genetic component underlies aspirin insensitivity. To generate more information, we aimed to evaluate the association of four common polymorphisms (rs3842787, rs20417, rs201184269, rs1126643 from four candidate genes (COX-1, COX-2, ITGA2B, ITGA2 with aspirin insensitivity via a meta-analysis. METHODS AND RESULTS: In total, there were 4 (353/595, 6 (344/698, 10 (588/878 and 7 (209/676 articles (patients/controls qualified for rs3842787, rs20417, rs20118426 and rs1126643, respectively. The data were extracted in duplicate and analyzed by STATA software (Version 11.2. The risk estimate was expressed as odds ratio (OR and 95% confidence interval (95% CI. Analyses of the full data set indicated significant associations of rs20417 (OR; 95% CI; P: 1.86; 1.44-2.41; <0.0005 and rs1126643 (2.37; 1.44-3.89; 0.001 with aspirin insensitivity under allelic model. In subgroup analyses, the risk estimate for rs1126643 was greatly potentiated among patients with aspirin semi-resistance relative to those with aspirin resistance, especially under dominant model (aspirin semi-resistance: 5.44; 1.42-20.83; 0.013 versus aspirin resistance: 1.96; 1.07-3.6; 0.03. Further grouping articles by ethnicity observed a stronger prediction of all, but rs20417, examined polymorphisms for aspirin insensitivity in Chinese than in Caucasians. Finally, meta-regression analyses observed that the differences in percentage of coronary artery disease (P = 0.034 and averaged platelet numbers (P = 0.012 between two groups explained a large part of heterogeneity for rs20417 and rs1126643, respectively. CONCLUSION: Our findings provide strong evidence that COX-2 and ITGA2 genetic defects might increase the risk of having aspirin insensitivity, especially for aspirin semi-resistance and in Chinese populations.

Geometric anisotropic spatial point pattern analysis and Cox processes

DEFF Research Database (Denmark)

Møller, Jesper; Toftaker, Håkon

. In particular we study Cox process models with an elliptical pair correlation function, including shot noise Cox processes and log Gaussian Cox processes, and we develop estimation procedures using summary statistics and Bayesian methods. Our methodology is illustrated on real and synthetic datasets of spatial...

Proteomic Analysis Shows Constitutive Secretion of MIF and p53-associated Activity of COX-2−/− Lung Fibroblasts

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Mandar Dave

2017-12-01

Full Text Available The differential expression of two closelyassociated cyclooxygenase isozymes, COX-1 and COX-2, exhibited functions beyond eicosanoid metabolism. We hypothesized that COX-1 or COX-2 knockout lung fibroblasts may display altered protein profiles which may allow us to further differentiate the functional roles of these isozymes at the molecular level. Proteomic analysis shows constitutive production of macrophage migration inhibitory factor (MIF in lung fibroblasts derived from COX-2−/− but not wild-type (WT or COX-1−/− mice. MIF was spontaneously released in high levels into the extracellular milieu of COX2−/− fibroblasts seemingly from the preformed intracellular stores, with no change in the basal gene expression of MIF. The secretion and regulation of MIF in COX-2−/− was “prostaglandin-independent.” GO analysis showed that concurrent with upregulation of MIF, there is a significant surge in expression of genes related to fibroblast growth, FK506 binding proteins, and isomerase activity in COX-2−/− cells. Furthermore, COX-2−/− fibroblasts also exhibit a significant increase in transcriptional activity of various regulators, antagonists, and co-modulators of p53, as well as in the expression of oncogenes and related transcripts. Integrative Oncogenomics Cancer Browser (IntroGen analysis shows downregulation of COX-2 and amplification of MIF and/or p53 activity during development of glioblastomas, ependymoma, and colon adenomas. These data indicate the functional role of the MIF-COX-p53 axis in inflammation and cancer at the genomic and proteomic levels in COX-2-ablated cells. This systematic analysis not only shows the proinflammatory state but also unveils a molecular signature of a pro-oncogenic state of COX-1 in COX-2 ablated cells.

A SAS-macro for estimation of the cumulative incidence using Poisson regression

DEFF Research Database (Denmark)

Waltoft, Berit Lindum

2009-01-01

the hazard rates, and the hazard rates are often estimated by the Cox regression. This procedure may not be suitable for large studies due to limited computer resources. Instead one uses Poisson regression, which approximates the Cox regression. Rosthøj et al. presented a SAS-macro for the estimation...... of the cumulative incidences based on the Cox regression. I present the functional form of the probabilities and variances when using piecewise constant hazard rates and a SAS-macro for the estimation using Poisson regression. The use of the macro is demonstrated through examples and compared to the macro presented...

COX-2 and PPAR-γ confer cannabidiol-induced apoptosis of human lung cancer cells.

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Ramer, Robert; Heinemann, Katharina; Merkord, Jutta; Rohde, Helga; Salamon, Achim; Linnebacher, Michael; Hinz, Burkhard

2013-01-01

The antitumorigenic mechanism of cannabidiol is still controversial. This study investigates the role of COX-2 and PPAR-γ in cannabidiol's proapoptotic and tumor-regressive action. In lung cancer cell lines (A549, H460) and primary cells from a patient with lung cancer, cannabidiol elicited decreased viability associated with apoptosis. Apoptotic cell death by cannabidiol was suppressed by NS-398 (COX-2 inhibitor), GW9662 (PPAR-γ antagonist), and siRNA targeting COX-2 and PPAR-γ. Cannabidiol-induced apoptosis was paralleled by upregulation of COX-2 and PPAR-γ mRNA and protein expression with a maximum induction of COX-2 mRNA after 8 hours and continuous increases of PPAR-γ mRNA when compared with vehicle. In response to cannabidiol, tumor cell lines exhibited increased levels of COX-2-dependent prostaglandins (PG) among which PGD(2) and 15-deoxy-Δ(12,14)-PGJ(2) (15d-PGJ(2)) caused a translocation of PPAR-γ to the nucleus and induced a PPAR-γ-dependent apoptotic cell death. Moreover, in A549-xenografted nude mice, cannabidiol caused upregulation of COX-2 and PPAR-γ in tumor tissue and tumor regression that was reversible by GW9662. Together, our data show a novel proapoptotic mechanism of cannabidiol involving initial upregulation of COX-2 and PPAR-γ and a subsequent nuclear translocation of PPAR-γ by COX-2-dependent PGs.

A random effects meta-analysis model with Box-Cox transformation.

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Yamaguchi, Yusuke; Maruo, Kazushi; Partlett, Christopher; Riley, Richard D

2017-07-19

In a random effects meta-analysis model, true treatment effects for each study are routinely assumed to follow a normal distribution. However, normality is a restrictive assumption and the misspecification of the random effects distribution may result in a misleading estimate of overall mean for the treatment effect, an inappropriate quantification of heterogeneity across studies and a wrongly symmetric prediction interval. We focus on problems caused by an inappropriate normality assumption of the random effects distribution, and propose a novel random effects meta-analysis model where a Box-Cox transformation is applied to the observed treatment effect estimates. The proposed model aims to normalise an overall distribution of observed treatment effect estimates, which is sum of the within-study sampling distributions and the random effects distribution. When sampling distributions are approximately normal, non-normality in the overall distribution will be mainly due to the random effects distribution, especially when the between-study variation is large relative to the within-study variation. The Box-Cox transformation addresses this flexibly according to the observed departure from normality. We use a Bayesian approach for estimating parameters in the proposed model, and suggest summarising the meta-analysis results by an overall median, an interquartile range and a prediction interval. The model can be applied for any kind of variables once the treatment effect estimate is defined from the variable. A simulation study suggested that when the overall distribution of treatment effect estimates are skewed, the overall mean and conventional I 2 from the normal random effects model could be inappropriate summaries, and the proposed model helped reduce this issue. We illustrated the proposed model using two examples, which revealed some important differences on summary results, heterogeneity measures and prediction intervals from the normal random effects model. The

A random effects meta-analysis model with Box-Cox transformation

Directory of Open Access Journals (Sweden)

Yusuke Yamaguchi

2017-07-01

Full Text Available Abstract Background In a random effects meta-analysis model, true treatment effects for each study are routinely assumed to follow a normal distribution. However, normality is a restrictive assumption and the misspecification of the random effects distribution may result in a misleading estimate of overall mean for the treatment effect, an inappropriate quantification of heterogeneity across studies and a wrongly symmetric prediction interval. Methods We focus on problems caused by an inappropriate normality assumption of the random effects distribution, and propose a novel random effects meta-analysis model where a Box-Cox transformation is applied to the observed treatment effect estimates. The proposed model aims to normalise an overall distribution of observed treatment effect estimates, which is sum of the within-study sampling distributions and the random effects distribution. When sampling distributions are approximately normal, non-normality in the overall distribution will be mainly due to the random effects distribution, especially when the between-study variation is large relative to the within-study variation. The Box-Cox transformation addresses this flexibly according to the observed departure from normality. We use a Bayesian approach for estimating parameters in the proposed model, and suggest summarising the meta-analysis results by an overall median, an interquartile range and a prediction interval. The model can be applied for any kind of variables once the treatment effect estimate is defined from the variable. Results A simulation study suggested that when the overall distribution of treatment effect estimates are skewed, the overall mean and conventional I 2 from the normal random effects model could be inappropriate summaries, and the proposed model helped reduce this issue. We illustrated the proposed model using two examples, which revealed some important differences on summary results, heterogeneity measures and

Limitations of Cox Proportional Hazards Analysis in Mortality Prediction of Patients with Acute Coronary Syndrome

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Babińska Magdalena

2015-12-01

Full Text Available The aim of this study was to evaluate the possibility of incorrect assessment of mortality risk factors in a group of patients affected by acute coronary syndrome, due to the lack of hazard proportionality in the Cox regression model. One hundred and fifty consecutive patients with acute coronary syndrome (ACS and no age limit were enrolled. Univariable and multivariable Cox proportional hazard analyses were performed. The proportional hazard assumptions were verified using Schoenfeld residuals, χ2 test and rank correlation coefficient t between residuals and time. In the total group of 150 patients, 33 (22.0% deaths from any cause were registered in the follow-up time period of 64 months. The non-survivors were significantly older and had increased prevalence of diabetes and erythrocyturia, longer history of coronary artery disease, higher concentrations of serum creatinine, cystatin C, uric acid, glucose, C-reactive protein (CRP, homocysteine and B-type natriuretic peptide (NT-proBNP, and lower concentrations of serum sodium. No significant differences in echocardiography parameters were observed between groups. The following factors were risk of death factors and fulfilled the proportional hazard assumption in the univariable model: smoking, occurrence of diabetes and anaemia, duration of coronary artery disease, and abnormal serum concentrations of uric acid, sodium, homocysteine, cystatin C and NT-proBNP, while in the multivariable model, the risk of death factors were: smoking and elevated concentrations of homocysteine and NT-proBNP. The study has demonstrated that violation of the proportional hazard assumption in the Cox regression model may lead to creating a false model that does not include only time-independent predictive factors.

Box-Cox transformation of left-censored data with application to the analysis of coronary artery calcification and pharmacokinetic data.

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Han, Cong; Kronmal, Richard

2004-12-15

Box-Cox transformation is investigated for regression models for left-censored data. Examples are provided using coronary calcification data from the Multi-Ethnic Study of Atherosclerosis and pharmacokinetic data of a nicotine nasal spray. Copyright 2004 John Wiley & Sons, Ltd.

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

NARCIS (Netherlands)

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

2008-01-01

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

ORACLE INEQUALITIES FOR THE LASSO IN THE COX MODEL.

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Huang, Jian; Sun, Tingni; Ying, Zhiliang; Yu, Yi; Zhang, Cun-Hui

2013-06-01

We study the absolute penalized maximum partial likelihood estimator in sparse, high-dimensional Cox proportional hazards regression models where the number of time-dependent covariates can be larger than the sample size. We establish oracle inequalities based on natural extensions of the compatibility and cone invertibility factors of the Hessian matrix at the true regression coefficients. Similar results based on an extension of the restricted eigenvalue can be also proved by our method. However, the presented oracle inequalities are sharper since the compatibility and cone invertibility factors are always greater than the corresponding restricted eigenvalue. In the Cox regression model, the Hessian matrix is based on time-dependent covariates in censored risk sets, so that the compatibility and cone invertibility factors, and the restricted eigenvalue as well, are random variables even when they are evaluated for the Hessian at the true regression coefficients. Under mild conditions, we prove that these quantities are bounded from below by positive constants for time-dependent covariates, including cases where the number of covariates is of greater order than the sample size. Consequently, the compatibility and cone invertibility factors can be treated as positive constants in our oracle inequalities.

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

DEFF Research Database (Denmark)

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

1989-01-01

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

Principal component regression analysis with SPSS.

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

2003-06-01

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

Comment on "Why reduced-form regression models of health effects versus exposures should not replace QRA: livestock production and infant mortality as an example," by Louis Anthony (Tony) Cox, Jr., Risk Analysis 2009, Vol. 29, No. 12.

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Sneeringer, Stacy

2010-04-01

While a recent paper by Cox in this journal uses as its motivating factor the benefits of quantitative risk assessment, its content is entirely devoted to critiquing Sneeringer's article in the American Journal of Agricultural Economics. Cox's two main critiques of Sneeringer are fundamentally flawed and misrepresent the original article. Cox posits that Sneeringer did A and B, and then argues why A and B are incorrect. However, Sneeringer in fact did C and D; thus critiques of A and B are not applicable to Sneeringer's analysis.

Cox proportional hazards models have more statistical power than logistic regression models in cross-sectional genetic association studies

NARCIS (Netherlands)

van der Net, Jeroen B.; Janssens, A. Cecile J. W.; Eijkemans, Marinus J. C.; Kastelein, John J. P.; Sijbrands, Eric J. G.; Steyerberg, Ewout W.

2008-01-01

Cross-sectional genetic association studies can be analyzed using Cox proportional hazards models with age as time scale, if age at onset of disease is known for the cases and age at data collection is known for the controls. We assessed to what degree and under what conditions Cox proportional

A fast identification algorithm for Box-Cox transformation based radial basis function neural network.

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Hong, Xia

2006-07-01

In this letter, a Box-Cox transformation-based radial basis function (RBF) neural network is introduced using the RBF neural network to represent the transformed system output. Initially a fixed and moderate sized RBF model base is derived based on a rank revealing orthogonal matrix triangularization (QR decomposition). Then a new fast identification algorithm is introduced using Gauss-Newton algorithm to derive the required Box-Cox transformation, based on a maximum likelihood estimator. The main contribution of this letter is to explore the special structure of the proposed RBF neural network for computational efficiency by utilizing the inverse of matrix block decomposition lemma. Finally, the Box-Cox transformation-based RBF neural network, with good generalization and sparsity, is identified based on the derived optimal Box-Cox transformation and a D-optimality-based orthogonal forward regression algorithm. The proposed algorithm and its efficacy are demonstrated with an illustrative example in comparison with support vector machine regression.

Box-Cox transformation for QTL mapping.

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Yang, Runqing; Yi, Nengjun; Xu, Shizhong

2006-01-01

The maximum likelihood method of QTL mapping assumes that the phenotypic values of a quantitative trait follow a normal distribution. If the assumption is violated, some forms of transformation should be taken to make the assumption approximately true. The Box-Cox transformation is a general transformation method which can be applied to many different types of data. The flexibility of the Box-Cox transformation is due to a variable, called transformation factor, appearing in the Box-Cox formula. We developed a maximum likelihood method that treats the transformation factor as an unknown parameter, which is estimated from the data simultaneously along with the QTL parameters. The method makes an objective choice of data transformation and thus can be applied to QTL analysis for many different types of data. Simulation studies show that (1) Box-Cox transformation can substantially increase the power of QTL detection; (2) Box-Cox transformation can replace some specialized transformation methods that are commonly used in QTL mapping; and (3) applying the Box-Cox transformation to data already normally distributed does not harm the result.

Box-Cox transformation on dataset from compositional studies of archaeological potteries

International Nuclear Information System (INIS)

Santos, J.O.; Santana Reis, Michael; Silva, J.E.

2017-01-01

In archaeometric data set it was verified by statistical tests that some variables almost never follow a multivariate normal distribution using logarithmic transformation or other. This work presents a multivariate Box-Cox transformation for Mardia's and Royton's tests for a data set of fifty ceramic fragments from archaeological site Justino, Xingo, Brazil, and one clay sample collected near of the site. The samples were analyzed by instrumental neutron activation analysis, INAA. The study was made using companion to applied regression package from R software and was tested by Hotelling's T"2 statistics. (author)

Updating prognosis in primary biliary cirrhosis using a time-dependent Cox regression model. PBC1 and PBC2 trial groups

DEFF Research Database (Denmark)

Christensen, E; Altman, D G; Neuberger, J

1993-01-01

BACKGROUND: The precision of current prognostic models in primary biliary cirrhosis (PBC) is rather low, partly because they are based on data from just one time during the course of the disease. The aim of this study was to design a new, more precise prognostic model by incorporating follow......-up data in the development of the model. METHODS: We have performed Cox regression analyses with time-dependent variables in 237 PBC patients followed up regularly for up to 11 years. The validity of the obtained models was tested by comparing predicted and observed survival in 147 independent PBC...... patients followed for up to 6 years. RESULTS: In the obtained model the following time-dependent variables independently indicated a poor prognosis: high bilirubin, low albumin, ascites, gastrointestinal bleeding, and old age. When including histological variables, cirrhosis, central cholestasis, and low...

Hierarchical Neural Regression Models for Customer Churn Prediction

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Golshan Mohammadi

2013-01-01

Full Text Available As customers are the main assets of each industry, customer churn prediction is becoming a major task for companies to remain in competition with competitors. In the literature, the better applicability and efficiency of hierarchical data mining techniques has been reported. This paper considers three hierarchical models by combining four different data mining techniques for churn prediction, which are backpropagation artificial neural networks (ANN, self-organizing maps (SOM, alpha-cut fuzzy c-means (α-FCM, and Cox proportional hazards regression model. The hierarchical models are ANN + ANN + Cox, SOM + ANN + Cox, and α-FCM + ANN + Cox. In particular, the first component of the models aims to cluster data in two churner and nonchurner groups and also filter out unrepresentative data or outliers. Then, the clustered data as the outputs are used to assign customers to churner and nonchurner groups by the second technique. Finally, the correctly classified data are used to create Cox proportional hazards model. To evaluate the performance of the hierarchical models, an Iranian mobile dataset is considered. The experimental results show that the hierarchical models outperform the single Cox regression baseline model in terms of prediction accuracy, Types I and II errors, RMSE, and MAD metrics. In addition, the α-FCM + ANN + Cox model significantly performs better than the two other hierarchical models.

Cox1 mutation abrogates need for Cox23 in cytochrome c oxidase biogenesis

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Richard Dela Cruz

2016-06-01

Full Text Available Cox23 is a known conserved assembly factor for cytochrome c oxidase, although its role in cytochrome c oxidase (CcO biogenesis remains unresolved. To gain additional insights into its role, we isolated spontaneous suppressors of the respiratory growth defect in cox23∆ yeast cells. We recovered independent colonies that propagated on glycerol/lactate medium for cox23∆ cells at 37°C. We mapped these mutations to the mitochondrial genome and specifically to COX1 yielding an I101F substitution. The I101F Cox1 allele is a gain-of-function mutation enabling yeast to respire in the absence of Cox23. CcO subunit steady-state levels were restored with the I101F Cox1 suppressor mutation and oxygen consumption and CcO activity were likewise restored. Cells harboring the mitochondrial genome encoding I101F Cox1 were used to delete genes for other CcO assembly factors to test the specificity of the Cox1 mutation as a suppressor of cox23∆ cells. The Cox1 mutant allele fails to support respiratory growth in yeast lacking Cox17, Cox19, Coa1, Coa2, Cox14 or Shy1, demonstrating its specific suppressor activity for cox23∆ cells.

Introduction to the use of regression models in epidemiology.

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Bender, Ralf

2009-01-01

Regression modeling is one of the most important statistical techniques used in analytical epidemiology. By means of regression models the effect of one or several explanatory variables (e.g., exposures, subject characteristics, risk factors) on a response variable such as mortality or cancer can be investigated. From multiple regression models, adjusted effect estimates can be obtained that take the effect of potential confounders into account. Regression methods can be applied in all epidemiologic study designs so that they represent a universal tool for data analysis in epidemiology. Different kinds of regression models have been developed in dependence on the measurement scale of the response variable and the study design. The most important methods are linear regression for continuous outcomes, logistic regression for binary outcomes, Cox regression for time-to-event data, and Poisson regression for frequencies and rates. This chapter provides a nontechnical introduction to these regression models with illustrating examples from cancer research.

Polynomial regression analysis and significance test of the regression function

International Nuclear Information System (INIS)

Gao Zhengming; Zhao Juan; He Shengping

2012-01-01

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

Applied regression analysis a research tool

CERN Document Server

Pantula, Sastry; Dickey, David

1998-01-01

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

Assessing outcomes of large-scale public health interventions in the absence of baseline data using a mixture of Cox and binomial regressions

Science.gov (United States)

2014-01-01

Background Large-scale public health interventions with rapid scale-up are increasingly being implemented worldwide. Such implementation allows for a large target population to be reached in a short period of time. But when the time comes to investigate the effectiveness of these interventions, the rapid scale-up creates several methodological challenges, such as the lack of baseline data and the absence of control groups. One example of such an intervention is Avahan, the India HIV/AIDS initiative of the Bill & Melinda Gates Foundation. One question of interest is the effect of Avahan on condom use by female sex workers with their clients. By retrospectively reconstructing condom use and sex work history from survey data, it is possible to estimate how condom use rates evolve over time. However formal inference about how this rate changes at a given point in calendar time remains challenging. Methods We propose a new statistical procedure based on a mixture of binomial regression and Cox regression. We compare this new method to an existing approach based on generalized estimating equations through simulations and application to Indian data. Results Both methods are unbiased, but the proposed method is more powerful than the existing method, especially when initial condom use is high. When applied to the Indian data, the new method mostly agrees with the existing method, but seems to have corrected some implausible results of the latter in a few districts. We also show how the new method can be used to analyze the data of all districts combined. Conclusions The use of both methods can be recommended for exploratory data analysis. However for formal statistical inference, the new method has better power. PMID:24397563

Improving Your Data Transformations: Applying the Box-Cox Transformation

Directory of Open Access Journals (Sweden)

Jason W. Osborne

2010-10-01

Full Text Available Many of us in the social sciences deal with data that do not conform to assumptions of normality and/or homoscedasticity/homogeneity of variance. Some research has shown that parametric tests (e.g., multiple regression, ANOVA can be robust to modest violations of these assumptions. Yet the reality is that almost all analyses (even nonparametric tests benefit from improved the normality of variables, particularly where substantial non-normality is present. While many are familiar with select traditional transformations (e.g., square root, log, inverse for improving normality, the Box-Cox transformation (Box & Cox, 1964 represents a family of power transformations that incorporates and extends the traditional options to help researchers easily find the optimal normalizing transformation for each variable. As such, Box-Cox represents a potential best practice where normalizing data or equalizing variance is desired. This paper briefly presents an overview of traditional normalizing transformations and how Box-Cox incorporates, extends, and improves on these traditional approaches to normalizing data. Examples of applications are presented, and details of how to automate and use this technique in SPSS and SAS are included.

Regression Analysis by Example. 5th Edition

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Chatterjee, Samprit; Hadi, Ali S.

2012-01-01

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

Marginal regression analysis of recurrent events with coarsened censoring times.

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Hu, X Joan; Rosychuk, Rhonda J

2016-12-01

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

riskRegression

DEFF Research Database (Denmark)

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

2017-01-01

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

Analysis of the cytochrome c oxidase subunit II (COX2) gene in giant panda, Ailuropoda melanoleuca.

Science.gov (United States)

Ling, S S; Zhu, Y; Lan, D; Li, D S; Pang, H Z; Wang, Y; Li, D Y; Wei, R P; Zhang, H M; Wang, C D; Hu, Y D

2017-01-23

The giant panda, Ailuropoda melanoleuca (Ursidae), has a unique bamboo-based diet; however, this low-energy intake has been sufficient to maintain the metabolic processes of this species since the fourth ice age. As mitochondria are the main sites for energy metabolism in animals, the protein-coding genes involved in mitochondrial respiratory chains, particularly cytochrome c oxidase subunit II (COX2), which is the rate-limiting enzyme in electron transfer, could play an important role in giant panda metabolism. Therefore, the present study aimed to isolate, sequence, and analyze the COX2 DNA from individuals kept at the Giant Panda Protection and Research Center, China, and compare these sequences with those of the other Ursidae family members. Multiple sequence alignment showed that the COX2 gene had three point mutations that defined three haplotypes, with 60% of the sequences corresponding to haplotype I. The neutrality tests revealed that the COX2 gene was conserved throughout evolution, and the maximum likelihood phylogenetic analysis, using homologous sequences from other Ursidae species, showed clustering of the COX2 sequences of giant pandas, suggesting that this gene evolved differently in them.

Regression analysis with categorized regression calibrated exposure: some interesting findings

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Hjartåker Anette

2006-07-01

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

Monitoring of Fasciola Species Contamination in Water Dropwort by cox1 Mitochondrial and ITS-2 rDNA Sequencing Analysis.

Science.gov (United States)

Choi, In-Wook; Kim, Hwang-Yong; Quan, Juan-Hua; Ryu, Jae-Gee; Sun, Rubing; Lee, Young-Ha

2015-10-01

Fascioliasis, a food-borne trematode zoonosis, is a disease primarily in cattle and sheep and occasionally in humans. Water dropwort (Oenanthe javanica), an aquatic perennial herb, is a common second intermediate host of Fasciola, and the fresh stems and leaves are widely used as a seasoning in the Korean diet. However, no information regarding Fasciola species contamination in water dropwort is available. Here, we collected 500 samples of water dropwort in 3 areas in Korea during February and March 2015, and the water dropwort contamination of Fasciola species was monitored by DNA sequencing analysis of the Fasciola hepatica and Fasciola gigantica specific mitochondrial cytochrome c oxidase subunit 1 (cox1) and nuclear ribosomal internal transcribed spacer 2 (ITS-2). Among the 500 samples assessed, the presence of F. hepatica cox1 and 1TS-2 markers were detected in 2 samples, and F. hepatica contamination was confirmed by sequencing analysis. The nucleotide sequences of cox1 PCR products from the 2 F. hepatica-contaminated samples were 96.5% identical to the F. hepatica cox1 sequences in GenBank, whereas F. gigantica cox1 sequences were 46.8% similar with the sequence detected from the cox1 positive samples. However, F. gigantica cox1 and ITS-2 markers were not detected by PCR in the 500 samples of water dropwort. Collectively, in this survey of the water dropwort contamination with Fasciola species, very low prevalence of F. hepatica contamination was detected in the samples.

Gaussian process regression analysis for functional data

CERN Document Server

Shi, Jian Qing

2011-01-01

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

COX-1 vs. COX-2 as a determinant of basal tone in the internal anal sphincter.

Science.gov (United States)

de Godoy, Márcio A F; Rattan, Neeru; Rattan, Satish

2009-02-01

Prostanoids, produced endogenously via cyclooxygenases (COXs), have been implicated in the sustained contraction of different smooth muscles. The two major types of COXs are COX-1 and COX-2. The COX subtype involved in the basal state of the internal anal sphincter (IAS) smooth muscle tone is not known. To identify the COX subtype, we examined the effect of COX-1- and COX-2-selective inhibitors, SC-560 and rofecoxib, respectively, on basal tone in the rat IAS. We also determined the effect of selective deletion of COX-1 and COX-2 genes (COX-1(-/-) and COX-2(-/-) mice) on basal tone in murine IAS. Our data show that SC-560 causes significantly more efficacious and potent concentration-dependent decreases in IAS tone than rofecoxib. In support of these data, significantly higher levels of COX-1 than COX-2 mRNA were found in the IAS. In addition, higher levels of COX-1 mRNA and protein were expressed in rat IAS than rectal smooth muscle. In wild-type mice, IAS tone was decreased 41.4 +/- 3.4% (mean +/- SE) by SC-560 (1 x 10(-5) M) and 5.4 +/- 2.2% by rofecoxib (P IAS from wild-type mice and significantly less (0.080 +/- 0.015 mN/mg) in the IAS from COX-1(-/-) mice (P IAS tone.

Regression and regression analysis time series prediction modeling on climate data of quetta, pakistan

International Nuclear Information System (INIS)

Jafri, Y.Z.; Kamal, L.

2007-01-01

Various statistical techniques was used on five-year data from 1998-2002 of average humidity, rainfall, maximum and minimum temperatures, respectively. The relationships to regression analysis time series (RATS) were developed for determining the overall trend of these climate parameters on the basis of which forecast models can be corrected and modified. We computed the coefficient of determination as a measure of goodness of fit, to our polynomial regression analysis time series (PRATS). The correlation to multiple linear regression (MLR) and multiple linear regression analysis time series (MLRATS) were also developed for deciphering the interdependence of weather parameters. Spearman's rand correlation and Goldfeld-Quandt test were used to check the uniformity or non-uniformity of variances in our fit to polynomial regression (PR). The Breusch-Pagan test was applied to MLR and MLRATS, respectively which yielded homoscedasticity. We also employed Bartlett's test for homogeneity of variances on a five-year data of rainfall and humidity, respectively which showed that the variances in rainfall data were not homogenous while in case of humidity, were homogenous. Our results on regression and regression analysis time series show the best fit to prediction modeling on climatic data of Quetta, Pakistan. (author)

A new semi-supervised learning model combined with Cox and SP-AFT models in cancer survival analysis.

Science.gov (United States)

Chai, Hua; Li, Zi-Na; Meng, De-Yu; Xia, Liang-Yong; Liang, Yong

2017-10-12

Gene selection is an attractive and important task in cancer survival analysis. Most existing supervised learning methods can only use the labeled biological data, while the censored data (weakly labeled data) far more than the labeled data are ignored in model building. Trying to utilize such information in the censored data, a semi-supervised learning framework (Cox-AFT model) combined with Cox proportional hazard (Cox) and accelerated failure time (AFT) model was used in cancer research, which has better performance than the single Cox or AFT model. This method, however, is easily affected by noise. To alleviate this problem, in this paper we combine the Cox-AFT model with self-paced learning (SPL) method to more effectively employ the information in the censored data in a self-learning way. SPL is a kind of reliable and stable learning mechanism, which is recently proposed for simulating the human learning process to help the AFT model automatically identify and include samples of high confidence into training, minimizing interference from high noise. Utilizing the SPL method produces two direct advantages: (1) The utilization of censored data is further promoted; (2) the noise delivered to the model is greatly decreased. The experimental results demonstrate the effectiveness of the proposed model compared to the traditional Cox-AFT model.

Regression Analysis and the Sociological Imagination

Science.gov (United States)

De Maio, Fernando

2014-01-01

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

COX-2 activation is associated with Akt phosphorylation and poor survival in ER-negative, HER2-positive breast cancer

International Nuclear Information System (INIS)

Glynn, Sharon A; Ambs, Stefan; Prueitt, Robyn L; Ridnour, Lisa A; Boersma, Brenda J; Dorsey, Tiffany M; Wink, David A; Goodman, Julie E; Yfantis, Harris G; Lee, Dong H

2010-01-01

Inducible cyclooxgenase-2 (COX-2) is commonly overexpressed in breast tumors and is a target for cancer therapy. Here, we studied the association of COX-2 with breast cancer survival and how this association is influenced by tumor estrogen and HER2 receptor status and Akt pathway activation. Tumor COX-2, HER2 and estrogen receptor α (ER) expression and phosphorylation of Akt, BAD, and caspase-9 were analyzed immunohistochemically in 248 cases of breast cancer. Spearman's correlation and multivariable logistic regression analyses were used to examine the relationship between COX-2 and tumor characteristics. Kaplan-Meier survival and multivariable Cox proportional hazards regression analyses were used to examine the relationship between COX-2 and disease-specific survival. COX-2 was significantly associated with breast cancer outcome in ER-negative [Hazard ratio (HR) = 2.72; 95% confidence interval (CI), 1.36-5.41; comparing high versus low COX-2] and HER2 overexpressing breast cancer (HR = 2.84; 95% CI, 1.07-7.52). However, the hazard of poor survival associated with increased COX-2 was highest among patients who were both ER-negative and HER2-positive (HR = 5.95; 95% CI, 1.01-34.9). Notably, COX-2 expression in the ER-negative and HER2-positive tumors correlated significantly with increased phosphorylation of Akt and of the two Akt targets, BAD at Ser136 and caspase-9 at Ser196. Up-regulation of COX-2 in ER-negative and HER2-positive breast tumors is associated with Akt pathway activation and is a marker of poor outcome. The findings suggest that COX-2-specific inhibitors and inhibitors of the Akt pathway may act synergistically as anticancer drugs in the ER-negative and HER2-positive breast cancer subtype

The analysis of soil cores polluted with certain metals using the Box-Cox transformation

International Nuclear Information System (INIS)

Meloun, Milan; Sanka, Milan; Nemec, Pavel; Kritkova, Sona; Kupka, Karel

2005-01-01

To define the soil properties for a given area or country including the level of pollution, soil survey and inventory programs are essential tools. Soil data transformations enable the expression of the original data on a new scale, more suitable for data analysis. In the computer-aided interactive analysis of large data files of soil characteristics containing outliers, the diagnostic plots of the exploratory data analysis (EDA) often find that the sample distribution is systematically skewed or reject sample homogeneity. Under such circumstances the original data should be transformed. The Box-Cox transformation improves sample symmetry and stabilizes spread. The logarithmic plot of a profile likelihood function enables the optimum transformation parameter to be found. Here, a proposed procedure for data transformation in univariate data analysis is illustrated on a determination of cadmium content in the plough zone of agricultural soils. A typical soil pollution survey concerns the determination of the elements Be (16 544 values available), Cd (40 317 values), Co (22 176 values), Cr (40 318 values), Hg (32 344 values), Ni (34 989 values), Pb (40 344 values), V (20 373 values) and Zn (36 123 values) in large samples. - A new procedure of statistical analysis, with exploratory data diagnostics and Box-Cox transformation was used

The analysis of soil cores polluted with certain metals using the Box-Cox transformation

Energy Technology Data Exchange (ETDEWEB)

Meloun, Milan [Department of Analytical Chemistry, University of Pardubice, CZ532 10 Pardubice (Czech Republic)]. E-mail: milan.meloun@upce.cz; Sanka, Milan [Central Institute for Supervisiting and Testing in Agriculture Division of Agrochemistry, Soil and Plant Nutrition, Hroznova 2, CZ656 06 Brno - Pisarky (Czech Republic); Nemec, Pavel [Central Institute for Supervisiting and Testing in Agriculture Division of Agrochemistry, Soil and Plant Nutrition, Hroznova 2, CZ656 06 Brno - Pisarky (Czech Republic)]. E-mail: pavel.nemec@ukzuz.cz; Kritkova, Sona [Department of Analytical Chemistry, University of Pardubice, CZ532 10 Pardubice (Czech Republic); Kupka, Karel [Trilobyte Statistical Software Ltd., CZ530 02 Pardubice (Czech Republic)]. E-mail: kupka@trilobyte.cz

2005-09-15

To define the soil properties for a given area or country including the level of pollution, soil survey and inventory programs are essential tools. Soil data transformations enable the expression of the original data on a new scale, more suitable for data analysis. In the computer-aided interactive analysis of large data files of soil characteristics containing outliers, the diagnostic plots of the exploratory data analysis (EDA) often find that the sample distribution is systematically skewed or reject sample homogeneity. Under such circumstances the original data should be transformed. The Box-Cox transformation improves sample symmetry and stabilizes spread. The logarithmic plot of a profile likelihood function enables the optimum transformation parameter to be found. Here, a proposed procedure for data transformation in univariate data analysis is illustrated on a determination of cadmium content in the plough zone of agricultural soils. A typical soil pollution survey concerns the determination of the elements Be (16 544 values available), Cd (40 317 values), Co (22 176 values), Cr (40 318 values), Hg (32 344 values), Ni (34 989 values), Pb (40 344 values), V (20 373 values) and Zn (36 123 values) in large samples. - A new procedure of statistical analysis, with exploratory data diagnostics and Box-Cox transformation was used.

An appreciation of Richard Threlkeld Cox

Science.gov (United States)

Tribus, Myron

2002-05-01

Richard T. Cox's contributions to the foundations of probability theory and inductive logic are not generally appreciated or understood. This paper reviews his life and accomplishments, especially those in his book The Algebra of Probable Inference and his final publication Inference and Inquiry which, in this author's opinion, has the potential to influence in a significant way the design and analysis of self organizing systems which learn from experience. A simple application to the simulation of a neuron is presented as an example of the power of Cox's contribution.

Analysis of a genetically structured variance heterogeneity model using the Box-Cox transformation

DEFF Research Database (Denmark)

Yang, Ye; Christensen, Ole Fredslund; Sorensen, Daniel

2011-01-01

of the marginal distribution of the data. To investigate how the scale of measurement affects inferences, the genetically structured heterogeneous variance model is extended to accommodate the family of Box–Cox transformations. Litter size data in rabbits and pigs that had previously been analysed...... in the untransformed scale were reanalysed in a scale equal to the mode of the marginal posterior distribution of the Box–Cox parameter. In the rabbit data, the statistical evidence for a genetic component at the level of the environmental variance is considerably weaker than that resulting from an analysis...... in the original metric. In the pig data, the statistical evidence is stronger, but the coefficient of correlation between additive genetic effects affecting mean and variance changes sign, compared to the results in the untransformed scale. The study confirms that inferences on variances can be strongly affected...

Polylinear regression analysis in radiochemistry

International Nuclear Information System (INIS)

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

1995-01-01

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

Efficacy and safety of COX-2 inhibitors for advanced non-small-cell lung cancer with chemotherapy: a meta-analysis

Directory of Open Access Journals (Sweden)

Dai P

2018-02-01

Full Text Available Ping Dai, Jing Li, Xiao-Ping Ma, Jian Huang, Juan-Juan Meng, Ping Gong Department of Oncology, The First Affiliated Hospital, Shihezi University School of Medicine, Shihezi, Xinjiang, People’s Republic of China Background: The study of cyclooxygenase-2 (COX-2 inhibitors is now mired in controversy. We performed a meta-analysis to assess the efficacy and safety profile of COX-2 inhibitors in patients with advanced non-small-cell lung cancer (NSCLC.Patients and methods: A literature search of PubMed, EMBASE, the Cochrane Central databases, and ClinicalTrials.gov, up until March 26, 2017, identified relevant randomized controlled trials. Data analysis was performed using Stata 12.0.Results: Six eligible trials (1,794 patients were selected from the 407 studies that were identified initially. A significant difference, favoring COX-2 inhibitors plus chemotherapy over chemotherapy alone, was observed in the overall response rate (relative risk [RR] =1.25, 95% confidence interval [CI]: 1.06–1.48. Further, we conducted two subgroup analyses according to the type of COX-2 inhibitors (celecoxib, rofecoxib, or apricoxib and treatment line (first or second chemotherapy. The first-line treatment includes: NP (changchun red bean + cisplatin or carboplatin, GP (double fluorine cytidine + cisplatin or carboplatin, or TP (paclitaxel + cisplatin or carboplatin, docetaxel + cisplatin or carboplatin. The second-line treatment includes two internationally recognized compounds, one is docetaxel and the other is the pemetrexed, both of which are individually selected. In subgroup analysis, significantly increased overall response rate (ORR results were found for rofecoxib plus chemotherapy (RR =1.56, 95% CI: 1.08–2.25 and COX-2 inhibitor given with first-line chemotherapy (RR =1.27, 95% CI: 1.07–1.50. However, there was no difference between COX-2 inhibitors plus chemotherapy and chemotherapy alone in overall survival (hazard ratio [HR] =1.04, 95% CI: 0.91–1

[Analysis of COX1 sequences of Taenia isolates from four areas of Guangxi].

Science.gov (United States)

Yang, Yi-Chao; Ou-Yang, Yi; Su, Ai-Rong; Wan, Xiao-Ling; Li, Shu-Lin

2012-06-01

To analyze the COX1 sequences of Taenia isolates from four areas of Guangxi Zhuang Autonomous Region, and to understand the distribution of Taenia asiatica in Guangxi. Patients with taeniasis in Luzhai, Rongshui, Tiandong and Sanjiang in Guangxi were treated by deworming, and the Taenia isolates were collected. Cyclooxygenase-1 (COX1) sequences of these isolates were amplified by PCR, and the PCR products were sequenced by T-A clone sequencing. The homogeneities and genetic distances were calculated and analyzed, and the phylogenic trees were constructed by some softwares. Meanwhile, the COX1 sequences of the isolates from the 4 areas were compared separately with the sequences of Taenia species in GenBank. The COX1 sequence of the 5 Taenia isolates collected had the same length of 444 bp. There were 5 variable positions between the Luzhai isolate and Taenia asiatica, the homogeneity was 98.87% and their genetic distance was 0.011. The phylogenetic tree analysis revealed that the Luzhai isolate and Taenia asiatica locating at the same node had a close relationship. The homogeneity between Rongshui isolate A and Taenia solium was 100%, while the homogeneity of Rongshui isolate B with Taeniasis saginata and Taenia asiatica were 98.20% and 96.17%, respectively. The homogeneities of the Tiandong and Sanjiang isolates with Taenia solium were 99.55% and 96.40%, respectively, and the genetic distances were 0.005 and 0.037, respectively. The homogeneity between the Luzhai isolate and Taeniasis saginate was 96.40%. Taenia asiatica exists in Luzhai and Taenia solium and Taenia saginata coexist in Rongshui, Guangxi Zhuang Autonomous Region.

Maximum likelihood estimation for Cox's regression model under nested case-control sampling

DEFF Research Database (Denmark)

Scheike, Thomas Harder; Juul, Anders

2004-01-01

-like growth factor I was associated with ischemic heart disease. The study was based on a population of 3784 Danes and 231 cases of ischemic heart disease where controls were matched on age and gender. We illustrate the use of the MLE for these data and show how the maximum likelihood framework can be used......Nested case-control sampling is designed to reduce the costs of large cohort studies. It is important to estimate the parameters of interest as efficiently as possible. We present a new maximum likelihood estimator (MLE) for nested case-control sampling in the context of Cox's proportional hazards...... model. The MLE is computed by the EM-algorithm, which is easy to implement in the proportional hazards setting. Standard errors are estimated by a numerical profile likelihood approach based on EM aided differentiation. The work was motivated by a nested case-control study that hypothesized that insulin...

COX-2 verexpression in pretreatment biopsies predicts response of rectal cancers to neoadjuvant radiochemotherapy

International Nuclear Information System (INIS)

Smith, Fraser M.; Reynolds, John V.; Kay, Elaine W.; Crotty, Paul; Murphy, James O.; Hollywood, Donal; Gaffney, Eoin F.; Stephens, Richard B.; Kennedy, M. John

2006-01-01

Purpose: To determine the utility of COX-2 expression as a response predictor for patients with rectal cancer who are undergoing neoadjuvant radiochemotherapy (RCT). Methods and Materials: Pretreatment biopsies (PTB) from 49 patients who underwent RCT were included. COX-2 and proliferation in PTB were assessed by immunohistochemistry (IHC) and apoptosis was detected by TUNEL stain. Response to treatment was assessed by a 5-point tumor-regression grade (TRG) based on the ratio of residual tumor to fibrosis. Results: Good response (TRG 1 + 2), moderate response (TRG 3), and poor response (TRG 4 + 5) were seen in 21 patients (42%), 11 patients (22%), and 17 patients (34%), respectively. Patients with COX-2 overexpression in PTB were more likely to demonstrate moderate or poor response (TRG 3 + 4) to treatment than were those with normal COX-2 expression (p = 0.026, chi-square test). Similarly, poor response was more likely if patients had low levels of spontaneous apoptosis in PTBs (p = 0.0007, chi-square test). Conclusions: COX-2 overexpression and reduced apoptosis in PTB can predict poor response of rectal cancer to RCT. As COX-2 inhibitors are commercially available, their administration to patients who overexpress COX-2 warrants assessment in clinical trials in an attempt to increase overall response rates

On the use of Cox regression to examine the temporal clustering of flooding and heavy precipitation across the central United States

Science.gov (United States)

Mallakpour, Iman; Villarini, Gabriele; Jones, Michael P.; Smith, James A.

2017-08-01

The central United States is plagued by frequent catastrophic flooding, such as the flood events of 1993, 2008, 2011, 2013, 2014 and 2016. The goal of this study is to examine whether it is possible to describe the occurrence of flood and heavy precipitation events at the sub-seasonal scale in terms of variations in the climate system. Daily streamflow and precipitation time series over the central United States (defined here to include North Dakota, South Dakota, Nebraska, Kansas, Missouri, Iowa, Minnesota, Wisconsin, Illinois, West Virginia, Kentucky, Ohio, Indiana, and Michigan) are used in this study. We model the occurrence/non-occurrence of a flood and heavy precipitation event over time using regression models based on Cox processes, which can be viewed as a generalization of Poisson processes. Rather than assuming that an event (i.e., flooding or precipitation) occurs independently of the occurrence of the previous one (as in Poisson processes), Cox processes allow us to account for the potential presence of temporal clustering, which manifests itself in an alternation of quiet and active periods. Here we model the occurrence/non-occurrence of flood and heavy precipitation events using two climate indices as time-varying covariates: the Arctic Oscillation (AO) and the Pacific-North American pattern (PNA). We find that AO and/or PNA are important predictors in explaining the temporal clustering in flood occurrences in over 78% of the stream gages we considered. Similar results are obtained when working with heavy precipitation events. Analyses of the sensitivity of the results to different thresholds used to identify events lead to the same conclusions. The findings of this work highlight that variations in the climate system play a critical role in explaining the occurrence of flood and heavy precipitation events at the sub-seasonal scale over the central United States.

Linear Regression Analysis

CERN Document Server

Seber, George A F

2012-01-01

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

Properties of spatial Cox process models

DEFF Research Database (Denmark)

Møller, Jesper

Probabilistic properties of Cox processes of relevance for statistical modelling and inference are studied. Particularly, we study the most important classes of Cox processes, including log Gaussian Cox processes, shot noise Cox processes, and permanent Cox processes. We consider moment properties...... and point process operations such as thinning, displacements, and superpositioning. We also discuss how to simulate specific Cox processes....

Correlation analysis between expression of PCNA, Ki-67 and COX-2 and X-ray features in mammography in breast cancer.

Science.gov (United States)

Qiu, Xiaoming; Mei, Jixin; Yin, Jianjun; Wang, Hong; Wang, Jinqi; Xie, Ming

2017-09-01

This study investigated expression of proliferating cell nuclear antigen (PCNA), proliferation-associated nuclear antigen (Ki-67) and cyclooxygenase-2 (COX-2) in tissues of breast invasive ductal carcinoma, and analyzed the correlations between these indexes and X-ray features in mammography. A total of 90 patients who were admitted to Huangshi Central Hospital and diagnosed as breast invasive ductal carcinoma from January 2014 to January 2016 were selected. The expression of PCNA, Ki-67 and COX-2 in cancer tissues and cancer-adjacent normal tissues of patients were detected by immunohistochemical staining, and X-ray features in mammography of patients were observed. By using Spearman correlation analysis, the correlations between expression of PCNA, Ki-67 and COX-2 and X-ray features in mammography in breast cancer were investigated. As a result, the positive expression rates of PCNA, Ki-67 and COX-2 in cancer tissues of the patient groups were respectively 42.2, 45.6 and 51.1%, which were significantly higher than those in cancer-adjacent normal tissues of the control group (pcorrelation with age and tumor size (p>0.05). PCNA, Ki-67 and COX-2 expression in cancer tissues of the patient group had no correlation with the existence of lumps and localized density-increased shadows (p>0.05), but were associated with manifestations of architectural distortion, calcification as well as skin and nipple depression (pcorrelation analysis revealed that there was a significantly positive correlation between the expression of PCNA and COX-2 in cancer tissues of the patient group (r=0.676, pcorrelation between the expression of Ki-67 and COX-2 (r=0.724, pcorrelation with the expression of Ki-67 (p>0.05). In conclusion, PCNA, Ki-67 and COX-2 expression is of great significance in the occurrence, invasion and metastasis of breast invasive ductal carcinoma. There is a strong correlation between PCNA, Ki-67 and COX-2 expression levels and X-ray features in mammography in breast

Pregnancy induced changes in Cox-1, Cox-2 and NOSIII vascular and renal expression.

Science.gov (United States)

Bobadilla, Rosa A; Bracho, Ismael; Alvarez, Victor M Pérez; Anguiano, Liliana; López, Pedro

2004-01-01

In order to establish if there is a mutual regulation between COX and NOS in vascular and renal tissue during pregnancy, we measured the protein expression of COX-1, COX-2 and NOSIII by Western blot comparing the thoracic and abdominal aorta and the renal cortex and medulla of non pregnant and pregnant (21st day) Wistar rats. We found there was no difference in the quantity of protein of any of the two isoforms of COX between the two segments of the aorta of non pregnant animals while an increased expression of both COX-1 And COX-2 was found in the abdominal compared to the thoracic segment of the pregnant rats. An increased expression of NOS III was found in the abdominal segment of the aorta form pregnant rats. No changes were found between pregnant and no pregnant animals in the expression of COX-1 and COX-2 in the renal cortex or medulla while an increased expression of NOS III was found in the cortex from pregnant compared to non pregnant animals. These results suggest the influence of pregnancy is not homogeneous along the aorta and also that a balance between prostaglandins and nitric oxide is responsible of the blunted vascular reactivity during pregnancy in the rat.

CoX zeolites and their exchange with deuterium

Energy Technology Data Exchange (ETDEWEB)

Novakova, J; Kubelkova, L; Jiru, P [Ceskoslovenska Akademie Ved, Prague. Ustav Fyzikalni Chemie

1976-04-01

An analysis of the gaseous phase using a mass spectrometer and analysis of the solid phase using an infrared spectrophotometer was made to investigate the deuterium exchange with hydrogen mostly bound in hydroxyl groups of zeolites CoX(21 and 47%) and NaX. It was found that with the increasing amount of cobalt ions the number of exchangeable hydrogens of the zeolite increases; the respective types of the hydrogen are discussed with respect to the particular dehydration temperatures. The rate of the D/sub 2/+OH exchange is substantially faster with the CoX than with the NaX zeolite, and exhibits a decrease with increasing dehydration. On the other hand, the rate of D/sub 2/+H/sub 2/ exchange without zeolite hydrogen incorporation, catalyzed by CoX zeolites, increases with increasing dehydration. The increased activation of gaseous hydrogen molecules is related to the presence in the zeolite of cobalt ions whose properties change during dehydration with the change in their environment. Hydroxyl groups of the CoX zeolites are not equivalent during the exchange; the hydroxyl hydrogens of the 3740 cm/sup -1/ band are exchanged more slowly than are the other hydrogens.

CoX zeolites and their exchange with deuterium

International Nuclear Information System (INIS)

Novakova, J.; Kubelkova, L.; Jiru, P.

1976-01-01

An analysis of the gaseous phase using a mass spectrometer and analysis of the solid phase using an infrared spectrophotometer was made to investigate the deuterium exchange with hydrogen mostly bound in hydroxyl groups of zeolites CoX(21 and 47%) and NaX. It was found that with the increasing amount of cobalt ions the number of exchangeable hydrogens of the zeolite increases; the respective types of the hydrogen are discussed with respect to the particular dehydration temperatures. The rate of the D 2 +OH exchange is substantially faster with the CoX than with the NaX zeolite, and exhibits a decrease with increasing dehydration. On the other hand, the rate of D 2 +H 2 exchange without zeolite hydrogen incorporation, catalyzed by CoX zeolites, increases with increasing dehydration. The increased activation of gaseous hydrogen molecules is related to the presence in the zeolite of cobalt ions whose properties change during dehydration with the change in their environment. Hydroxyl groups of the CoX zeolites are not equivalent during the exchange; the hydroxyl hydrogens of the 3740 cm -1 band are exchanged more slowly than are the other hydrogens. (author)

Exploring selectivity requirements for COX-2 versus COX-1 binding of 2-(5-phenyl-pyrazol-1-yl)-5-methanesulfonylpyridines using topological and physico-chemical parameters.

Science.gov (United States)

Chakraborty, Santanu; Sengupta, Chandana; Roy, Kunal

2005-04-01

Considering the current need for development of selective cyclooxygenase-2 (COX-2) inhibitors, an attempt has been made to explore physico-chemical requirements of 2-(5-phenyl-pyrazol-1-yl)-5-methanesulfonylpyridines for binding with COX-1 and COX-2 enzyme subtypes and also to explore the selectivity requirements. In this study, E-states of different common atoms of the molecules (calculated according to Kier & Hall), first order valence connectivity and physicochemical parameters (hydrophobicity pi, Hammett sigma and molar refractivity MR of different ring substituents) were used as independent variables along with suitable dummy parameters in the stepwise regression method. The best equation describing COX-1 binding affinity [n = 25, Q2 = 0.606, R(a)2 = 0.702, R2 = 0.752, R = 0.867, s = 0.447, F = 15.2 (df 4, 20)] suggests that the COX-1 binding affinity increases in the presence of a halogen substituent at R1 position and a p-alkoxy or p-methylthio substituent at R2 position. Furthermore, a difluoromethyl group is preferred over a trifluoromethyl group at R position for the COX-1 binding. The best equation describing COX-2 binding affinity [n = 32, Q2 = 0.622, R(a)2= 0.692, R2 = 0.732, R = 0.856, s = 0.265, F = 18.4 (df 4, 27)] shows that the COX-2 binding affinity increases with the presence of a halogen substituent at R1 position and increase of size of R2 substituents. However, it decreases in case of simultaneous presence of 3-chloro and 4-methoxy groups on the phenyl nucleus and in the presence of highly lipophilic R2 substituents. The best selectivity relation [n = 25, Q2 = 0.455, R(a)2 = 0.605, R2 = 0.670, R = 0.819, s = 0.423, F = 10.2 (df 4, 20)] suggests that the COX-2 selectivity decreases in the presence of p-alkoxy group and electron-withdrawing para substituents at R2 position. Again, a trifluoro group is conductive for the selectivity instead of a difluoromethyl group at R position. Furthermore, branching may also play significant role in

Preface to Berk's "Regression Analysis: A Constructive Critique"

OpenAIRE

de Leeuw, Jan

2003-01-01

It is pleasure to write a preface for the book ”Regression Analysis” of my fellow series editor Dick Berk. And it is a pleasure in particular because the book is about regression analysis, the most popular and the most fundamental technique in applied statistics. And because it is critical of the way regression analysis is used in the sciences, in particular in the social and behavioral sciences. Although the book can be read as an introduction to regression analysis, it can also be read as a...

Multicollinearity and Regression Analysis

Science.gov (United States)

Daoud, Jamal I.

2017-12-01

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

Properties of spatial Cox process models

DEFF Research Database (Denmark)

Møller, Jesper

2005-01-01

Particularly, we study the most important classes of Cox processes, including log Gaussian Cox processes, shot noise Cox processes, and permanent Cox processes. We consider moment properties and point process operations such as thinning, displacements, and super positioning. We also discuss how...... to simulate specific Cox processes....

SECOND ORDER LEAST SQUARE ESTIMATION ON ARCH(1 MODEL WITH BOX-COX TRANSFORMED DEPENDENT VARIABLE

Directory of Open Access Journals (Sweden)

Herni Utami

2014-03-01

Full Text Available Box-Cox transformation is often used to reduce heterogeneity and to achieve a symmetric distribution of response variable. In this paper, we estimate the parameters of Box-Cox transformed ARCH(1 model using second-order leastsquare method and then we study the consistency and asymptotic normality for second-order least square (SLS estimators. The SLS estimation was introduced byWang (2003, 2004 to estimate the parameters of nonlinear regression models with independent and identically distributed errors

Testing among functional forms: an extension of the Generalized Box-Cox formulation.

NARCIS (Netherlands)

Oude Lansink, A.G.J.M.; Thijssen, G.

1998-01-01

This paper uses the Generalized Box - Cox framework and Double Length artificial Regression to test whether different specifications of the profit function are able to mimic the technology underlying panel data of Dutch arable farms for the period 1970 - 1988. To this end, a linear GBC is developed

Lévy based Cox point processes

DEFF Research Database (Denmark)

Hellmund, Gunnar; Prokesová, Michaela; Jensen, Eva Bjørn Vedel

2008-01-01

In this paper we introduce Lévy-driven Cox point processes (LCPs) as Cox point processes with driving intensity function Λ defined by a kernel smoothing of a Lévy basis (an independently scattered, infinitely divisible random measure). We also consider log Lévy-driven Cox point processes (LLCPs......) with Λ equal to the exponential of such a kernel smoothing. Special cases are shot noise Cox processes, log Gaussian Cox processes, and log shot noise Cox processes. We study the theoretical properties of Lévy-based Cox processes, including moment properties described by nth-order product densities...

Hierarchical regression analysis in structural Equation Modeling

NARCIS (Netherlands)

de Jong, P.F.

1999-01-01

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

Multivariate Regression Analysis and Slaughter Livestock,

Science.gov (United States)

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

riskRegression

DEFF Research Database (Denmark)

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

2017-01-01

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

Prediction of unwanted pregnancies using logistic regression, probit regression and discriminant analysis.

Science.gov (United States)

Ebrahimzadeh, Farzad; Hajizadeh, Ebrahim; Vahabi, Nasim; Almasian, Mohammad; Bakhteyar, Katayoon

2015-01-01

Unwanted pregnancy not intended by at least one of the parents has undesirable consequences for the family and the society. In the present study, three classification models were used and compared to predict unwanted pregnancies in an urban population. In this cross-sectional study, 887 pregnant mothers referring to health centers in Khorramabad, Iran, in 2012 were selected by the stratified and cluster sampling; relevant variables were measured and for prediction of unwanted pregnancy, logistic regression, discriminant analysis, and probit regression models and SPSS software version 21 were used. To compare these models, indicators such as sensitivity, specificity, the area under the ROC curve, and the percentage of correct predictions were used. The prevalence of unwanted pregnancies was 25.3%. The logistic and probit regression models indicated that parity and pregnancy spacing, contraceptive methods, household income and number of living male children were related to unwanted pregnancy. The performance of the models based on the area under the ROC curve was 0.735, 0.733, and 0.680 for logistic regression, probit regression, and linear discriminant analysis, respectively. Given the relatively high prevalence of unwanted pregnancies in Khorramabad, it seems necessary to revise family planning programs. Despite the similar accuracy of the models, if the researcher is interested in the interpretability of the results, the use of the logistic regression model is recommended.

Bayesian logistic regression analysis

NARCIS (Netherlands)

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

2012-01-01

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

[Use of multiple regression models in observational studies (1970-2013) and requirements of the STROBE guidelines in Spanish scientific journals].

Science.gov (United States)

Real, J; Cleries, R; Forné, C; Roso-Llorach, A; Martínez-Sánchez, J M

In medicine and biomedical research, statistical techniques like logistic, linear, Cox and Poisson regression are widely known. The main objective is to describe the evolution of multivariate techniques used in observational studies indexed in PubMed (1970-2013), and to check the requirements of the STROBE guidelines in the author guidelines in Spanish journals indexed in PubMed. A targeted PubMed search was performed to identify papers that used logistic linear Cox and Poisson models. Furthermore, a review was also made of the author guidelines of journals published in Spain and indexed in PubMed and Web of Science. Only 6.1% of the indexed manuscripts included a term related to multivariate analysis, increasing from 0.14% in 1980 to 12.3% in 2013. In 2013, 6.7, 2.5, 3.5, and 0.31% of the manuscripts contained terms related to logistic, linear, Cox and Poisson regression, respectively. On the other hand, 12.8% of journals author guidelines explicitly recommend to follow the STROBE guidelines, and 35.9% recommend the CONSORT guideline. A low percentage of Spanish scientific journals indexed in PubMed include the STROBE statement requirement in the author guidelines. Multivariate regression models in published observational studies such as logistic regression, linear, Cox and Poisson are increasingly used both at international level, as well as in journals published in Spanish. Copyright © 2015 Sociedad Española de Médicos de Atención Primaria (SEMERGEN). Publicado por Elsevier España, S.L.U. All rights reserved.

Regression analysis using dependent Polya trees.

Science.gov (United States)

Schörgendorfer, Angela; Branscum, Adam J

2013-11-30

Many commonly used models for linear regression analysis force overly simplistic shape and scale constraints on the residual structure of data. We propose a semiparametric Bayesian model for regression analysis that produces data-driven inference by using a new type of dependent Polya tree prior to model arbitrary residual distributions that are allowed to evolve across increasing levels of an ordinal covariate (e.g., time, in repeated measurement studies). By modeling residual distributions at consecutive covariate levels or time points using separate, but dependent Polya tree priors, distributional information is pooled while allowing for broad pliability to accommodate many types of changing residual distributions. We can use the proposed dependent residual structure in a wide range of regression settings, including fixed-effects and mixed-effects linear and nonlinear models for cross-sectional, prospective, and repeated measurement data. A simulation study illustrates the flexibility of our novel semiparametric regression model to accurately capture evolving residual distributions. In an application to immune development data on immunoglobulin G antibodies in children, our new model outperforms several contemporary semiparametric regression models based on a predictive model selection criterion. Copyright © 2013 John Wiley & Sons, Ltd.

RAWS II: A MULTIPLE REGRESSION ANALYSIS PROGRAM,

Science.gov (United States)

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

Generalised shot noise Cox processes

DEFF Research Database (Denmark)

Møller, Jesper; Torrisi, Giovanni Luca

2005-01-01

We introduce a class of cox cluster processes called generalised shot noise Cox processes (GSNCPs), which extends the definition of shot noise Cox processes (SNCPs) in two directions: the point process that drives the shot noise is not necessarily Poisson, and the kernel of the shot noise can...

Combined Analysis of COX-2 and p53 Expressions Reveals Synergistic Inverse Correlations with Microsatellite Instability and CpG Island Methylator Phenotype in Colorectal Cancer

Directory of Open Access Journals (Sweden)

Shuji Ogino

2006-06-01

Full Text Available Cyclooxygenase-2 (COX-2 overexpression and mutations of p53 (a known COX-2 regulator are inversely associated with microsatellite instability—high (MSI-H and CpG island methylator phenotype (CIMP, characterized by extensive promoter methylation, is associated with MSI-H. However, no studies have comprehensively examined interrelations between COX-2, p53, MSI, and CIMP. Using MethyLight, we measured DNA methylation in five CIMP-specific gene promoters [CACNA1G, CDKN2A (p16/INK4A, CRABP1, MLH1, and NEUROG1] in relatively unbiased samples of 751 colorectal cancer cases obtained from two large prospective cohorts; 115 (15% tumors were CIMP-high (≥ 4 of 5 methylated promoters, 251 (33% were CIMP-low (1 to 3 methylated promoters, and the remaining 385 (51% were CIMP-0 (no methylated promoters. CIMP-high tumors were much less frequent in COX-2+/p53+ tumors (4.6% than in COX-2+/p53- tumors (19%; P < .0001, COX-2-/p53+ tumors (17%; P = .04, and COX-2-/p53- tumors (28%; P < .0001. In addition, COX-2+/p53+ tumors were significantly less common in MSI-H CIMP-high tumors (9.7% than in non-MSI-H CIMP-low/CIMP-0 tumors (44–47%; P < .0001. In conclusion, COX-2 and p53 alterations were synergistically inversely correlated with both MSI-H and CIMP-high. Our data suggest that a combined analysis of COX-2 and p53 may be more useful for the molecular classification of colorectal cancer than either COX-2 or p53 analysis alone.

Pharmacologic inhibition of COX-1 and COX-2 in influenza A viral infection in mice.

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Michelle A Carey

Full Text Available BACKGROUND: We previously demonstrated that cyclooxygenase (COX-1 deficiency results in greater morbidity and inflammation, whereas COX-2 deficiency leads to reduced morbidity, inflammation and mortality in influenza infected mice. METHODOLOGY/PRINCIPAL FINDINGS: We investigated the effects of COX-1 and COX-2 inhibitors in influenza A viral infection. Mice were given a COX-1 inhibitor (SC-560, a COX-2 inhibitor (celecoxib or no inhibitor beginning 2 weeks prior to influenza A viral infection (200 PFU and throughout the course of the experiment. Body weight and temperature were measured daily as indicators of morbidity. Animals were sacrificed on days 1 and 4 post-infection and bronchoalveolar lavage (BAL fluid was collected or daily mortality was recorded up to 2 weeks post-infection. Treatment with SC-560 significantly increased mortality and was associated with profound hypothermia and greater weight loss compared to celecoxib or control groups. On day 4 of infection, BAL fluid cells were modestly elevated in celecoxib treated mice compared to SC-560 or control groups. Viral titres were similar between treatment groups. Levels of TNF-alpha and G-CSF were significantly attenuated in the SC-560 and celecoxib groups versus control and IL-6 levels were significantly lower in BAL fluid of celecoxib treated mice versus control and versus the SC-560 group. The chemokine KC was significantly lower in SC-560 group versus control. CONCLUSIONS/SIGNIFICANCE: Treatment with a COX-1 inhibitor during influenza A viral infection is detrimental to the host whereas inhibition of COX-2 does not significantly modulate disease severity. COX-1 plays a critical role in controlling the thermoregulatory response to influenza A viral infection in mice.

Forecasts of non-Gaussian parameter spaces using Box-Cox transformations

Science.gov (United States)

Joachimi, B.; Taylor, A. N.

2011-09-01

Forecasts of statistical constraints on model parameters using the Fisher matrix abound in many fields of astrophysics. The Fisher matrix formalism involves the assumption of Gaussianity in parameter space and hence fails to predict complex features of posterior probability distributions. Combining the standard Fisher matrix with Box-Cox transformations, we propose a novel method that accurately predicts arbitrary posterior shapes. The Box-Cox transformations are applied to parameter space to render it approximately multivariate Gaussian, performing the Fisher matrix calculation on the transformed parameters. We demonstrate that, after the Box-Cox parameters have been determined from an initial likelihood evaluation, the method correctly predicts changes in the posterior when varying various parameters of the experimental setup and the data analysis, with marginally higher computational cost than a standard Fisher matrix calculation. We apply the Box-Cox-Fisher formalism to forecast cosmological parameter constraints by future weak gravitational lensing surveys. The characteristic non-linear degeneracy between matter density parameter and normalization of matter density fluctuations is reproduced for several cases, and the capabilities of breaking this degeneracy by weak-lensing three-point statistics is investigated. Possible applications of Box-Cox transformations of posterior distributions are discussed, including the prospects for performing statistical data analysis steps in the transformed Gaussianized parameter space.

Adverse Effects of COX-2 Inhibitors

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Jagdish N. Sharma

2005-01-01

Full Text Available Cyclooxygenase-2 selective inhibitors (COXIBs were developed with the prime object of minimizing gastrointestinal adverse effects, which are seen with the use of traditional nonsteroidal anti-inflammatory drugs (NSAIDs. Their long-term use is limited by the development of hypertension, edema, and congestive heart failure in a significant proportion of patients. NSAIDs block the activity of both COX isozymes, COX-1 and COX-2, which mediate the enzymatic conversion of arachidonate to prostaglandin H2 (PGH2 and other prostaglandin (PG metabolites. It is well established that the cardiovascular profile of COX-2 inhibitors can be accounted for by inhibition of COX-dependent PG synthesis. Following the COX-mediated synthesis of PGH2 from arachidonate, PGH2 is metabolized to one of at least five bioactive PGs, including PGE2, PGI2, PGF2, PGD2, or thromboxane A2 (TXA2. These prostanoids have pleiotropic cardiovascular effects, altering platelet function and renal function, and they are acting either as vasodilators or vasoconstrictors. Although COX-1 and COX-2 exhibit similar biochemical activity in converting arachidonate to PGH2in vitro, the ultimate prostanoids they produce in vivo may be different due to differential regulation of COX-1 and COX-2, tissue distribution, and availability of the prostanoid synthases. PGs have been established as being critically involved in mitigating hypertension, helping to maintain medullary blood flow (MBF, promoting urinary salt excretion, and preserving the normal homeostasis of thrombosis, and the researchers found that the use of COX-2 inhibitors caused many serious complications in altering the normal body homeostasis. The purpose of the present research is to explain briefly the side effects of COX-2 inhibitors on the renal and cardiovascular system.

Common pitfalls in statistical analysis: Linear regression analysis

Directory of Open Access Journals (Sweden)

Rakesh Aggarwal

2017-01-01

Full Text Available In a previous article in this series, we explained correlation analysis which describes the strength of relationship between two continuous variables. In this article, we deal with linear regression analysis which predicts the value of one continuous variable from another. We also discuss the assumptions and pitfalls associated with this analysis.

Cancer survival analysis using semi-supervised learning method based on Cox and AFT models with L1/2 regularization.

Science.gov (United States)

Liang, Yong; Chai, Hua; Liu, Xiao-Ying; Xu, Zong-Ben; Zhang, Hai; Leung, Kwong-Sak

2016-03-01

One of the most important objectives of the clinical cancer research is to diagnose cancer more accurately based on the patients' gene expression profiles. Both Cox proportional hazards model (Cox) and accelerated failure time model (AFT) have been widely adopted to the high risk and low risk classification or survival time prediction for the patients' clinical treatment. Nevertheless, two main dilemmas limit the accuracy of these prediction methods. One is that the small sample size and censored data remain a bottleneck for training robust and accurate Cox classification model. In addition to that, similar phenotype tumours and prognoses are actually completely different diseases at the genotype and molecular level. Thus, the utility of the AFT model for the survival time prediction is limited when such biological differences of the diseases have not been previously identified. To try to overcome these two main dilemmas, we proposed a novel semi-supervised learning method based on the Cox and AFT models to accurately predict the treatment risk and the survival time of the patients. Moreover, we adopted the efficient L1/2 regularization approach in the semi-supervised learning method to select the relevant genes, which are significantly associated with the disease. The results of the simulation experiments show that the semi-supervised learning model can significant improve the predictive performance of Cox and AFT models in survival analysis. The proposed procedures have been successfully applied to four real microarray gene expression and artificial evaluation datasets. The advantages of our proposed semi-supervised learning method include: 1) significantly increase the available training samples from censored data; 2) high capability for identifying the survival risk classes of patient in Cox model; 3) high predictive accuracy for patients' survival time in AFT model; 4) strong capability of the relevant biomarker selection. Consequently, our proposed semi

Meta-analysis of the association between COX-2 polymorphisms and risk of colorectal cancer based on case-control studies.

Directory of Open Access Journals (Sweden)

Qiliu Peng

Full Text Available OBJECTIVE: Cyclooxygenase-2 (COX-2 is an inducible enzyme converting arachidonic acid to prostaglandins and playing important roles in inflammatory diseases as well as tumor development. Previous studies investigating the association between COX-2 polymorphisms and colorectal cancer (CRC risk reported conflicting results. We performed a meta-analysis of all available studies to explore this association. METHODS: All studies published up to October 2013 on the association between COX-2 polymorphisms and CRC risk were identified by searching electronic databases PubMed, EMBASE, and Cochrane library. The association between COX-2 polymorphisms and CRC risk was assessed by odds ratios (ORs together with their 95% confidence intervals (CIs. RESULTS: Ten studies with 6,774 cases and 9,772 controls were included for -1195A>G polymorphism, 13 studies including 6,807 cases and 10,052 controls were available for -765G>C polymorphism, and 8 studies containing 5,121 cases and 7,487 controls were included for 8473T>C polymorphism. With respect to -765G>C polymorphism, we did not find a significant association with CRC risk when all eligible studies were pooled into the meta-analysis. However, in subgroup analyses by ethnicity and cancer location, with a Bonferroni corrected alpha of 0.05/2, statistical significant increased CRC risk was found in the Asian populations (dominant model CC+CG vs. GG: OR = 1.399, 95%CI: 1.113-1.760, P = 0.004 and rectum cancer patients (CC vs. GG: OR = 2.270, 95%CI: 1.295-3.980, P = 0.004; Recessive model CC vs. CG+GG: OR = 2.269, 95%CI: 1.297-3.970, P = 0.004. In subgroup analysis according to source of control, no significant association was detected. With respect to -1195A>G and 8473T>C polymorphisms, no significant association with CRC risk was demonstrated in the overall and subgroup analyses. CONCLUSIONS: The present meta-analysis suggests that the COX-2 -765G>C polymorphism may be a risk factor for

Prognostic significance of COX-2 and β-catenin in colorectal ...

African Journals Online (AJOL)

Amani Kazem

2013-07-17

Jul 17, 2013 ... (wingless type) signaling pathway, increased protein concentrations promote transcription of genes .... under a light microscope and the histological type of colorectal .... of signet ring cell carcinoma showed weak COX-2 positivity. 3.2. Analysis .... COX-2 expression was detected in other tumors, and was be-.

Palm distributions for log Gaussian Cox processes

DEFF Research Database (Denmark)

Coeurjolly, Jean-Francois; Møller, Jesper; Waagepetersen, Rasmus Plenge

2017-01-01

This paper establishes a remarkable result regarding Palm distributions for a log Gaussian Cox process: the reduced Palm distribution for a log Gaussian Cox process is itself a log Gaussian Cox process that only differs from the original log Gaussian Cox process in the intensity function. This new...... result is used to study functional summaries for log Gaussian Cox processes....

SEKULARISASI DALAM PANDANGAN HARVEY COX

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Fauzan Fauzan

2017-02-01

Full Text Available Sebagian besar kaum agamawan (ortodoks memandang sekularisasi sebagai ancaman terhadap eksistensi agama. Namun sebaliknya, Harvey Cox memandang sekularisasi sebagai teologi perubahan sosial yang bertujuan mendobrak kebuntuan agama yang terbelenggu oleh ide “pemeliharaan” dan “kemapanan”. Tulisan ini membahas pandangan Harvey Cox tentang sekularisasi, konsepnya tentang Kota Sekuler (Secular City, dan Tuhan pada masyarakat sekuler. Cox melihat sekularisasi merupakan sebuah keniscayaan sejarah. Sekularisasi merupakan gerakan yang membebaskan manusia dari dogma yang membelenggu kebebasan manusia. Melalui simbol Kota Sekuler, Cox menghadirkan paradigma teologi yang lebih sesuai dengan keadaan masyarakat modern saat ini. Cox melihat bahwa Tuhan sebagaimana yang diajarkan oleh Kristiani –juga agama lain– bukanlah Tuhan yang sebenarnya. Tuhan tak lebih dari sebuah penamaan yang kehadirannya terkadang kosong dan ambigu. Semenjak penamaan dilekatkan dalam lingkungan sosio kultural tertentu, maka kata “Tuhan” tidak suci lagi. Apabila Tuhan dimaknai secara “ketat” dalam ruang tradisi yang berbeda-beda, maka akan terjadi benturan yang terkadang membutuhkan pengorbanan jiwa.

Moderation analysis using a two-level regression model.

Science.gov (United States)

Yuan, Ke-Hai; Cheng, Ying; Maxwell, Scott

2014-10-01

Moderation analysis is widely used in social and behavioral research. The most commonly used model for moderation analysis is moderated multiple regression (MMR) in which the explanatory variables of the regression model include product terms, and the model is typically estimated by least squares (LS). This paper argues for a two-level regression model in which the regression coefficients of a criterion variable on predictors are further regressed on moderator variables. An algorithm for estimating the parameters of the two-level model by normal-distribution-based maximum likelihood (NML) is developed. Formulas for the standard errors (SEs) of the parameter estimates are provided and studied. Results indicate that, when heteroscedasticity exists, NML with the two-level model gives more efficient and more accurate parameter estimates than the LS analysis of the MMR model. When error variances are homoscedastic, NML with the two-level model leads to essentially the same results as LS with the MMR model. Most importantly, the two-level regression model permits estimating the percentage of variance of each regression coefficient that is due to moderator variables. When applied to data from General Social Surveys 1991, NML with the two-level model identified a significant moderation effect of race on the regression of job prestige on years of education while LS with the MMR model did not. An R package is also developed and documented to facilitate the application of the two-level model.

Regulation of COX and LOX by curcumin.

Science.gov (United States)

Rao, Chinthalapally V

2007-01-01

Turmeric (Curcuma longa) is extensively used as a household remedy for various diseases. For the last few decades, work has been done to establish the biological activities and pharmacological actions of curcumin, the principle constituent of turmeric. Curcumin has proven to be beneficial in the prevention and treatment of a number of inflammatory diseases due to its anti-inflammatory activity. Arachidonic acid-derived lipid mediators that are intimately involved in inflammation are biosynthesized by pathways dependent on cyclooxygenase (COX) and lipoxygenase (LOX) enzymes. The role of LOX and COX isoforms, particularly COX-2, in the inflammation has been well established. At cellular and molecular levels, curcumin has been shown to regulate a number of signaling pathways, including the eicosanoid pathway involving COX and LOX. A number of studies have been conducted that support curcumin-mediated regulation of COX and LOX pathways, which is an important mechanism by which curcumin prevents a number of disease processes, including the cancer. The specific regulation of 5-LOX and COX-2 by curcumin is not fully established; however, existing evidence indicates that curcumin regulates LOX and COX-2 predominately at the transcriptional level and, to a certain extent, the posttranslational level. Thus, the curcumin-selective transcriptional regulatory action of COX-2, and dual COX/LOX inhibitory potential of this naturally occurring agent provides distinctive advantages over synthetic COX/LOX inhibitors, such as nonsteroidal anti-inflammatory drugs. In this review, we discuss evidence that supports the regulation of COX and LOX enzymes by curcumin as the key mechanism for its beneficial effects in preventing various inflammatory diseases.

New Inference Procedures for Semiparametric Varying-Coefficient Partially Linear Cox Models

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Yunbei Ma

2014-01-01

Full Text Available In biomedical research, one major objective is to identify risk factors and study their risk impacts, as this identification can help clinicians to both properly make a decision and increase efficiency of treatments and resource allocation. A two-step penalized-based procedure is proposed to select linear regression coefficients for linear components and to identify significant nonparametric varying-coefficient functions for semiparametric varying-coefficient partially linear Cox models. It is shown that the penalized-based resulting estimators of the linear regression coefficients are asymptotically normal and have oracle properties, and the resulting estimators of the varying-coefficient functions have optimal convergence rates. A simulation study and an empirical example are presented for illustration.

Radioprotection of intestinal crypt cells by cox-inhibitors

International Nuclear Information System (INIS)

Bisnar, Paul O.; Dones, Rosa Angela S.A.; Serna, Paulene-Ver A.; Deocaris, Chester C.; Guttierez, Kalangitan V.; Deocaris, Custer C.

2006-01-01

The regulation of tissue homeostasis in the gastrointestinal epithelium after epithelial injury focuses on the prostaglandins(PGs) as its major mediators. The two cyclooxygenase isoforms, cox-1 and cox-2, catalyze synthesis of PGs. Cox-1 is the predominant cyclooxygenase isoform found in the normal intestine. In contrast, cox-2 is present at low levels in normal intestine but is elevated at sites of inflammation, and in adenomas and carcinomas. To study the effects of various commercially-available cox-inhibitors (Ketorolac: cox-1 selective; Celecoxib: cox-2 selective; and Indocid: cox-1/2 non-selective), we determine mouse crypt epithelial cell fate after genotoxic injury with whole-body gamma-ray exposure at 15 Gy. Intestinal tissues of mice treated with cox-2 inhibitors that showed invariable apoptotic event, however, have increased occurrence of regenerating cells. Our results suggest a potential application of cox-2 selective inhibitors as radioprotective agent for normal cells after radiotherapy. (Author)

Artificial neural networks versus proportional hazards Cox models to predict 45-year all-cause mortality in the Italian Rural Areas of the Seven Countries Study

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Puddu Paolo

2012-07-01

Full Text Available Abstract Background Projection pursuit regression, multilayer feed-forward networks, multivariate adaptive regression splines and trees (including survival trees have challenged classic multivariable models such as the multiple logistic function, the proportional hazards life table Cox model (Cox, the Poisson’s model, and the Weibull’s life table model to perform multivariable predictions. However, only artificial neural networks (NN have become popular in medical applications. Results We compared several Cox versus NN models in predicting 45-year all-cause mortality (45-ACM by 18 risk factors selected a priori: age; father life status; mother life status; family history of cardiovascular diseases; job-related physical activity; cigarette smoking; body mass index (linear and quadratic terms; arm circumference; mean blood pressure; heart rate; forced expiratory volume; serum cholesterol; corneal arcus; diagnoses of cardiovascular diseases, cancer and diabetes; minor ECG abnormalities at rest. Two Italian rural cohorts of the Seven Countries Study, made up of men aged 40 to 59 years, enrolled and first examined in 1960 in Italy. Cox models were estimated by: a forcing all factors; b a forward-; and c a backward-stepwise procedure. Observed cases of deaths and of survivors were computed in decile classes of estimated risk. Forced and stepwise NN were run and compared by C-statistics (ROC analysis with the Cox models. Out of 1591 men, 1447 died. Model global accuracies were extremely high by all methods (ROCs > 0.810 but there was no clear-cut superiority of any model to predict 45-ACM. The highest ROCs (> 0.838 were observed by NN. There were inter-model variations to select predictive covariates: whereas all models concurred to define the role of 10 covariates (mainly cardiovascular risk factors, family history, heart rate and minor ECG abnormalities were not contributors by Cox models but were so by forced NN. Forced expiratory volume and arm

Coupled variable selection for regression modeling of complex treatment patterns in a clinical cancer registry.

Science.gov (United States)

Schmidtmann, I; Elsäßer, A; Weinmann, A; Binder, H

2014-12-30

For determining a manageable set of covariates potentially influential with respect to a time-to-event endpoint, Cox proportional hazards models can be combined with variable selection techniques, such as stepwise forward selection or backward elimination based on p-values, or regularized regression techniques such as component-wise boosting. Cox regression models have also been adapted for dealing with more complex event patterns, for example, for competing risks settings with separate, cause-specific hazard models for each event type, or for determining the prognostic effect pattern of a variable over different landmark times, with one conditional survival model for each landmark. Motivated by a clinical cancer registry application, where complex event patterns have to be dealt with and variable selection is needed at the same time, we propose a general approach for linking variable selection between several Cox models. Specifically, we combine score statistics for each covariate across models by Fisher's method as a basis for variable selection. This principle is implemented for a stepwise forward selection approach as well as for a regularized regression technique. In an application to data from hepatocellular carcinoma patients, the coupled stepwise approach is seen to facilitate joint interpretation of the different cause-specific Cox models. In conditional survival models at landmark times, which address updates of prediction as time progresses and both treatment and other potential explanatory variables may change, the coupled regularized regression approach identifies potentially important, stably selected covariates together with their effect time pattern, despite having only a small number of events. These results highlight the promise of the proposed approach for coupling variable selection between Cox models, which is particularly relevant for modeling for clinical cancer registries with their complex event patterns. Copyright © 2014 John Wiley & Sons

Two Paradoxes in Linear Regression Analysis

Science.gov (United States)

FENG, Ge; PENG, Jing; TU, Dongke; ZHENG, Julia Z.; FENG, Changyong

2016-01-01

Summary Regression is one of the favorite tools in applied statistics. However, misuse and misinterpretation of results from regression analysis are common in biomedical research. In this paper we use statistical theory and simulation studies to clarify some paradoxes around this popular statistical method. In particular, we show that a widely used model selection procedure employed in many publications in top medical journals is wrong. Formal procedures based on solid statistical theory should be used in model selection. PMID:28638214

Matérn thinned Cox processes

DEFF Research Database (Denmark)

Andersen, Ina Trolle; Hahn, Ute

2016-01-01

and hard core behaviour can be achieved by applying a dependent Matérn thinning to a Cox process. An exact formula for the intensity of a Matérn thinned shot noise Cox process is derived from the Palm distribution. For the more general class of Matérn thinned Cox processes, formulae for the intensity...

Matérn thinned Cox processes

DEFF Research Database (Denmark)

Andersen, Ina Trolle; Hahn, Ute

of clustering and hard core behaviour can be achieved by applying a dependent Matérn thinning to a Cox process. An exact formula for the intensity of a Matérn thinned shot noise Cox process is derived from the Palm distribution. For the more general class of Matérn thinned Cox processes, formulae...

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

Science.gov (United States)

Linden, Ariel; Yarnold, Paul R

2017-12-01

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

Using Dominance Analysis to Determine Predictor Importance in Logistic Regression

Science.gov (United States)

Azen, Razia; Traxel, Nicole

2009-01-01

This article proposes an extension of dominance analysis that allows researchers to determine the relative importance of predictors in logistic regression models. Criteria for choosing logistic regression R[superscript 2] analogues were determined and measures were selected that can be used to perform dominance analysis in logistic regression. A…

Linear regression and sensitivity analysis in nuclear reactor design

International Nuclear Information System (INIS)

Kumar, Akansha; Tsvetkov, Pavel V.; McClarren, Ryan G.

2015-01-01

Highlights: • Presented a benchmark for the applicability of linear regression to complex systems. • Applied linear regression to a nuclear reactor power system. • Performed neutronics, thermal–hydraulics, and energy conversion using Brayton’s cycle for the design of a GCFBR. • Performed detailed sensitivity analysis to a set of parameters in a nuclear reactor power system. • Modeled and developed reactor design using MCNP, regression using R, and thermal–hydraulics in Java. - Abstract: The paper presents a general strategy applicable for sensitivity analysis (SA), and uncertainity quantification analysis (UA) of parameters related to a nuclear reactor design. This work also validates the use of linear regression (LR) for predictive analysis in a nuclear reactor design. The analysis helps to determine the parameters on which a LR model can be fit for predictive analysis. For those parameters, a regression surface is created based on trial data and predictions are made using this surface. A general strategy of SA to determine and identify the influential parameters those affect the operation of the reactor is mentioned. Identification of design parameters and validation of linearity assumption for the application of LR of reactor design based on a set of tests is performed. The testing methods used to determine the behavior of the parameters can be used as a general strategy for UA, and SA of nuclear reactor models, and thermal hydraulics calculations. A design of a gas cooled fast breeder reactor (GCFBR), with thermal–hydraulics, and energy transfer has been used for the demonstration of this method. MCNP6 is used to simulate the GCFBR design, and perform the necessary criticality calculations. Java is used to build and run input samples, and to extract data from the output files of MCNP6, and R is used to perform regression analysis and other multivariate variance, and analysis of the collinearity of data

Least Squares Adjustment: Linear and Nonlinear Weighted Regression Analysis

DEFF Research Database (Denmark)

Nielsen, Allan Aasbjerg

2007-01-01

This note primarily describes the mathematics of least squares regression analysis as it is often used in geodesy including land surveying and satellite positioning applications. In these fields regression is often termed adjustment. The note also contains a couple of typical land surveying...... and satellite positioning application examples. In these application areas we are typically interested in the parameters in the model typically 2- or 3-D positions and not in predictive modelling which is often the main concern in other regression analysis applications. Adjustment is often used to obtain...... the clock error) and to obtain estimates of the uncertainty with which the position is determined. Regression analysis is used in many other fields of application both in the natural, the technical and the social sciences. Examples may be curve fitting, calibration, establishing relationships between...

Design and analysis of experiments classical and regression approaches with SAS

CERN Document Server

Onyiah, Leonard C

2008-01-01

Introductory Statistical Inference and Regression Analysis Elementary Statistical Inference Regression Analysis Experiments, the Completely Randomized Design (CRD)-Classical and Regression Approaches Experiments Experiments to Compare Treatments Some Basic Ideas Requirements of a Good Experiment One-Way Experimental Layout or the CRD: Design and Analysis Analysis of Experimental Data (Fixed Effects Model) Expected Values for the Sums of Squares The Analysis of Variance (ANOVA) Table Follow-Up Analysis to Check fo

A computational prospect to aspirin side effects: aspirin and COX-1 interaction analysis based on non-synonymous SNPs.

Science.gov (United States)

Marjan, Mojtabavi Naeini; Hamzeh, Mesrian Tanha; Rahman, Emamzadeh; Sadeq, Vallian

2014-08-01

Aspirin (ASA) is a commonly used nonsteroidal anti-inflammatory drug (NSAID), which exerts its therapeutic effects through inhibition of cyclooxygenase (COX) isoform 2 (COX-2), while the inhibition of COX-1 by ASA leads to apparent side effects. In the present study, the relationship between COX-1 non-synonymous single nucleotide polymorphisms (nsSNPs) and aspirin related side effects was investigated. The functional impacts of 37 nsSNPs on aspirin inhibition potency of COX-1 with COX-1/aspirin molecular docking were computationally analyzed, and each SNP was scored based on DOCK Amber score. The data predicted that 22 nsSNPs could reduce COX-1 inhibition, while 15 nsSNPs showed increasing inhibition level in comparison to the regular COX-1 protein. In order to perform a comparing state, the Amber scores for two Arg119 mutants (R119A and R119Q) were also calculated. Moreover, among nsSNP variants, rs117122585 represented the closest Amber score to R119A mutant. A separate docking computation validated the score and represented a new binding position for ASA that acetyl group was located within the distance of 3.86Å from Ser529 OH group. This could predict an associated loss of activity of ASA through this nsSNP variant. Our data represent a computational sub-population pattern for aspirin COX-1 related side effects, and provide basis for further research on COX-1/ASA interaction. Copyright © 2014 Elsevier Ltd. All rights reserved.

Sparse Regression by Projection and Sparse Discriminant Analysis

KAUST Repository

Qi, Xin

2015-04-03

© 2015, © American Statistical Association, Institute of Mathematical Statistics, and Interface Foundation of North America. Recent years have seen active developments of various penalized regression methods, such as LASSO and elastic net, to analyze high-dimensional data. In these approaches, the direction and length of the regression coefficients are determined simultaneously. Due to the introduction of penalties, the length of the estimates can be far from being optimal for accurate predictions. We introduce a new framework, regression by projection, and its sparse version to analyze high-dimensional data. The unique nature of this framework is that the directions of the regression coefficients are inferred first, and the lengths and the tuning parameters are determined by a cross-validation procedure to achieve the largest prediction accuracy. We provide a theoretical result for simultaneous model selection consistency and parameter estimation consistency of our method in high dimension. This new framework is then generalized such that it can be applied to principal components analysis, partial least squares, and canonical correlation analysis. We also adapt this framework for discriminant analysis. Compared with the existing methods, where there is relatively little control of the dependency among the sparse components, our method can control the relationships among the components. We present efficient algorithms and related theory for solving the sparse regression by projection problem. Based on extensive simulations and real data analysis, we demonstrate that our method achieves good predictive performance and variable selection in the regression setting, and the ability to control relationships between the sparse components leads to more accurate classification. In supplementary materials available online, the details of the algorithms and theoretical proofs, and R codes for all simulation studies are provided.

The Use of Nonparametric Kernel Regression Methods in Econometric Production Analysis

DEFF Research Database (Denmark)

Czekaj, Tomasz Gerard

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

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...

Decomposition of variance for spatial Cox processes

DEFF Research Database (Denmark)

Jalilian, Abdollah; Guan, Yongtao; Waagepetersen, Rasmus

Spatial Cox point processes is a natural framework for quantifying the various sources of variation governing the spatial distribution of rain forest trees. We introduce a general criterion for variance decomposition for spatial Cox processes and apply it to specific Cox process models...

Decomposition of variance for spatial Cox processes

DEFF Research Database (Denmark)

Jalilian, Abdollah; Guan, Yongtao; Waagepetersen, Rasmus

2013-01-01

Spatial Cox point processes is a natural framework for quantifying the various sources of variation governing the spatial distribution of rain forest trees. We introduce a general criterion for variance decomposition for spatial Cox processes and apply it to specific Cox process models...

Decomposition of variance for spatial Cox processes

DEFF Research Database (Denmark)

Jalilian, Abdollah; Guan, Yongtao; Waagepetersen, Rasmus

Spatial Cox point processes is a natural framework for quantifying the various sources of variation governing the spatial distribution of rain forest trees. We introducea general criterion for variance decomposition for spatial Cox processes and apply it to specific Cox process models with additive...

General Nature of Multicollinearity in Multiple Regression Analysis.

Science.gov (United States)

Liu, Richard

1981-01-01

Discusses multiple regression, a very popular statistical technique in the field of education. One of the basic assumptions in regression analysis requires that independent variables in the equation should not be highly correlated. The problem of multicollinearity and some of the solutions to it are discussed. (Author)

Radiolabeled COX-2 Inhibitors for Non-Invasive Visualization of COX-2 Expression and Activity — A Critical Update

Directory of Open Access Journals (Sweden)

Torsten Kniess

2013-05-01

Full Text Available Cyclooxygenase-2 (COX-2 is a key player in inflammation. Its overexpression is directly associated with various inflammatory diseases and, additionally, with several processes of carcinogenesis. The development of new selective COX-2 inhibitors (COXIBs for use in cancer treatment is in the focus of the medicinal chemistry research field. For this purpose, a set of methods is available to determine COX-2 expression and activity in vitro and ex vivo but it is still a problem to functionally characterize COX-2 in vivo. This review focusses on imaging agents targeting COX-2 which have been developed for positron emission tomography (PET and single photon emission computed tomography (SPECT since 2005. The literature reveals that different radiochemical methods are available to synthesize COXIBs radiolabeled with fluorine-18, carbon-11, and isotopes of radioiodine. Unfortunately, most of the compounds tested did not show sufficient stability in vivo due to de[18F]fluorination or de[11C]methylation or they failed to bind specifically in the target region. So, suitable stability in vivo, matching lipophilicity for the target compartment and both high affinity and selectivity for COX-2 were identified as prominent criteria for radiotracer development. Up to now, it is not clear what approach and which model is the most suited to evaluate COX-2 targeting imaging agents in vivo. However, for proof of principle it has been shown that some radiolabeled compounds can bind specifically in COX-2 overexpressing tissue which gives hope for future work in this field.

Bioinformatics and Phylogenetic Analysis of Mitochondrial COX3 Gene in Iranian Camelus Dromedaries and Camelus Bactrianus

Directory of Open Access Journals (Sweden)

Tooba Abbassi-Daloii

2016-11-01

Full Text Available Introduction Camels belong to the family of Camelidae, suborder of Tylopoda, order of artiodactyla and class of mammalians. The family Camelidae has two old world species, double-humped camel (CAMELUS BACTRIANUS and single-humped camel (CAMELUS DROMEDARIES and four new world (tribe Lamini species, guanaco (LAMA GUANICOE, llama (LAMA GLAMA, alpaca (LAMA PACOS and vicuna (LAMA VICUGNA or VICUGNA VICUGNA at present time. The single-humped camel inhabits Afro-Arabia, Ethiopia and west Central Asia while the double-humped inhabits eastern Central Asia and China. Camel has been historically and economically an important species worldwide especially in the Africa and Asia. Camel has unique characteristics enable it to adapt its desert environment. The total worldwide camel population at present estimated to be about 23 million in the world. Somalia and Sudan together hold approximately 50% of the whole camel population. In the last 40 years, the number of camels has increased by almost 45%. Iranian native species are considered as part of the national capital so their preservation is so important. Due to severe decrease in their population in some areas, more attention to conservation genetics perspective of these species is very important. The aim of this study was to bioinformatics and phylogenetic analysis of mitochondrial sequence of cytochrome c oxidase subunit 3 (COX3 in Iranian Camelus dromedaries and Camelus bactrianus. Materials and Methods For this purpose 10 blood samples were collected from each species (totally 20 samples. After DNA extraction, the fragment with 979 bp length from mitochondrial DNA was amplified using polymerase chain reaction. Sequencing was performed by automated Sanger methods then the obtained sequences were compared with sequences from other studies. The nucleotide sequences obtained were edited using the PHRED software (http://www.phrap.org /phredphrapconsed.html. After editing, basic local alignment search tool

On logistic regression analysis of dichotomized responses.

Science.gov (United States)

Lu, Kaifeng

2017-01-01

We study the properties of treatment effect estimate in terms of odds ratio at the study end point from logistic regression model adjusting for the baseline value when the underlying continuous repeated measurements follow a multivariate normal distribution. Compared with the analysis that does not adjust for the baseline value, the adjusted analysis produces a larger treatment effect as well as a larger standard error. However, the increase in standard error is more than offset by the increase in treatment effect so that the adjusted analysis is more powerful than the unadjusted analysis for detecting the treatment effect. On the other hand, the true adjusted odds ratio implied by the normal distribution of the underlying continuous variable is a function of the baseline value and hence is unlikely to be able to be adequately represented by a single value of adjusted odds ratio from the logistic regression model. In contrast, the risk difference function derived from the logistic regression model provides a reasonable approximation to the true risk difference function implied by the normal distribution of the underlying continuous variable over the range of the baseline distribution. We show that different metrics of treatment effect have similar statistical power when evaluated at the baseline mean. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

The Moxie of Kathy Cox

Science.gov (United States)

Johns, Stephanie

2010-01-01

Kathy Cox, the superintendent of schools for Georgia, believes "excellence is not an accident". She made a name for herself by winning $1 million proving she was smarter than a fifth-grader on a popular television show. This article presents a profile of Cox, her family, her role as school superintendent, and her accomplishments.…

Approximate median regression for complex survey data with skewed response.

Science.gov (United States)

Fraser, Raphael André; Lipsitz, Stuart R; Sinha, Debajyoti; Fitzmaurice, Garrett M; Pan, Yi

2016-12-01

The ready availability of public-use data from various large national complex surveys has immense potential for the assessment of population characteristics using regression models. Complex surveys can be used to identify risk factors for important diseases such as cancer. Existing statistical methods based on estimating equations and/or utilizing resampling methods are often not valid with survey data due to complex survey design features. That is, stratification, multistage sampling, and weighting. In this article, we accommodate these design features in the analysis of highly skewed response variables arising from large complex surveys. Specifically, we propose a double-transform-both-sides (DTBS)'based estimating equations approach to estimate the median regression parameters of the highly skewed response; the DTBS approach applies the same Box-Cox type transformation twice to both the outcome and regression function. The usual sandwich variance estimate can be used in our approach, whereas a resampling approach would be needed for a pseudo-likelihood based on minimizing absolute deviations (MAD). Furthermore, the approach is relatively robust to the true underlying distribution, and has much smaller mean square error than a MAD approach. The method is motivated by an analysis of laboratory data on urinary iodine (UI) concentration from the National Health and Nutrition Examination Survey. © 2016, The International Biometric Society.

Analysis of a genetically structured variance heterogeneity model using the Box-Cox transformation.

Science.gov (United States)

Yang, Ye; Christensen, Ole F; Sorensen, Daniel

2011-02-01

Over recent years, statistical support for the presence of genetic factors operating at the level of the environmental variance has come from fitting a genetically structured heterogeneous variance model to field or experimental data in various species. Misleading results may arise due to skewness of the marginal distribution of the data. To investigate how the scale of measurement affects inferences, the genetically structured heterogeneous variance model is extended to accommodate the family of Box-Cox transformations. Litter size data in rabbits and pigs that had previously been analysed in the untransformed scale were reanalysed in a scale equal to the mode of the marginal posterior distribution of the Box-Cox parameter. In the rabbit data, the statistical evidence for a genetic component at the level of the environmental variance is considerably weaker than that resulting from an analysis in the original metric. In the pig data, the statistical evidence is stronger, but the coefficient of correlation between additive genetic effects affecting mean and variance changes sign, compared to the results in the untransformed scale. The study confirms that inferences on variances can be strongly affected by the presence of asymmetry in the distribution of data. We recommend that to avoid one important source of spurious inferences, future work seeking support for a genetic component acting on environmental variation using a parametric approach based on normality assumptions confirms that these are met.

On two flexible methods of 2-dimensional regression analysis

Czech Academy of Sciences Publication Activity Database

Volf, Petr

2012-01-01

Roč. 18, č. 4 (2012), s. 154-164 ISSN 1803-9782 Grant - others:GA ČR(CZ) GAP209/10/2045 Institutional support: RVO:67985556 Keywords : regression analysis * Gordon surface * prediction error * projection pursuit Subject RIV: BB - Applied Statistics, Operational Research http://library.utia.cas.cz/separaty/2013/SI/volf-on two flexible methods of 2-dimensional regression analysis.pdf

Resting-state functional magnetic resonance imaging: the impact of regression analysis.

Science.gov (United States)

Yeh, Chia-Jung; Tseng, Yu-Sheng; Lin, Yi-Ru; Tsai, Shang-Yueh; Huang, Teng-Yi

2015-01-01

To investigate the impact of regression methods on resting-state functional magnetic resonance imaging (rsfMRI). During rsfMRI preprocessing, regression analysis is considered effective for reducing the interference of physiological noise on the signal time course. However, it is unclear whether the regression method benefits rsfMRI analysis. Twenty volunteers (10 men and 10 women; aged 23.4 ± 1.5 years) participated in the experiments. We used node analysis and functional connectivity mapping to assess the brain default mode network by using five combinations of regression methods. The results show that regressing the global mean plays a major role in the preprocessing steps. When a global regression method is applied, the values of functional connectivity are significantly lower (P ≤ .01) than those calculated without a global regression. This step increases inter-subject variation and produces anticorrelated brain areas. rsfMRI data processed using regression should be interpreted carefully. The significance of the anticorrelated brain areas produced by global signal removal is unclear. Copyright © 2014 by the American Society of Neuroimaging.

Development of a User Interface for a Regression Analysis Software Tool

Science.gov (United States)

Ulbrich, Norbert Manfred; Volden, Thomas R.

2010-01-01

An easy-to -use user interface was implemented in a highly automated regression analysis tool. The user interface was developed from the start to run on computers that use the Windows, Macintosh, Linux, or UNIX operating system. Many user interface features were specifically designed such that a novice or inexperienced user can apply the regression analysis tool with confidence. Therefore, the user interface s design minimizes interactive input from the user. In addition, reasonable default combinations are assigned to those analysis settings that influence the outcome of the regression analysis. These default combinations will lead to a successful regression analysis result for most experimental data sets. The user interface comes in two versions. The text user interface version is used for the ongoing development of the regression analysis tool. The official release of the regression analysis tool, on the other hand, has a graphical user interface that is more efficient to use. This graphical user interface displays all input file names, output file names, and analysis settings for a specific software application mode on a single screen which makes it easier to generate reliable analysis results and to perform input parameter studies. An object-oriented approach was used for the development of the graphical user interface. This choice keeps future software maintenance costs to a reasonable limit. Examples of both the text user interface and graphical user interface are discussed in order to illustrate the user interface s overall design approach.

LC-MS/MS confirms that COX-1 drives vascular prostacyclin whilst gene expression pattern reveals non-vascular sites of COX-2 expression.

Directory of Open Access Journals (Sweden)

Nicholas S Kirkby

Full Text Available There are two schools of thought regarding the cyclooxygenase (COX isoform active in the vasculature. Using urinary prostacyclin markers some groups have proposed that vascular COX-2 drives prostacyclin release. In contrast, we and others have found that COX-1, not COX-2, is responsible for vascular prostacyclin production. Our experiments have relied on immunoassays to detect the prostacyclin breakdown product, 6-keto-PGF1α and antibodies to detect COX-2 protein. Whilst these are standard approaches, used by many laboratories, antibody-based techniques are inherently indirect and have been criticized as limiting the conclusions that can be drawn. To address this question, we measured production of prostanoids, including 6-keto-PGF1α, by isolated vessels and in the circulation in vivo using liquid chromatography tandem mass spectrometry and found values essentially identical to those obtained by immunoassay. In addition, we determined expression from the Cox2 gene using a knockin reporter mouse in which luciferase activity reflects Cox2 gene expression. Using this we confirm the aorta to be essentially devoid of Cox2 driven expression. In contrast, thymus, renal medulla, and regions of the brain and gut expressed substantial levels of luciferase activity, which correlated well with COX-2-dependent prostanoid production. These data are consistent with the conclusion that COX-1 drives vascular prostacyclin release and puts the sparse expression of Cox2 in the vasculature in the context of the rest of the body. In doing so, we have identified the thymus, gut, brain and other tissues as target organs for consideration in developing a new understanding of how COX-2 protects the cardiovascular system.

Method for nonlinear exponential regression analysis

Science.gov (United States)

Junkin, B. G.

1972-01-01

Two computer programs developed according to two general types of exponential models for conducting nonlinear exponential regression analysis are described. Least squares procedure is used in which the nonlinear problem is linearized by expanding in a Taylor series. Program is written in FORTRAN 5 for the Univac 1108 computer.

Regression of uveal malignant melanomas following cobalt-60 plaque. Correlates between acoustic spectrum analysis and tumor regression

International Nuclear Information System (INIS)

Coleman, D.J.; Lizzi, F.L.; Silverman, R.H.; Ellsworth, R.M.; Haik, B.G.; Abramson, D.H.; Smith, M.E.; Rondeau, M.J.

1985-01-01

Parameters derived from computer analysis of digital radio-frequency (rf) ultrasound scan data of untreated uveal malignant melanomas were examined for correlations with tumor regression following cobalt-60 plaque. Parameters included tumor height, normalized power spectrum and acoustic tissue type (ATT). Acoustic tissue type was based upon discriminant analysis of tumor power spectra, with spectra of tumors of known pathology serving as a model. Results showed ATT to be correlated with tumor regression during the first 18 months following treatment. Tumors with ATT associated with spindle cell malignant melanoma showed over twice the percentage reduction in height as those with ATT associated with mixed/epithelioid melanomas. Pre-treatment height was only weakly correlated with regression. Additionally, significant spectral changes were observed following treatment. Ultrasonic spectrum analysis thus provides a noninvasive tool for classification, prediction and monitoring of tumor response to cobalt-60 plaque

Detecting overdispersion in count data: A zero-inflated Poisson regression analysis

Science.gov (United States)

Afiqah Muhamad Jamil, Siti; Asrul Affendi Abdullah, M.; Kek, Sie Long; Nor, Maria Elena; Mohamed, Maryati; Ismail, Norradihah

2017-09-01

This study focusing on analysing count data of butterflies communities in Jasin, Melaka. In analysing count dependent variable, the Poisson regression model has been known as a benchmark model for regression analysis. Continuing from the previous literature that used Poisson regression analysis, this study comprising the used of zero-inflated Poisson (ZIP) regression analysis to gain acute precision on analysing the count data of butterfly communities in Jasin, Melaka. On the other hands, Poisson regression should be abandoned in the favour of count data models, which are capable of taking into account the extra zeros explicitly. By far, one of the most popular models include ZIP regression model. The data of butterfly communities which had been called as the number of subjects in this study had been taken in Jasin, Melaka and consisted of 131 number of subjects visits Jasin, Melaka. Since the researchers are considering the number of subjects, this data set consists of five families of butterfly and represent the five variables involve in the analysis which are the types of subjects. Besides, the analysis of ZIP used the SAS procedure of overdispersion in analysing zeros value and the main purpose of continuing the previous study is to compare which models would be better than when exists zero values for the observation of the count data. The analysis used AIC, BIC and Voung test of 5% level significance in order to achieve the objectives. The finding indicates that there is a presence of over-dispersion in analysing zero value. The ZIP regression model is better than Poisson regression model when zero values exist.

An Analysis of Bank Service Satisfaction Based on Quantile Regression and Grey Relational Analysis

Directory of Open Access Journals (Sweden)

Wen-Tsao Pan

2016-01-01

Full Text Available Bank service satisfaction is vital to the success of a bank. In this paper, we propose to use the grey relational analysis to gauge the levels of service satisfaction of the banks. With the grey relational analysis, we compared the effects of different variables on service satisfaction. We gave ranks to the banks according to their levels of service satisfaction. We further used the quantile regression model to find the variables that affected the satisfaction of a customer at a specific quantile of satisfaction level. The result of the quantile regression analysis provided a bank manager with information to formulate policies to further promote satisfaction of the customers at different quantiles of satisfaction level. We also compared the prediction accuracies of the regression models at different quantiles. The experiment result showed that, among the seven quantile regression models, the median regression model has the best performance in terms of RMSE, RTIC, and CE performance measures.

Research and analyze of physical health using multiple regression analysis

Directory of Open Access Journals (Sweden)

T. S. Kyi

2014-01-01

Full Text Available This paper represents the research which is trying to create a mathematical model of the "healthy people" using the method of regression analysis. The factors are the physical parameters of the person (such as heart rate, lung capacity, blood pressure, breath holding, weight height coefficient, flexibility of the spine, muscles of the shoulder belt, abdominal muscles, squatting, etc.., and the response variable is an indicator of physical working capacity. After performing multiple regression analysis, obtained useful multiple regression models that can predict the physical performance of boys the aged of fourteen to seventeen years. This paper represents the development of regression model for the sixteen year old boys and analyzed results.

Density functional theory analysis and molecular docking evaluation of 1-(2, 5-dichloro-4-sulfophenyl)-3-methyl-5-pyrazolone as COX2 inhibitor against inflammatory diseases

Science.gov (United States)

Kavitha, T.; Velraj, G.

2017-08-01

The molecular structure of 1-(2, 5-Dichloro-4-Sulfophenyl)-3-Methyl-5-Pyrazolone (DSMP) was optimized using DFT/B3LYP/6-31++G(d,p) level and its corresponding experimental as well as theoretical FT-IR, FT-Raman vibrational frequencies and UV-Vis spectral analysis were carried out. The vibrational assignments and total energy distributions of each vibration were presented with the aid of Veda 4xx software. The molecular electrostatic potential, HOMO-LUMO energies, global and local reactivity descriptors and natural bond orbitals were analyzed in order to find the most possible reactive sites of the molecule and it was found that DSMP molecule possess enhanced nucleophilic activity. One of the common known COX2 inhibitor, celecoxib (CXB) was also found to exhibit similar reactivity properties and hence DSMP was also expected to inhibit COX enzymes. In order to detect the COX inhibition nature of DSMP, molecular docking analysis was carried out with the help of Autodock software. For that, the optimized structure was in turn used for docking DSMP with COX enzymes. The binding energy scores and inhibitory constant values reveal that the DSMP molecule possess good binding affinity and low inhibition constant towards COX2 enzyme and hence it can be used as an anti-inflammatory drug after carrying out necessary biological tests.

An improved multiple linear regression and data analysis computer program package

Science.gov (United States)

Sidik, S. M.

1972-01-01

NEWRAP, an improved version of a previous multiple linear regression program called RAPIER, CREDUC, and CRSPLT, allows for a complete regression analysis including cross plots of the independent and dependent variables, correlation coefficients, regression coefficients, analysis of variance tables, t-statistics and their probability levels, rejection of independent variables, plots of residuals against the independent and dependent variables, and a canonical reduction of quadratic response functions useful in optimum seeking experimentation. A major improvement over RAPIER is that all regression calculations are done in double precision arithmetic.

Molecular basis of cyclooxygenase enzymes (COXs) selective inhibition

Science.gov (United States)

Limongelli, Vittorio; Bonomi, Massimiliano; Marinelli, Luciana; Gervasio, Francesco Luigi; Cavalli, Andrea; Novellino, Ettore; Parrinello, Michele

2010-01-01

The widely used nonsteroidal anti-inflammatory drugs block the cyclooxygenase enzymes (COXs) and are clinically used for the treatment of inflammation, pain, and cancers. A selective inhibition of the different isoforms, particularly COX-2, is desirable, and consequently a deeper understanding of the molecular basis of selective inhibition is of great demand. Using an advanced computational technique we have simulated the full dissociation process of a highly potent and selective inhibitor, SC-558, in both COX-1 and COX-2. We have found a previously unreported alternative binding mode in COX-2 explaining the time-dependent inhibition exhibited by this class of inhibitors and consequently their long residence time inside this isoform. Our metadynamics-based approach allows us to illuminate the highly dynamical character of the ligand/protein recognition process, thus explaining a wealth of experimental data and paving the way to an innovative strategy for designing new COX inhibitors with tuned selectivity. PMID:20215464

COX-2 and p53 in human sinonasal cancer

DEFF Research Database (Denmark)

Holmila, Reetta; Cyr, Diane; Luce, Danièle

2008-01-01

The causal role of wood-dust exposure in sinonasal cancer (SNC) has been established in epidemiological studies, but the mechanisms of SNC carcinogenesis are still largely unknown. Increased amounts of COX-2 are found in both premalignant and malignant tissues, and experimental evidence link COX-2...... to development of cancer. Many signals that activate COX-2 also induce tumor suppressor p53, a transcription factor central in cellular stress response. We investigated COX-2 and p53 expressions by immunohistochemistry in 50 SNCs (23 adenocarcinomas, and 27 squamous cell carcinomas (SCC); 48 analyzed for COX-2...... displayed adenocarcinoma. COX-2 was expressed at higher levels in adenocarcinoma as compared to SSC (p COX-2 expression showed significant association with occupational exposure to wood dust (p = 0.024), and with nonsmoking status (p = 0.001). No statistically significant associations between...

Effects of electroacupuncture on luteal regression and steroidogenesis in ovarian hyperstimulation syndrome model rat.

Science.gov (United States)

Huang, Xuan; Chen, Li; Xia, You-Bing; Xie, Min; Sun, Qin; Yao, Bing

2018-03-15

Electroacupuncture (EA) is an effective and safe therapeutic method widely used for treating clinical diseases. Previously, we found that EA could decrease serum hormones and reduce ovarian size in ovarian hyperstimulation syndrome (OHSS) rat model. Nevertheless, the mechanisms that contribute to these improvements remain unclear. HE staining was used to count the number of corpora lutea (CL) and follicles. Immunohistochemical and ELISA were applied to examine luteal functional and structural regression. Immunoprecipitation was used for analyzing the interaction between NPY (neuropeptide Y) and COX-2; western blotting and qRT-PCR were used to evaluate the expressions of steroidogenic enzymes and PKA/CREB pathway. EA treatment significantly reduced the ovarian weight and the number of CL, also decreased ovarian and serum levels of PGE2 and COX-2 expression; increased ovarian PGF2α levels and PGF2α/PGE2 ratio; decreased PCNA expression and distribution; and increased cyclin regulatory inhibitor p27 expression to have further effect on the luteal formation, and promote luteal functional and structural regression. Moreover, expression of COX-2 in ovaries was possessed interactivity increased expression of NPY. Furthermore, EA treatment lowered the serum hormone levels, inhibited PKA/CREB pathway and decreased the expressions of steroidogenic enzymes. Hence, interaction with COX-2, NPY may affect the levels of PGF2α and PGE2 as well as impact the proliferation of granulosa cells in ovaries, thus further reducing the luteal formation, and promoting luteal structural and functional regression, as well as the ovarian steroidogenesis following EA treatment. EA treatment could be an option for preventing OHSS in ART. Copyright © 2018 Elsevier Inc. All rights reserved.

Estimating functions for inhomogeneous Cox processes

DEFF Research Database (Denmark)

Waagepetersen, Rasmus

2006-01-01

Estimation methods are reviewed for inhomogeneous Cox processes with tractable first and second order properties. We illustrate the various suggestions by means of data examples.......Estimation methods are reviewed for inhomogeneous Cox processes with tractable first and second order properties. We illustrate the various suggestions by means of data examples....

Functional data analysis of generalized regression quantiles

KAUST Repository

Guo, Mengmeng; Zhou, Lan; Huang, Jianhua Z.; Hä rdle, Wolfgang Karl

2013-01-01

Generalized regression quantiles, including the conditional quantiles and expectiles as special cases, are useful alternatives to the conditional means for characterizing a conditional distribution, especially when the interest lies in the tails. We develop a functional data analysis approach to jointly estimate a family of generalized regression quantiles. Our approach assumes that the generalized regression quantiles share some common features that can be summarized by a small number of principal component functions. The principal component functions are modeled as splines and are estimated by minimizing a penalized asymmetric loss measure. An iterative least asymmetrically weighted squares algorithm is developed for computation. While separate estimation of individual generalized regression quantiles usually suffers from large variability due to lack of sufficient data, by borrowing strength across data sets, our joint estimation approach significantly improves the estimation efficiency, which is demonstrated in a simulation study. The proposed method is applied to data from 159 weather stations in China to obtain the generalized quantile curves of the volatility of the temperature at these stations. © 2013 Springer Science+Business Media New York.

Functional data analysis of generalized regression quantiles

KAUST Repository

Guo, Mengmeng

2013-11-05

Generalized regression quantiles, including the conditional quantiles and expectiles as special cases, are useful alternatives to the conditional means for characterizing a conditional distribution, especially when the interest lies in the tails. We develop a functional data analysis approach to jointly estimate a family of generalized regression quantiles. Our approach assumes that the generalized regression quantiles share some common features that can be summarized by a small number of principal component functions. The principal component functions are modeled as splines and are estimated by minimizing a penalized asymmetric loss measure. An iterative least asymmetrically weighted squares algorithm is developed for computation. While separate estimation of individual generalized regression quantiles usually suffers from large variability due to lack of sufficient data, by borrowing strength across data sets, our joint estimation approach significantly improves the estimation efficiency, which is demonstrated in a simulation study. The proposed method is applied to data from 159 weather stations in China to obtain the generalized quantile curves of the volatility of the temperature at these stations. © 2013 Springer Science+Business Media New York.

Analysis of Relationship Between Personality and Favorite Places with Poisson Regression Analysis

Directory of Open Access Journals (Sweden)

Yoon Song Ha

2018-01-01

Full Text Available A relationship between human personality and preferred locations have been a long conjecture for human mobility research. In this paper, we analyzed the relationship between personality and visiting place with Poisson Regression. Poisson Regression can analyze correlation between countable dependent variable and independent variable. For this analysis, 33 volunteers provided their personality data and 49 location categories data are used. Raw location data is preprocessed to be normalized into rates of visit and outlier data is prunned. For the regression analysis, independent variables are personality data and dependent variables are preprocessed location data. Several meaningful results are found. For example, persons with high tendency of frequent visiting to university laboratory has personality with high conscientiousness and low openness. As well, other meaningful location categories are presented in this paper.

Functional form diagnostics for Cox's proportional hazards model.

Science.gov (United States)

León, Larry F; Tsai, Chih-Ling

2004-03-01

We propose a new type of residual and an easily computed functional form test for the Cox proportional hazards model. The proposed test is a modification of the omnibus test for testing the overall fit of a parametric regression model, developed by Stute, González Manteiga, and Presedo Quindimil (1998, Journal of the American Statistical Association93, 141-149), and is based on what we call censoring consistent residuals. In addition, we develop residual plots that can be used to identify the correct functional forms of covariates. We compare our test with the functional form test of Lin, Wei, and Ying (1993, Biometrika80, 557-572) in a simulation study. The practical application of the proposed residuals and functional form test is illustrated using both a simulated data set and a real data set.

application of multilinear regression analysis in modeling of soil

African Journals Online (AJOL)

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Accordingly [1, 3] in their work, they applied linear regression ... (MLRA) is a statistical technique that uses several explanatory ... order to check this, they adopted bivariate correlation analysis .... groups, namely A-1 through A-7, based on their relative expected ..... Multivariate Regression in Gorgan Province North of Iran” ...

Multiple regression analysis of Jominy hardenability data for boron treated steels

International Nuclear Information System (INIS)

Komenda, J.; Sandstroem, R.; Tukiainen, M.

1997-01-01

The relations between chemical composition and their hardenability of boron treated steels have been investigated using a multiple regression analysis method. A linear model of regression was chosen. The free boron content that is effective for the hardenability was calculated using a model proposed by Jansson. The regression analysis for 1261 steel heats provided equations that were statistically significant at the 95% level. All heats met the specification according to the nordic countries producers classification. The variation in chemical composition explained typically 80 to 90% of the variation in the hardenability. In the regression analysis elements which did not significantly contribute to the calculated hardness according to the F test were eliminated. Carbon, silicon, manganese, phosphorus and chromium were of importance at all Jominy distances, nickel, vanadium, boron and nitrogen at distances above 6 mm. After the regression analysis it was demonstrated that very few outliers were present in the data set, i.e. data points outside four times the standard deviation. The model has successfully been used in industrial practice replacing some of the necessary Jominy tests. (orig.)

The cardiac copper chaperone proteins Sco1 and CCS are up-regulated, but Cox 1 and Cox4 are down-regulated, by copper deficiency.

Science.gov (United States)

Getz, Jean; Lin, Dingbo; Medeiros, Denis M

2011-10-01

Copper is ferried in a cell complexed to chaperone proteins, and in the heart much copper is required for cytochrome c oxidase (Cox). It is not completely understood how copper status affects the levels of these proteins. Here we determined if dietary copper deficiency could up- or down-regulate select copper chaperone proteins and Cox subunits 1 and 4 in cardiac tissue of rats. Sixteen weanling male Long-Evans rats were randomized into treatment groups, one group receiving a copper-deficient diet (CCS, Sco1, Ctr1, Cox17, Cox1, and Cox4 by SDS-PAGE and Western blotting. No changes were observed in the concentrations of CTR1 and Cox17 between copper-adequate and copper-deficient rats. CCS and Sco1 were up-regulated and Cox1 and Cox4 were both down-regulated as a result of copper deficiency. These data suggest that select chaperone proteins and may be up-regulated, and Cox1 and 4 down-regulated, by a dietary copper deficiency, whereas others appear not to be affected by copper status.

Understanding logistic regression analysis

OpenAIRE

Sperandei, Sandro

2014-01-01

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

Molecular docking and analgesic studies of Erythrina variegata׳s derived phytochemicals with COX enzymes.

Science.gov (United States)

Uddin, Mir Muhammad Nasir; Emran, Talha Bin; Mahib, Muhammad Mamunur Rashid; Dash, Raju

2014-01-01

Secondary metabolites from plants are a good source for the NSAID drug development. We studied the analgesic activity of ethanolic extract of Erythrina variegata L. (Fabaceae) followed by molecular docking analysis. The analgesic activity of Erythrina variegata L. is evaluated by various methods viz., acetic acid-induced writhing test, hot plate and tail immersion test. Subsequently, molecular docking analysis has been performed to identify compounds having activity against COX-1 and COX-2 enzymes by using GOLD docking fitness. The result of preliminary phytochemical screening revealed that the extract contains alkaloids and flavonoids. In analgesic activity tests, the extract at the doses of 50, 100 and 200 mg/kg body weight (b.w.) produced a increase in pain threshold in a dose dependent manner. In acetic acid induced writhing test, the inhibitory effect was similar to the reference drug diclofenac sodium. The extract showed 18.89% writhing inhibitory effect at the dose 200 mg/kg b.w., whereas diclofenac sodium showed 79.42% inhibition of writhing at a dose of 10 mg/kg b.w. The results of tail immersion and hot plate test also showed potential analgesic activity of the extract which is also comparable to the standard drug morphine (5 mg/kg b.w.). Docking studies shows that phaseollin of Erythrina variegata L. has the best fitness score against the COX-1 which is 56.64 and 59.63 for COX- 2 enzyme. Phaseollin of Erythrina variegata L. detected with significant fitness score and hydrogen bonding against COX-1 and COX-2 is reported for further validation.

Combination COX-2 inhibitor and metformin attenuate rate of joint replacement in osteoarthritis with diabetes: A nationwide, retrospective, matched-cohort study in Taiwan.

Science.gov (United States)

Lu, Chieh-Hua; Chung, Chi-Hsiang; Lee, Chien-Hsing; Hsieh, Chang-Hsun; Hung, Yi-Jen; Lin, Fu-Huang; Tsao, Chang-Huei; Hsieh, Po-Shiuan; Chien, Wu-Chien

2018-01-01

Osteoarthritis (OA) is the most common form of arthritis associated with an increased prevalence of type 2 diabetes mellitus (T2DM), however their impact on decreasing joint replacement surgery has yet to be elucidated. This study aimed to investigate if the combination of COX-2 inhibitor and metformin therapy in OA with T2DM were associated with lower the rate of joint replacement surgery than COX-2 inhibitor alone. In total, 968 subjects with OA and T2DM under COX-2 inhibitor and metformin therapy (case group) between 1 January to 31 December 2000 were selected from the National Health Insurance Research Database of Taiwan, along with 1936 patients were the 1:2 gender-, age-, and index year-controls matched without metformin therapy (control group) in this study. Cox proportional hazards analysis was used to compare the rate of receiving joint replacement surgery during 10 years of follow-up. At the end of follow-up, 438 of all enrolled subjects (15.08%) had received the joint replacement surgery, including 124 in the case group (12.81%) and 314 in the control group (16.22%). The case group tended to be associated with lower rate of receiving the joint replacement surgery at the end of follow-up than the control group (p = 0.003). Cox proportional hazards regression (HR) analysis revealed that study subjects under combination therapy with metformin had lower rate of joint replacement surgery (adjusted HR 0.742 (95% CI = 0.601-0.915, p = 0.005)). In the subgroups, study subjects in the combination metformin therapy who were female, good adherence (>80%), lived in the highest urbanization levels of residence, treatment in the hospital center and lower monthly insurance premiums were associated with a lower risk of joint replacement surgery than those without. Patients who have OA and T2DM receiving combination COX-2 inhibitors and metformin therapy associated with lower joint replacement surgery rates than those without and this may be attributable to combination

The CoxD protein, a novel AAA+ ATPase involved in metal cluster assembly: hydrolysis of nucleotide-triphosphates and oligomerization.

Directory of Open Access Journals (Sweden)

Tobias Maisel

Full Text Available CoxD of the α-proteobacterium Oligotropha carboxidovorans is a membrane protein which is involved in the posttranslational biosynthesis of the [CuSMoO₂] cluster in the active site of the enzyme CO dehydrogenase. The bacteria synthesize CoxD only in the presence of CO. Recombinant CoxD produced in E. coli K38 pGP1-2/pETMW2 appeared in inclusion bodies from where it was solubilized by urea and refolded by stepwise dilution. Circular dichroism spectroscopy revealed the presence of secondary structural elements in refolded CoxD. CoxD is a P-loop ATPase of the AAA-protein family. Refolded CoxD catalyzed the hydrolysis of MgATP yielding MgADP and inorganic phosphate at a 1∶1∶1 molar ratio. The reaction was inhibited by the slow hydrolysable MgATP-γ-S. GTPase activity of CoxD did not exceed 2% of the ATPase activity. Employing different methods (non linear regression, Hanes and Woolf, Lineweaver-Burk, preparations of CoxD revealed a mean K(M value of 0.69±0.14 mM ATP and an apparent V(max value of 19.3±2.3 nmol ATP hydrolyzed min⁻¹ mg⁻¹. Sucrose density gradient centrifugation and gel filtration showed that refolded CoxD can exist in various multimeric states (2-mer, 4-mer or 6-mer, preferentially as hexamer or dimer. Within weeks the hexamer dissociates into the dimer, a process which can be reversed by MgATP or MgATP-γ-S within hours. Only the hexamers and the dimers exhibited MgATPase activity. Transmission electron microscopy of negatively stained CoxD preparations revealed distinct particles within a size range of 10-16 nm, which further corroborates the oligomeric organization. The 3D structure of CoxD was modeled with the 3D structure of BchI from Rhodobacter capsulatus as template. It has the key elements of an AAA+ domain in the same arrangement and at same positions as in BchI and displays the characteristic inserts of the PS-II-insert clade. Possible functions of CoxD in [CuSMoO₂] cluster assembly are discussed.

Effects of the estrous cycle, pregnancy and interferon tau on expression of cyclooxygenase two (COX-2 in ovine endometrium

Directory of Open Access Journals (Sweden)

Bazer Fuller W

2003-08-01

Full Text Available Abstract In sheep, the uterus produces luteolytic pulses of prostaglandin F2α (PGF on Days 15 to 16 of estrous cycle to regress the corpus luteum (CL. These PGF pulses are produced by the endometrial lumenal epithelium (LE and superficial ductal glandular epithelium (sGE in response to binding of pituitary and/or luteal oxytocin to oxytocin receptors (OTR and liberation of arachidonic acid, the precursor of PGF. Cyclooxygenase-one (COX-1 and COX-2 are rate-limiting enzymes in PGF synthesis, and COX-2 is the major form expressed in ovine endometrium. During pregnancy recognition, interferon tau (IFNτ, produced by the conceptus trophectoderm, acts in a paracrine manner to suppress development of the endometrial epithelial luteolytic mechanism by inhibiting transcription of estrogen receptor α (ERα (directly and OTR (indirectly genes. Conflicting studies indicate that IFNτ increases, decreases or has no effect on COX-2 expression in bovine and ovine endometrial cells. In Study One, COX-2 mRNA and protein were detected solely in endometrial LE and sGE of both cyclic and pregnant ewes. During the estrous cycle, COX-2 expression increased from Days 10 to 12 and then decreased to Day 16. During early pregnancy, COX-2 expression increased from Days 10 to 12 and remained higher than in cyclic ewes. In Study Two, intrauterine infusion of recombinant ovine IFNτ in cyclic ewes from Days 11 to 16 post-estrus did not affect COX-2 expression in the endometrial epithelium. These results clearly indicate that IFNτ has no effect on expression of the COX-2 gene in the ovine endometrium. Therefore, antiluteolytic effects of IFNτ are to inhibit ERα and OTR gene transcription, thereby preventing endometrial production of luteolytic pulses of PGF. Indeed, expression of COX-2 in the endometrial epithelia as well as conceptus is likely to have a beneficial regulatory role in implantation and development of the conceptus.

Decomposition of Variance for Spatial Cox Processes.

Science.gov (United States)

Jalilian, Abdollah; Guan, Yongtao; Waagepetersen, Rasmus

2013-03-01

Spatial Cox point processes is a natural framework for quantifying the various sources of variation governing the spatial distribution of rain forest trees. We introduce a general criterion for variance decomposition for spatial Cox processes and apply it to specific Cox process models with additive or log linear random intensity functions. We moreover consider a new and flexible class of pair correlation function models given in terms of normal variance mixture covariance functions. The proposed methodology is applied to point pattern data sets of locations of tropical rain forest trees.

COX-2, VEGF and tumour angiogenesis.

LENUS (Irish Health Repository)

Toomey, D P

2009-06-01

Epidemiological evidence suggests a protective effective of regular NSAID use against developing cancer. Cyclooxygenase-2, a target of NSAIDs, is upregulated in many cancers and has been associated with increased VEGF production and angiogenesis. Angiogenesis is the formation of new vessels from existing vasculature and as an essential process for tumour development represents an important therapeutic target. Following an extensive review of the literature this article details the current knowledge on the role of COX-2 in tumorigenesis focusing on its relationship to angiogenesis and VEGF production by tumour cells. While COX-2 is clearly detrimental to prognosis and NSAIDs have a beneficial effect, the possibility of COX-2 independent effects being partly or wholly responsible for this benefit cannot be excluded.

Background stratified Poisson regression analysis of cohort data.

Science.gov (United States)

Richardson, David B; Langholz, Bryan

2012-03-01

Background stratified Poisson regression is an approach that has been used in the analysis of data derived from a variety of epidemiologically important studies of radiation-exposed populations, including uranium miners, nuclear industry workers, and atomic bomb survivors. We describe a novel approach to fit Poisson regression models that adjust for a set of covariates through background stratification while directly estimating the radiation-disease association of primary interest. The approach makes use of an expression for the Poisson likelihood that treats the coefficients for stratum-specific indicator variables as 'nuisance' variables and avoids the need to explicitly estimate the coefficients for these stratum-specific parameters. Log-linear models, as well as other general relative rate models, are accommodated. This approach is illustrated using data from the Life Span Study of Japanese atomic bomb survivors and data from a study of underground uranium miners. The point estimate and confidence interval obtained from this 'conditional' regression approach are identical to the values obtained using unconditional Poisson regression with model terms for each background stratum. Moreover, it is shown that the proposed approach allows estimation of background stratified Poisson regression models of non-standard form, such as models that parameterize latency effects, as well as regression models in which the number of strata is large, thereby overcoming the limitations of previously available statistical software for fitting background stratified Poisson regression models.

MENENTUKAN PROBABILITAS QUALITAS LULUSAN PROGRAM STUDI MENGGUNAKAN LOGISTIC REGRESSION

Directory of Open Access Journals (Sweden)

Maxsi Ary

2016-03-01

Full Text Available Abstract – Human resources (HR is one of the success factors in the economic field, namely how to create a human resources (HR qualified and have the skills and highly competitive in the global competition. Educational level of the labor force that is still relatively low. The structure of education of the workforce is still dominated Indonesian basic education which is about 63.2%. The issue raised is to determine the probability of a program of study (whether or not to see some of the ratio of the number of graduates by the number of students per class, the amount of quota size class (large or small using logistic regression models. Data were obtained from a search result based on the amount of data the study program students and graduates in 2010 Data processing using SPSS. The results of the analysis by assessing model fit and the results will be given for each model fit. Starting with the hypothesis for assessing model fit, statistical -2LogL, Cox and Snell's R Square, Hosmer and Lemeshow's Goodness of Fit Test, and the classification table. The results of the analysis using SPSS as a tool aimed at measuring quality of graduate courses at a university, college, or academy, whether or not based on the ratio of the number of graduates and class quotas. Keywords: Quota Class, Probability, Logistic Regression Abstrak – Sumberdaya manusia (SDM adalah salah satu faktor kesuksesan dalam bidang ekonomi, yaitu bagaimana menciptakan sumber daya manusia (SDM yang berkualitas dan memiliki keterampilan serta berdaya saing tinggi dalam persaingan global. Tingkat pendidikan angkatan kerja yang ada masih relatif rendah. Struktur pendidikan angkatan kerja Indonesia masih didominasi pendidikan dasar yaitu sekitar 63,2%. Persoalan yang dikemukakan adalah menentukan probabilitas sebuah program studi (baik atau tidak dengan melihat beberapa rasio jumlah lulusan dengan jumlah mahasiswa per angkatan, ukuran besarnya kuota kelas (besar atau kecil menggunakan

Poisson Regression Analysis of Illness and Injury Surveillance Data

Energy Technology Data Exchange (ETDEWEB)

Frome E.L., Watkins J.P., Ellis E.D.

2012-12-12

The Department of Energy (DOE) uses illness and injury surveillance to monitor morbidity and assess the overall health of the work force. Data collected from each participating site include health events and a roster file with demographic information. The source data files are maintained in a relational data base, and are used to obtain stratified tables of health event counts and person time at risk that serve as the starting point for Poisson regression analysis. The explanatory variables that define these tables are age, gender, occupational group, and time. Typical response variables of interest are the number of absences due to illness or injury, i.e., the response variable is a count. Poisson regression methods are used to describe the effect of the explanatory variables on the health event rates using a log-linear main effects model. Results of fitting the main effects model are summarized in a tabular and graphical form and interpretation of model parameters is provided. An analysis of deviance table is used to evaluate the importance of each of the explanatory variables on the event rate of interest and to determine if interaction terms should be considered in the analysis. Although Poisson regression methods are widely used in the analysis of count data, there are situations in which over-dispersion occurs. This could be due to lack-of-fit of the regression model, extra-Poisson variation, or both. A score test statistic and regression diagnostics are used to identify over-dispersion. A quasi-likelihood method of moments procedure is used to evaluate and adjust for extra-Poisson variation when necessary. Two examples are presented using respiratory disease absence rates at two DOE sites to illustrate the methods and interpretation of the results. In the first example the Poisson main effects model is adequate. In the second example the score test indicates considerable over-dispersion and a more detailed analysis attributes the over-dispersion to extra

Acute upregulation of COX-2 by renal artery stenosis

DEFF Research Database (Denmark)

Mann, Birgitte; Hartner, A; Jensen, B L

2001-01-01

This study aimed to characterize the influence of acute renal artery stenosis on cyclooxygenase-2 (COX-2) and renin expression in the juxtaglomerular apparatus. For this purpose, male Sprague-Dawley rats received a left renal artery clip, and COX-2 mRNA, COX-2 immunoreactivity, plasma renin...... activity, and renin mRNA levels were determined. COX-2 mRNA and COX-2 immunoreactivity in the macula densa region in the clipped kidneys increased as early as 6 h after clipping and reached a maximal expression 1-2 days after clipping. Although values for plasma renin activity were elevated markedly at all...... time points examined, remaining renin mRNA levels were unchanged after 6 h and then increased to reach a maximum value 1-2 days after clipping. In the contralateral intact kidney, renin mRNA and COX-2 immunoreactivity decreased to approximately 50% of their normal values. To investigate a possible...

Cox-2 inhibitors and the risk of cardiovascular thrombotic events.

LENUS (Irish Health Repository)

Khan, M

2012-04-01

In 1971, Vane showed that the analgesic action of traditional NSAIDs relies on inhibition of the cyclo-oxygenase (COX) enzyme, which in turn results in reduced synthesis of proalgesic prostaglandins. Two decades later COX was shown to exist as two distinct isoforms. The constitutive isoform COX-1, supports the beneficial homeostatic functions whereas the inducible isoform, COX-2 becomes up regulated by inflammatory mediators and its products cause many of the symptoms of inflammatory diseases such as rheumatoid and osteoarthritis. Despite the benefits of NSAIDs for acute and chronic pain one of the most clinically significant and well characterized adverse effect is on GI mucosa. The search for NSAIDs with less gastrointestinal toxicity led to the introduction of the selective cyclo-oxygenase-2 (COX-2) inhibitors. The COX-2 selective (COX-1 sparing) inhibitors are associated with reduced GI mucosal damage as demonstrated in several trials. In light of the overwhelming and sometimes contradictory information for patients and physicians regarding the safety of COX-2 agents this article will summarize the available evidence regarding cardiovascular (CV) safety data and contemporary recommendations for prescribing of COX-2-selective NSAIDs.

Optimization of Acid Orange 7 Degradation in Heterogeneous Fenton-like Reaction Using Fe3-xCoxO4 Catalyst

Science.gov (United States)

Ibrahim, M. Z.; Alrozi, R.; Zubir, N. A.; Bashah, N. A.; Ali, S. A. Md; Ibrahim, N.

2018-05-01

The oxidation process such as heterogeneous Fenton and/or Fenton-like reactions is considered as an effective and efficient method for treatment of dye degradation. In this study, the degradation of Acid Orange 7 (AO7) was investigated by using Fe3-xCoxO4 as a heterogeneous Fenton-like catalyst. Response surface methodology (RSM) was used to optimize the operational parameters condition and the interaction of two or more parameters. The parameter studies were catalyst dosage (X1 ), pH (X2 ) and H2O2 concentration (X3 ) towards AO7 degradation. Based on analysis of variance (ANOVA), the derived quadratic polynomial model was significant whereby the predicted values matched the experimental values with regression coefficient of R2 = 0.9399. The optimum condition for AO7 degradation was obtained at catalyst dosage of 0.84 g/L, pH of 3 and H2O2 concentration of 46.70 mM which resulted in 86.30% removal of AO7 dye. These findings present new insights into the influence of operational parameters in the heterogeneous Fenton-like oxidation of AO7 using Fe3-xCoxO4 catalyst.

Una estimación no paramétrica y robusta de la transformación Box-Cox para el modelo de regresión

Directory of Open Access Journals (Sweden)

Elkin Castaño Vélez

2011-12-01

Full Text Available In regression analysis, it is frequently required to transform the dependent variable in order to obtain additivity and normal errors with constant variance. Box and Cox (1964 proposed a parametric power transformation based on the assumption of normality with the aim to achieve these goals. However, some authors such as Carroll (1980, 1982b, Bickel and Doksum (1981, Powell (1991, Chamberlain (1994, Buchinsky (1995, Marazzi and Yohai (2004 and Fitzenberger et al. (2005 have pointed out that this transformation is not robust to the presence of outliers, and propose robust estimators for the transformation parameter by replacing the normal likelihood with an objective function that is less sensitive to them. This paper presents a non-parametric alternative procedure for obtaining a power transformation within the Box-Cox family which is robust to the presence of outliers in the dependent variable. The procedure is an extension of the one proposed by Castaño (1994, 1995 for a symmetry transformation of a dataset.

A Quality Assessment Tool for Non-Specialist Users of Regression Analysis

Science.gov (United States)

Argyrous, George

2015-01-01

This paper illustrates the use of a quality assessment tool for regression analysis. It is designed for non-specialist "consumers" of evidence, such as policy makers. The tool provides a series of questions such consumers of evidence can ask to interrogate regression analysis, and is illustrated with reference to a recent study published…

Regulation of Cox-2 by Cyclic AMP Response Element Binding Protein in Prostate Cancer: Potential Role for Nexrutine

Directory of Open Access Journals (Sweden)

Rita Ghosh

2007-11-01

Full Text Available We recently showed that NexrutineR, a Phellodendron amurense bark extract, suppresses proliferation of prostate cancer cell lines and tumor development in the transgenic adenocarcinoma of mouse prostate (TRAMP model. Our data also indicate that the antiproliferative effects of NexrutineR are mediated in part by Akt and Cyclic AMP response element binding protein (CREB. Cyclooxygenase (Cox-2, a pro-inflammatory mediator, is a CREB target that induces prostaglandin E2 (PGE2 and suppresses apoptosis. Treatment of LNCaP cells with NexrutineR reduced tumor necrosis factor α-induced enzymatic as well as promoter activities of Cox-2. NexrutineR also reduced the expression and promoter activity of Cox-2 in PC-3 cells that express high constitutive levels of Cox-2. Deletion analysis coupled with mutational analysis of the Cox-2 promoter identified CRE as being sufficient for mediating NexrutineR response. Immunohistochemical analysis of human prostate tumors show increased expression of CREB and DNA binding activity in high-grade tumors (three-fold higher in human prostate tumors compared to normal prostate; P = .01. We have identified CREB-mediated activation of Cox-2 as a potential signaling pathway in prostate cancer which can be blocked with a nontoxic, cost-effective dietary supplement like NexrutineR, demonstrating a prospective for development of NexrutineR for prostate cancer management.

Log Gaussian Cox processes on the sphere

DEFF Research Database (Denmark)

Pacheco, Francisco Andrés Cuevas; Møller, Jesper

We define and study the existence of log Gaussian Cox processes (LGCPs) for the description of inhomogeneous and aggregated/clustered point patterns on the d-dimensional sphere, with d = 2 of primary interest. Useful theoretical properties of LGCPs are studied and applied for the description of sky...... positions of galaxies, in comparison with previous analysis using a Thomas process. We focus on simple estimation procedures and model checking based on functional summary statistics and the global envelope test....

Background stratified Poisson regression analysis of cohort data

International Nuclear Information System (INIS)

Richardson, David B.; Langholz, Bryan

2012-01-01

Background stratified Poisson regression is an approach that has been used in the analysis of data derived from a variety of epidemiologically important studies of radiation-exposed populations, including uranium miners, nuclear industry workers, and atomic bomb survivors. We describe a novel approach to fit Poisson regression models that adjust for a set of covariates through background stratification while directly estimating the radiation-disease association of primary interest. The approach makes use of an expression for the Poisson likelihood that treats the coefficients for stratum-specific indicator variables as 'nuisance' variables and avoids the need to explicitly estimate the coefficients for these stratum-specific parameters. Log-linear models, as well as other general relative rate models, are accommodated. This approach is illustrated using data from the Life Span Study of Japanese atomic bomb survivors and data from a study of underground uranium miners. The point estimate and confidence interval obtained from this 'conditional' regression approach are identical to the values obtained using unconditional Poisson regression with model terms for each background stratum. Moreover, it is shown that the proposed approach allows estimation of background stratified Poisson regression models of non-standard form, such as models that parameterize latency effects, as well as regression models in which the number of strata is large, thereby overcoming the limitations of previously available statistical software for fitting background stratified Poisson regression models. (orig.)

Understanding logistic regression analysis.

Science.gov (United States)

Sperandei, Sandro

2014-01-01

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

Palm distributions for log Gaussian Cox processes

DEFF Research Database (Denmark)

Coeurjolly, Jean-Francois; Møller, Jesper; Waagepetersen, Rasmus

This paper reviews useful results related to Palm distributions of spatial point processes and provides a new result regarding the characterization of Palm distributions for the class of log Gaussian Cox processes. This result is used to study functional summary statistics for a log Gaussian Cox...

The analysis of soil cores polluted with certain metals using the Box-Cox transformation.

Science.gov (United States)

Meloun, Milan; Sánka, Milan; Nemec, Pavel; Krítková, Sona; Kupka, Karel

2005-09-01

To define the soil properties for a given area or country including the level of pollution, soil survey and inventory programs are essential tools. Soil data transformations enable the expression of the original data on a new scale, more suitable for data analysis. In the computer-aided interactive analysis of large data files of soil characteristics containing outliers, the diagnostic plots of the exploratory data analysis (EDA) often find that the sample distribution is systematically skewed or reject sample homogeneity. Under such circumstances the original data should be transformed. The Box-Cox transformation improves sample symmetry and stabilizes spread. The logarithmic plot of a profile likelihood function enables the optimum transformation parameter to be found. Here, a proposed procedure for data transformation in univariate data analysis is illustrated on a determination of cadmium content in the plough zone of agricultural soils. A typical soil pollution survey concerns the determination of the elements Be (16 544 values available), Cd (40 317 values), Co (22 176 values), Cr (40 318 values), Hg (32 344 values), Ni (34 989 values), Pb (40 344 values), V (20 373 values) and Zn (36 123 values) in large samples.

Polymorphism in COX-2 modifies the inverse association between Helicobacter pylori seropositivity and esophageal squamous cell carcinoma risk in Taiwan: a case control study.

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Hu, Huang-Ming; Kuo, Chao-Hung; Lee, Chien-Hung; Wu, I-Chen; Lee, Ka-Wo; Lee, Jang-Ming; Goan, Yih-Gang; Chou, Shah-Hwa; Kao, Ein-Long; Wu, Ming-Tsang; Wu, Deng-Chyang

2009-05-23

Overexpression of Cyclooxygenase-2 (COX-2) was observed in many types of cancers, including esophageal squamous cell carcinoma (ESCC). One functional SNP, COX-2 -1195G/A, has been reported to mediate susceptibility of ESCC in Chinese populations. In our previous study, the presence of Helicobacter pylori (H. pylori) was found to play a protective role in development of ESCC. The interaction of COX-2 and H. pylori in gastric cancer was well investigated. However, literature on their interaction in ESCC risk is scarce. The purpose of this study was to evaluate the association and interaction between COX-2 single nucleotide polymorphism (SNP), H. pylori infection and the risk of developing ESCC. One hundred and eighty patients with ESCC and 194 controls were enrolled in this study. Personal data regarding related risk factors, including alcohol consumption, smoking habits and betel quid chewing, were collected via questionnaire. Genotypes of the COX-2 -1195 polymorphism were determined by PCR-based restriction fragment length polymorphism. H. pylori seropositivity was defined by immunochromatographic screening test. Data was analyzed by chi-squared tests and polytomous logistics regression. In analysis adjusting for the covariates and confounders, H. pylori seropositivity was found to be inversely association with the ESCC development (adjusted OR: 0.5, 95% CI: 0.3 - 0.9). COX-2 -1195 AA homozygous was associated with an increased risk of contracting ESCC in comparison with the non-AA group, especially among patients with H. pylori seronegative (adjusted OR ratio: 2.9, 95% CI: 1.2 - 7.3). The effect was strengthened among patients with lower third ESCC (adjusted OR ratio: 6.9, 95% CI 2.1 - 22.5). Besides, H. pylori seropositivity conveyed a notably inverse effect among patients with COX-2 AA polymorphism (AOR ratio: 0.3, 95% CI: 0.1 - 0.9), and the effect was observed to be enhanced for the lower third ESCC patients (AOR ratio: 0.09, 95% CI: 0.02 - 0.47, p for

Analysis of the cytochrome c oxidase subunit 1 (COX1) gene reveals the unique evolution of the giant panda.

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Hu, Yao-Dong; Pang, Hui-Zhong; Li, De-Sheng; Ling, Shan-Shan; Lan, Dan; Wang, Ye; Zhu, Yun; Li, Di-Yan; Wei, Rong-Ping; Zhang, He-Min; Wang, Cheng-Dong

2016-11-05

As the rate-limiting enzyme of the mitochondrial respiratory chain, cytochrome c oxidase (COX) plays a crucial role in biological metabolism. "Living fossil" giant panda (Ailuropoda melanoleuca) is well-known for its special bamboo diet. In an effort to explore functional variation of COX1 in the energy metabolism behind giant panda's low-energy bamboo diet, we looked at genetic variation of COX1 gene in giant panda, and tested for its selection effect. In 1545 base pairs of the gene from 15 samples, 9 positions were variable and 1 mutation leaded to an amino acid sequence change. COX1 gene produces six haplotypes, nucleotide (pi), haplotype diversity (Hd). In addition, the average number of nucleotide differences (k) is 0.001629±0.001036, 0.8083±0.0694 and 2.517, respectively. Also, dN/dS ratio is significantly below 1. These results indicated that giant panda had a low population genetic diversity, and an obvious purifying selection of the COX1 gene which reduces synthesis of ATP determines giant panda's low-energy bamboo diet. Phylogenetic trees based on the COX1 gene were constructed to demonstrate that giant panda is the sister group of other Ursidae. Copyright © 2016 Elsevier B.V. All rights reserved.

Retro-regression--another important multivariate regression improvement.

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Randić, M

2001-01-01

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

Cell-type-specific roles for COX-2 in UVB-induced skin cancer

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Herschman, Harvey

2014-01-01

In human tumors, and in mouse models, cyclooxygenase-2 (COX-2) levels are frequently correlated with tumor development/burden. In addition to intrinsic tumor cell expression, COX-2 is often present in fibroblasts, myofibroblasts and endothelial cells of the tumor microenvironment, and in infiltrating immune cells. Intrinsic cancer cell COX-2 expression is postulated as only one of many sources for prostanoids required for tumor promotion/progression. Although both COX-2 inhibition and global Cox-2 gene deletion ameliorate ultraviolet B (UVB)-induced SKH-1 mouse skin tumorigenesis, neither manipulation can elucidate the cell type(s) in which COX-2 expression is required for tumorigenesis; both eliminate COX-2 activity in all cells. To address this question, we created Cox-2 flox/flox mice, in which the Cox-2 gene can be eliminated in a cell-type-specific fashion by targeted Cre recombinase expression. Cox-2 deletion in skin epithelial cells of SKH-1 Cox-2 flox/flox;K14Cre + mice resulted, following UVB irradiation, in reduced skin hyperplasia and increased apoptosis. Targeted epithelial cell Cox-2 deletion also resulted in reduced tumor incidence, frequency, size and proliferation rate, altered tumor cell differentiation and reduced tumor vascularization. Moreover, Cox-2 flox/flox;K14Cre + papillomas did not progress to squamous cell carcinomas. In contrast, Cox-2 deletion in SKH-1 Cox-2 flox/flox; LysMCre + myeloid cells had no effect on UVB tumor induction. We conclude that (i) intrinsic epithelial COX-2 activity plays a major role in UVB-induced skin cancer, (ii) macrophage/myeloid COX-2 plays no role in UVB-induced skin cancer and (iii) either there may be another COX-2-dependent prostanoid source(s) that drives UVB skin tumor induction or there may exist a COX-2-independent pathway(s) to UVB-induced skin cancer. PMID:24469308

Pengaruh kualitas Udara ( Debu,COx, NOx, SOx Terminal Terhadap Gangguan Fungsi Paru Pada Pedagang Tetap Terminal Bus Induk Jawa Tengah, 2002

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Soedjono Soedjono

2015-12-01

Full Text Available ABSTRACT Background : The high growth of motor vehicle in Central Java in 2000 reached 11,8% a year and from these number the city bus, 4,5%. This condition has seriously brought negative effect to environment. Many researchers found that the equipment of transportation and the industry are sources of air pollution, which very large and very dominant. The bus terminal is one location that is the highest air pollution than other locations because the bus terminal is a central of activities that need a transportation service. Beside that the bus terminal is a influence of sir quality dust, COx, NOx, SOx, in the bus terminal to the lung dysfunction of the permanent seller in the 15 prime bus terminals in Central Java, 2002 and to find the exposed duration, the work duration, the habit of smoking and age which can influence  the lung disfunction. Method : This was an analytic research using cross sectional approach. The samples of this research were 309 respondents (total population. The concentration of dust, COx, NOx, SOx, was directly  measured in the 15 prime bus terminals. The other data was measured by  interviewing with the sellers in the bus terminal who had been limited their ages (40 years old to down. The logistic regression analysis was used to test the influence of dust, COx, NOx, SOx, the exposed duration, the work duration, the habit of smoking and age. Result : The result of descriptive analysis shows that all variables have influence to the instance of the lung disfunction. It can be seen from the number of percentage of respondent who experienced the lung disfunction in  each variable. From analitical statistic, only the variable of anamnesis / the other diseases has influence which very significant to the instance of the lung disfunction. Other variables are risk factors to the instance of the lung disfunction. Key word : Dust, COx, NOx, SOx, concentration, interference lung – function, Seller, Bus Terminal.

Linear regression analysis: part 14 of a series on evaluation of scientific publications.

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Schneider, Astrid; Hommel, Gerhard; Blettner, Maria

2010-11-01

Regression analysis is an important statistical method for the analysis of medical data. It enables the identification and characterization of relationships among multiple factors. It also enables the identification of prognostically relevant risk factors and the calculation of risk scores for individual prognostication. This article is based on selected textbooks of statistics, a selective review of the literature, and our own experience. After a brief introduction of the uni- and multivariable regression models, illustrative examples are given to explain what the important considerations are before a regression analysis is performed, and how the results should be interpreted. The reader should then be able to judge whether the method has been used correctly and interpret the results appropriately. The performance and interpretation of linear regression analysis are subject to a variety of pitfalls, which are discussed here in detail. The reader is made aware of common errors of interpretation through practical examples. Both the opportunities for applying linear regression analysis and its limitations are presented.

Management of Industrial Performance Indicators: Regression Analysis and Simulation

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Walter Roberto Hernandez Vergara

2017-11-01

Full Text Available Stochastic methods can be used in problem solving and explanation of natural phenomena through the application of statistical procedures. The article aims to associate the regression analysis and systems simulation, in order to facilitate the practical understanding of data analysis. The algorithms were developed in Microsoft Office Excel software, using statistical techniques such as regression theory, ANOVA and Cholesky Factorization, which made it possible to create models of single and multiple systems with up to five independent variables. For the analysis of these models, the Monte Carlo simulation and analysis of industrial performance indicators were used, resulting in numerical indices that aim to improve the goals’ management for compliance indicators, by identifying systems’ instability, correlation and anomalies. The analytical models presented in the survey indicated satisfactory results with numerous possibilities for industrial and academic applications, as well as the potential for deployment in new analytical techniques.

Least-Squares Linear Regression and Schrodinger's Cat: Perspectives on the Analysis of Regression Residuals.

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Hecht, Jeffrey B.

The analysis of regression residuals and detection of outliers are discussed, with emphasis on determining how deviant an individual data point must be to be considered an outlier and the impact that multiple suspected outlier data points have on the process of outlier determination and treatment. Only bivariate (one dependent and one independent)…

Analysis of multi-species point patterns using multivariate log Gaussian Cox processes

DEFF Research Database (Denmark)

Waagepetersen, Rasmus; Guan, Yongtao; Jalilian, Abdollah

Multivariate log Gaussian Cox processes are flexible models for multivariate point patterns. However, they have so far only been applied in bivariate cases. In this paper we move beyond the bivariate case in order to model multi-species point patterns of tree locations. In particular we address t...... of the data. The selected number of common latent fields provides an index of complexity of the multivariate covariance structure. Hierarchical clustering is used to identify groups of species with similar patterns of dependence on the common latent fields.......Multivariate log Gaussian Cox processes are flexible models for multivariate point patterns. However, they have so far only been applied in bivariate cases. In this paper we move beyond the bivariate case in order to model multi-species point patterns of tree locations. In particular we address...... the problems of identifying parsimonious models and of extracting biologically relevant information from the fitted models. The latent multivariate Gaussian field is decomposed into components given in terms of random fields common to all species and components which are species specific. This allows...

Predicting Dropouts of University Freshmen: A Logit Regression Analysis.

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Lam, Y. L. Jack

1984-01-01

Stepwise discriminant analysis coupled with logit regression analysis of freshmen data from Brandon University (Manitoba) indicated that six tested variables drawn from research on university dropouts were useful in predicting attrition: student status, residence, financial sources, distance from home town, goal fulfillment, and satisfaction with…

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

Expression of beta-catenin, COX-2 and iNOS in colorectal cancer: relevance of COX-2 adn iNOS inhibitors for treatment in Malaysia.

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Hong, Seok Kwan; Gul, Yunus A; Ithnin, Hairuszah; Talib, Arni; Seow, Heng Fong

2004-01-01

Promising new pharmacological agents and gene therapy targeting cyclooxygenase-2 (COX-2) and inducible nitric oxide synthase (iNOS) could modulate treatment of colorectal cancer in the future. The aim of this study was to elucidate the expression fo beta-catenin and teh presence of COX-2 and iNOS in colorectal cancer specimens in Malaysia. This is a useful prelude to future studies investigating interventions directed towards COX-2 adn iNOS. A cross-section study using retrospective data over a 2-year period (1999-2000) involved 101 archival, formalin-fixed, paraffin-embedded tissue samples of colorectal cancers that were surgically resected in a tertiary referral. COX-2 production was detected in adjacent normal tissue in 34 sample (33.7%) and in tumour tissue in 60 samples (59.4%). More tumours expressed iNOS (82/101, 81.2%) than COX-2. No iNOS expression was detected in adjacent normal tissue. Intense beta-catenin immunoreactivity at the cell-to-cell border. Poorly differentiated tumours had significantly lower total beta-catenin (p = 0.009) and COX-2 scores (p = 0.031). No significant relationships were established between pathological stage and beta-catenin, COX-2 and iNOS scores. the accumulation of beta-catenin does not seem to be sufficient to activate pathways that lead to increased COX-2 and iNOS expression. A high proportion of colorectal cancers were found to express COX-2 and a significant number produced iNOS, suggesting that their inhibitors may be potentially useful as chemotherapeutic agents in the management of colorectal cancer.

NSAIDs and serious cardiovascular disorders: especially cox-2 inhibitors and diclofenac.

Science.gov (United States)

2016-01-01

Nonsteroidal anti-inflammatory drugs (NSAIDs) used as analgesics expose patients to cardiovascular risks that can be predicted from their pharmacological properties. As of mid-2015, what is known about the cardiovascular harms of the NSAIDs of choice, ibuprofen and naproxen? Most of the data from comparative trials of NSAIDs concern cox-2 inhibitors, diclofenac, ibuprofen and naproxen. Few studies have addressed the serious cardiovascular effects of other NSAIDs. In 2013, a U.K. team published a large meta-analysis of hundreds of randomised trials comparing NSAIDs with placebo or one NSAID with another NSAID. Compared with placebo, a statistically significant increase in the risk of serious cardiovascular adverse effects was demonstrated with cox-2 inhibitors and with diclofenac (about +40%). This risk is mainly due to an increase in myocardial infarctions and vascular deaths. Another meta-analysis found similar results in terms of cardiovascular deaths. The results of epidemiological studies are consistent with those of randomised clinical trials. According to meta-analyses of randomised trials, high-dose ibuprofen increases cardiovascular risks to the same degree as diclofenac or cox-2 inhibitors. The risk seems to mainly apply to daily doses of 2400 mg, a finding borne out by epidemiological studies that showed no increased risk with ibuprofen 1200 mg. Two meta-analyses of clinical trials showed that all NSAIDs roughly double the risk of heart failure. One meta-analysis showed a small, statistically significant increase in the risk of atrial fibrillation. In practice, from a cardiovascular perspective, the NSAIDs of choice are ibuprofen, on condition that the dose does not exceed 1200 mg per day, and naproxen. In contrast, it would appear from the study data that cox-2 inhibitors, diclofenac and high-dose ibuprofen (2400 mg per day) are best avoided. As for other NSAIDs, the clinical data are too sparse to allow a meaningful comparison with the better studied

Quality of life in breast cancer patients--a quantile regression analysis.

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Pourhoseingholi, Mohamad Amin; Safaee, Azadeh; Moghimi-Dehkordi, Bijan; Zeighami, Bahram; Faghihzadeh, Soghrat; Tabatabaee, Hamid Reza; Pourhoseingholi, Asma

2008-01-01

Quality of life study has an important role in health care especially in chronic diseases, in clinical judgment and in medical resources supplying. Statistical tools like linear regression are widely used to assess the predictors of quality of life. But when the response is not normal the results are misleading. The aim of this study is to determine the predictors of quality of life in breast cancer patients, using quantile regression model and compare to linear regression. A cross-sectional study conducted on 119 breast cancer patients that admitted and treated in chemotherapy ward of Namazi hospital in Shiraz. We used QLQ-C30 questionnaire to assessment quality of life in these patients. A quantile regression was employed to assess the assocciated factors and the results were compared to linear regression. All analysis carried out using SAS. The mean score for the global health status for breast cancer patients was 64.92+/-11.42. Linear regression showed that only grade of tumor, occupational status, menopausal status, financial difficulties and dyspnea were statistically significant. In spite of linear regression, financial difficulties were not significant in quantile regression analysis and dyspnea was only significant for first quartile. Also emotion functioning and duration of disease statistically predicted the QOL score in the third quartile. The results have demonstrated that using quantile regression leads to better interpretation and richer inference about predictors of the breast cancer patient quality of life.

In vitro and In Silico Studies on Curcumin and Its Analogues as Dual Inhibitors for cyclooxygenase-1 (COX-1 and cyclooxygenase-2 (COX-2

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Nunung Yuniarti

2012-03-01

Full Text Available Curcumin has been widely reported as an anti-inflammatory agent isolated from the plant Curcuma longa L. (turmeric. This anti-inflammatory activity was associated with the ability of this compound to inhibit the activity of both cyclooxygenase-1 (COX-1 and cyclooxygenase-2 (COX-2 in arachidonic acid metabolism. Dual COX-1 and COX-2 inhibitors are preferred to be employed in the therapy of chronic inflammatory diseases compared to selective inhibitors, since it was reported that the use of selective inhibitors led to severe adverse side effect. In the present study, in vitro and in silico assays on curcumin and its analogues as dual inhibitors for both COX-1 and COX-2 were performed. The results provide theoretical contribution in understanding the ligand-protein interactions at the molecular level to develop new curcumin analogues which possess better anti-inflammatory activity as well as to avoid unsolicited side effects.

Additive Intensity Regression Models in Corporate Default Analysis

DEFF Research Database (Denmark)

Lando, David; Medhat, Mamdouh; Nielsen, Mads Stenbo

2013-01-01

We consider additive intensity (Aalen) models as an alternative to the multiplicative intensity (Cox) models for analyzing the default risk of a sample of rated, nonfinancial U.S. firms. The setting allows for estimating and testing the significance of time-varying effects. We use a variety of mo...

Ensembling Variable Selectors by Stability Selection for the Cox Model

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Qing-Yan Yin

2017-01-01

Full Text Available As a pivotal tool to build interpretive models, variable selection plays an increasingly important role in high-dimensional data analysis. In recent years, variable selection ensembles (VSEs have gained much interest due to their many advantages. Stability selection (Meinshausen and Bühlmann, 2010, a VSE technique based on subsampling in combination with a base algorithm like lasso, is an effective method to control false discovery rate (FDR and to improve selection accuracy in linear regression models. By adopting lasso as a base learner, we attempt to extend stability selection to handle variable selection problems in a Cox model. According to our experience, it is crucial to set the regularization region Λ in lasso and the parameter λmin properly so that stability selection can work well. To the best of our knowledge, however, there is no literature addressing this problem in an explicit way. Therefore, we first provide a detailed procedure to specify Λ and λmin. Then, some simulated and real-world data with various censoring rates are used to examine how well stability selection performs. It is also compared with several other variable selection approaches. Experimental results demonstrate that it achieves better or competitive performance in comparison with several other popular techniques.

Visual grading characteristics and ordinal regression analysis during optimisation of CT head examinations.

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Zarb, Francis; McEntee, Mark F; Rainford, Louise

2015-06-01

To evaluate visual grading characteristics (VGC) and ordinal regression analysis during head CT optimisation as a potential alternative to visual grading assessment (VGA), traditionally employed to score anatomical visualisation. Patient images (n = 66) were obtained using current and optimised imaging protocols from two CT suites: a 16-slice scanner at the national Maltese centre for trauma and a 64-slice scanner in a private centre. Local resident radiologists (n = 6) performed VGA followed by VGC and ordinal regression analysis. VGC alone indicated that optimised protocols had similar image quality as current protocols. Ordinal logistic regression analysis provided an in-depth evaluation, criterion by criterion allowing the selective implementation of the protocols. The local radiology review panel supported the implementation of optimised protocols for brain CT examinations (including trauma) in one centre, achieving radiation dose reductions ranging from 24 % to 36 %. In the second centre a 29 % reduction in radiation dose was achieved for follow-up cases. The combined use of VGC and ordinal logistic regression analysis led to clinical decisions being taken on the implementation of the optimised protocols. This improved method of image quality analysis provided the evidence to support imaging protocol optimisation, resulting in significant radiation dose savings. • There is need for scientifically based image quality evaluation during CT optimisation. • VGC and ordinal regression analysis in combination led to better informed clinical decisions. • VGC and ordinal regression analysis led to dose reductions without compromising diagnostic efficacy.

Regression analysis of radiological parameters in nuclear power plants

International Nuclear Information System (INIS)

Bhargava, Pradeep; Verma, R.K.; Joshi, M.L.

2003-01-01

Indian Pressurized Heavy Water Reactors (PHWRs) have now attained maturity in their operations. Indian PHWR operation started in the year 1972. At present there are 12 operating PHWRs collectively producing nearly 2400 MWe. Sufficient radiological data are available for analysis to draw inferences which may be utilised for better understanding of radiological parameters influencing the collective internal dose. Tritium is the main contributor to the occupational internal dose originating in PHWRs. An attempt has been made to establish the relationship between radiological parameters, which may be useful to draw inferences about the internal dose. Regression analysis have been done to find out the relationship, if it exist, among the following variables: A. Specific tritium activity of heavy water (Moderator and PHT) and tritium concentration in air at various work locations. B. Internal collective occupational dose and tritium release to environment through air route. C. Specific tritium activity of heavy water (Moderator and PHT) and collective internal occupational dose. For this purpose multivariate regression analysis has been carried out. D. Tritium concentration in air at various work location and tritium release to environment through air route. For this purpose multivariate regression analysis has been carried out. This analysis reveals that collective internal dose has got very good correlation with the tritium activity release to the environment through air route. Whereas no correlation has been found between specific tritium activity in the heavy water systems and collective internal occupational dose. The good correlation has been found in case D and F test reveals that it is not by chance. (author)

Comparison of cranial sex determination by discriminant analysis and logistic regression.

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Amores-Ampuero, Anabel; Alemán, Inmaculada

2016-04-05

Various methods have been proposed for estimating dimorphism. The objective of this study was to compare sex determination results from cranial measurements using discriminant analysis or logistic regression. The study sample comprised 130 individuals (70 males) of known sex, age, and cause of death from San José cemetery in Granada (Spain). Measurements of 19 neurocranial dimensions and 11 splanchnocranial dimensions were subjected to discriminant analysis and logistic regression, and the percentages of correct classification were compared between the sex functions obtained with each method. The discriminant capacity of the selected variables was evaluated with a cross-validation procedure. The percentage accuracy with discriminant analysis was 78.2% for the neurocranium (82.4% in females and 74.6% in males) and 73.7% for the splanchnocranium (79.6% in females and 68.8% in males). These percentages were higher with logistic regression analysis: 85.7% for the neurocranium (in both sexes) and 94.1% for the splanchnocranium (100% in females and 91.7% in males).

Regression Analysis: Instructional Resource for Cost/Managerial Accounting

Science.gov (United States)

Stout, David E.

2015-01-01

This paper describes a classroom-tested instructional resource, grounded in principles of active learning and a constructivism, that embraces two primary objectives: "demystify" for accounting students technical material from statistics regarding ordinary least-squares (OLS) regression analysis--material that students may find obscure or…

Robust Mediation Analysis Based on Median Regression

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Yuan, Ying; MacKinnon, David P.

2014-01-01

Mediation analysis has many applications in psychology and the social sciences. The most prevalent methods typically assume that the error distribution is normal and homoscedastic. However, this assumption may rarely be met in practice, which can affect the validity of the mediation analysis. To address this problem, we propose robust mediation analysis based on median regression. Our approach is robust to various departures from the assumption of homoscedasticity and normality, including heavy-tailed, skewed, contaminated, and heteroscedastic distributions. Simulation studies show that under these circumstances, the proposed method is more efficient and powerful than standard mediation analysis. We further extend the proposed robust method to multilevel mediation analysis, and demonstrate through simulation studies that the new approach outperforms the standard multilevel mediation analysis. We illustrate the proposed method using data from a program designed to increase reemployment and enhance mental health of job seekers. PMID:24079925

A generalized multivariate regression model for modelling ocean wave heights

Science.gov (United States)

Wang, X. L.; Feng, Y.; Swail, V. R.

2012-04-01

In this study, a generalized multivariate linear regression model is developed to represent the relationship between 6-hourly ocean significant wave heights (Hs) and the corresponding 6-hourly mean sea level pressure (MSLP) fields. The model is calibrated using the ERA-Interim reanalysis of Hs and MSLP fields for 1981-2000, and is validated using the ERA-Interim reanalysis for 2001-2010 and ERA40 reanalysis of Hs and MSLP for 1958-2001. The performance of the fitted model is evaluated in terms of Pierce skill score, frequency bias index, and correlation skill score. Being not normally distributed, wave heights are subjected to a data adaptive Box-Cox transformation before being used in the model fitting. Also, since 6-hourly data are being modelled, lag-1 autocorrelation must be and is accounted for. The models with and without Box-Cox transformation, and with and without accounting for autocorrelation, are inter-compared in terms of their prediction skills. The fitted MSLP-Hs relationship is then used to reconstruct historical wave height climate from the 6-hourly MSLP fields taken from the Twentieth Century Reanalysis (20CR, Compo et al. 2011), and to project possible future wave height climates using CMIP5 model simulations of MSLP fields. The reconstructed and projected wave heights, both seasonal means and maxima, are subject to a trend analysis that allows for non-linear (polynomial) trends.

Global gene expression analysis of canine osteosarcoma stem cells reveals a novel role for COX-2 in tumour initiation.

Science.gov (United States)

Pang, Lisa Y; Gatenby, Emma L; Kamida, Ayako; Whitelaw, Bruce A; Hupp, Ted R; Argyle, David J

2014-01-01

Osteosarcoma is the most common primary bone tumour of both children and dogs. It is an aggressive tumour in both species with a rapid clinical course leading ultimately to metastasis. In dogs and children distant metastasis occurs in >80% of individuals treated by surgery alone. Both canine and human osteosarcoma has been shown to contain a sub-population of cancer stem cells (CSCs), which may drive tumour growth, recurrence and metastasis, suggesting that naturally occurring canine osteosarcoma could act as a preclinical model for the human disease. Here we report the successful isolation of CSCs from primary canine osteosarcoma, as well as established cell lines. We show that these cells can form tumourspheres, and demonstrate relative resistance to chemotherapy. We demonstrate similar results for the human osteosarcma cell lines, U2OS and SAOS2. Utilizing the Affymetrix canine microarray, we are able to definitively show that there are significant differences in global gene expression profiles of isolated osteosarcoma stem cells and the daughter adherent cells. We identified 13,221 significant differences (p = 0.05), and significantly, COX-2 was expressed 141-fold more in CSC spheres than daughter adherent cells. To study the role of COX-2 expression in CSCs we utilized the COX-2 inhibitors meloxicam and mavacoxib. We found that COX-2 inhibition had no effect on CSC growth, or resistance to chemotherapy. However inhibition of COX-2 in daughter cells prevented sphere formation, indicating a potential significant role for COX-2 in tumour initiation.

Global gene expression analysis of canine osteosarcoma stem cells reveals a novel role for COX-2 in tumour initiation.

Directory of Open Access Journals (Sweden)

Lisa Y Pang

Full Text Available Osteosarcoma is the most common primary bone tumour of both children and dogs. It is an aggressive tumour in both species with a rapid clinical course leading ultimately to metastasis. In dogs and children distant metastasis occurs in >80% of individuals treated by surgery alone. Both canine and human osteosarcoma has been shown to contain a sub-population of cancer stem cells (CSCs, which may drive tumour growth, recurrence and metastasis, suggesting that naturally occurring canine osteosarcoma could act as a preclinical model for the human disease. Here we report the successful isolation of CSCs from primary canine osteosarcoma, as well as established cell lines. We show that these cells can form tumourspheres, and demonstrate relative resistance to chemotherapy. We demonstrate similar results for the human osteosarcma cell lines, U2OS and SAOS2. Utilizing the Affymetrix canine microarray, we are able to definitively show that there are significant differences in global gene expression profiles of isolated osteosarcoma stem cells and the daughter adherent cells. We identified 13,221 significant differences (p = 0.05, and significantly, COX-2 was expressed 141-fold more in CSC spheres than daughter adherent cells. To study the role of COX-2 expression in CSCs we utilized the COX-2 inhibitors meloxicam and mavacoxib. We found that COX-2 inhibition had no effect on CSC growth, or resistance to chemotherapy. However inhibition of COX-2 in daughter cells prevented sphere formation, indicating a potential significant role for COX-2 in tumour initiation.

Multiplication factor versus regression analysis in stature estimation from hand and foot dimensions.

Science.gov (United States)

Krishan, Kewal; Kanchan, Tanuj; Sharma, Abhilasha

2012-05-01

Estimation of stature is an important parameter in identification of human remains in forensic examinations. The present study is aimed to compare the reliability and accuracy of stature estimation and to demonstrate the variability in estimated stature and actual stature using multiplication factor and regression analysis methods. The study is based on a sample of 246 subjects (123 males and 123 females) from North India aged between 17 and 20 years. Four anthropometric measurements; hand length, hand breadth, foot length and foot breadth taken on the left side in each subject were included in the study. Stature was measured using standard anthropometric techniques. Multiplication factors were calculated and linear regression models were derived for estimation of stature from hand and foot dimensions. Derived multiplication factors and regression formula were applied to the hand and foot measurements in the study sample. The estimated stature from the multiplication factors and regression analysis was compared with the actual stature to find the error in estimated stature. The results indicate that the range of error in estimation of stature from regression analysis method is less than that of multiplication factor method thus, confirming that the regression analysis method is better than multiplication factor analysis in stature estimation. Copyright © 2012 Elsevier Ltd and Faculty of Forensic and Legal Medicine. All rights reserved.

COX-2 is associated with periodontitis in Europeans

NARCIS (Netherlands)

Schaefer, A.S.; Richter, G.M.; Nothnagel, M.; Laine, M.L.; Noack, B.; Glas, J.; Schrezenmeir, J.; Groessner-Schreiber, B.; Jepsen, S.; Loos, B.G.; Schreiber, S.

2010-01-01

COX-2 plays an important role in periodontitis by mediating inflammatory reactions in periodontal tissues, and the COX-2 polymorphisms rs20417 and rs689466 have been reported to be associated with periodontitis in populations of Taiwanese and Chinese ethnicity. To test whether these variants were

Polymorphism in COX-2 modifies the inverse association between Helicobacter pylori seropositivity and esophageal squamous cell carcinoma risk in Taiwan: a case control study

Directory of Open Access Journals (Sweden)

Lee Jang-Ming

2009-05-01

Full Text Available Abstract Background Overexpression of Cyclooxygenase-2 (COX-2 was observed in many types of cancers, including esophageal squamous cell carcinoma (ESCC. One functional SNP, COX-2 -1195G/A, has been reported to mediate susceptibility of ESCC in Chinese populations. In our previous study, the presence of Helicobacter pylori (H. pylori was found to play a protective role in development of ESCC. The interaction of COX-2 and H. pylori in gastric cancer was well investigated. However, literature on their interaction in ESCC risk is scarce. The purpose of this study was to evaluate the association and interaction between COX-2 single nucleotide polymorphism (SNP, H. pylori infection and the risk of developing ESCC. Methods One hundred and eighty patients with ESCC and 194 controls were enrolled in this study. Personal data regarding related risk factors, including alcohol consumption, smoking habits and betel quid chewing, were collected via questionnaire. Genotypes of the COX-2 -1195 polymorphism were determined by PCR-based restriction fragment length polymorphism. H. pylori seropositivity was defined by immunochromatographic screening test. Data was analyzed by chi-squared tests and polytomous logistics regression. Results In analysis adjusting for the covariates and confounders, H. pylori seropositivity was found to be inversely association with the ESCC development (adjusted OR: 0.5, 95% CI: 0.3 – 0.9. COX-2 -1195 AA homozygous was associated with an increased risk of contracting ESCC in comparison with the non-AA group, especially among patients with H. pylori seronegative (adjusted OR ratio: 2.9, 95% CI: 1.2 – 7.3. The effect was strengthened among patients with lower third ESCC (adjusted OR ratio: 6.9, 95% CI 2.1 – 22.5. Besides, H. pylori seropositivity conveyed a notably inverse effect among patients with COX-2 AA polymorphism (AOR ratio: 0.3, 95% CI: 0.1 – 0.9, and the effect was observed to be enhanced for the lower third ESCC

A comparative study of multiple regression analysis and back ...

Indian Academy of Sciences (India)

Abhijit Sarkar

artificial neural network (ANN) models to predict weld bead geometry and HAZ width in submerged arc welding ... Keywords. Submerged arc welding (SAW); multi-regression analysis (MRA); artificial neural network ..... Degree of freedom.

IL1β-mediated Stromal COX-2 signaling mediates proliferation and invasiveness of colonic epithelial cancer cells

International Nuclear Information System (INIS)

Zhu, Yingting; Zhu, Min; Lance, Peter

2012-01-01

COX-2 is a major inflammatory mediator implicated in colorectal inflammation and cancer. However, the exact origin and role of COX-2 on colorectal inflammation and carcinogenesis are still not well defined. Recently, we reported that COX-2 and iNOS signalings interact in colonic CCD18Co fibroblasts. In this article, we investigated whether activation of COX-2 signaling by IL1β in primary colonic fibroblasts obtained from normal and cancer patients play a critical role in regulation of proliferation and invasiveness of human colonic epithelial cancer cells. Our results demonstrated that COX-2 level was significantly higher in cancer associated fibroblasts than that in normal fibroblasts with or without stimulation of IL-1β, a powerful stimulator of COX-2. Using in vitro assays for estimating proliferative and invasive potential, we discovered that the proliferation and invasiveness of the epithelial cancer cells were much greater when the cells were co-cultured with cancer associated fibroblasts than with normal fibroblasts, with or without stimulation of IL1β. Further analysis indicated that the major COX-2 product, prostaglandin E 2 , directly enhanced proliferation and invasiveness of the epithelial cancer cells in the absence of fibroblasts. Moreover, a selective COX-2 inhibitor, NS-398, blocked the proliferative and invasive effect of both normal and cancer associate fibroblasts on the epithelial cancer cells, with or without stimulation of IL-1β. Those results indicate that activation of COX-2 signaling in the fibroblasts plays a major role in promoting proliferation and invasiveness of the epithelial cancer cells. In this process, PKC is involved in the activation of COX-2 signaling induced by IL-1β in the fibroblasts.

Multilayer perceptron for robust nonlinear interval regression analysis using genetic algorithms.

Science.gov (United States)

Hu, Yi-Chung

2014-01-01

On the basis of fuzzy regression, computational models in intelligence such as neural networks have the capability to be applied to nonlinear interval regression analysis for dealing with uncertain and imprecise data. When training data are not contaminated by outliers, computational models perform well by including almost all given training data in the data interval. Nevertheless, since training data are often corrupted by outliers, robust learning algorithms employed to resist outliers for interval regression analysis have been an interesting area of research. Several approaches involving computational intelligence are effective for resisting outliers, but the required parameters for these approaches are related to whether the collected data contain outliers or not. Since it seems difficult to prespecify the degree of contamination beforehand, this paper uses multilayer perceptron to construct the robust nonlinear interval regression model using the genetic algorithm. Outliers beyond or beneath the data interval will impose slight effect on the determination of data interval. Simulation results demonstrate that the proposed method performs well for contaminated datasets.

Bootstrapping Cox’s Regression Model.

Science.gov (United States)

1985-11-01

crucial points a multivariate martingale central limit theorem. Involved in this is a p x p covariance matrix Z with elements T j2= f {2(s8 ) - s(l)( s ,8o...1980). The statistical analaysis of failure time data. Wiley, New York. Meyer, P.-A. (1971). Square integrable martingales, a survey. Lecture Notes

Exploratory regression analysis: a tool for selecting models and determining predictor importance.

Science.gov (United States)

Braun, Michael T; Oswald, Frederick L

2011-06-01

Linear regression analysis is one of the most important tools in a researcher's toolbox for creating and testing predictive models. Although linear regression analysis indicates how strongly a set of predictor variables, taken together, will predict a relevant criterion (i.e., the multiple R), the analysis cannot indicate which predictors are the most important. Although there is no definitive or unambiguous method for establishing predictor variable importance, there are several accepted methods. This article reviews those methods for establishing predictor importance and provides a program (in Excel) for implementing them (available for direct download at http://dl.dropbox.com/u/2480715/ERA.xlsm?dl=1) . The program investigates all 2(p) - 1 submodels and produces several indices of predictor importance. This exploratory approach to linear regression, similar to other exploratory data analysis techniques, has the potential to yield both theoretical and practical benefits.

Regression analysis for LED color detection of visual-MIMO system

Science.gov (United States)

Banik, Partha Pratim; Saha, Rappy; Kim, Ki-Doo

2018-04-01

Color detection from a light emitting diode (LED) array using a smartphone camera is very difficult in a visual multiple-input multiple-output (visual-MIMO) system. In this paper, we propose a method to determine the LED color using a smartphone camera by applying regression analysis. We employ a multivariate regression model to identify the LED color. After taking a picture of an LED array, we select the LED array region, and detect the LED using an image processing algorithm. We then apply the k-means clustering algorithm to determine the number of potential colors for feature extraction of each LED. Finally, we apply the multivariate regression model to predict the color of the transmitted LEDs. In this paper, we show our results for three types of environmental light condition: room environmental light, low environmental light (560 lux), and strong environmental light (2450 lux). We compare the results of our proposed algorithm from the analysis of training and test R-Square (%) values, percentage of closeness of transmitted and predicted colors, and we also mention about the number of distorted test data points from the analysis of distortion bar graph in CIE1931 color space.

The first Chameleon transcriptome: comparative genomic analysis of the OXPHOS system reveals loss of COX8 in Iguanian lizards.

Science.gov (United States)

Bar-Yaacov, Dan; Bouskila, Amos; Mishmar, Dan

2013-01-01

Recently, we found dramatic mitochondrial DNA divergence of Israeli Chamaeleo chamaeleon populations into two geographically distinct groups. We aimed to examine whether the same pattern of divergence could be found in nuclear genes. However, no genomic resource is available for any chameleon species. Here we present the first chameleon transcriptome, obtained using deep sequencing (SOLiD). Our analysis identified 164,000 sequence contigs of which 19,000 yielded unique BlastX hits. To test the efficacy of our sequencing effort, we examined whether the chameleon and other available reptilian transcriptomes harbored complete sets of genes comprising known biochemical pathways, focusing on the nDNA-encoded oxidative phosphorylation (OXPHOS) genes as a model. As a reference for the screen, we used the human 86 (including isoforms) known structural nDNA-encoded OXPHOS subunits. Analysis of 34 publicly available vertebrate transcriptomes revealed orthologs for most human OXPHOS genes. However, OXPHOS subunit COX8 (Cytochrome C oxidase subunit 8), including all its known isoforms, was consistently absent in transcriptomes of iguanian lizards, implying loss of this subunit during the radiation of this suborder. The lack of COX8 in the suborder Iguania is intriguing, since it is important for cellular respiration and ATP production. Our sequencing effort added a new resource for comparative genomic studies, and shed new light on the evolutionary dynamics of the OXPHOS system.

Evaluation of syngas production unit cost of bio-gasification facility using regression analysis techniques

Energy Technology Data Exchange (ETDEWEB)

Deng, Yangyang; Parajuli, Prem B.

2011-08-10

Evaluation of economic feasibility of a bio-gasification facility needs understanding of its unit cost under different production capacities. The objective of this study was to evaluate the unit cost of syngas production at capacities from 60 through 1800Nm 3/h using an economic model with three regression analysis techniques (simple regression, reciprocal regression, and log-log regression). The preliminary result of this study showed that reciprocal regression analysis technique had the best fit curve between per unit cost and production capacity, with sum of error squares (SES) lower than 0.001 and coefficient of determination of (R 2) 0.996. The regression analysis techniques determined the minimum unit cost of syngas production for micro-scale bio-gasification facilities of $0.052/Nm 3, under the capacity of 2,880 Nm 3/h. The results of this study suggest that to reduce cost, facilities should run at a high production capacity. In addition, the contribution of this technique could be the new categorical criterion to evaluate micro-scale bio-gasification facility from the perspective of economic analysis.

Utility of COX1 phylogenetics to differentiate between locally acquired and imported Plasmodium knowlesi infections in Singapore

Science.gov (United States)

Loh, Jin Phang; Gao, Qiu Han Christine; Lee, Vernon J; Tetteh, Kevin; Drakeley, Chris

2016-01-01

INTRODUCTION Although there have been several phylogenetic studies on Plasmodium knowlesi (P. knowlesi), only cytochrome c oxidase subunit 1 (COX1) gene analysis has shown some geographical differentiation between the isolates of different countries. METHODS Phylogenetic analysis of locally acquired P. knowlesi infections, based on circumsporozoite, small subunit ribosomal ribonucleic acid (SSU rRNA), merozoite surface protein 1 and COX1 gene targets, was performed. The results were compared with the published sequences of regional isolates from Malaysia and Thailand. RESULTS Phylogenetic analysis of the circumsporozoite, SSU rRNA and merozoite surface protein 1 gene sequences for regional P. knowlesi isolates showed no obvious differentiation that could be attributed to their geographical origin. However, COX1 gene analysis showed that it was possible to differentiate between Singapore-acquired P. knowlesi infections and P. knowlesi infections from Peninsular Malaysia and Sarawak, Borneo, Malaysia. CONCLUSION The ability to differentiate between locally acquired P. knowlesi infections and imported P. knowlesi infections has important utility for the monitoring of P. knowlesi malaria control programmes in Singapore. PMID:26805667

Utility of COX1 phylogenetics to differentiate between locally acquired and imported Plasmodium knowlesi infections in Singapore.

Science.gov (United States)

Loh, Jin Phang; Gao, Qiu Han Christine; Lee, Vernon J; Tetteh, Kevin; Drakeley, Chris

2016-12-01

Although there have been several phylogenetic studies on Plasmodium knowlesi (P. knowlesi), only cytochrome c oxidase subunit 1 (COX1) gene analysis has shown some geographical differentiation between the isolates of different countries. Phylogenetic analysis of locally acquired P. knowlesi infections, based on circumsporozoite, small subunit ribosomal ribonucleic acid (SSU rRNA), merozoite surface protein 1 and COX1 gene targets, was performed. The results were compared with the published sequences of regional isolates from Malaysia and Thailand. Phylogenetic analysis of the circumsporozoite, SSU rRNA and merozoite surface protein 1 gene sequences for regional P. knowlesi isolates showed no obvious differentiation that could be attributed to their geographical origin. However, COX1 gene analysis showed that it was possible to differentiate between Singapore-acquired P. knowlesi infections and P. knowlesi infections from Peninsular Malaysia and Sarawak, Borneo, Malaysia. The ability to differentiate between locally acquired P. knowlesi infections and imported P. knowlesi infections has important utility for the monitoring of P. knowlesi malaria control programmes in Singapore. Copyright: © Singapore Medical Association

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

DEFF Research Database (Denmark)

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

2017-01-01

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

Minimizing the cancer-promotional activity of cox-2 as a central strategy in cancer prevention.

Science.gov (United States)

McCarty, Mark F

2012-01-01

A recent meta-analysis examining long-term mortality in subjects who participated in controlled studies evaluating the impact of daily aspirin on vascular risk, has concluded that aspirin confers substantial protection from cancer mortality. Remarkably, low-dose aspirin was as effective as higher-dose regimens; hence this protection may be achievable with minimal risk. There is reason to believe that this protection stems primarily from inhibition of cox-2 in pre-neoplastic lesions. Since safe aspirin regimens can only achieve a partial and transitory inhibition of cox-2, it may be feasible to complement the cancer-protective benefit of aspirin with other measures which decrease cox-2 expression or which limit the bioactivity of cox-2-derived PGE2. Oxidative stress boosts cox-2 expression by up-regulating activation of NF-kappaB and MAP kinases; NADPH oxidase activation may thus promote carcinogenesis by increasing cox-2 expression while also amplifying oxidant-mediated mutagenesis. A prospective cohort study has observed that relatively elevated serum bilirubin levels are associated with a marked reduction in subsequent cancer mortality; this may reflect bilirubin's physiological role as a potent inhibitor of NADPH oxidase. It may be feasible to mimic this protective effect by supplementing with spirulina, a rich source of a phycobilin which shares bilirubin's ability to inhibit NADPH oxidase. Ancillary antioxidant measures - phase 2 inducing phytochemicals, melatonin, N-acetylcysteine, and astaxanthin - may also aid cox-2 down-regulation. The cancer protection often associated with high-normal vitamin D status may be attributable, in part, to the ability of the activated vitamin D receptor to decrease cox-2 expression while promoting PGE2 catabolism and suppressing the expression of PGE2 receptors. Diets with a relatively low ratio of omega-6 to long-chain omega-3 fats may achieve cancer protection by antagonizing the production and bioactivity of PGE2. Growth

On spatio-temporal Lévy based Cox processes

DEFF Research Database (Denmark)

Prokesova, Michaela; Hellmund, Gunnar; Jensen, Eva Bjørn Vedel

2006-01-01

The paper discusses a new class of models for spatio-temporal Cox point processes. In these models, the driving field is defined by means of an integral of a weight function with respect to a Lévy basis. The relations to other Cox process models studied previously are discussed and formulas for t...

COX-2 rs689466, rs5275, and rs20417 polymorphisms and risk of head and neck squamous cell carcinoma: a meta-analysis of adjusted and unadjusted data

International Nuclear Information System (INIS)

Leng, Wei-Dong; Wen, Xiu-Jie; Kwong, Joey S. W.; Huang, Wei; Chen, Jian-Gang; Zeng, Xian-Tao

2016-01-01

Numerous case–control studies have been performed to investigate the association between three cyclooxygenase-2 (COX-2) polymorphisms (rs20417 (−765G > C), rs689466 (−1195G > A), and rs5275 (8473 T > C)) and the risk of head and neck squamous cell carcinoma (HNSCC). However, the results were inconsistent. Therefore, we conducted this meta-analysis to investigate the association. We searched in PubMed, Embase, and Web of Science up to January 20, 2015 (last updated on May 12, 2016). Two independent reviewers extracted the data. Odds ratios (ORs) with their 95 % confidence intervals (CIs) were used to assess the association. All statistical analyses were performed using the Review Manager (RevMan) 5.2 software. Finally 8 case–control studies were included in this meta-analysis. For unadjusted data, an association with increased risk was observed in three genetic models in COX-2 rs689466 polymorphism; however, COX-2 rs5275 and rs20417 polymorphisms were not related to HNSCC risk in this study. The pooled results from adjusted data all revealed non-significant association between these three polymorphisms and risk of HNSCC. We also found a similar result in the subgroup analyses, based on both unadjusted data and adjusted data. Current results suggest that COX-2 rs689466, rs5275, and rs20417 polymorphisms are not associated with HNSCC. Further large and well-designed studies are necessary to validate this association

Transgenic expression of cyclooxygenase-2 (COX2) causes premature aging phenotypes in mice.

Science.gov (United States)

Kim, Joohwee; Vaish, Vivek; Feng, Mingxiao; Field, Kevin; Chatzistamou, Ioulia; Shim, Minsub

2016-10-07

Cyclooxygenase (COX) is a key enzyme in the biosynthesis of prostanoids, lipid signaling molecules that regulate various physiological processes. COX2, one of the isoforms of COX, is highly inducible in response to a wide variety of cellular and environmental stresses. Increased COX2 expression is thought to play a role in the pathogenesis of many age-related diseases. COX2 expression is also reported to be increased in the tissues of aged humans and mice, which suggests the involvement of COX2 in the aging process. However, it is not clear whether the increased COX2 expression is causal to or a result of aging. We have now addressed this question by creating an inducible COX2 transgenic mouse model. Here we show that post-natal expression of COX2 led to a panel of aging-related phenotypes. The expression of p16, p53, and phospho-H2AX was increased in the tissues of COX2 transgenic mice. Additionally, adult mouse lung fibroblasts from COX2 transgenic mice exhibited increased expression of the senescence-associated β-galactosidase. Our study reveals that the increased COX2 expression has an impact on the aging process and suggests that modulation of COX2 and its downstream signaling may be an approach for intervention of age-related disorders.

A primer for biomedical scientists on how to execute model II linear regression analysis.

Science.gov (United States)

Ludbrook, John

2012-04-01

1. There are two very different ways of executing linear regression analysis. One is Model I, when the x-values are fixed by the experimenter. The other is Model II, in which the x-values are free to vary and are subject to error. 2. I have received numerous complaints from biomedical scientists that they have great difficulty in executing Model II linear regression analysis. This may explain the results of a Google Scholar search, which showed that the authors of articles in journals of physiology, pharmacology and biochemistry rarely use Model II regression analysis. 3. I repeat my previous arguments in favour of using least products linear regression analysis for Model II regressions. I review three methods for executing ordinary least products (OLP) and weighted least products (WLP) regression analysis: (i) scientific calculator and/or computer spreadsheet; (ii) specific purpose computer programs; and (iii) general purpose computer programs. 4. Using a scientific calculator and/or computer spreadsheet, it is easy to obtain correct values for OLP slope and intercept, but the corresponding 95% confidence intervals (CI) are inaccurate. 5. Using specific purpose computer programs, the freeware computer program smatr gives the correct OLP regression coefficients and obtains 95% CI by bootstrapping. In addition, smatr can be used to compare the slopes of OLP lines. 6. When using general purpose computer programs, I recommend the commercial programs systat and Statistica for those who regularly undertake linear regression analysis and I give step-by-step instructions in the Supplementary Information as to how to use loss functions. © 2011 The Author. Clinical and Experimental Pharmacology and Physiology. © 2011 Blackwell Publishing Asia Pty Ltd.

External Tank Liquid Hydrogen (LH2) Prepress Regression Analysis Independent Review Technical Consultation Report

Science.gov (United States)

Parsons, Vickie s.

2009-01-01

The request to conduct an independent review of regression models, developed for determining the expected Launch Commit Criteria (LCC) External Tank (ET)-04 cycle count for the Space Shuttle ET tanking process, was submitted to the NASA Engineering and Safety Center NESC on September 20, 2005. The NESC team performed an independent review of regression models documented in Prepress Regression Analysis, Tom Clark and Angela Krenn, 10/27/05. This consultation consisted of a peer review by statistical experts of the proposed regression models provided in the Prepress Regression Analysis. This document is the consultation's final report.

Tutorial on Biostatistics: Linear Regression Analysis of Continuous Correlated Eye Data.

Science.gov (United States)

Ying, Gui-Shuang; Maguire, Maureen G; Glynn, Robert; Rosner, Bernard

2017-04-01

To describe and demonstrate appropriate linear regression methods for analyzing correlated continuous eye data. We describe several approaches to regression analysis involving both eyes, including mixed effects and marginal models under various covariance structures to account for inter-eye correlation. We demonstrate, with SAS statistical software, applications in a study comparing baseline refractive error between one eye with choroidal neovascularization (CNV) and the unaffected fellow eye, and in a study determining factors associated with visual field in the elderly. When refractive error from both eyes were analyzed with standard linear regression without accounting for inter-eye correlation (adjusting for demographic and ocular covariates), the difference between eyes with CNV and fellow eyes was 0.15 diopters (D; 95% confidence interval, CI -0.03 to 0.32D, p = 0.10). Using a mixed effects model or a marginal model, the estimated difference was the same but with narrower 95% CI (0.01 to 0.28D, p = 0.03). Standard regression for visual field data from both eyes provided biased estimates of standard error (generally underestimated) and smaller p-values, while analysis of the worse eye provided larger p-values than mixed effects models and marginal models. In research involving both eyes, ignoring inter-eye correlation can lead to invalid inferences. Analysis using only right or left eyes is valid, but decreases power. Worse-eye analysis can provide less power and biased estimates of effect. Mixed effects or marginal models using the eye as the unit of analysis should be used to appropriately account for inter-eye correlation and maximize power and precision.

Non-stationary hydrologic frequency analysis using B-spline quantile regression

Science.gov (United States)

Nasri, B.; Bouezmarni, T.; St-Hilaire, A.; Ouarda, T. B. M. J.

2017-11-01

Hydrologic frequency analysis is commonly used by engineers and hydrologists to provide the basic information on planning, design and management of hydraulic and water resources systems under the assumption of stationarity. However, with increasing evidence of climate change, it is possible that the assumption of stationarity, which is prerequisite for traditional frequency analysis and hence, the results of conventional analysis would become questionable. In this study, we consider a framework for frequency analysis of extremes based on B-Spline quantile regression which allows to model data in the presence of non-stationarity and/or dependence on covariates with linear and non-linear dependence. A Markov Chain Monte Carlo (MCMC) algorithm was used to estimate quantiles and their posterior distributions. A coefficient of determination and Bayesian information criterion (BIC) for quantile regression are used in order to select the best model, i.e. for each quantile, we choose the degree and number of knots of the adequate B-spline quantile regression model. The method is applied to annual maximum and minimum streamflow records in Ontario, Canada. Climate indices are considered to describe the non-stationarity in the variable of interest and to estimate the quantiles in this case. The results show large differences between the non-stationary quantiles and their stationary equivalents for an annual maximum and minimum discharge with high annual non-exceedance probabilities.

Survival analysis of postoperative nausea and vomiting in patients receiving patient-controlled epidural analgesia

Directory of Open Access Journals (Sweden)

Shang-Yi Lee

2014-11-01

Conclusion: Survival analysis using Cox regression showed that the average consumption of opioids played an important role in postoperative nausea and vomiting, a result not found by logistic regression. Therefore, the incidence of postoperative nausea and vomiting in patients cannot be reliably determined on the basis of a single visit at one point in time.

Alternative Methods of Regression

CERN Document Server

Birkes, David

2011-01-01

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

On macroeconomic values investigation using fuzzy linear regression analysis

Directory of Open Access Journals (Sweden)

Richard Pospíšil

2017-06-01

Full Text Available The theoretical background for abstract formalization of the vague phenomenon of complex systems is the fuzzy set theory. In the paper, vague data is defined as specialized fuzzy sets - fuzzy numbers and there is described a fuzzy linear regression model as a fuzzy function with fuzzy numbers as vague parameters. To identify the fuzzy coefficients of the model, the genetic algorithm is used. The linear approximation of the vague function together with its possibility area is analytically and graphically expressed. A suitable application is performed in the tasks of the time series fuzzy regression analysis. The time-trend and seasonal cycles including their possibility areas are calculated and expressed. The examples are presented from the economy field, namely the time-development of unemployment, agricultural production and construction respectively between 2009 and 2011 in the Czech Republic. The results are shown in the form of the fuzzy regression models of variables of time series. For the period 2009-2011, the analysis assumptions about seasonal behaviour of variables and the relationship between them were confirmed; in 2010, the system behaved fuzzier and the relationships between the variables were vaguer, that has a lot of causes, from the different elasticity of demand, through state interventions to globalization and transnational impacts.

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)

Predicting a future lifetime through Box-Cox transformation.

Science.gov (United States)

Yang, Z

1999-09-01

In predicting a future lifetime based on a sample of past lifetimes, the Box-Cox transformation method provides a simple and unified procedure that is shown in this article to meet or often outperform the corresponding frequentist solution in terms of coverage probability and average length of prediction intervals. Kullback-Leibler information and second-order asymptotic expansion are used to justify the Box-Cox procedure. Extensive Monte Carlo simulations are also performed to evaluate the small sample behavior of the procedure. Certain popular lifetime distributions, such as Weibull, inverse Gaussian and Birnbaum-Saunders are served as illustrative examples. One important advantage of the Box-Cox procedure lies in its easy extension to linear model predictions where the exact frequentist solutions are often not available.

REGRESSION ANALYSIS OF SEA-SURFACE-TEMPERATURE PATTERNS FOR THE NORTH PACIFIC OCEAN.

Science.gov (United States)

SEA WATER, *SURFACE TEMPERATURE, *OCEANOGRAPHIC DATA, PACIFIC OCEAN, REGRESSION ANALYSIS , STATISTICAL ANALYSIS, UNDERWATER EQUIPMENT, DETECTION, UNDERWATER COMMUNICATIONS, DISTRIBUTION, THERMAL PROPERTIES, COMPUTERS.

Regression analysis understanding and building business and economic models using Excel

CERN Document Server

Wilson, J Holton

2012-01-01

The technique of regression analysis is used so often in business and economics today that an understanding of its use is necessary for almost everyone engaged in the field. This book will teach you the essential elements of building and understanding regression models in a business/economic context in an intuitive manner. The authors take a non-theoretical treatment that is accessible even if you have a limited statistical background. It is specifically designed to teach the correct use of regression, while advising you of its limitations and teaching about common pitfalls. This book describe

COX-independent mechanisms of cancer chemoprevention by anti-inflammatory drugs

Directory of Open Access Journals (Sweden)

Evrim eGurpinar

2013-07-01

Full Text Available Epidemiological and clinical studies suggest that non-steroidal anti-inflammatory drugs (NSAIDs, including cyclooxygenase (COX-2 selective inhibitors, reduce the risk of developing cancer. Experimental studies in human cancer cell lines and rodent models of carcinogenesis support these observations by providing strong evidence for the antineoplastic properties of NSAIDs. The involvement of COX-2 in tumorigenesis and its overexpression in various cancer tissues suggest that inhibition of COX-2 is responsible for the chemopreventive efficacy of these agents. However, the precise mechanisms by which NSAIDs exert their antiproliferative effects are still a matter of debate. Numerous other studies have shown that NSAIDs can act through COX-independent mechanisms. This review provides a detailed description of the major COX-independent molecular targets of NSAIDs and discusses how these targets may be involved in their anticancer effects. Toxicities resulting from COX inhibition and the suppression of prostaglandin synthesis preclude the long-term use of NSAIDs for cancer chemoprevention. Furthermore, chemopreventive efficacy is incomplete and treatment often leads to the development of resistance. Identification of alternative NSAID targets and elucidation of the biochemical processes by which they inhibit tumor growth could lead to the development of safer and more efficacious drugs for cancer chemoprevention.

Two encyclopedia contributions

DEFF Research Database (Denmark)

Andersen, Per Kragh

2003-01-01

censoring; Cox regression model; counting process; event history analysis; intensity process; multi-state model; non-parametric inference; parametric models; survival analysis; Cox's proportional hazards model; hazard function, regression model; time-dependent covariate; time scale...

Nonlinear regression analysis for evaluating tracer binding parameters using the programmable K1003 desk computer

International Nuclear Information System (INIS)

Sarrach, D.; Strohner, P.

1986-01-01

The Gauss-Newton algorithm has been used to evaluate tracer binding parameters of RIA by nonlinear regression analysis. The calculations were carried out on the K1003 desk computer. Equations for simple binding models and its derivatives are presented. The advantages of nonlinear regression analysis over linear regression are demonstrated

Regression analysis for the social sciences

CERN Document Server

Gordon, Rachel A

2010-01-01

The book provides graduate students in the social sciences with the basic skills that they need to estimate, interpret, present, and publish basic regression models using contemporary standards. Key features of the book include: interweaving the teaching of statistical concepts with examples developed for the course from publicly-available social science data or drawn from the literature. thorough integration of teaching statistical theory with teaching data processing and analysis. teaching of both SAS and Stata "side-by-side" and use of chapter exercises in which students practice programming and interpretation on the same data set and course exercises in which students can choose their own research questions and data set.

Determinant Factors in Graft Rejection Using Cox Regression, among the Recipients of Second Renal Transplant in Imam Khomeini Hospital in Urmia, 1988-2000

Directory of Open Access Journals (Sweden)

Rahim Tahmasebi

2010-09-01

Full Text Available Background: The objective of this study was to evaluate graft survival among the recipients of second renal transplant in Imam Khomeini centre hospital in Urmia. Methods: The study population consisted of 50 patients receiving renal grafts for the second time between 1988 and 2008 in Imam Khomeini centre hospital in Urmia. Two survival outcomes, first and second graft survival, were analyzed. Graft survival was defined from date of transplant until its rejection. For the purpose of graft survival analysis, graft failure was defined as return to dialysis, and death due to the functioning graft. Data were collected through individual patient questionnaires. Demographic and clinical factors, transfusion history, type of immunosuppressive drugs, levels of serum creatinine, triglyceride, cholesterol, and LDL at 3 and 6 months after transplantation were collected. Cox-proportional hazard model and Kaplan-Meier were used to data analysis. Results: First graft survival at 1, 2, 3, and 5 years was 74%, 66%, 53%, and 41%, respectively. Second graft survival at 1, 2, 3, and 5 years was 81%, 74%, 70%, and 61%, respectively. Causes of graft loss in first renal transplantation were 6% sever acute graft rejection, 12% acute graft rejection and 82% chronic graft rejection. In the multivariate analysis, only serum creatinine, blood pressure, and immunosuppressive drugs predicted first graft loss and serum creatinine, immunosuppressive drugs, and related donor family predicted second graft rejection. Conclusion: The serum creatinine and immunosuppressive drugs including cyclosporine, cellcept, and prednisolone are the most influential factors on graft survival.

Involvement of Cox-2 in the metastatic potential of chemotherapy-resistant breast cancer cells

International Nuclear Information System (INIS)

Kang, Ju-Hee; Song, Ki-Hoon; Jeong, Kyung-Chae; Kim, Sunshin; Choi, Changsun; Lee, Chang Hoon; Oh, Seung Hyun

2011-01-01

A major problem with the use of current chemotherapy regimens for several cancers, including breast cancer, is development of intrinsic or acquired drug resistance, which results in disease recurrence and metastasis. However, the mechanisms underlying this drug resistance are unknown. To study the molecular mechanisms underlying the invasive and metastatic activities of drug-resistant cancer cells, we generated a doxorubicin-resistant MCF-7 breast cancer cell line (MCF-7/DOX). We used MTT (3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide) assays, flow cytometry assays, DNA fragmentation assays, Western blot analysis, cell invasion assays, small interfering RNA (siRNA) transfection, reverse transcription-polymerase chain reaction, experimental lung metastasis models, and gelatin and fibrinogen/plasminogen zymography to study the molecular mechanism of metastatic activities in MCF-7/DOX cells. We found that MCF-7/DOX acquired invasive activities. In addition, Western blot analysis showed increased expression of epidermal growth factor receptor (EGFR) and Cox-2 in MCF-7/DOX cells. Inhibition of Cox-2, phosphoinositide 3-kinase (PI3K)/Akt, or mitogen-activated protein kinase (MAPK) pathways effectively inhibited the invasive activities of MCF-7/DOX cells. Gelatin and fibrinogen/plasminogen zymography analysis showed that the enzymatic activities of matrix metalloproteinase-2 (MMP-2), MMP-9, and urokinase-type plasminogen activator were markedly higher in MCF-7/DOX cells than in the MCF-7 cells. In vitro invasion assays and mouse models of lung metastasis demonstrated that MCF-7/DOX cells acquired invasive abilities. Using siRNAs and agonists specific for prostaglandin E (EP) receptors, we found that EP1 and EP3 played important roles in the invasiveness of MCF-7/DOX cells. We found that the invasive activity of MCF-7/DOX cells is mediated by Cox-2, which is induced by the EGFR-activated PI3K/Akt and MAPK pathways. In addition, EP1 and EP3 are important in

Multivariate Linear Regression and CART Regression Analysis of TBM Performance at Abu Hamour Phase-I Tunnel

Science.gov (United States)

Jakubowski, J.; Stypulkowski, J. B.; Bernardeau, F. G.

2017-12-01

The first phase of the Abu Hamour drainage and storm tunnel was completed in early 2017. The 9.5 km long, 3.7 m diameter tunnel was excavated with two Earth Pressure Balance (EPB) Tunnel Boring Machines from Herrenknecht. TBM operation processes were monitored and recorded by Data Acquisition and Evaluation System. The authors coupled collected TBM drive data with available information on rock mass properties, cleansed, completed with secondary variables and aggregated by weeks and shifts. Correlations and descriptive statistics charts were examined. Multivariate Linear Regression and CART regression tree models linking TBM penetration rate (PR), penetration per revolution (PPR) and field penetration index (FPI) with TBM operational and geotechnical characteristics were performed for the conditions of the weak/soft rock of Doha. Both regression methods are interpretable and the data were screened with different computational approaches allowing enriched insight. The primary goal of the analysis was to investigate empirical relations between multiple explanatory and responding variables, to search for best subsets of explanatory variables and to evaluate the strength of linear and non-linear relations. For each of the penetration indices, a predictive model coupling both regression methods was built and validated. The resultant models appeared to be stronger than constituent ones and indicated an opportunity for more accurate and robust TBM performance predictions.

Extensions and Applications of the Cox-Aalen Survival Model

DEFF Research Database (Denmark)

Scheike, Thomas H.; Zhang, Mei-Jie

2003-01-01

Aalen additive risk model; competing risk; counting processes; Cox model; cumulative incidence function; goodness of fit; prediction of survival probability; time-varying effects......Aalen additive risk model; competing risk; counting processes; Cox model; cumulative incidence function; goodness of fit; prediction of survival probability; time-varying effects...

Composite marginal quantile regression analysis for longitudinal adolescent body mass index data.

Science.gov (United States)

Yang, Chi-Chuan; Chen, Yi-Hau; Chang, Hsing-Yi

2017-09-20

Childhood and adolescenthood overweight or obesity, which may be quantified through the body mass index (BMI), is strongly associated with adult obesity and other health problems. Motivated by the child and adolescent behaviors in long-term evolution (CABLE) study, we are interested in individual, family, and school factors associated with marginal quantiles of longitudinal adolescent BMI values. We propose a new method for composite marginal quantile regression analysis for longitudinal outcome data, which performs marginal quantile regressions at multiple quantile levels simultaneously. The proposed method extends the quantile regression coefficient modeling method introduced by Frumento and Bottai (Biometrics 2016; 72:74-84) to longitudinal data accounting suitably for the correlation structure in longitudinal observations. A goodness-of-fit test for the proposed modeling is also developed. Simulation results show that the proposed method can be much more efficient than the analysis without taking correlation into account and the analysis performing separate quantile regressions at different quantile levels. The application to the longitudinal adolescent BMI data from the CABLE study demonstrates the practical utility of our proposal. Copyright © 2017 John Wiley & Sons, Ltd. Copyright © 2017 John Wiley & Sons, Ltd.

Involvement of COX2–thromboxane pathway in TCDD-induced precardiac edema in developing zebrafish

International Nuclear Information System (INIS)

Teraoka, Hiroki; Okuno, Yuki; Nijoukubo, Daisuke; Yamakoshi, Ayumi; Peterson, Richard E.; Stegeman, John J.; Kitazawa, Takio; Hiraga, Takeo; Kubota, Akira

2014-01-01

Highlights: • We establish a new indicator of pericardial edema in developing zebrafish (precardiac edema). • Property of precardiac edema by TCDD is similar to that for conventional pericardial edema. • COX2b (but not COX2a)–thromboxane pathway is involved in precardiac edema by TCDD. - Abstract: The cardiovascular system is one of the most characteristic and important targets for developmental toxicity by 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD) in fish larvae. However, knowledge of the mechanism of TCDD-induced edema after heterodimerization of aryl hydrocarbon receptor type 2 (AHR2) and AHR nuclear translocator type 1 (ARNT1) is still limited. In the present study, microscopic analysis with a high-speed camera revealed that TCDD increased the size of a small cavity between the heart and body wall in early eleutheroembryos, a toxic effect that we designate as precardiac edema. A concentration–response curve for precardiac edema at 2 days post fertilization (dpf) showed close similarity to that for conventional pericardial edema at 3 dpf. Precardiac edema caused by TCDD was reduced by morpholino knockdown of AHR2 and ARNT1, as well as by an antioxidant (ascorbic acid). A selective inhibitor of cyclooxygenase type 2 (COX2), NS398, also markedly inhibited TCDD-induced precardiac edema. A thromboxane receptor (TP) antagonist, ICI-192,605 almost abolished TCDD-induced precardiac edema and this effect was canceled by U46619, a TP agonist, which was not influential in the action of TCDD by itself. Knockdown of COX2b and thromboxane A synthase 1 (TBXS), but not COX2a, strongly reduced TCDD-induced precardiac edema. Knockdown of COX2b was without effect on mesencephalic circulation failure caused by TCDD. The edema by TCDD was also inhibited by knockdown of c-mpl, a thrombopoietin receptor necessary for thromobocyte production. Finally, induction of COX2b, but not COX2a, by TCDD was seen in eleutheroembryos at 3 dpf. These results suggest a role of the COX2b�

Involvement of COX2–thromboxane pathway in TCDD-induced precardiac edema in developing zebrafish

Energy Technology Data Exchange (ETDEWEB)

Teraoka, Hiroki, E-mail: hteraoka@rakuno.ac.jp [School of Veterinary Medicine, Rakuno Gakuen University, Ebetsu (Japan); Okuno, Yuki; Nijoukubo, Daisuke; Yamakoshi, Ayumi [School of Veterinary Medicine, Rakuno Gakuen University, Ebetsu (Japan); Peterson, Richard E. [School of Pharmacy, University of Wisconsin, Madison, WI (United States); Stegeman, John J. [Biology Department, Woods Hole Oceanographic Institution, Woods Hole, MA (United States); Kitazawa, Takio; Hiraga, Takeo [School of Veterinary Medicine, Rakuno Gakuen University, Ebetsu (Japan); Kubota, Akira [School of Veterinary Medicine, Rakuno Gakuen University, Ebetsu (Japan); Biology Department, Woods Hole Oceanographic Institution, Woods Hole, MA (United States)

2014-09-15

Highlights: • We establish a new indicator of pericardial edema in developing zebrafish (precardiac edema). • Property of precardiac edema by TCDD is similar to that for conventional pericardial edema. • COX2b (but not COX2a)–thromboxane pathway is involved in precardiac edema by TCDD. - Abstract: The cardiovascular system is one of the most characteristic and important targets for developmental toxicity by 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD) in fish larvae. However, knowledge of the mechanism of TCDD-induced edema after heterodimerization of aryl hydrocarbon receptor type 2 (AHR2) and AHR nuclear translocator type 1 (ARNT1) is still limited. In the present study, microscopic analysis with a high-speed camera revealed that TCDD increased the size of a small cavity between the heart and body wall in early eleutheroembryos, a toxic effect that we designate as precardiac edema. A concentration–response curve for precardiac edema at 2 days post fertilization (dpf) showed close similarity to that for conventional pericardial edema at 3 dpf. Precardiac edema caused by TCDD was reduced by morpholino knockdown of AHR2 and ARNT1, as well as by an antioxidant (ascorbic acid). A selective inhibitor of cyclooxygenase type 2 (COX2), NS398, also markedly inhibited TCDD-induced precardiac edema. A thromboxane receptor (TP) antagonist, ICI-192,605 almost abolished TCDD-induced precardiac edema and this effect was canceled by U46619, a TP agonist, which was not influential in the action of TCDD by itself. Knockdown of COX2b and thromboxane A synthase 1 (TBXS), but not COX2a, strongly reduced TCDD-induced precardiac edema. Knockdown of COX2b was without effect on mesencephalic circulation failure caused by TCDD. The edema by TCDD was also inhibited by knockdown of c-mpl, a thrombopoietin receptor necessary for thromobocyte production. Finally, induction of COX2b, but not COX2a, by TCDD was seen in eleutheroembryos at 3 dpf. These results suggest a role of the COX2b�

Treating experimental data of inverse kinetic method by unitary linear regression analysis

International Nuclear Information System (INIS)

Zhao Yusen; Chen Xiaoliang

2009-01-01

The theory of treating experimental data of inverse kinetic method by unitary linear regression analysis was described. Not only the reactivity, but also the effective neutron source intensity could be calculated by this method. Computer code was compiled base on the inverse kinetic method and unitary linear regression analysis. The data of zero power facility BFS-1 in Russia were processed and the results were compared. The results show that the reactivity and the effective neutron source intensity can be obtained correctly by treating experimental data of inverse kinetic method using unitary linear regression analysis and the precision of reactivity measurement is improved. The central element efficiency can be calculated by using the reactivity. The result also shows that the effect to reactivity measurement caused by external neutron source should be considered when the reactor power is low and the intensity of external neutron source is strong. (authors)

Regression analysis of informative current status data with the additive hazards model.

Science.gov (United States)

Zhao, Shishun; Hu, Tao; Ma, Ling; Wang, Peijie; Sun, Jianguo

2015-04-01

This paper discusses regression analysis of current status failure time data arising from the additive hazards model in the presence of informative censoring. Many methods have been developed for regression analysis of current status data under various regression models if the censoring is noninformative, and also there exists a large literature on parametric analysis of informative current status data in the context of tumorgenicity experiments. In this paper, a semiparametric maximum likelihood estimation procedure is presented and in the method, the copula model is employed to describe the relationship between the failure time of interest and the censoring time. Furthermore, I-splines are used to approximate the nonparametric functions involved and the asymptotic consistency and normality of the proposed estimators are established. A simulation study is conducted and indicates that the proposed approach works well for practical situations. An illustrative example is also provided.

DPPC regulates COX-2 expression in monocytes via phosphorylation of CREB

International Nuclear Information System (INIS)

Morris, R.H.K.; Tonks, A.J.; Jones, K.P.; Ahluwalia, M.K.; Thomas, A.W.; Tonks, A.; Jackson, S.K.

2008-01-01

The major phospholipid in pulmonary surfactant dipalmitoyl phosphatidylcholine (DPPC) has been shown to modulate inflammatory responses. Using human monocytes, this study demonstrates that DPPC significantly increased PGE 2 (P < 0.05) production by 2.5-fold when compared to untreated monocyte controls. Mechanistically, this effect was concomitant with an increase in COX-2 expression which was abrogated in the presence of a COX-2 inhibitor. The regulation of COX-2 expression was independent of NF-κB activity. Further, DPPC increased the phosphorylation of the cyclic AMP response element binding protein (CREB; an important nuclear transcription factor important in regulating COX-2 expression). In addition, we also show that changing the fatty acid groups of PC (e.g. using L-α-phosphatidylcholine β-arachidonoyl-γ-palmitoyl (PAPC)) has a profound effect on the regulation of COX-2 expression and CREB activation. This study provides new evidence for the anti-inflammatory activity of DPPC and that this activity is at least in part mediated via CREB activation of COX-2

Late Results of Cox Maze III Procedure in Patients with Atrial Fibrillation Associated with Structural Heart Disease.

Science.gov (United States)

Gomes, Gustavo Gir; Gali, Wagner Luis; Sarabanda, Alvaro Valentim Lima; Cunha, Claudio Ribeiro da; Kessler, Iruena Moraes; Atik, Fernando Antibas

2017-07-01

Cox-Maze III procedure is one of the surgical techniques used in the surgical treatment of atrial fibrillation (AF). To determine late results of Cox-Maze III in terms of maintenance of sinus rhythm, and mortality and stroke rates. Between January 2006 and January 2013, 93 patients were submitted to the cut-and-sew Cox-Maze III procedure in combination with structural heart disease repair. Heart rhythm was determined by 24-hour Holter monitoring. Procedural success rates were determined by longitudinal methods and recurrence predictors by multivariate Cox regression models. Thirteen patients that obtained hospital discharge alive were excluded due to lost follow-up. The remaining 80 patients were aged 49.9 ± 12 years and 47 (58.7%) of them were female. Involvement of mitral valve and rheumatic heart disease were found in 67 (83.7%) and 63 (78.7%) patients, respectively. Seventy patients (87.5%) had persistent or long-standing persistent AF. Mean follow-up with Holter monitoring was 27.5 months. There were no hospital deaths. Sinus rhythm maintenance rates were 88%, 85.1% and 80.6% at 6 months, 24 months and 36 months, respectively. Predictors of late recurrence of AF were female gender (HR 3.52; 95% CI 1.21-10.25; p = 0.02), coronary artery disease (HR 4.73 95% CI 1.37-16.36; p = 0.01) and greater left atrium diameter (HR 1.05; 95% CI 1.01-1.09; p = 0.02). Actuarial survival was 98.5% at 12, 24 and 48 months and actuarial freedom from stroke was 100%, 100% and 97.5% in the same time frames. The Cox-Maze III procedure, in our experience, is efficacious for sinus rhythm maintenance, with very low late mortality and stroke rates. A operação de Cox-Maze III é uma das variantes técnicas no tratamento cirúrgico da fibrilação atrial (FA). Estudar os resultados tardios da operação de Cox-Maze III, quanto à eficácia na manutenção de ritmo sinusal e taxas de mortalidade e acidente vascular cerebral (AVC). Entre janeiro de 2006 a janeiro de 2013, 93 pacientes

Credit Scoring Problem Based on Regression Analysis

OpenAIRE

Khassawneh, Bashar Suhil Jad Allah

2014-01-01

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

MULGRES: a computer program for stepwise multiple regression analysis

Science.gov (United States)

A. Jeff Martin

1971-01-01

MULGRES is a computer program source deck that is designed for multiple regression analysis employing the technique of stepwise deletion in the search for most significant variables. The features of the program, along with inputs and outputs, are briefly described, with a note on machine compatibility.

Real-time regression analysis with deep convolutional neural networks

OpenAIRE

Huerta, E. A.; George, Daniel; Zhao, Zhizhen; Allen, Gabrielle

2018-01-01

We discuss the development of novel deep learning algorithms to enable real-time regression analysis for time series data. We showcase the application of this new method with a timely case study, and then discuss the applicability of this approach to tackle similar challenges across science domains.

Generalised shot noise Cox processes

DEFF Research Database (Denmark)

Møller, Jesper; Torrisi, Giovanni Luca

We introduce a new class of Cox cluster processes called generalised shot-noise processes (GSNCPs), which extends the definition of shot noise Cox processes (SNCPs) in two directions: the point process which drives the shot noise is not necessarily Poisson, and the kernel of the shot noise can...... be random. Thereby a very large class of models for aggregated or clustered point patterns is obtained. Due to the structure of GSNCPs, a number of useful results can be established. We focus first on deriving summary statistics for GSNCPs and next on how to make simulation for GSNCPs. Particularly, results...... for first and second order moment measures, reduced Palm distributions, the -function, simulation with or without edge effects, and conditional simulation of the intensity function driving a GSNCP are given. Our results are exemplified for special important cases of GSNCPs, and we discuss the relation...

[Comparison of application of Cochran-Armitage trend test and linear regression analysis for rate trend analysis in epidemiology study].

Science.gov (United States)

Wang, D Z; Wang, C; Shen, C F; Zhang, Y; Zhang, H; Song, G D; Xue, X D; Xu, Z L; Zhang, S; Jiang, G H

2017-05-10

We described the time trend of acute myocardial infarction (AMI) from 1999 to 2013 in Tianjin incidence rate with Cochran-Armitage trend (CAT) test and linear regression analysis, and the results were compared. Based on actual population, CAT test had much stronger statistical power than linear regression analysis for both overall incidence trend and age specific incidence trend (Cochran-Armitage trend P valuelinear regression P value). The statistical power of CAT test decreased, while the result of linear regression analysis remained the same when population size was reduced by 100 times and AMI incidence rate remained unchanged. The two statistical methods have their advantages and disadvantages. It is necessary to choose statistical method according the fitting degree of data, or comprehensively analyze the results of two methods.

Nucleobindin co-localizes and associates with cyclooxygenase (COX-2 in human neutrophils.

Directory of Open Access Journals (Sweden)

Patrick Leclerc

2008-05-01

Full Text Available The inducible cyclooxygenase isoform (COX-2 is associated with inflammation, tumorigenesis, as well as with physiological events. Despite efforts deployed in order to understand the biology of this multi-faceted enzyme, much remains to be understood. Nucleobindin (Nuc, a ubiquitous Ca(2+-binding protein, possesses a putative COX-binding domain. In this study, we investigated its expression and subcellular localization in human neutrophils, its affinity for COX-2 as well as its possible impact on PGE(2 biosynthesis. Complementary subcellular localization approaches including nitrogen cavitation coupled to Percoll fractionation, immunofluorescence, confocal and electron microscopy collectively placed Nuc, COX-2, and all of the main enzymes involved in prostanoid synthesis, in the Golgi apparatus and endoplasmic reticulum of human neutrophils. Immunoprecipitation experiments indicated a high affinity between Nuc and COX-2. Addition of human recombinant (hr Nuc to purified hrCOX-2 dose-dependently caused an increase in PGE(2 biosynthesis in response to arachidonic acid. Co-incubation of Nuc with COX-2-expressing neutrophil lysates also increased their capacity to produce PGE(2. Moreover, neutrophil transfection with hrNuc specifically enhanced PGE(2 biosynthesis. Together, these results identify a COX-2-associated protein which may have an impact in prostanoid biosynthesis.

The evolution of GDP in USA using cyclic regression analysis

OpenAIRE

Catalin Angelo IOAN; Gina IOAN

2013-01-01

Based on the four major types of economic cycles (Kondratieff, Juglar, Kitchin, Kuznet), the paper aims to determine their actual length (for the U.S. economy) using cyclic regressions based on Fourier analysis.

Quantile regression for the statistical analysis of immunological data with many non-detects.

Science.gov (United States)

Eilers, Paul H C; Röder, Esther; Savelkoul, Huub F J; van Wijk, Roy Gerth

2012-07-07

Immunological parameters are hard to measure. A well-known problem is the occurrence of values below the detection limit, the non-detects. Non-detects are a nuisance, because classical statistical analyses, like ANOVA and regression, cannot be applied. The more advanced statistical techniques currently available for the analysis of datasets with non-detects can only be used if a small percentage of the data are non-detects. Quantile regression, a generalization of percentiles to regression models, models the median or higher percentiles and tolerates very high numbers of non-detects. We present a non-technical introduction and illustrate it with an implementation to real data from a clinical trial. We show that by using quantile regression, groups can be compared and that meaningful linear trends can be computed, even if more than half of the data consists of non-detects. Quantile regression is a valuable addition to the statistical methods that can be used for the analysis of immunological datasets with non-detects.

Optimal choice of basis functions in the linear regression analysis

International Nuclear Information System (INIS)

Khotinskij, A.M.

1988-01-01

Problem of optimal choice of basis functions in the linear regression analysis is investigated. Step algorithm with estimation of its efficiency, which holds true at finite number of measurements, is suggested. Conditions, providing the probability of correct choice close to 1 are formulated. Application of the step algorithm to analysis of decay curves is substantiated. 8 refs

Automated Box-Cox Transformations for Improved Visual Encoding.

Science.gov (United States)

Maciejewski, Ross; Pattath, Avin; Ko, Sungahn; Hafen, Ryan; Cleveland, William S; Ebert, David S

2013-01-01

The concept of preconditioning data (utilizing a power transformation as an initial step) for analysis and visualization is well established within the statistical community and is employed as part of statistical modeling and analysis. Such transformations condition the data to various inherent assumptions of statistical inference procedures, as well as making the data more symmetric and easier to visualize and interpret. In this paper, we explore the use of the Box-Cox family of power transformations to semiautomatically adjust visual parameters. We focus on time-series scaling, axis transformations, and color binning for choropleth maps. We illustrate the usage of this transformation through various examples, and discuss the value and some issues in semiautomatically using these transformations for more effective data visualization.

Regression analysis for the social sciences

CERN Document Server

Gordon, Rachel A

2015-01-01

Provides graduate students in the social sciences with the basic skills they need to estimate, interpret, present, and publish basic regression models using contemporary standards. Key features of the book include: interweaving the teaching of statistical concepts with examples developed for the course from publicly-available social science data or drawn from the literature. thorough integration of teaching statistical theory with teaching data processing and analysis. teaching of Stata and use of chapter exercises in which students practice programming and interpretation on the same data set. A separate set of exercises allows students to select a data set to apply the concepts learned in each chapter to a research question of interest to them, all updated for this edition.

A method for nonlinear exponential regression analysis

Science.gov (United States)

Junkin, B. G.

1971-01-01

A computer-oriented technique is presented for performing a nonlinear exponential regression analysis on decay-type experimental data. The technique involves the least squares procedure wherein the nonlinear problem is linearized by expansion in a Taylor series. A linear curve fitting procedure for determining the initial nominal estimates for the unknown exponential model parameters is included as an integral part of the technique. A correction matrix was derived and then applied to the nominal estimate to produce an improved set of model parameters. The solution cycle is repeated until some predetermined criterion is satisfied.

Analysis of Functional Data with Focus on Multinomial Regression and Multilevel Data

DEFF Research Database (Denmark)

Mousavi, Seyed Nourollah

Functional data analysis (FDA) is a fast growing area in statistical research with increasingly diverse range of application from economics, medicine, agriculture, chemometrics, etc. Functional regression is an area of FDA which has received the most attention both in aspects of application...... and methodological development. Our main Functional data analysis (FDA) is a fast growing area in statistical research with increasingly diverse range of application from economics, medicine, agriculture, chemometrics, etc. Functional regression is an area of FDA which has received the most attention both in aspects...

Regression analysis of a chemical reaction fouling model

International Nuclear Information System (INIS)

Vasak, F.; Epstein, N.

1996-01-01

A previously reported mathematical model for the initial chemical reaction fouling of a heated tube is critically examined in the light of the experimental data for which it was developed. A regression analysis of the model with respect to that data shows that the reference point upon which the two adjustable parameters of the model were originally based was well chosen, albeit fortuitously. (author). 3 refs., 2 tabs., 2 figs

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

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

Directory of Open Access Journals (Sweden)

Shahrbanoo Goli

2016-01-01

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

Application of multilinear regression analysis in modeling of soil ...

African Journals Online (AJOL)

The application of Multi-Linear Regression Analysis (MLRA) model for predicting soil properties in Calabar South offers a technical guide and solution in foundation designs problems in the area. Forty-five soil samples were collected from fifteen different boreholes at a different depth and 270 tests were carried out for CBR, ...

MCEM algorithm for the log-Gaussian Cox process

OpenAIRE

Delmas, Celine; Dubois-Peyrard, Nathalie; Sabbadin, Regis

2014-01-01

Log-Gaussian Cox processes are an important class of models for aggregated point patterns. They have been largely used in spatial epidemiology (Diggle et al., 2005), in agronomy (Bourgeois et al., 2012), in forestry (Moller et al.), in ecology (sightings of wild animals) or in environmental sciences (radioactivity counts). A log-Gaussian Cox process is a Poisson process with a stochastic intensity depending on a Gaussian random eld. We consider the case where this Gaussian random eld is ...

Hepatic ischemia and reperfusion injury in the absence of myeloid cell-derived COX-2 in mice.

Directory of Open Access Journals (Sweden)

Sergio Duarte

Full Text Available Cyclooxygenase-2 (COX-2 is a mediator of hepatic ischemia and reperfusion injury (IRI. While both global COX-2 deletion and pharmacologic COX-2 inhibition ameliorate liver IRI, the clinical use of COX-2 inhibitors has been linked to increased risks of heart attack and stroke. Therefore, a better understanding of the role of COX-2 in different cell types may lead to improved therapeutic strategies for hepatic IRI. Macrophages of myeloid origin are currently considered to be important sources of the COX-2 in damaged livers. Here, we used a Cox-2flox conditional knockout mouse (COX-2-M/-M to examine the function of COX-2 expression in myeloid cells during liver IRI. COX-2-M/-M mice and their WT control littermates were subjected to partial liver ischemia followed by reperfusion. COX-2-M/-M macrophages did not express COX-2 upon lipopolysaccharide stimulation and COX-2-M/-M livers showed reduced levels of COX-2 protein post-IRI. Nevertheless, selective deletion of myeloid cell-derived COX-2 failed to ameliorate liver IRI; serum transaminases and histology were comparable in both COX-2-M/-M and WT mice. COX-2-M/-M livers, like WT livers, developed extensive necrosis, vascular congestion, leukocyte infiltration and matrix metalloproteinase-9 (MMP-9 expression post-reperfusion. In addition, myeloid COX-2 deletion led to a transient increase in IL-6 levels after hepatic reperfusion, when compared to controls. Administration of celecoxib, a selective COX-2 inhibitor, resulted in significantly improved liver function and histology in both COX-2-M/-M and WT mice post-reperfusion, providing evidence that COX-2-mediated liver IRI is caused by COX-2 derived from a source(s other than myeloid cells. In conclusion, these results support the view that myeloid COX-2, including myeloid-macrophage COX-2, is not responsible for the hepatic IRI phenotype.

Inhibition of COX-2 expression by topical diclofenac enhanced radiation sensitivity via enhancement of TRAIL in human prostate adenocarcinoma xenograft model

Science.gov (United States)

2013-01-01

Background COX-2 inhibitors have an antitumor potential and have been verified by many researchers. Treatment of cancer cells with external stressors such as irradiation can stimulate the over-expression of COX-2 and possibly confer radiation resistance. In this study, we tested if topical diclofenac, which inhibits both COX-1 and COX-2, administration rendered prostate tumor cells sensitize to the effects of radiation. Methods LNCaP-COX-2 and LNCaP-Neo cells were treated with 0 to 1000 μM diclofenac. Next, a clonogenic assay was performed in which cells were subjected to irradiation (0 to 4 Gy) with or without diclofenac. COX-2 expression and other relevant molecules were measured by real-time PCR and immunohistochemistry after irradiation and diclofenac treatment. In addition, we assessed the tumor volumes of xenograft LNCaP-COX-2 cells treated with topical diclofenac with or without radiation therapy (RT). Results LNCaP-COX-2 and LNCaP-Neo cell lines experienced cytotoxic effects of diclofenac in a dose related manner. Clonogenic assays demonstrated that LNCaP-COX-2 cells were significantly more resistant to RT than LNCaP-Neo cells. Furthermore, the addition of diclofenac sensitized LNCaP-COX-2 not but LNCaP-Neo cells to the cytocidal effects of radiation. In LNCaP-COX-2 cells, diclofenac enhanced radiation-induced apoptosis compared with RT alone. This phenomenon might be attributed to enhancement of RT-induced TRAIL expression as demonstrated by real-time PCR analysis. Lastly, tumor volumes of LNCaP-COX-2 cells xenograft treated with diclofenac or RT alone was >4-fold higher than in mice treated with combined diclofenac and radiation (pdiclofenac enhances the effect of RT on prostate cancer cells that express COX-2. Thus, diclofenac may have potential as radiosensitizer for treatment of prostate cancer. PMID:23289871

Boosted beta regression.

Directory of Open Access Journals (Sweden)

Matthias Schmid

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

Bias due to two-stage residual-outcome regression analysis in genetic association studies.

Science.gov (United States)

Demissie, Serkalem; Cupples, L Adrienne

2011-11-01

Association studies of risk factors and complex diseases require careful assessment of potential confounding factors. Two-stage regression analysis, sometimes referred to as residual- or adjusted-outcome analysis, has been increasingly used in association studies of single nucleotide polymorphisms (SNPs) and quantitative traits. In this analysis, first, a residual-outcome is calculated from a regression of the outcome variable on covariates and then the relationship between the adjusted-outcome and the SNP is evaluated by a simple linear regression of the adjusted-outcome on the SNP. In this article, we examine the performance of this two-stage analysis as compared with multiple linear regression (MLR) analysis. Our findings show that when a SNP and a covariate are correlated, the two-stage approach results in biased genotypic effect and loss of power. Bias is always toward the null and increases with the squared-correlation between the SNP and the covariate (). For example, for , 0.1, and 0.5, two-stage analysis results in, respectively, 0, 10, and 50% attenuation in the SNP effect. As expected, MLR was always unbiased. Since individual SNPs often show little or no correlation with covariates, a two-stage analysis is expected to perform as well as MLR in many genetic studies; however, it produces considerably different results from MLR and may lead to incorrect conclusions when independent variables are highly correlated. While a useful alternative to MLR under , the two -stage approach has serious limitations. Its use as a simple substitute for MLR should be avoided. © 2011 Wiley Periodicals, Inc.

Inhibition of 5-LOX, COX-1, and COX-2 increases tendon healing and reduces muscle fibrosis and lipid accumulation after rotator cuff repair.

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Oak, Nikhil R; Gumucio, Jonathan P; Flood, Michael D; Saripalli, Anjali L; Davis, Max E; Harning, Julie A; Lynch, Evan B; Roche, Stuart M; Bedi, Asheesh; Mendias, Christopher L

2014-12-01

The repair and restoration of function after chronic rotator cuff tears are often complicated by muscle atrophy, fibrosis, and fatty degeneration of the diseased muscle. The inflammatory response has been implicated in the development of fatty degeneration after cuff injuries. Licofelone is a novel anti-inflammatory drug that inhibits 5-lipoxygenase (5-LOX), as well as cyclooxygenase (COX)-1 and COX-2 enzymes, which play important roles in inducing inflammation after injuries. While previous studies have demonstrated that nonsteroidal anti-inflammatory drugs and selective inhibitors of COX-2 (coxibs) may prevent the proper healing of muscles and tendons, studies about bone and cartilage have demonstrated that drugs that inhibit 5-LOX concurrently with COX-1 and COX-2 may enhance tissue regeneration. After the repair of a chronic rotator cuff tear in rats, licofelone would increase the load to failure of repaired tendons and increase the force production of muscle fibers. Controlled laboratory study. Rats underwent supraspinatus release followed by repair 28 days later. After repair, rats began a treatment regimen of either licofelone or a vehicle for 14 days, at which time animals were euthanized. Supraspinatus muscles and tendons were then subjected to contractile, mechanical, histological, and biochemical analyses. Compared with controls, licofelone-treated rats had a grossly apparent decrease in inflammation and increased fibrocartilage formation at the enthesis, along with a 62% increase in the maximum load to failure and a 51% increase in peak stress to failure. Licofelone resulted in a marked reduction in fibrosis and lipid content in supraspinatus muscles as well as reduced expression of several genes involved in fatty infiltration. Despite the decline in fibrosis and fat accumulation, muscle fiber specific force production was reduced by 23%. The postoperative treatment of cuff repair with licofelone may reduce fatty degeneration and enhance the development

Significance of Cox-2 expression in rectal cancers with or without preoperative radiotherapy

International Nuclear Information System (INIS)

Pachkoria, Ketevan; Zhang Hong; Adell, Gunnar; Jarlsfelt, Ingvar; Sun Xiaofeng

2005-01-01

Purpose: Radiotherapy has reduced local recurrence of rectal cancers, but the result is not satisfactory. Further biologic factors are needed to identify patients for more effective radiotherapy. Our aims were to investigate the relationship of cyclooxygenase-2 (Cox-2) expression to radiotherapy, and clinicopathologic/biologic variables in rectal cancers with or without radiotherapy. Methods and Materials: Cox-2 expression was immunohistochemically examined in distal normal mucosa (n = 28), in adjacent normal mucosa (n = 107), in primary cancer (n = 138), lymph node metastasis (n = 30), and biopsy (n = 85). The patients participated in a rectal cancer trial of preoperative radiotherapy. Results: Cox-2 expression was increased in primary tumor compared with normal mucosa (p < 0.0001), but there was no significant change between primary tumor and metastasis. Cox-2 positivity was or tended to be related to more p53 and Ki-67 expression, and less apoptosis (p ≤ 0.05). In Cox-2-negative cases of either biopsy (p = 0.01) or surgical samples (p = 0.02), radiotherapy was related to less frequency of local recurrence, but this was not the case in Cox-2-positive cases. Conclusion: Cox-2 expression seemed to be an early event involved in rectal cancer development. Radiotherapy might reduce a rate of local recurrence in the patients with Cox-2 weakly stained tumors, but not in those with Cox-2 strongly stained tumors

An Original Stepwise Multilevel Logistic Regression Analysis of Discriminatory Accuracy

DEFF Research Database (Denmark)

Merlo, Juan; Wagner, Philippe; Ghith, Nermin

2016-01-01

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

CONVERGENT SYNTHESIS AND EVALUATION OF 18F-LABELED AZULENIC COX2 PROBES FOR CANCER IMAGING

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Donald D. Nolting

2013-01-01

Full Text Available The overall objectives of this research are to (i develop azulene-based PET probes and (ii image COX2 as a potential biomarker of breast cancer. Several lines of research have demonstrated that COX2 is overexpressed in breast cancer and that its presence correlates with poor prognoses. While other studies have reported that COX2 inhibition can be modulated and used beneficially as a chemopreventive strategy in cancer, no viable mechanism for achieving that approach has yet been developed. This shortfall could be circumvented through in vivo imaging of COX2 activity, particularly using sensitive imaging techniques such as PET. Toward that goal, our laboratory focuses on the development of novel 18F-labled COX2 probes. We began the synthesis of the probes by transforming tropolone into a lactone, which was subjected to an [8+2] cycloaddition reaction to yield 2-methylazulene as the core ring of the probe. After exploring numerous synthetic routes, the final target molecule and precursor PET compounds were prepared successfully using convergent synthesis. Conventional 18F labeling methods caused precursor decomposition, which prompted us to hypothesize that the acidic protons of the methylene moiety between the azulene and thiazole rings were readily abstracted by a strong base such as potassium carbonate. Ultimately, this caused the precursors to disintegrate. This observation was supported after successfully using an 18F labeling strategy that employed a much milder phosphate buffer. The 18F-labeled COX2 probe was tested in a breast cancer xenograft mouse model. The data obtained via successive whole-body PET/CT scans indicated probe accumulation and retention in the tumor. Overall, the probe was stable in vivo and no defluorination was observed. A biodistribution study and Western blot analysis corroborate with the imaging data. In conclusion, this novel COX2 PET probe was shown to be a promising agent for cancer imaging and deserves further

Population death sequences and Cox processes driven by interacting Feller diffusions

CERN Document Server

Wei Gang; Feng Jian Feng

2002-01-01

We carry out a complete study on the relationship between Cox processes driven by interacting Feller diffusions and death sequences of immigration-emigration linked population networks. It is first proved that the Cox process driven by a Feller diffusion is equivalent to the death sequence of a birth and death process. The conclusion is then generalized to the case of Cox processes driven by interacting Feller diffusions and death sequences of interacting populations.

Population death sequences and Cox processes driven by interacting Feller diffusions

International Nuclear Information System (INIS)

Wei Gang; Clifford, Peter; Feng Jianfeng

2002-01-01

We carry out a complete study on the relationship between Cox processes driven by interacting Feller diffusions and death sequences of immigration-emigration linked population networks. It is first proved that the Cox process driven by a Feller diffusion is equivalent to the death sequence of a birth and death process. The conclusion is then generalized to the case of Cox processes driven by interacting Feller diffusions and death sequences of interacting populations

Population death sequences and Cox processes driven by interacting Feller diffusions

Energy Technology Data Exchange (ETDEWEB)

Wei Gang [Department of Mathematics, Baptist University, Hong Kong (China); Clifford, Peter [Department of Statistics, 1 South Parks Road, Oxford (United Kingdom); Feng Jianfeng [COGS, Sussex University, Brighton (United Kingdom)

2002-11-08

We carry out a complete study on the relationship between Cox processes driven by interacting Feller diffusions and death sequences of immigration-emigration linked population networks. It is first proved that the Cox process driven by a Feller diffusion is equivalent to the death sequence of a birth and death process. The conclusion is then generalized to the case of Cox processes driven by interacting Feller diffusions and death sequences of interacting populations.

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

Science.gov (United States)

Marill, Keith A

2004-01-01

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

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

International Nuclear Information System (INIS)

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

2007-01-01

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

Forecasting urban water demand: A meta-regression analysis.

Science.gov (United States)

Sebri, Maamar

2016-12-01

Water managers and planners require accurate water demand forecasts over the short-, medium- and long-term for many purposes. These range from assessing water supply needs over spatial and temporal patterns to optimizing future investments and planning future allocations across competing sectors. This study surveys the empirical literature on the urban water demand forecasting using the meta-analytical approach. Specifically, using more than 600 estimates, a meta-regression analysis is conducted to identify explanations of cross-studies variation in accuracy of urban water demand forecasting. Our study finds that accuracy depends significantly on study characteristics, including demand periodicity, modeling method, forecasting horizon, model specification and sample size. The meta-regression results remain robust to different estimators employed as well as to a series of sensitivity checks performed. The importance of these findings lies in the conclusions and implications drawn out for regulators and policymakers and for academics alike. Copyright © 2016. Published by Elsevier Ltd.

The use of cognitive ability measures as explanatory variables in regression analysis.

Science.gov (United States)

Junker, Brian; Schofield, Lynne Steuerle; Taylor, Lowell J

2012-12-01

Cognitive ability measures are often taken as explanatory variables in regression analysis, e.g., as a factor affecting a market outcome such as an individual's wage, or a decision such as an individual's education acquisition. Cognitive ability is a latent construct; its true value is unobserved. Nonetheless, researchers often assume that a test score , constructed via standard psychometric practice from individuals' responses to test items, can be safely used in regression analysis. We examine problems that can arise, and suggest that an alternative approach, a "mixed effects structural equations" (MESE) model, may be more appropriate in many circumstances.

Temporal trends in sperm count: a systematic review and meta-regression analysis.

Science.gov (United States)

Levine, Hagai; Jørgensen, Niels; Martino-Andrade, Anderson; Mendiola, Jaime; Weksler-Derri, Dan; Mindlis, Irina; Pinotti, Rachel; Swan, Shanna H

2017-11-01

Reported declines in sperm counts remain controversial today and recent trends are unknown. A definitive meta-analysis is critical given the predictive value of sperm count for fertility, morbidity and mortality. To provide a systematic review and meta-regression analysis of recent trends in sperm counts as measured by sperm concentration (SC) and total sperm count (TSC), and their modification by fertility and geographic group. PubMed/MEDLINE and EMBASE were searched for English language studies of human SC published in 1981-2013. Following a predefined protocol 7518 abstracts were screened and 2510 full articles reporting primary data on SC were reviewed. A total of 244 estimates of SC and TSC from 185 studies of 42 935 men who provided semen samples in 1973-2011 were extracted for meta-regression analysis, as well as information on years of sample collection and covariates [fertility group ('Unselected by fertility' versus 'Fertile'), geographic group ('Western', including North America, Europe Australia and New Zealand versus 'Other', including South America, Asia and Africa), age, ejaculation abstinence time, semen collection method, method of measuring SC and semen volume, exclusion criteria and indicators of completeness of covariate data]. The slopes of SC and TSC were estimated as functions of sample collection year using both simple linear regression and weighted meta-regression models and the latter were adjusted for pre-determined covariates and modification by fertility and geographic group. Assumptions were examined using multiple sensitivity analyses and nonlinear models. SC declined significantly between 1973 and 2011 (slope in unadjusted simple regression models -0.70 million/ml/year; 95% CI: -0.72 to -0.69; P regression analysis reports a significant decline in sperm counts (as measured by SC and TSC) between 1973 and 2011, driven by a 50-60% decline among men unselected by fertility from North America, Europe, Australia and New Zealand. Because

Neighborhood social capital and crime victimization: comparison of spatial regression analysis and hierarchical regression analysis.

Science.gov (United States)

Takagi, Daisuke; Ikeda, Ken'ichi; Kawachi, Ichiro

2012-11-01

Crime is an important determinant of public health outcomes, including quality of life, mental well-being, and health behavior. A body of research has documented the association between community social capital and crime victimization. The association between social capital and crime victimization has been examined at multiple levels of spatial aggregation, ranging from entire countries, to states, metropolitan areas, counties, and neighborhoods. In multilevel analysis, the spatial boundaries at level 2 are most often drawn from administrative boundaries (e.g., Census tracts in the U.S.). One problem with adopting administrative definitions of neighborhoods is that it ignores spatial spillover. We conducted a study of social capital and crime victimization in one ward of Tokyo city, using a spatial Durbin model with an inverse-distance weighting matrix that assigned each respondent a unique level of "exposure" to social capital based on all other residents' perceptions. The study is based on a postal questionnaire sent to 20-69 years old residents of Arakawa Ward, Tokyo. The response rate was 43.7%. We examined the contextual influence of generalized trust, perceptions of reciprocity, two types of social network variables, as well as two principal components of social capital (constructed from the above four variables). Our outcome measure was self-reported crime victimization in the last five years. In the spatial Durbin model, we found that neighborhood generalized trust, reciprocity, supportive networks and two principal components of social capital were each inversely associated with crime victimization. By contrast, a multilevel regression performed with the same data (using administrative neighborhood boundaries) found generally null associations between neighborhood social capital and crime. Spatial regression methods may be more appropriate for investigating the contextual influence of social capital in homogeneous cultural settings such as Japan. Copyright

COX-2 Gene Promoter Polymorphism and Coronary Artery Disease in Middle-Aged Men: The Helsinki Sudden Death Study

Directory of Open Access Journals (Sweden)

Kati H. Huuskonen

2008-01-01

Full Text Available Cyclooxygenase (COX catalyzes formation of prostaglandins that contribute to the inflammation in atherosclerosis. Our objective was to study whether the functional C variant of the −765G→C polymorphism in the human COX-2 gene associates with the severity of coronary atherosclerosis measured at the coronary artery level. The Helsinki sudden death study autopsy material (n = 300 comprised of Finnish men who died suddenly. The area of atherosclerotic lesions in the coronary arteries was quantitated, and coronary narrowing was measured. The occurrence of myocardial infarction (MI was assessed. Genotyping was by restriction endonuclease analysis. Men carrying the minor C allele had larger areas of complicated lesions (P = .024 and a higher number of coronary arteries that had over 50% stenosis (P = .036 compared to men representing the common GG genotype. The COX-2 polymorphism was not associated with MI. Our data suggest that COX-2 may be involved in plaque growth.

Introduction to regression graphics

CERN Document Server

Cook, R Dennis

2009-01-01

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

Involvement of COX-2 in nickel elution from a wire implanted subcutaneously in mice.

Science.gov (United States)

Sato, Taiki; Kishimoto, Yu; Asakawa, Sanki; Mizuno, Natsumi; Hiratsuka, Masahiro; Hirasawa, Noriyasu

2016-07-01

Many types of medical alloys include nickel (Ni), and the elution of Ni ions from these materials causes toxicities and inflammation. We have previously reported that inflammation enhances Ni elution, although the molecular mechanisms underlying this effect remain unclear. In this study, we investigated how inflammatory responses enhanced Ni elution in a wire-implantation mouse model. Subcutaneous implantation of Ni wire induced the expression of cyclooxygenase-2 (COX-2) and microsomal prostaglandin E synthase-1 (mPGES-1) mRNA in the surrounding tissues. Immunostaining analysis showed that cells expressing COX-2 were mainly fibroblast-like cells 8h after implantation of a Ni wire, but were mainly infiltrated leukocytes at 24h. NiCl2 induced the expression of COX-2 mRNA in primary fibroblasts, neutrophils, RAW 264 cells, and THP-1 cells, indicating that Ni ions can induce COX-2 expression in various types of cells. The elution of Ni ions from the implanted Ni wire at 8h was reduced by dexamethasone (Dex), indomethacin (Ind), or celecoxib (Cel) treatment. Ni wire implantation induced an increase in mRNA levels for anaerobic glycolytic pathway components glucose transporter 1 (GLUT1), hexokinase 2 (HK2), lactate dehydrogenase A (LDHA), and monocarboxylate transporter 4 (MCT4); the expression of these genes was also inhibited by Dex, Ind, and Cel. In primary fibroblasts, the expression of these mRNAs and the production of lactate were induced by NiCl2 and further potentiated by PGE2. Furthermore, Ni wire-induced infiltration of inflammatory leukocytes was significantly reduced by Dex, Ind, or Cel. Depletion of neutrophils with a specific antibody caused reduction of both leukocyte infiltration and Ni elution. These results indicate that Ni ions eluted from wire induced COX-2 expression, which further promoted elution of Ni ions by increasing lactate production and leukocyte infiltration. Since COX inhibitors and Dex reduced the elution of Ni ions, these drugs may be

Analysis of γ spectra in airborne radioactivity measurements using multiple linear regressions

International Nuclear Information System (INIS)

Bao Min; Shi Quanlin; Zhang Jiamei

2004-01-01

This paper describes the net peak counts calculating of nuclide 137 Cs at 662 keV of γ spectra in airborne radioactivity measurements using multiple linear regressions. Mathematic model is founded by analyzing every factor that has contribution to Cs peak counts in spectra, and multiple linear regression function is established. Calculating process adopts stepwise regression, and the indistinctive factors are eliminated by F check. The regression results and its uncertainty are calculated using Least Square Estimation, then the Cs peak net counts and its uncertainty can be gotten. The analysis results for experimental spectrum are displayed. The influence of energy shift and energy resolution on the analyzing result is discussed. In comparison with the stripping spectra method, multiple linear regression method needn't stripping radios, and the calculating result has relation with the counts in Cs peak only, and the calculating uncertainty is reduced. (authors)

Regression Analysis and Calibration Recommendations for the Characterization of Balance Temperature Effects

Science.gov (United States)

Ulbrich, N.; Volden, T.

2018-01-01

Analysis and use of temperature-dependent wind tunnel strain-gage balance calibration data are discussed in the paper. First, three different methods are presented and compared that may be used to process temperature-dependent strain-gage balance data. The first method uses an extended set of independent variables in order to process the data and predict balance loads. The second method applies an extended load iteration equation during the analysis of balance calibration data. The third method uses temperature-dependent sensitivities for the data analysis. Physical interpretations of the most important temperature-dependent regression model terms are provided that relate temperature compensation imperfections and the temperature-dependent nature of the gage factor to sets of regression model terms. Finally, balance calibration recommendations are listed so that temperature-dependent calibration data can be obtained and successfully processed using the reviewed analysis methods.

Clinical evaluation of a novel population-based regression analysis for detecting glaucomatous visual field progression.

Science.gov (United States)

Kovalska, M P; Bürki, E; Schoetzau, A; Orguel, S F; Orguel, S; Grieshaber, M C

2011-04-01

The distinction of real progression from test variability in visual field (VF) series may be based on clinical judgment, on trend analysis based on follow-up of test parameters over time, or on identification of a significant change related to the mean of baseline exams (event analysis). The aim of this study was to compare a new population-based method (Octopus field analysis, OFA) with classic regression analyses and clinical judgment for detecting glaucomatous VF changes. 240 VF series of 240 patients with at least 9 consecutive examinations available were included into this study. They were independently classified by two experienced investigators. The results of such a classification served as a reference for comparison for the following statistical tests: (a) t-test global, (b) r-test global, (c) regression analysis of 10 VF clusters and (d) point-wise linear regression analysis. 32.5 % of the VF series were classified as progressive by the investigators. The sensitivity and specificity were 89.7 % and 92.0 % for r-test, and 73.1 % and 93.8 % for the t-test, respectively. In the point-wise linear regression analysis, the specificity was comparable (89.5 % versus 92 %), but the sensitivity was clearly lower than in the r-test (22.4 % versus 89.7 %) at a significance level of p = 0.01. A regression analysis for the 10 VF clusters showed a markedly higher sensitivity for the r-test (37.7 %) than the t-test (14.1 %) at a similar specificity (88.3 % versus 93.8 %) for a significant trend (p = 0.005). In regard to the cluster distribution, the paracentral clusters and the superior nasal hemifield progressed most frequently. The population-based regression analysis seems to be superior to the trend analysis in detecting VF progression in glaucoma, and may eliminate the drawbacks of the event analysis. Further, it may assist the clinician in the evaluation of VF series and may allow better visualization of the correlation between function and structure owing to VF

Selective principal component regression analysis of fluorescence hyperspectral image to assess aflatoxin contamination in corn

Science.gov (United States)

Selective principal component regression analysis (SPCR) uses a subset of the original image bands for principal component transformation and regression. For optimal band selection before the transformation, this paper used genetic algorithms (GA). In this case, the GA process used the regression co...

Determining Balıkesir’s Energy Potential Using a Regression Analysis Computer Program

Directory of Open Access Journals (Sweden)

Bedri Yüksel

2014-01-01

Full Text Available Solar power and wind energy are used concurrently during specific periods, while at other times only the more efficient is used, and hybrid systems make this possible. When establishing a hybrid system, the extent to which these two energy sources support each other needs to be taken into account. This paper is a study of the effects of wind speed, insolation levels, and the meteorological parameters of temperature and humidity on the energy potential in Balıkesir, in the Marmara region of Turkey. The relationship between the parameters was studied using a multiple linear regression method. Using a designed-for-purpose computer program, two different regression equations were derived, with wind speed being the dependent variable in the first and insolation levels in the second. The regression equations yielded accurate results. The computer program allowed for the rapid calculation of different acceptance rates. The results of the statistical analysis proved the reliability of the equations. An estimate of identified meteorological parameters and unknown parameters could be produced with a specified precision by using the regression analysis method. The regression equations also worked for the evaluation of energy potential.

Covariate Imbalance and Adjustment for Logistic Regression Analysis of Clinical Trial Data

Science.gov (United States)

Ciolino, Jody D.; Martin, Reneé H.; Zhao, Wenle; Jauch, Edward C.; Hill, Michael D.; Palesch, Yuko Y.

2014-01-01

In logistic regression analysis for binary clinical trial data, adjusted treatment effect estimates are often not equivalent to unadjusted estimates in the presence of influential covariates. This paper uses simulation to quantify the benefit of covariate adjustment in logistic regression. However, International Conference on Harmonization guidelines suggest that covariate adjustment be pre-specified. Unplanned adjusted analyses should be considered secondary. Results suggest that that if adjustment is not possible or unplanned in a logistic setting, balance in continuous covariates can alleviate some (but never all) of the shortcomings of unadjusted analyses. The case of log binomial regression is also explored. PMID:24138438

Declining Bias and Gender Wage Discrimination? A Meta-Regression Analysis

Science.gov (United States)

Jarrell, Stephen B.; Stanley, T. D.

2004-01-01

The meta-regression analysis reveals that there is a strong tendency for discrimination estimates to fall and wage discrimination exist against the woman. The biasing effect of researchers' gender of not correcting for selection bias has weakened and changes in labor market have made it less important.

Statistical methods in regression and calibration analysis of chromosome aberration data

International Nuclear Information System (INIS)

Merkle, W.

1983-01-01

The method of iteratively reweighted least squares for the regression analysis of Poisson distributed chromosome aberration data is reviewed in the context of other fit procedures used in the cytogenetic literature. As an application of the resulting regression curves methods for calculating confidence intervals on dose from aberration yield are described and compared, and, for the linear quadratic model a confidence interval is given. Emphasis is placed on the rational interpretation and the limitations of various methods from a statistical point of view. (orig./MG)

The synthesis of isotopic fluorine and iodine-labeled COX-II inhibitor and in vitro validation

Energy Technology Data Exchange (ETDEWEB)

An, Gwang Gil; Lee, Tae Sub; Lee, Kyo Chul; Moon, Byung Seok; Choi, Chang Woon; Chun, Kwon Soo [Korea Institute of Radiological and Medical Sciences, Seoul (Korea, Republic of)

2005-07-01

In these day, NASIDs (non-steroidal antiinflammatory drugs) such as aspirin, diclofenac and ibuprofen are the most common medications used to reduce pain and inflammation. However, they act by inhibiting both COX-I and COX-II which can cause serious gastrointestinal side effects such as ulcers, stomach perforations and bleeds. COX-I produces prostaglandins believed to be responsible for the protection of the stomach lining. However, COX-II produces prostaglandins believed to be responsible for pain and inflammation. Recently, the most widely studied selective COX-II inhibitor such as celecoxib and rofecoxib' one work by inhibiting the effect of COX-II on pain and inflammation without inhibiting COX-I which protects gastrointestinal lining.

The tariff for fire and theft car insurance: analysis with a Cox model

OpenAIRE

Bruno Scarpa

2013-01-01

In this paper we analyze the problem of identification of a tariff for a Fire & Theft Car policy for Insurance Companies. Usually companies obtain this tariff by empirical estimate of the pure rate by evaluating the impact of some personalization variables. In this paper we propose the usage of a semi-parametric Cox model, where the response variable is not the waiting time until an event, but the degree of damage because of theft or fire of a car. The proposed model allows to easily tackle t...

COX-2 disruption leads to increased central vasopressin stores and impaired urine concentrating ability in mice

DEFF Research Database (Denmark)

Norregaard, Rikke; Madsen, Kirsten Morill; Hansen, Pernille Bl

2011-01-01

It was hypothesized that cyclooxygenase-2 (COX-2) activity promotes urine concentrating ability through stimulation of vasopressin (AVP) release after water deprivation (WD). COX-2-deficient (COX-2(-/-), C57BL/6) and wild-type (WT) mice were water deprived for 24 h, and water balance, central AVP m...... osmolality in COX-2(-/-) mice irrespective of gender. Hypothalamic AVP mRNA level increased and was unchanged between COX-2(-/-) and WT after WD. AVP peptide content was higher in COX-2(-/-) compared with WT. At baseline, plasma AVP concentration was elevated in conscious chronically catheterized COX-2......(-/-) mice, but after WD plasma AVP was unchanged between COX-2(-/-) and WT mice (43 ± 11 vs. 70 ± 16 pg/ml). Renal V2 receptor abundance was downregulated in COX-2(-/-) mice. Medullary interstitial osmolality increased and did not differ between COX-2(-/-) and WT after WD. Aquaporin-2 (AQP2; cortex...

Expression of Beta-catenin, COX-2 and iNOS in Colorectal Cancer: Relevance of COX-2 and iNOS Inhibitors for Treatment in Malaysia

Directory of Open Access Journals (Sweden)

Seok Kwan Hong

2004-01-01

Conclusions: The accumulation of β-catenin does not seem to be sufficient to activate pathways that lead to increased COX-2 and iNOS expression. A high proportion of colorectal cancers were found to express COX-2 and a significant number produced iNOS, suggesting that their inhibitors may be potentially useful as chemotherapeutic agents in the management of colorectal cancer.

Bond and CDS Pricing via the Stochastic Recovery Black-Cox Model

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Albert Cohen

2017-04-01

Full Text Available Building on recent work incorporating recovery risk into structural models by Cohen & Costanzino (2015, we consider the Black-Cox model with an added recovery risk driver. The recovery risk driver arises naturally in the context of imperfect information implicit in the structural framework. This leads to a two-factor structural model we call the Stochastic Recovery Black-Cox model, whereby the asset risk driver At defines the default trigger and the recovery risk driver Rt defines the amount recovered in the event of default. We then price zero-coupon bonds and credit default swaps under the Stochastic Recovery Black-Cox model. Finally, we compare our results with the classic Black-Cox model, give explicit expressions for the recovery risk premium in the Stochastic Recovery Black-Cox model, and detail how the introduction of separate but correlated risk drivers leads to a decoupling of the default and recovery risk premiums in the credit spread. We conclude this work by computing the effect of adding coupons that are paid continuously until default, and price perpetual (consol bonds in our two-factor firm value model, extending calculations in the seminal paper by Leland (1994.

Length bias correction in gene ontology enrichment analysis using logistic regression.

Science.gov (United States)

Mi, Gu; Di, Yanming; Emerson, Sarah; Cumbie, Jason S; Chang, Jeff H

2012-01-01

When assessing differential gene expression from RNA sequencing data, commonly used statistical tests tend to have greater power to detect differential expression of genes encoding longer transcripts. This phenomenon, called "length bias", will influence subsequent analyses such as Gene Ontology enrichment analysis. In the presence of length bias, Gene Ontology categories that include longer genes are more likely to be identified as enriched. These categories, however, are not necessarily biologically more relevant. We show that one can effectively adjust for length bias in Gene Ontology analysis by including transcript length as a covariate in a logistic regression model. The logistic regression model makes the statistical issue underlying length bias more transparent: transcript length becomes a confounding factor when it correlates with both the Gene Ontology membership and the significance of the differential expression test. The inclusion of the transcript length as a covariate allows one to investigate the direct correlation between the Gene Ontology membership and the significance of testing differential expression, conditional on the transcript length. We present both real and simulated data examples to show that the logistic regression approach is simple, effective, and flexible.

Characterization and Sequencing of MT-Cox1 Gene in Khorasan ...

African Journals Online (AJOL)

The aim of this study was to investigate the nucleotide sequence of COX1 gene in mitochondrial genome of Khorasan native chicken and detect the possible mutations in the genome. For this purpose, after sampling and extracting DNA from the whole blood samples, the COX1 gene was amplified using specific primers and ...

Convergent synthesis and evaluation of {sup 18}F-labeled azulenic COX2 probes for cancer imaging

Energy Technology Data Exchange (ETDEWEB)

Nolting, Donald D.; Nickels, Michael; Tantawy, Mohammed N.; Yu, James Y. H.; Xie, Jingping [Department of Radiology, Institute of Imaging Science, Vanderbilt University, Nashville, TN (United States); Peterson, Todd E. [Department of Radiology, Institute of Imaging Science, Vanderbilt University, Nashville, TN (United States); Department of Physics and Astronomy, Vanderbilt University, Nashville, TN (United States); Crews, Brenda C. [Department of Chemistry, Vanderbilt University, Nashville, TN (United States); Vanderbilt Institute of Chemical Biology, Nashville, TN (United States); Marnett, Larry [Department of Chemistry, Vanderbilt University, Nashville, TN (United States); Vanderbilt Institute of Chemical Biology, Nashville, TN (United States); Vanderbilt Ingram Cancer Center, Vanderbilt University, Nashville, TN (United States); Gore, John C. [Department of Radiology, Institute of Imaging Science, Vanderbilt University, Nashville, TN (United States); Department of Physics and Astronomy, Vanderbilt University, Nashville, TN (United States); Vanderbilt Ingram Cancer Center, Vanderbilt University, Nashville, TN (United States); Department of Biomedical Engineering, Vanderbilt University, Nashville, TN (United States); Department of Molecular Physiology and Biophysics, Vanderbilt University, Nashville, TN (United States); Pham, Wellington, E-mail: wellington.pham@vanderbilt.edu [Department of Radiology, Institute of Imaging Science, Vanderbilt University, Nashville, TN (United States); Vanderbilt Institute of Chemical Biology, Nashville, TN (United States); Vanderbilt Ingram Cancer Center, Vanderbilt University, Nashville, TN (United States); Department of Biomedical Engineering, Vanderbilt University, Nashville, TN (United States); Department of Neuroscience, Vanderbilt University, Nashville, TN (United States)

2013-01-03

The overall objectives of this research are to (i) develop azulene-based positron emission tomography (PET) probes and (ii) image COX2 as a potential biomarker of breast cancer. Several lines of research have demonstrated that COX2 is overexpressed in breast cancer and that its presence correlates with poor prognoses. While other studies have reported that COX2 inhibition can be modulated and used beneficially as a chemopreventive strategy in cancer, no viable mechanism for achieving that approach has yet been developed. This shortfall could be circumvented through in vivo imaging of COX2 activity, particularly using sensitive imaging techniques such as PET. Toward that goal, our laboratory focuses on the development of novel {sup 18}F-labled COX2 probes. We began the synthesis of the probes by transforming tropolone into a lactone, which was subjected to an [8 + 2] cycloaddition reaction to yield 2-methylazulene as the core ring of the probe. After exploring numerous synthetic routes, the final target molecule and precursor PET compounds were prepared successfully using convergent synthesis. Conventional {sup 18}F labeling methods caused precursor decomposition, which prompted us to hypothesize that the acidic protons of the methylene moiety between the azulene and thiazole rings were readily abstracted by a strong base such as potassium carbonate. Ultimately, this caused the precursors to disintegrate. This observation was supported after successfully using an {sup 18}F labeling strategy that employed a much milder phosphate buffer. The {sup 18}F-labeled COX2 probe was tested in a breast cancer xenograft mouse model. The data obtained via successive whole-body PET/CT scans indicated probe accumulation and retention in the tumor. Overall, the probe was stable in vivo and no defluorination was observed. A biodistribution study and Western blot analysis corroborate with the imaging data. In conclusion, this novel COX2 PET probe was shown to be a promising agent for

COX-2 gene expression in colon cancer tissue related to regulating factors and promoter methylation status

International Nuclear Information System (INIS)

Asting, Annika Gustafsson; Carén, Helena; Andersson, Marianne; Lönnroth, Christina; Lagerstedt, Kristina; Lundholm, Kent

2011-01-01

Increased cyclooxygenase activity promotes progression of colorectal cancer, but the mechanisms behind COX-2 induction remain elusive. This study was therefore aimed to define external cell signaling and transcription factors relating to high COX-2 expression in colon cancer tissue. Tumor and normal colon tissue were collected at primary curative operation in 48 unselected patients. COX-2 expression in tumor and normal colon tissue was quantified including microarray analyses on tumor mRNA accounting for high and low tumor COX-2 expression. Cross hybridization was performed between tumor and normal colon tissue. Methylation status of up-stream COX-2 promoter region was evaluated. Tumors with high COX-2 expression displayed large differences in gene expression compared to normal colon. Numerous genes with altered expression appeared in tumors of high COX-2 expression compared to tumors of low COX-2. COX-2 expression in normal colon was increased in patients with tumors of high COX-2 compared to normal colon from patients with tumors of low COX-2. IL1β, IL6 and iNOS transcripts were up-regulated among external cell signaling factors; nine transcription factors (ATF3, C/EBP, c-Fos, Fos-B, JDP2, JunB, c-Maf, NF-κB, TCF4) showed increased expression and 5 (AP-2, CBP, Elk-1, p53, PEA3) were decreased in tumors with high COX-2. The promoter region of COX-2 gene did not show consistent methylation in tumor or normal colon tissue. Transcription and external cell signaling factors are altered as covariates to COX-2 expression in colon cancer tissue, but DNA methylation of the COX-2 promoter region was not a significant factor behind COX-2 expression in tumor and normal colon tissue

COX-2 gene expression in colon cancer tissue related to regulating factors and promoter methylation status

Directory of Open Access Journals (Sweden)

Lagerstedt Kristina

2011-06-01

Full Text Available Abstract Background Increased cyclooxygenase activity promotes progression of colorectal cancer, but the mechanisms behind COX-2 induction remain elusive. This study was therefore aimed to define external cell signaling and transcription factors relating to high COX-2 expression in colon cancer tissue. Method Tumor and normal colon tissue were collected at primary curative operation in 48 unselected patients. COX-2 expression in tumor and normal colon tissue was quantified including microarray analyses on tumor mRNA accounting for high and low tumor COX-2 expression. Cross hybridization was performed between tumor and normal colon tissue. Methylation status of up-stream COX-2 promoter region was evaluated. Results Tumors with high COX-2 expression displayed large differences in gene expression compared to normal colon. Numerous genes with altered expression appeared in tumors of high COX-2 expression compared to tumors of low COX-2. COX-2 expression in normal colon was increased in patients with tumors of high COX-2 compared to normal colon from patients with tumors of low COX-2. IL1β, IL6 and iNOS transcripts were up-regulated among external cell signaling factors; nine transcription factors (ATF3, C/EBP, c-Fos, Fos-B, JDP2, JunB, c-Maf, NF-κB, TCF4 showed increased expression and 5 (AP-2, CBP, Elk-1, p53, PEA3 were decreased in tumors with high COX-2. The promoter region of COX-2 gene did not show consistent methylation in tumor or normal colon tissue. Conclusions Transcription and external cell signaling factors are altered as covariates to COX-2 expression in colon cancer tissue, but DNA methylation of the COX-2 promoter region was not a significant factor behind COX-2 expression in tumor and normal colon tissue.

Analysis of designed experiments by stabilised PLS Regression and jack-knifing

DEFF Research Database (Denmark)

Martens, Harald; Høy, M.; Westad, F.

2001-01-01

Pragmatical, visually oriented methods for assessing and optimising bi-linear regression models are described, and applied to PLS Regression (PLSR) analysis of multi-response data from controlled experiments. The paper outlines some ways to stabilise the PLSR method to extend its range...... the reliability of the linear and bi-linear model parameter estimates. The paper illustrates how the obtained PLSR "significance" probabilities are similar to those from conventional factorial ANOVA, but the PLSR is shown to give important additional overview plots of the main relevant structures in the multi....... An Introduction, Wiley, Chichester, UK, 2001]....

Predictors of postoperative outcomes of cubital tunnel syndrome treatments using multiple logistic regression analysis.

Science.gov (United States)

Suzuki, Taku; Iwamoto, Takuji; Shizu, Kanae; Suzuki, Katsuji; Yamada, Harumoto; Sato, Kazuki

2017-05-01

This retrospective study was designed to investigate prognostic factors for postoperative outcomes for cubital tunnel syndrome (CubTS) using multiple logistic regression analysis with a large number of patients. Eighty-three patients with CubTS who underwent surgeries were enrolled. The following potential prognostic factors for disease severity were selected according to previous reports: sex, age, type of surgery, disease duration, body mass index, cervical lesion, presence of diabetes mellitus, Workers' Compensation status, preoperative severity, and preoperative electrodiagnostic testing. Postoperative severity of disease was assessed 2 years after surgery by Messina's criteria which is an outcome measure specifically for CubTS. Bivariate analysis was performed to select candidate prognostic factors for multiple linear regression analyses. Multiple logistic regression analysis was conducted to identify the association between postoperative severity and selected prognostic factors. Both bivariate and multiple linear regression analysis revealed only preoperative severity as an independent risk factor for poor prognosis, while other factors did not show any significant association. Although conflicting results exist regarding prognosis of CubTS, this study supports evidence from previous studies and concludes early surgical intervention portends the most favorable prognosis. Copyright © 2017 The Japanese Orthopaedic Association. Published by Elsevier B.V. All rights reserved.

Multiple linear regression analysis

Science.gov (United States)

Edwards, T. R.

1980-01-01

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

Use of the Box-Cox Transformation in Detecting Changepoints in Daily Precipitation Data Series

Science.gov (United States)

Wang, X. L.; Chen, H.; Wu, Y.; Pu, Q.

2009-04-01

This study integrates a Box-Cox power transformation procedure into two statistical tests for detecting changepoints in Gaussian data series, to make the changepoint detection methods applicable to non-Gaussian data series, such as daily precipitation amounts. The detection power aspects of transformed methods in a common trend two-phase regression setting are assessed by Monte Carlo simulations for data of a log-normal or Gamma distribution. The results show that the transformed methods have increased the power of detection, in comparison with the corresponding original (untransformed) methods. The transformed data much better approximate to a Gaussian distribution. As an example of application, the new methods are applied to a series of daily precipitation amounts recorded at a station in Canada, showing satisfactory detection power.

Exploring factors associated with traumatic dental injuries in preschool children: a Poisson regression analysis.

Science.gov (United States)

Feldens, Carlos Alberto; Kramer, Paulo Floriani; Ferreira, Simone Helena; Spiguel, Mônica Hermann; Marquezan, Marcela

2010-04-01

This cross-sectional study aimed to investigate the factors associated with dental trauma in preschool children using Poisson regression analysis with robust variance. The study population comprised 888 children aged 3- to 5-year-old attending public nurseries in Canoas, southern Brazil. Questionnaires assessing information related to the independent variables (age, gender, race, mother's educational level and family income) were completed by the parents. Clinical examinations were carried out by five trained examiners in order to assess traumatic dental injuries (TDI) according to Andreasen's classification. One of the five examiners was calibrated to assess orthodontic characteristics (open bite and overjet). Multivariable Poisson regression analysis with robust variance was used to determine the factors associated with dental trauma as well as the strengths of association. Traditional logistic regression was also performed in order to compare the estimates obtained by both methods of statistical analysis. 36.4% (323/888) of the children suffered dental trauma and there was no difference in prevalence rates from 3 to 5 years of age. Poisson regression analysis showed that the probability of the outcome was almost 30% higher for children whose mothers had more than 8 years of education (Prevalence Ratio = 1.28; 95% CI = 1.03-1.60) and 63% higher for children with an overjet greater than 2 mm (Prevalence Ratio = 1.63; 95% CI = 1.31-2.03). Odds ratios clearly overestimated the size of the effect when compared with prevalence ratios. These findings indicate the need for preventive orientation regarding TDI, in order to educate parents and caregivers about supervising infants, particularly those with increased overjet and whose mothers have a higher level of education. Poisson regression with robust variance represents a better alternative than logistic regression to estimate the risk of dental trauma in preschool children.

Decision tree analysis to stratify risk of de novo non-melanoma skin cancer following liver transplantation.

Science.gov (United States)

Tanaka, Tomohiro; Voigt, Michael D

2018-03-01

Non-melanoma skin cancer (NMSC) is the most common de novo malignancy in liver transplant (LT) recipients; it behaves more aggressively and it increases mortality. We used decision tree analysis to develop a tool to stratify and quantify risk of NMSC in LT recipients. We performed Cox regression analysis to identify which predictive variables to enter into the decision tree analysis. Data were from the Organ Procurement Transplant Network (OPTN) STAR files of September 2016 (n = 102984). NMSC developed in 4556 of the 105984 recipients, a mean of 5.6 years after transplant. The 5/10/20-year rates of NMSC were 2.9/6.3/13.5%, respectively. Cox regression identified male gender, Caucasian race, age, body mass index (BMI) at LT, and sirolimus use as key predictive or protective factors for NMSC. These factors were entered into a decision tree analysis. The final tree stratified non-Caucasians as low risk (0.8%), and Caucasian males > 47 years, BMI decision tree model accurately stratifies the risk of developing NMSC in the long-term after LT.

Application of range-test in multiple linear regression analysis in ...

African Journals Online (AJOL)

Application of range-test in multiple linear regression analysis in the presence of outliers is studied in this paper. First, the plot of the explanatory variables (i.e. Administration, Social/Commercial, Economic services and Transfer) on the dependent variable (i.e. GDP) was done to identify the statistical trend over the years.

Efek ekstrak daun singkong (Manihot utilissima terhadap ekspresi COX-2 pada monosit yang dipapar LPS E.coli (The effect of Manihot utilissima extracts on COX-2 expression of monocytes induced by LPS E. coli

Directory of Open Access Journals (Sweden)

Zahara Meilawaty

2013-12-01

Full Text Available Background: Periodontal disease is a common and widespread disease in the community. Gram negative bacteria have a role inperiodontitis. These bacteria secrete a variety of products such as endotoxin lipopolysaccharide (LPS, which causes the occurrenceof inflammation or infection. The body defense responses are neutrophils and mononuclear cells (monocytes and macrophages. Inresponse to defense mechanism, the body will be expressed enzyme cyclooxygenase (COX which functions convert arachidonic acidto prostaglandins. Cassava leaf cells known to play a role in reducing inflammation, but the mechanism for inhibiting COX-2, is notknown. Purpose: The study was aimed to determine the effect of cassava leaf extract (Manihot utilissima on expression of enzyme COX-2 in monocytes which were exposed by LPS E. coli. Methods: This study was in vitro experimental studies with the design of posttestonly control group design. The sample was the cassava leaves extract (Manihot utilissima at concentration of 12.5 % and 25 %. Theexpression of COX-2 was determined by immunocytochemistry method. Isolated monocytes were incubated in cassava leaf extract, andthen exposed to LPS, after washing imunostaning procedure was performed using a monoclonal antibody (MAb anti-human COX-2.The research data was the number of monocytes that express COX-2. Results: Expression of COX-2 in the group cassava leaf extractwas higher than the group that induced by LPS E. coli only. Conclusion: Cassava leaf extract did not inhibit the expression of COX-2in monocytes which were exposed by LPS E. coli.Latar belakang: Penyakit periodontal merupakan penyakit umum dan tersebar luas di masyarakat. Bakteri yang banyak berperanpada periodontitis adalah Gram negatif. Bakteri ini mengeluarkan berbagai produk antara lain endotoksin lipopolisakarida (LPS yangmenyebabkan inflamasi atau infeksi. Respon pertahanan tubuh pertama adalah netrofil dan sel mononuklear (monosit dan makrofag.Pada respon

Big Data Toolsets to Pharmacometrics: Application of Machine Learning for Time-to-Event Analysis.

Science.gov (United States)

Gong, Xiajing; Hu, Meng; Zhao, Liang

2018-05-01

Additional value can be potentially created by applying big data tools to address pharmacometric problems. The performances of machine learning (ML) methods and the Cox regression model were evaluated based on simulated time-to-event data synthesized under various preset scenarios, i.e., with linear vs. nonlinear and dependent vs. independent predictors in the proportional hazard function, or with high-dimensional data featured by a large number of predictor variables. Our results showed that ML-based methods outperformed the Cox model in prediction performance as assessed by concordance index and in identifying the preset influential variables for high-dimensional data. The prediction performances of ML-based methods are also less sensitive to data size and censoring rates than the Cox regression model. In conclusion, ML-based methods provide a powerful tool for time-to-event analysis, with a built-in capacity for high-dimensional data and better performance when the predictor variables assume nonlinear relationships in the hazard function. © 2018 The Authors. Clinical and Translational Science published by Wiley Periodicals, Inc. on behalf of American Society for Clinical Pharmacology and Therapeutics.

Multiple regression analysis of anthropometric measurements influencing the cephalic index of male Japanese university students.

Science.gov (United States)

Hossain, Md Golam; Saw, Aik; Alam, Rashidul; Ohtsuki, Fumio; Kamarul, Tunku

2013-09-01

Cephalic index (CI), the ratio of head breadth to head length, is widely used to categorise human populations. The aim of this study was to access the impact of anthropometric measurements on the CI of male Japanese university students. This study included 1,215 male university students from Tokyo and Kyoto, selected using convenient sampling. Multiple regression analysis was used to determine the effect of anthropometric measurements on CI. The variance inflation factor (VIF) showed no evidence of a multicollinearity problem among independent variables. The coefficients of the regression line demonstrated a significant positive relationship between CI and minimum frontal breadth (p regression analysis showed a greater likelihood for minimum frontal breadth (p regression analysis revealed bizygomatic breadth, head circumference, minimum frontal breadth, head height and morphological facial height to be the best predictor craniofacial measurements with respect to CI. The results suggest that most of the variables considered in this study appear to influence the CI of adult male Japanese students.

Secretory phospholipase A(2) induces delayed neuronal COX-2 expression compared with glutamate

DEFF Research Database (Denmark)

Kolko, Miriam; Nielsen, Marianne; Bazan, Nicolas G

2002-01-01

and immunohistochemistry. An up-regulation of COX-2, c-fos, and c-jun, but not COX-1, was observed around the lesion as well as in the neocortex 4 hr after the injection. Hippocampal up-regulation of COX-2 was seen in dentate gyrus 8 hr after injection. When glutamate was injected, up-regulation of the early...

Understanding poisson regression.

Science.gov (United States)

Hayat, Matthew J; Higgins, Melinda

2014-04-01

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

Survival analysis of clinical mastitis data using a nested frailty Cox model fit as a mixed-effects Poisson model.

Science.gov (United States)

Elghafghuf, Adel; Dufour, Simon; Reyher, Kristen; Dohoo, Ian; Stryhn, Henrik

2014-12-01

Mastitis is a complex disease affecting dairy cows and is considered to be the most costly disease of dairy herds. The hazard of mastitis is a function of many factors, both managerial and environmental, making its control a difficult issue to milk producers. Observational studies of clinical mastitis (CM) often generate datasets with a number of characteristics which influence the analysis of those data: the outcome of interest may be the time to occurrence of a case of mastitis, predictors may change over time (time-dependent predictors), the effects of factors may change over time (time-dependent effects), there are usually multiple hierarchical levels, and datasets may be very large. Analysis of such data often requires expansion of the data into the counting-process format - leading to larger datasets - thus complicating the analysis and requiring excessive computing time. In this study, a nested frailty Cox model with time-dependent predictors and effects was applied to Canadian Bovine Mastitis Research Network data in which 10,831 lactations of 8035 cows from 69 herds were followed through lactation until the first occurrence of CM. The model was fit to the data as a Poisson model with nested normally distributed random effects at the cow and herd levels. Risk factors associated with the hazard of CM during the lactation were identified, such as parity, calving season, herd somatic cell score, pasture access, fore-stripping, and proportion of treated cases of CM in a herd. The analysis showed that most of the predictors had a strong effect early in lactation and also demonstrated substantial variation in the baseline hazard among cows and between herds. A small simulation study for a setting similar to the real data was conducted to evaluate the Poisson maximum likelihood estimation approach with both Gaussian quadrature method and Laplace approximation. Further, the performance of the two methods was compared with the performance of a widely used estimation

Analysis of the influence of quantile regression model on mainland tourists' service satisfaction performance.

Science.gov (United States)

Wang, Wen-Cheng; Cho, Wen-Chien; Chen, Yin-Jen

2014-01-01

It is estimated that mainland Chinese tourists travelling to Taiwan can bring annual revenues of 400 billion NTD to the Taiwan economy. Thus, how the Taiwanese Government formulates relevant measures to satisfy both sides is the focus of most concern. Taiwan must improve the facilities and service quality of its tourism industry so as to attract more mainland tourists. This paper conducted a questionnaire survey of mainland tourists and used grey relational analysis in grey mathematics to analyze the satisfaction performance of all satisfaction question items. The first eight satisfaction items were used as independent variables, and the overall satisfaction performance was used as a dependent variable for quantile regression model analysis to discuss the relationship between the dependent variable under different quantiles and independent variables. Finally, this study further discussed the predictive accuracy of the least mean regression model and each quantile regression model, as a reference for research personnel. The analysis results showed that other variables could also affect the overall satisfaction performance of mainland tourists, in addition to occupation and age. The overall predictive accuracy of quantile regression model Q0.25 was higher than that of the other three models.

Analysis of the Influence of Quantile Regression Model on Mainland Tourists' Service Satisfaction Performance

Science.gov (United States)

Wang, Wen-Cheng; Cho, Wen-Chien; Chen, Yin-Jen

2014-01-01

It is estimated that mainland Chinese tourists travelling to Taiwan can bring annual revenues of 400 billion NTD to the Taiwan economy. Thus, how the Taiwanese Government formulates relevant measures to satisfy both sides is the focus of most concern. Taiwan must improve the facilities and service quality of its tourism industry so as to attract more mainland tourists. This paper conducted a questionnaire survey of mainland tourists and used grey relational analysis in grey mathematics to analyze the satisfaction performance of all satisfaction question items. The first eight satisfaction items were used as independent variables, and the overall satisfaction performance was used as a dependent variable for quantile regression model analysis to discuss the relationship between the dependent variable under different quantiles and independent variables. Finally, this study further discussed the predictive accuracy of the least mean regression model and each quantile regression model, as a reference for research personnel. The analysis results showed that other variables could also affect the overall satisfaction performance of mainland tourists, in addition to occupation and age. The overall predictive accuracy of quantile regression model Q0.25 was higher than that of the other three models. PMID:24574916

Analysis of the Influence of Quantile Regression Model on Mainland Tourists’ Service Satisfaction Performance

Directory of Open Access Journals (Sweden)

Wen-Cheng Wang

2014-01-01

Full Text Available It is estimated that mainland Chinese tourists travelling to Taiwan can bring annual revenues of 400 billion NTD to the Taiwan economy. Thus, how the Taiwanese Government formulates relevant measures to satisfy both sides is the focus of most concern. Taiwan must improve the facilities and service quality of its tourism industry so as to attract more mainland tourists. This paper conducted a questionnaire survey of mainland tourists and used grey relational analysis in grey mathematics to analyze the satisfaction performance of all satisfaction question items. The first eight satisfaction items were used as independent variables, and the overall satisfaction performance was used as a dependent variable for quantile regression model analysis to discuss the relationship between the dependent variable under different quantiles and independent variables. Finally, this study further discussed the predictive accuracy of the least mean regression model and each quantile regression model, as a reference for research personnel. The analysis results showed that other variables could also affect the overall satisfaction performance of mainland tourists, in addition to occupation and age. The overall predictive accuracy of quantile regression model Q0.25 was higher than that of the other three models.

Econometric analysis of realised covariation: high frequency covariance, regression and correlation in financial economics

OpenAIRE

Ole E. Barndorff-Nielsen; Neil Shephard

2002-01-01

This paper analyses multivariate high frequency financial data using realised covariation. We provide a new asymptotic distribution theory for standard methods such as regression, correlation analysis and covariance. It will be based on a fixed interval of time (e.g. a day or week), allowing the number of high frequency returns during this period to go to infinity. Our analysis allows us to study how high frequency correlations, regressions and covariances change through time. In particular w...

Impact of BCL2 and p53 on postmastectomy radiotherapy response in high-risk breast cancer. A subgroup analysis of DBCG82 b&c

DEFF Research Database (Denmark)

Kyndi, Marianne; Sørensen, Flemming Brandt; Knudsen, Helle

2008-01-01

-Meier probability plots showed a significantly improved overall survival after PMRT for the BCL2 positive subgroup, whereas practically no survival improvement was seen after PMRT for the BCL2 negative subgroup. In multivariate analysis of OS, however, no significant interaction was found between BCL2......PURPOSE: To examine p53 and BCL2 expression in high-risk breast cancer patients randomized to postmastectomy radiotherapy (PMRT). PATIENTS AND METHODS: The present analysis included 1 000 of 3 083 high-risk breast cancer patients randomly assigned to PMRT in the DBCG82 b&c studies. Tissue...... tests, Kaplan-Meier probability plots, Log-rank test, and Cox univariate and multivariate regression analyses. RESULTS: p53 accumulation was not significantly associated with increased overall mortality, DM or LRR probability in univariate or multivariate Cox regression analyses. Kaplan...

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

International Nuclear Information System (INIS)

Janssen, I.; Stebbings, J.H.

1990-01-01

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

A rotor optimization using regression analysis

Science.gov (United States)

Giansante, N.

1984-01-01

The design and development of helicopter rotors is subject to the many design variables and their interactions that effect rotor operation. Until recently, selection of rotor design variables to achieve specified rotor operational qualities has been a costly, time consuming, repetitive task. For the past several years, Kaman Aerospace Corporation has successfully applied multiple linear regression analysis, coupled with optimization and sensitivity procedures, in the analytical design of rotor systems. It is concluded that approximating equations can be developed rapidly for a multiplicity of objective and constraint functions and optimizations can be performed in a rapid and cost effective manner; the number and/or range of design variables can be increased by expanding the data base and developing approximating functions to reflect the expanded design space; the order of the approximating equations can be expanded easily to improve correlation between analyzer results and the approximating equations; gradients of the approximating equations can be calculated easily and these gradients are smooth functions reducing the risk of numerical problems in the optimization; the use of approximating functions allows the problem to be started easily and rapidly from various initial designs to enhance the probability of finding a global optimum; and the approximating equations are independent of the analysis or optimization codes used.

Expression of integrin α3β1 and cyclooxygenase-2 (COX2) are positively correlated in human breast cancer

International Nuclear Information System (INIS)

Aggarwal, Anshu; Al-Rohil, Rami N; Batra, Anupam; Feustel, Paul J; Jones, David M; DiPersio, C Michael

2014-01-01

Expression of integrin α3β1 is associated with tumor progression, metastasis, and poor prognosis in several cancers, including breast cancer. Moreover, preclinical studies have revealed important pro-tumorigenic and pro-metastatic functions for this integrin, including tumor growth, survival, invasion, and paracrine induction of angiogenesis. Our previously published work in a preclinical breast cancer model showed that integrin α3β1 promotes expression of cyclooxygenase-2 (COX2/PTGS2), a known driver of breast cancer progression. However, the clinical significance of this regulation was unknown. The objective of the current study was to assess the clinical relevance of the relationship between integrin α3β1 and COX2 by testing for their correlated expression among various forms of human breast cancer. Immunohistochemistry was performed to assess co-expression of α3 and COX2 in specimens of human invasive ductal carcinoma (IDC), either on a commercial tissue microarray (n = 59 samples) or obtained from Albany Medical Center archives (n = 68 samples). Immunostaining intensity for the integrin α3 subunit or COX2 was scored, and Spearman’s rank correlation coefficient analysis was performed to assess their co-expression across and within different tumor subtypes or clinicopathologic criteria. Although expression of integrin α3 or COX2 varied among clinical IDC samples, a statistically significant, positive correlation was detected between α3 and COX2 in both tissue microarrays (r s = 0.49, p < 0.001, n = 59) and archived samples (r s = 0.59, p < 0.0001, n = 68). In both sample sets, this correlation was independent of hormone receptor status, histological grade, or disease stage. COX2 and α3 are correlated in IDC independently of hormone receptor status or other clinicopathologic features, supporting the hypothesis that integrin α3β1 is a determinant of COX2 expression in human breast cancer. These results support the clinical relevance of α3β1

Regression and local control rates after radiotherapy for jugulotympanic paragangliomas: Systematic review and meta-analysis

International Nuclear Information System (INIS)

Hulsteijn, Leonie T. van; Corssmit, Eleonora P.M.; Coremans, Ida E.M.; Smit, Johannes W.A.; Jansen, Jeroen C.; Dekkers, Olaf M.

2013-01-01

The primary treatment goal of radiotherapy for paragangliomas of the head and neck region (HNPGLs) is local control of the tumor, i.e. stabilization of tumor volume. Interestingly, regression of tumor volume has also been reported. Up to the present, no meta-analysis has been performed giving an overview of regression rates after radiotherapy in HNPGLs. The main objective was to perform a systematic review and meta-analysis to assess regression of tumor volume in HNPGL-patients after radiotherapy. A second outcome was local tumor control. Design of the study is systematic review and meta-analysis. PubMed, EMBASE, Web of Science, COCHRANE and Academic Search Premier and references of key articles were searched in March 2012 to identify potentially relevant studies. Considering the indolent course of HNPGLs, only studies with ⩾12 months follow-up were eligible. Main outcomes were the pooled proportions of regression and local control after radiotherapy as initial, combined (i.e. directly post-operatively or post-embolization) or salvage treatment (i.e. after initial treatment has failed) for HNPGLs. A meta-analysis was performed with an exact likelihood approach using a logistic regression with a random effect at the study level. Pooled proportions with 95% confidence intervals (CI) were reported. Fifteen studies were included, concerning a total of 283 jugulotympanic HNPGLs in 276 patients. Pooled regression proportions for initial, combined and salvage treatment were respectively 21%, 33% and 52% in radiosurgery studies and 4%, 0% and 64% in external beam radiotherapy studies. Pooled local control proportions for radiotherapy as initial, combined and salvage treatment ranged from 79% to 100%. Radiotherapy for jugulotympanic paragangliomas results in excellent local tumor control and therefore is a valuable treatment for these types of tumors. The effects of radiotherapy on regression of tumor volume remain ambiguous, although the data suggest that regression can

Robust analysis of trends in noisy tokamak confinement data using geodesic least squares regression

Energy Technology Data Exchange (ETDEWEB)

Verdoolaege, G., E-mail: geert.verdoolaege@ugent.be [Department of Applied Physics, Ghent University, B-9000 Ghent (Belgium); Laboratory for Plasma Physics, Royal Military Academy, B-1000 Brussels (Belgium); Shabbir, A. [Department of Applied Physics, Ghent University, B-9000 Ghent (Belgium); Max Planck Institute for Plasma Physics, Boltzmannstr. 2, 85748 Garching (Germany); Hornung, G. [Department of Applied Physics, Ghent University, B-9000 Ghent (Belgium)

2016-11-15

Regression analysis is a very common activity in fusion science for unveiling trends and parametric dependencies, but it can be a difficult matter. We have recently developed the method of geodesic least squares (GLS) regression that is able to handle errors in all variables, is robust against data outliers and uncertainty in the regression model, and can be used with arbitrary distribution models and regression functions. We here report on first results of application of GLS to estimation of the multi-machine scaling law for the energy confinement time in tokamaks, demonstrating improved consistency of the GLS results compared to standard least squares.

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

Science.gov (United States)

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

2014-06-17

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

GROWTH FACTORS AND COX2 IN WOUND HEALING: AN EXPERIMENTAL STUDY WITH EHRLICH TUMORS.

Science.gov (United States)

Salgado, Flávio L L; Artigiani-Neto, Ricardo; Lopes-Filho, Gaspar de Jesus

2016-01-01

Healing is an innate biological phenomenon, and carcinogenesis acquired, but with common humoral and cellular elements. Carcinogenesis interferes negatively in healing. To evaluate the histological changes in laparotomy scars of healthy Balb/c mice and with an Ehrlich tumor in its various forms of presentation. Fifty-four mice were divided into three groups of 18 animals. First group was the control; the second had Ehrlich tumor with ascites; and the third had the subcutaneous form of this tumor. Seven days after tumor inoculation, all 54 mice were submitted to laparotomy. All of the animals in the experiment were operated on again on 7th day after surgery, with resection of the scar and subsequent euthanasia of the animal. The scars were sent for histological assessment using immunohistochemical techniques to evaluate Cox-2 (cyclooxygenase 2), VEGF (vascular endothelial growth factor) and FGF (fibroblast growth factor). Semi-quantitatively analysis was done in the laparotomy scars and in the abdominal walls far away from the site of the operation. Assessing the weight of the animals, the correct inoculation of the tumor and weight gain in the group with tumoral ascites was observed. The histological studies showed that groups with the tumor showed a statistically significant higher presence of Cox-2 compared to the control. In the Cox-2 analysis of the abdominal wall, the ascites group showed the most significant difference. VEGF did not present any significant differences between the three groups, regardless of the site. The FGF showed a significant increase in animals with the tumor. Histological findings in both laparotomy scar and the abdominal wall showed that with Ehrlich's neoplasia there was an exacerbated inflammatory response, translated by more intense expression of Cox-2 and greater fibroblast proliferation, translated by more intense expression of FGF, that is, it stimulated both the immediate inflammatory reactions, observed with Cox-2 reactions, and

Vector regression introduced

Directory of Open Access Journals (Sweden)

Mok Tik

2014-06-01

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

Niacin and biosynthesis of PGD₂by platelet COX-1 in mice and humans.

Science.gov (United States)

Song, Wen-Liang; Stubbe, Jane; Ricciotti, Emanuela; Alamuddin, Naji; Ibrahim, Salam; Crichton, Irene; Prempeh, Maxwell; Lawson, John A; Wilensky, Robert L; Rasmussen, Lars Melholt; Puré, Ellen; FitzGerald, Garret A

2012-04-01

The clinical use of niacin to treat dyslipidemic conditions is limited by noxious side effects, most commonly facial flushing. In mice, niacin-induced flushing results from COX-1-dependent formation of PGD₂ and PGE₂ followed by COX-2-dependent production of PGE₂. Consistent with this, niacin-induced flushing in humans is attenuated when niacin is combined with an antagonist of the PGD₂ receptor DP1. NSAID-mediated suppression of COX-2-derived PGI₂ has negative cardiovascular consequences, yet little is known about the cardiovascular biology of PGD₂. Here, we show that PGD₂ biosynthesis is augmented during platelet activation in humans and, although vascular expression of DP1 is conserved between humans and mice, platelet DP1 is not present in mice. Despite this, DP1 deletion in mice augmented aneurysm formation and the hypertensive response to Ang II and accelerated atherogenesis and thrombogenesis. Furthermore, COX inhibitors in humans, as well as platelet depletion, COX-1 knockdown, and COX-2 deletion in mice, revealed that niacin evoked platelet COX-1-derived PGD₂ biosynthesis. Finally, ADP-induced spreading on fibrinogen was augmented by niacin in washed human platelets, coincident with increased thromboxane (Tx) formation. However, in platelet-rich plasma, where formation of both Tx and PGD₂ was increased, spreading was not as pronounced and was inhibited by DP1 activation. Thus, PGD₂, like PGI₂, may function as a homeostatic response to thrombogenic and hypertensive stimuli and may have particular relevance as a constraint on platelets during niacin therapy.

Associations between COX-2 polymorphisms, blood cholesterol and risk of acute coronary syndrome

DEFF Research Database (Denmark)

Vogel, Ulla Birgitte; Segel, Stine; Dethlefsen, Claus

2010-01-01

the enzyme levels of COX-2, were associated with risk of ACS and if alcohol intake, smoking, and use of NSAID would modify the associations. We also wanted to investigate associations with blood lipid levels. Methods: A case–cohort study including 1031 ACS cases and a sub-cohort of 1703 persons was nested......), such that variant allele carriers with low alcohol intake had the lowest lipid levels. No statistically significant associations were observed in females. Conclusion: This study suggests that genetically determined COX-2 levels are associated with risk of ACS and blood lipid levels among males. No consistent......Background: The use of specific COX-2 inhibitors in cancer prevention has been associated with higher risk of acute coronary syndrome (ACS) and myocardial infarction. The aim of this study was to investigate if the polymorphisms COX2 T8473C (rs5275), and COX2 A-1195G (rs689466), which modify...

Repeated Results Analysis for Middleware Regression Benchmarking

Czech Academy of Sciences Publication Activity Database

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

2005-01-01

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

"Cox orange\\" and \\"Elstar\\" Apple Cultivars

African Journals Online (AJOL)

Thinning trials were conducted in the apple orchards of Klein Altendorf experimental station near Bonn, Germany, using 7 year old CV, \\'Cox orange\\' in the year 2001 and 8 year old \\'Elstar\\' apple trees in 2002. The objective was to reduce the number of fruits per tree, yield, improve fruit quality, overcome alternate bearing ...

Immunohistochemical Expression of COX-2 in Uterine Serous Carcinoma Tissue

Directory of Open Access Journals (Sweden)

Joseph Menczer

2016-03-01

Material and methods. Cox-2 expression assessment by immunohistochemistry was performed on deparaffinized sections of paraffin-embedded tissue blocks of consecutive available USC uterine specimens of patients diagnosed from 2000 to 2014. Staining of more than 10% of the cells was considered positive. Staining intensity was graded on a 0 and ndash;3 scale. A scoring index was calculated by multiplying the intensity grade by the percentage of stained cells and considered low when it was equal to 1 or less and high when it was more than 1. Clinicopathological data were retrospectively abstracted from the records of the study group patients Results. The study comprised uterine specimens of 31 USC patients. Positive immunohistochemical staining was observed in 25 (80.6% USC specimens and a high score in 6 (19.4% of them. No association between immunohistochemical staining parameters and clinicopathological prognostic factors was observed. Conclusion. Although our findings should be verified in larger series, it seems that in view of the lack of association between immunohistochemical Cox-2 staining parameters in USC tissue and clinicopathological prognostic factors, this aggressive tumor is not a candidate for the use of selective Cox-2 inhibitors. Key words: Cox-2 expression, uterine carcinosarcoma, clinicopathological prognostic factors [J Interdiscipl Histopathol 2016; 4(1.000: 9-12

Bayesian Analysis for Penalized Spline Regression Using WinBUGS

Directory of Open Access Journals (Sweden)

Ciprian M. Crainiceanu

2005-09-01

Full Text Available Penalized splines can be viewed as BLUPs in a mixed model framework, which allows the use of mixed model software for smoothing. Thus, software originally developed for Bayesian analysis of mixed models can be used for penalized spline regression. Bayesian inference for nonparametric models enjoys the flexibility of nonparametric models and the exact inference provided by the Bayesian inferential machinery. This paper provides a simple, yet comprehensive, set of programs for the implementation of nonparametric Bayesian analysis in WinBUGS. Good mixing properties of the MCMC chains are obtained by using low-rank thin-plate splines, while simulation times per iteration are reduced employing WinBUGS specific computational tricks.

Seizure following the Use of the COX-2 Inhibitor Etoricoxib

Directory of Open Access Journals (Sweden)

Valentina Arnao

2017-01-01

Full Text Available We describe a case of epileptic seizures occurring after the use of a COX-2 inhibitor. A 61-year-old man was admitted to our department because of a generalized tonic-clonic seizure. EEG showed generalized slowdown of the activity. Neuroimaging and blood samples studies did not evidence alterations, but a careful pharmacological history revealed that the patient had taken the COX-2 inhibitor etoricoxib to treat lumbago few days before the onset of clinical symptoms. No seizures were reported after etoricoxib discontinuation and an EEG resulted to be normal two months after this. Conclusion. Knowing the pharmacological history of a patient is important for understanding the clinical presentation and selecting appropriate treatment. This is, to the best of our knowledge, the first reported case of generalized seizures associated with the use of COX-2 inhibitors.

Forecasting municipal solid waste generation using prognostic tools and regression analysis.

Science.gov (United States)

Ghinea, Cristina; Drăgoi, Elena Niculina; Comăniţă, Elena-Diana; Gavrilescu, Marius; Câmpean, Teofil; Curteanu, Silvia; Gavrilescu, Maria

2016-11-01

For an adequate planning of waste management systems the accurate forecast of waste generation is an essential step, since various factors can affect waste trends. The application of predictive and prognosis models are useful tools, as reliable support for decision making processes. In this paper some indicators such as: number of residents, population age, urban life expectancy, total municipal solid waste were used as input variables in prognostic models in order to predict the amount of solid waste fractions. We applied Waste Prognostic Tool, regression analysis and time series analysis to forecast municipal solid waste generation and composition by considering the Iasi Romania case study. Regression equations were determined for six solid waste fractions (paper, plastic, metal, glass, biodegradable and other waste). Accuracy Measures were calculated and the results showed that S-curve trend model is the most suitable for municipal solid waste (MSW) prediction. Copyright © 2016 Elsevier Ltd. All rights reserved.

Impact of BCL2 and p53 on postmastectomy radiotherapy response in high-risk breast cancer. A subgroup analysis of DBCG82 b

DEFF Research Database (Denmark)

Kyndi, M.; Sorensen, F.B.; Alsner, J.

2008-01-01

-Meier probability plots showed a significantly improved overall survival after PMRT for the BCL2 positive subgroup, whereas practically no survival improvement was seen after PMRT for the BCL2 negative subgroup. In multivariate analysis of OS, however, no significant interaction was found between BCL2......Purpose. To examine p53 and BCL2 expression in high-risk breast cancer patients randomized to postmastectomy radiotherapy (PMRT). Patients and methods. The present analysis included 1000 of 3 083 high-risk breast cancer patients randomly assigned to PMRT in the DBCG82 b&c studies. Tissue microarray......, Kaplan-Meier probability plots, Log-rank test, and Cox univariate and multivariate regression analyses. Results. p53 accumulation was not significantly associated with increased overall mortality, DM or LRR probability in univariate or multivariate Cox regression analyses. Kaplan-Meier probability plots...

Development of Compressive Failure Strength for Composite Laminate Using Regression Analysis Method

Energy Technology Data Exchange (ETDEWEB)

Lee, Myoung Keon [Agency for Defense Development, Daejeon (Korea, Republic of); Lee, Jeong Won; Yoon, Dong Hyun; Kim, Jae Hoon [Chungnam Nat’l Univ., Daejeon (Korea, Republic of)

2016-10-15

This paper provides the compressive failure strength value of composite laminate developed by using regression analysis method. Composite material in this document is a Carbon/Epoxy unidirection(UD) tape prepreg(Cycom G40-800/5276-1) cured at 350°F(177°C). The operating temperature is –60°F~+200°F(-55°C - +95°C). A total of 56 compression tests were conducted on specimens from eight (8) distinct laminates that were laid up by standard angle layers (0°, +45°, –45° and 90°). The ASTM-D-6484 standard was used for test method. The regression analysis was performed with the response variable being the laminate ultimate fracture strength and the regressor variables being two ply orientations (0° and ±45°)

Development of Compressive Failure Strength for Composite Laminate Using Regression Analysis Method

International Nuclear Information System (INIS)

Lee, Myoung Keon; Lee, Jeong Won; Yoon, Dong Hyun; Kim, Jae Hoon

2016-01-01

This paper provides the compressive failure strength value of composite laminate developed by using regression analysis method. Composite material in this document is a Carbon/Epoxy unidirection(UD) tape prepreg(Cycom G40-800/5276-1) cured at 350°F(177°C). The operating temperature is –60°F~+200°F(-55°C - +95°C). A total of 56 compression tests were conducted on specimens from eight (8) distinct laminates that were laid up by standard angle layers (0°, +45°, –45° and 90°). The ASTM-D-6484 standard was used for test method. The regression analysis was performed with the response variable being the laminate ultimate fracture strength and the regressor variables being two ply orientations (0° and ±45°)

Standards for Standardized Logistic Regression Coefficients

Science.gov (United States)

Menard, Scott

2011-01-01

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

Comparing spatial regression to random forests for large ...

Science.gov (United States)

Environmental data may be “large” due to number of records, number of covariates, or both. Random forests has a reputation for good predictive performance when using many covariates, whereas spatial regression, when using reduced rank methods, has a reputation for good predictive performance when using many records. In this study, we compare these two techniques using a data set containing the macroinvertebrate multimetric index (MMI) at 1859 stream sites with over 200 landscape covariates. Our primary goal is predicting MMI at over 1.1 million perennial stream reaches across the USA. For spatial regression modeling, we develop two new methods to accommodate large data: (1) a procedure that estimates optimal Box-Cox transformations to linearize covariate relationships; and (2) a computationally efficient covariate selection routine that takes into account spatial autocorrelation. We show that our new methods lead to cross-validated performance similar to random forests, but that there is an advantage for spatial regression when quantifying the uncertainty of the predictions. Simulations are used to clarify advantages for each method. This research investigates different approaches for modeling and mapping national stream condition. We use MMI data from the EPA's National Rivers and Streams Assessment and predictors from StreamCat (Hill et al., 2015). Previous studies have focused on modeling the MMI condition classes (i.e., good, fair, and po

CADDIS Volume 4. Data Analysis: PECBO Appendix - R Scripts for Non-Parametric Regressions

Science.gov (United States)

Script for computing nonparametric regression analysis. Overview of using scripts to infer environmental conditions from biological observations, statistically estimating species-environment relationships, statistical scripts.

Δ9-THC-caused synaptic and memory impairments are mediated through COX-2 signaling

Science.gov (United States)

Yang, Hongwei; Tang, Ya-ping; Sun, Hao; Song, Yunping; Chen, Chu

2013-01-01

SUMMARY Marijuana has been used for thousands of years as a treatment for medical conditions. However, untoward side effects limit its medical value. Here we show that synaptic and cognitive impairments following repeated exposure to Δ9-tetrahydrocannabinol (Δ9-THC) are associated with the induction of cyclooxygenase-2 (COX-2), an inducible enzyme that converts arachidonic acid to prostanoids, in the brain. COX-2 induction by Δ9-THC is mediated via CB1 receptor-coupled G-protein βγ subunits. Pharmacological or genetic inhibition of COX-2 blocks down-regulation and internalization of glutamate receptor subunits and alterations of the dendritic spine density of hippocampal neurons induced by repeated Δ9-THC exposures. Ablation of COX-2 also eliminates Δ9-THC-impaired hippocampal long-term synaptic plasticity, spatial, and fear memories. Importantly, the beneficial effects of decreasing β-amyloid plaques and neurodegeneration by Δ9-THC in Alzheimer’s disease animals are retained in the presence of COX-2 inhibition. These results suggest that the applicability of medical marijuana would be broadened by concurrent inhibition of COX-2. PMID:24267894

Aneurysmal subarachnoid hemorrhage prognostic decision-making algorithm using classification and regression tree analysis.

Science.gov (United States)

Lo, Benjamin W Y; Fukuda, Hitoshi; Angle, Mark; Teitelbaum, Jeanne; Macdonald, R Loch; Farrokhyar, Forough; Thabane, Lehana; Levine, Mitchell A H

2016-01-01

Classification and regression tree analysis involves the creation of a decision tree by recursive partitioning of a dataset into more homogeneous subgroups. Thus far, there is scarce literature on using this technique to create clinical prediction tools for aneurysmal subarachnoid hemorrhage (SAH). The classification and regression tree analysis technique was applied to the multicenter Tirilazad database (3551 patients) in order to create the decision-making algorithm. In order to elucidate prognostic subgroups in aneurysmal SAH, neurologic, systemic, and demographic factors were taken into account. The dependent variable used for analysis was the dichotomized Glasgow Outcome Score at 3 months. Classification and regression tree analysis revealed seven prognostic subgroups. Neurological grade, occurrence of post-admission stroke, occurrence of post-admission fever, and age represented the explanatory nodes of this decision tree. Split sample validation revealed classification accuracy of 79% for the training dataset and 77% for the testing dataset. In addition, the occurrence of fever at 1-week post-aneurysmal SAH is associated with increased odds of post-admission stroke (odds ratio: 1.83, 95% confidence interval: 1.56-2.45, P tree was generated, which serves as a prediction tool to guide bedside prognostication and clinical treatment decision making. This prognostic decision-making algorithm also shed light on the complex interactions between a number of risk factors in determining outcome after aneurysmal SAH.

The tariff for fire and theft car insurance: analysis with a Cox model

Directory of Open Access Journals (Sweden)

Bruno Scarpa

2013-05-01

Full Text Available In this paper we analyze the problem of identification of a tariff for a Fire & Theft Car policy for Insurance Companies. Usually companies obtain this tariff by empirical estimate of the pure rate by evaluating the impact of some personalization variables. In this paper we propose the usage of a semi-parametric Cox model, where the response variable is not the waiting time until an event, but the degree of damage because of theft or fire of a car. The proposed model allows to easily tackle typical problems in data available to the companies, like the presence of franchises, which are treated as censored data.

Inferring gene expression dynamics via functional regression analysis

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Leng Xiaoyan

2008-01-01

Full Text Available Abstract Background Temporal gene expression profiles characterize the time-dynamics of expression of specific genes and are increasingly collected in current gene expression experiments. In the analysis of experiments where gene expression is obtained over the life cycle, it is of interest to relate temporal patterns of gene expression associated with different developmental stages to each other to study patterns of long-term developmental gene regulation. We use tools from functional data analysis to study dynamic changes by relating temporal gene expression profiles of different developmental stages to each other. Results We demonstrate that functional regression methodology can pinpoint relationships that exist between temporary gene expression profiles for different life cycle phases and incorporates dimension reduction as needed for these high-dimensional data. By applying these tools, gene expression profiles for pupa and adult phases are found to be strongly related to the profiles of the same genes obtained during the embryo phase. Moreover, one can distinguish between gene groups that exhibit relationships with positive and others with negative associations between later life and embryonal expression profiles. Specifically, we find a positive relationship in expression for muscle development related genes, and a negative relationship for strictly maternal genes for Drosophila, using temporal gene expression profiles. Conclusion Our findings point to specific reactivation patterns of gene expression during the Drosophila life cycle which differ in characteristic ways between various gene groups. Functional regression emerges as a useful tool for relating gene expression patterns from different developmental stages, and avoids the problems with large numbers of parameters and multiple testing that affect alternative approaches.

Use of generalized ordered logistic regression for the analysis of multidrug resistance data.

Science.gov (United States)

Agga, Getahun E; Scott, H Morgan

2015-10-01

Statistical analysis of antimicrobial resistance data largely focuses on individual antimicrobial's binary outcome (susceptible or resistant). However, bacteria are becoming increasingly multidrug resistant (MDR). Statistical analysis of MDR data is mostly descriptive often with tabular or graphical presentations. Here we report the applicability of generalized ordinal logistic regression model for the analysis of MDR data. A total of 1,152 Escherichia coli, isolated from the feces of weaned pigs experimentally supplemented with chlortetracycline (CTC) and copper, were tested for susceptibilities against 15 antimicrobials and were binary classified into resistant or susceptible. The 15 antimicrobial agents tested were grouped into eight different antimicrobial classes. We defined MDR as the number of antimicrobial classes to which E. coli isolates were resistant ranging from 0 to 8. Proportionality of the odds assumption of the ordinal logistic regression model was violated only for the effect of treatment period (pre-treatment, during-treatment and post-treatment); but not for the effect of CTC or copper supplementation. Subsequently, a partially constrained generalized ordinal logistic model was built that allows for the effect of treatment period to vary while constraining the effects of treatment (CTC and copper supplementation) to be constant across the levels of MDR classes. Copper (Proportional Odds Ratio [Prop OR]=1.03; 95% CI=0.73-1.47) and CTC (Prop OR=1.1; 95% CI=0.78-1.56) supplementation were not significantly associated with the level of MDR adjusted for the effect of treatment period. MDR generally declined over the trial period. In conclusion, generalized ordered logistic regression can be used for the analysis of ordinal data such as MDR data when the proportionality assumptions for ordered logistic regression are violated. Published by Elsevier B.V.

Regression analysis of growth responses to water depth in three wetland plant species

DEFF Research Database (Denmark)

Sorrell, Brian K; Tanner, Chris C; Brix, Hans

2012-01-01

depths from 0 – 0.5 m. Morphological and growth responses to depth were followed for 54 days before harvest, and then analysed by repeated measures analysis of covariance, and non-linear and quantile regression analysis (QRA), to compare flooding tolerances. Principal results Growth responses to depth...

A SOCIOLOGICAL ANALYSIS OF THE CHILDBEARING COEFFICIENT IN THE ALTAI REGION BASED ON METHOD OF FUZZY LINEAR REGRESSION

Directory of Open Access Journals (Sweden)

Sergei Vladimirovich Varaksin

2017-06-01

Full Text Available Purpose. Construction of a mathematical model of the dynamics of childbearing change in the Altai region in 2000–2016, analysis of the dynamics of changes in birth rates for multiple age categories of women of childbearing age. Methodology. A auxiliary analysis element is the construction of linear mathematical models of the dynamics of childbearing by using fuzzy linear regression method based on fuzzy numbers. Fuzzy linear regression is considered as an alternative to standard statistical linear regression for short time series and unknown distribution law. The parameters of fuzzy linear and standard statistical regressions for childbearing time series were defined with using the built in language MatLab algorithm. Method of fuzzy linear regression is not used in sociological researches yet. Results. There are made the conclusions about the socio-demographic changes in society, the high efficiency of the demographic policy of the leadership of the region and the country, and the applicability of the method of fuzzy linear regression for sociological analysis.

A Monte Carlo Investigation of the Box-Cox Model and a Nonlinear Least Squares Alternative.

OpenAIRE

Showalter, Mark H

1994-01-01

This paper reports a Monte Carlo study of the Box-Cox model and a nonlinear least squares alternative. Key results include the following: the transformation parameter in the Box-Cox model appears to be inconsistently estimated in the presence of conditional heteroskedasticity; the constant term in both the Box-Cox and the nonlinear least squares models is poorly estimated in small samples; conditional mean forecasts tend to underestimate their true value in the Box-Cox model when the transfor...

Relationship between serum levels of triglycerides and vascular inflammation, measured as COX-2, in arteries from diabetic patients: a translational study

Science.gov (United States)

2013-01-01

Background Inflammation is a common feature in the majority of cardiovascular disease, including Diabetes Mellitus (DM). Levels of pro-inflammatory markers have been found in increasing levels in serum from diabetic patients (DP). Moreover, levels of Cyclooxygenase-2 (COX-2) are increased in coronary arteries from DP. Methods Through a cross-sectional design, patients who underwent CABG were recruited. Vascular smooth muscle cells (VSMC) were cultured and COX-2 was measured by western blot. Biochemical and clinical data were collected from the medical record and by blood testing. COX-2 expression was analyzed in internal mammary artery cross-sections by confocal microscopy. Eventually, PGI2 and PGE2 were assessed from VSMC conditioned media by ELISA. Results Only a high glucose concentration, but a physiological concentration of triglycerides exposure of cultured human VSMC derived from non-diabetic patients increased COX-2 expression .Diabetic patients showed increasing serum levels of glucose, Hb1ac and triglycerides. The bivariate analysis of the variables showed that triglycerides was positively correlated with the expression of COX-2 in internal mammary arteries from patients (r2 = 0.214, P < 0.04). Conclusions We conclude that is not the glucose blood levels but the triglicerydes leves what increases the expression of COX-2 in arteries from DP. PMID:23642086

Multiple Logistic Regression Analysis of Cigarette Use among High School Students

Science.gov (United States)

Adwere-Boamah, Joseph

2011-01-01

A binary logistic regression analysis was performed to predict high school students' cigarette smoking behavior from selected predictors from 2009 CDC Youth Risk Behavior Surveillance Survey. The specific target student behavior of interest was frequent cigarette use. Five predictor variables included in the model were: a) race, b) frequency of…

Activating PTEN by COX-2 inhibitors antagonizes radiation-induced AKT activation contributing to radiosensitization

Energy Technology Data Exchange (ETDEWEB)

Meng, Zhen [Central Laboratory, Peking University School and Hospital of Stomatology, 22 Zhongguancun Avenue South, Haidian District, Beijing 100081 (China); Department of Oral & Maxillofacial Surgery, Peking University School and Hospital of Stomatology, 22 Zhongguancun Avenue South, Haidian District, Beijing 100081 (China); Gan, Ye-Hua, E-mail: kqyehuagan@bjmu.edu.cn [Central Laboratory, Peking University School and Hospital of Stomatology, 22 Zhongguancun Avenue South, Haidian District, Beijing 100081 (China); Department of Oral & Maxillofacial Surgery, Peking University School and Hospital of Stomatology, 22 Zhongguancun Avenue South, Haidian District, Beijing 100081 (China)

2015-05-01

Radiotherapy is still one of the most effective nonsurgical treatments for many tumors. However, radioresistance remains a major impediment to radiotherapy. Although COX-2 inhibitors can induce radiosensitization, the underlying mechanism is not fully understood. In this study, we showed that COX-2 selective inhibitor celecoxib enhanced the radiation-induced inhibition of cell proliferation and apoptosis in HeLa and SACC-83 cells. Treatment with celecoxib alone dephosphorylated phosphatase and tensin homolog deleted on chromosome ten (PTEN), promoted PTEN membrane translocation or activation, and correspondingly dephosphorylated or inactivated protein kinase B (AKT). By contrast, treatment with radiation alone increased PTEN phosphorylation, inhibited PTEN membrane translocation and correspondingly activated AKT in the two cell lines. However, treatment with celecoxib or another COX-2 selective inhibitor (valdecoxib) completely blocked radiation-induced increase of PTEN phosphorylation, rescued radiation-induced decrease in PTEN membrane translocation, and correspondingly inactivated AKT. Moreover, celecoxib could also upregulate PTEN protein expression by downregulating Sp1 expression, thereby leading to the activation of PTEN transcription. Our results suggested that COX-2 inhibitors could enhance radiosensitization at least partially by activating PTEN to antagonize radiation-induced AKT activation. - Highlights: • COX-2 inhibitor, celecoxib, could enhance radiosensitization. • Radiation induced PTEN inactivation (phosphorylation) and AKT activation. • COX-2 inhibitor induced PTEN expression and activation, and inactivated AKT. • COX-2 inhibitor enhanced radiosensitization through activating PTEN.

Early increased density of cyclooxygenase-2 (COX-2 immunoreactive neurons in Down syndrome

Directory of Open Access Journals (Sweden)

Maria Mulet

2017-06-01

Full Text Available Neuroinflammation is one of the hallmarks of Alzheimer’s disease. One of the enzymes involved in neuroinflammation, even in early stages of the disease, is COX-2, an inducible cyclooxygenase responsible for the generation of eicosanoids and for the generation of free radicals. Individuals with Down syndrome develop Alzheimer’s disease early in life. Previous studies pointed to the possible overexpression of COX-2 and correlated it to brain regions affected by the disease. We analysed the COX-2 expression levels in individuals with Down syndrome and in young, adult and old mice of the Ts65Dn mouse model for Down syndrome. We have observed an overexpression of COX-2 in both, Down syndrome individuals and mice. Importantly, mice already presented an overexpression of COX-2 at postnatal day 30, before neurodegeneration begins; which suggests that neuroinflammation may underlie the posterior neurodegeneration observed in individuals with Down syndrome and in Ts65Dn mice and could be a factor for the premature appearance of Alzheimer’s disease.

THE PROGNOSIS OF RUSSIAN DEFENSE INDUSTRY DEVELOPMENT IMPLEMENTED THROUGH REGRESSION ANALYSIS

Directory of Open Access Journals (Sweden)

L.M. Kapustina

2007-03-01

Full Text Available The article illustrates the results of investigation the major internal and external factors which influence the development of the defense industry, as well as the results of regression analysis which quantitatively displays the factorial contribution in the growth rate of Russian defense industry. On the basis of calculated regression dependences the authors fulfilled the medium-term prognosis of defense industry. Optimistic and inertial versions of defense product growth rate for the period up to 2009 are based on scenario conditions in Russian economy worked out by the Ministry of economy and development. In conclusion authors point out which factors and conditions have the largest impact on successful and stable operation of Russian defense industry.

Allan Cox 1926”1987

Science.gov (United States)

Coe, Rob; Dalrymple, Brent

More than 1000 friends, students, and colleagues from all over the country filled Stanford Memorial Chapel (Stanford, Calif.) on February 3, 1987, to join in “A Celebration of the Life of Allan Cox.” Allan died early on the morning of January 27 while bicycling, the sport he had come to love the most. Between pieces of his favorite music by Bach and Mozart, Stanford administrators and colleagues spoke in tribute of Allan's unique qualities as friend, scientist, teacher, and dean of the School of Earth Sciences. James Rosse, Vice President and Provost of Stanford University, struck a particularly resonant chord with his personal remarks: "Allan reached out to each person he knew with the warmth and attention that can only come from deep respect and affection for others. I never heard him speak ill of others, and I do not believe he was capable of doing anything that would harm another being. He cared too much to intrude where he was not wanted, but his curiosity about people and the loving care with which he approached them broke down reserve to create remarkable friendships. His enthusiasm and good humor made him a welcome guest in the hearts of the hundreds of students and colleagues who shared the opportunity of knowing Allan Cox as a person."

Applied linear regression

CERN Document Server

Weisberg, Sanford

2013-01-01

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

Noninvasive spectral imaging of skin chromophores based on multiple regression analysis aided by Monte Carlo simulation

Science.gov (United States)

Nishidate, Izumi; Wiswadarma, Aditya; Hase, Yota; Tanaka, Noriyuki; Maeda, Takaaki; Niizeki, Kyuichi; Aizu, Yoshihisa

2011-08-01

In order to visualize melanin and blood concentrations and oxygen saturation in human skin tissue, a simple imaging technique based on multispectral diffuse reflectance images acquired at six wavelengths (500, 520, 540, 560, 580 and 600nm) was developed. The technique utilizes multiple regression analysis aided by Monte Carlo simulation for diffuse reflectance spectra. Using the absorbance spectrum as a response variable and the extinction coefficients of melanin, oxygenated hemoglobin, and deoxygenated hemoglobin as predictor variables, multiple regression analysis provides regression coefficients. Concentrations of melanin and total blood are then determined from the regression coefficients using conversion vectors that are deduced numerically in advance, while oxygen saturation is obtained directly from the regression coefficients. Experiments with a tissue-like agar gel phantom validated the method. In vivo experiments with human skin of the human hand during upper limb occlusion and of the inner forearm exposed to UV irradiation demonstrated the ability of the method to evaluate physiological reactions of human skin tissue.

Δ9-THC-caused synaptic and memory impairments are mediated through COX-2 signaling.

Science.gov (United States)

Chen, Rongqing; Zhang, Jian; Fan, Ni; Teng, Zhao-Qian; Wu, Yan; Yang, Hongwei; Tang, Ya-Ping; Sun, Hao; Song, Yunping; Chen, Chu

2013-11-21

Marijuana has been used for thousands of years as a treatment for medical conditions. However, untoward side effects limit its medical value. Here, we show that synaptic and cognitive impairments following repeated exposure to Δ(9)-tetrahydrocannabinol (Δ(9)-THC) are associated with the induction of cyclooxygenase-2 (COX-2), an inducible enzyme that converts arachidonic acid to prostanoids in the brain. COX-2 induction by Δ(9)-THC is mediated via CB1 receptor-coupled G protein βγ subunits. Pharmacological or genetic inhibition of COX-2 blocks downregulation and internalization of glutamate receptor subunits and alterations of the dendritic spine density of hippocampal neurons induced by repeated Δ(9)-THC exposures. Ablation of COX-2 also eliminates Δ(9)-THC-impaired hippocampal long-term synaptic plasticity, working, and fear memories. Importantly, the beneficial effects of decreasing β-amyloid plaques and neurodegeneration by Δ(9)-THC in Alzheimer's disease animals are retained in the presence of COX-2 inhibition. These results suggest that the applicability of medical marijuana would be broadened by concurrent inhibition of COX-2. Copyright © 2013 Elsevier Inc. All rights reserved.

Multiple Regression Analysis of Unconfined Compression Strength of Mine Tailings Matrices

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Mahmood Ali A.

2017-01-01

Full Text Available As part of a novel approach of sustainable development of mine tailings, experimental and numerical analysis is carried out on newly formulated tailings matrices. Several physical characteristic tests are carried out including the unconfined compression strength test to ascertain the integrity of these matrices when subjected to loading. The current paper attempts a multiple regression analysis of the unconfined compressive strength test results of these matrices to investigate the most pertinent factors affecting their strength. Results of this analysis showed that the suggested equation is reasonably applicable to the range of binder combinations used.

Effect of uric acid on inflammatory COX-2 and ROS pathways in vascular smooth muscle cells.

Science.gov (United States)

Oğuz, Nurgül; Kırça, Mustafa; Çetin, Arzu; Yeşilkaya, Akın

2017-10-01

Hyperuricemia is thought to play a role in cardiovascular diseases (CVD), including hypertension, coronary artery disease and atherosclerosis. However, exactly how uric acid contributes to these pathologies is unknown. An underlying mechanism of inflammatory diseases, such as atherosclerosis, includes enhanced production of cyclooxygenase-2 (COX-2) and superoxide anion. Here, we aimed to examine the effect of uric acid on inflammatory COX-2 and superoxide anion production and to determine the role of losartan. Primarily cultured vascular smooth muscle cells (VSMCs) were time and dose-dependently induced by uric acid and COX-2 and superoxide anion levels were measured. COX-2 levels were determined by ELISA, and superoxide anion was measured by the superoxide dismutase (SOD)-inhibitable reduction of ferricytochrome c method. Uric acid elevated COX-2 levels in a time-dependent manner. Angiotensin-II receptor blocker, losartan, diminished uric-acid-induced COX-2 elevation. Uric acid also increased superoxide anion level in VSMCs. Uric acid plays an important role in CVD pathogenesis by inducing inflammatory COX-2 and ROS pathways. This is the first study demonstrating losartan's ability to reduce uric-acid-induced COX-2 elevation.

Optical, magnetic and structural characterization of Zn1−xCoxO ...

Indian Academy of Sciences (India)

attracted considerable attention, both theoretically and experi- mentally, due to their ... C and finally ground to powder. Zn1−x Cox O ... Figure 1. Flowchart for solvothermal synthesis of Zn1−x Cox O (x = 0·038, 0·072 and 0·115) nanoparticles.

The Regression Analysis of Individual Financial Performance: Evidence from Croatia

OpenAIRE

Bahovec, Vlasta; Barbić, Dajana; Palić, Irena

2017-01-01

Background: A large body of empirical literature indicates that gender and financial literacy are significant determinants of individual financial performance. Objectives: The purpose of this paper is to recognize the impact of the variable financial literacy and the variable gender on the variation of the financial performance using the regression analysis. Methods/Approach: The survey was conducted using the systematically chosen random sample of Croatian financial consumers. The cross sect...

A systematic review and meta-regression analysis of mivacurium for tracheal intubation

NARCIS (Netherlands)

Vanlinthout, L.E.H.; Mesfin, S.H.; Hens, N.; Vanacker, B.F.; Robertson, E.N.; Booij, L.H.D.J.

2014-01-01

We systematically reviewed factors associated with intubation conditions in randomised controlled trials of mivacurium, using random-effects meta-regression analysis. We included 29 studies of 1050 healthy participants. Four factors explained 72.9% of the variation in the probability of excellent

Considerations for analysis of time-to-event outcomes measured with error: Bias and correction with SIMEX.

Science.gov (United States)

Oh, Eric J; Shepherd, Bryan E; Lumley, Thomas; Shaw, Pamela A

2018-04-15

For time-to-event outcomes, a rich literature exists on the bias introduced by covariate measurement error in regression models, such as the Cox model, and methods of analysis to address this bias. By comparison, less attention has been given to understanding the impact or addressing errors in the failure time outcome. For many diseases, the timing of an event of interest (such as progression-free survival or time to AIDS progression) can be difficult to assess or reliant on self-report and therefore prone to measurement error. For linear models, it is well known that random errors in the outcome variable do not bias regression estimates. With nonlinear models, however, even random error or misclassification can introduce bias into estimated parameters. We compare the performance of 2 common regression models, the Cox and Weibull models, in the setting of measurement error in the failure time outcome. We introduce an extension of the SIMEX method to correct for bias in hazard ratio estimates from the Cox model and discuss other analysis options to address measurement error in the response. A formula to estimate the bias induced into the hazard ratio by classical measurement error in the event time for a log-linear survival model is presented. Detailed numerical studies are presented to examine the performance of the proposed SIMEX method under varying levels and parametric forms of the error in the outcome. We further illustrate the method with observational data on HIV outcomes from the Vanderbilt Comprehensive Care Clinic. Copyright © 2017 John Wiley & Sons, Ltd.

No rationale for 1 variable per 10 events criterion for binary logistic regression analysis.

Science.gov (United States)

van Smeden, Maarten; de Groot, Joris A H; Moons, Karel G M; Collins, Gary S; Altman, Douglas G; Eijkemans, Marinus J C; Reitsma, Johannes B

2016-11-24

Ten events per variable (EPV) is a widely advocated minimal criterion for sample size considerations in logistic regression analysis. Of three previous simulation studies that examined this minimal EPV criterion only one supports the use of a minimum of 10 EPV. In this paper, we examine the reasons for substantial differences between these extensive simulation studies. The current study uses Monte Carlo simulations to evaluate small sample bias, coverage of confidence intervals and mean square error of logit coefficients. Logistic regression models fitted by maximum likelihood and a modified estimation procedure, known as Firth's correction, are compared. The results show that besides EPV, the problems associated with low EPV depend on other factors such as the total sample size. It is also demonstrated that simulation results can be dominated by even a few simulated data sets for which the prediction of the outcome by the covariates is perfect ('separation'). We reveal that different approaches for identifying and handling separation leads to substantially different simulation results. We further show that Firth's correction can be used to improve the accuracy of regression coefficients and alleviate the problems associated with separation. The current evidence supporting EPV rules for binary logistic regression is weak. Given our findings, there is an urgent need for new research to provide guidance for supporting sample size considerations for binary logistic regression analysis.

Estimate the contribution of incubation parameters influence egg hatchability using multiple linear regression analysis.

Science.gov (United States)

Khalil, Mohamed H; Shebl, Mostafa K; Kosba, Mohamed A; El-Sabrout, Karim; Zaki, Nesma

2016-08-01

This research was conducted to determine the most affecting parameters on hatchability of indigenous and improved local chickens' eggs. Five parameters were studied (fertility, early and late embryonic mortalities, shape index, egg weight, and egg weight loss) on four strains, namely Fayoumi, Alexandria, Matrouh, and Montazah. Multiple linear regression was performed on the studied parameters to determine the most influencing one on hatchability. The results showed significant differences in commercial and scientific hatchability among strains. Alexandria strain has the highest significant commercial hatchability (80.70%). Regarding the studied strains, highly significant differences in hatching chick weight among strains were observed. Using multiple linear regression analysis, fertility made the greatest percent contribution (71.31%) to hatchability, and the lowest percent contributions were made by shape index and egg weight loss. A prediction of hatchability using multiple regression analysis could be a good tool to improve hatchability percentage in chickens.

Logistic Regression: Concept and Application

Science.gov (United States)

Cokluk, Omay

2010-01-01

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

Kaempferol attenuates COX-2 expression in IL-6-induced macrophages and carrageenan-induced mouse paw edema by targeting STAT3 and NF-kB

Directory of Open Access Journals (Sweden)

Anandita Basu

2017-10-01

Full Text Available Dietary polyphenols are reported to possess varied pharmacological activities, viz. antioxidant, anti-inflammatory, anti-cancer, anti-allergic actions. Here, we report the efficacy of Kaempferol (kae to attenuate expression of IL-6 induced cycloxygenase-2 (COX-2, an inducible isoform of cycloxygenase enzyme family that catalyzes synthesis of inflammatory mediators, prostanoids and prostaglandins. IL-6 is a pleiotropic cytokine involved in both acute and chronic inflammation. Our results showed that kae attenuated COX-2 expression at both mRNA and protein level in IL-6-induced THP1 macrophages. This attenuation of COX-2 expression by kae involved dose-dependent inhibition of phosphorylation of STAT3 (Tyr 705 and NF-kB p65 (Ser 536 leading to their deactivation and reduced nuclear localization in THP-1 macrophages. Moreover, kae modulates COX-2 expression as well as STAT3 and NF-kB activation in carrageenan-induced mouse paw edema model. RT-PCR and western blot analysis from paw tissues were harvested after kae injection (i.p followed by carrageenan-treatment in sub-plantar region of right hind paw. Results showed that kae attenuated COX-2 expression and STAT3 and NF-kB activation in carrageenan-induced mouse paw edema, suggesting that inhibition of both IL-6-STAT3-COX-2 and IL-6-NFkB-COX-2 axes by kae might be stimulus-independent. To understand binding affinity of kae with NF-kB and STAT3, docking analysis was performed using Patchdock server. From our findings, we observed strong binding affinity and transient interaction in both NF-kB/kae and STAT3/kae complexes. We noticed negative atomic contact energy and greater interface area for both the complexes. Selected complexes obtained from Patchdock were refined using Firedock online server which also suggested similar negative binding energy profile. It is plausible that kae attenuates COX-2 expression by directly binding to both STAT3 and NF-kB proteins and inhibiting their activation and

Resveratrol Targeting of Carcinogen-Induced Brain Endothelial Cell Inflammation Biomarkers MMP-9 and COX-2 is Sirt1-Independent

Directory of Open Access Journals (Sweden)

Borhane Annabi

2012-01-01

Full Text Available The occurrence of a functional relationship between the release of metalloproteinases (MMPs and the expression of cyclooxygenase (COX-2, two inducible pro-inflammatory biomarkers with important pro-angiogenic effects, has recently been inferred. While brain endothelial cells play an essential role as structural and functional components of the blood-brain barrier (BBB, increased BBB breakdown is thought to be linked to neuroinflammation. Chemopreventive mechanisms targeting both MMPs and COX-2 however remain poorly investigated. In this study, we evaluated the pharmacological targeting of Sirt1 by the diet-derived and antiinflammatory polyphenol resveratrol. Total RNA, cell lysates, and conditioned culture media from human brain microvascular endothelial cells (HBMEC were analyzed using qRT-PCR, immunoblotting, and zymography respectively. Tissue scan microarray analysis of grade I–IV brain tumours cDNA revealed increased gene expression of Sirt-1 from grade I–III but surprisingly not in grade IV brain tumours. HBMEC were treated with a combination of resveratrol and phorbol 12-myristate 13-acetate (PMA, a carcinogen known to increase MMP-9 and COX-2 through NF-κB. We found that resveratrol efficiently reversed the PMA-induced MMP-9 secretion and COX-2 expression. Gene silencing of Sirt1, a critical modulator of angiogenesis and putative target of resveratrol, did not lead to significant reversal of MMP-9 and COX-2 inhibition. Decreased resveratrol inhibitory potential of carcinogen-induced IκB phosphorylation in siSirt1-transfected HBMEC was however observed. Our results suggest that resveratrol may prevent BBB disruption during neuroinflammation by inhibiting MMP-9 and COX-2 and act as a pharmacological NF-κB signal transduction inhibitor independent of Sirt1.

COX-2 and PPARγ expression are potential markers of recurrence risk in mammary duct carcinoma in-situ

International Nuclear Information System (INIS)

Kulkarni, Swati; Patil, Deepa B; Diaz, Leslie K; Wiley, Elizabeth L; Morrow, Monica; Khan, Seema A

2008-01-01

In women with duct carcinoma in-situ (DCIS) receiving breast conservation therapy (BCT), in-breast recurrences are seen in approximately 10%, but cannot be accurately predicted using clinical and histological criteria. We performed a case-control study to identify protein markers of local recurrence risk in DCIS. Women treated for DCIS with BCT, who later developed in-breast recurrence (cases) were matched by age and year of treatment to women who remained free of recurrence (controls). A total of 69 women were included in the study, 31 cases and 38 controls. Immunohistochemical evaluation of DCIS tissue arrays was performed for estrogen receptor, progesterone receptor, HER-2/neu, cyclin D1, p53, p21, cycloxygenase-2 (COX-2) and peroxisome proliferator activated receptor γ (PPARγ). Two markers were significantly different between cases and controls on univariate analysis: strong COX-2 expression was associated with increased risk of recurrence, with 67% vs. 24% positivity in cases and controls p = 0.006; and nuclear expression of PPARγ was associated with protection from recurrence with 4% vs. 27% positivity in cases and controls, p = 0.024. In a multivariate model which included size, grade, COX-2 and PPARγ positivity, we found COX-2 positivity to be a strong independent risk factor for recurrence (OR 7.90, 95% CI 1.72–36.23)., whereas size and grade were of borderline significance. PPARγ expression continued to demonstrate a protective trend, (OR 0.14, 95% CI 0.06–1.84). Our findings suggest that COX-2 and PPARγ should be investigated further as biologic markers to predict DCIS recurrence, particularly since they are also potential therapeutic targets

A multiple regression analysis for accurate background subtraction in 99Tcm-DTPA renography

International Nuclear Information System (INIS)

Middleton, G.W.; Thomson, W.H.; Davies, I.H.; Morgan, A.

1989-01-01

A technique for accurate background subtraction in 99 Tc m -DTPA renography is described. The technique is based on a multiple regression analysis of the renal curves and separate heart and soft tissue curves which together represent background activity. It is compared, in over 100 renograms, with a previously described linear regression technique. Results show that the method provides accurate background subtraction, even in very poorly functioning kidneys, thus enabling relative renal filtration and excretion to be accurately estimated. (author)

Niacin and biosynthesis of PGD₂ by platelet COX-1 in mice and humans

DEFF Research Database (Denmark)

Song, Wen-Liang; Stubbe, Jane; Ricciotti, Emanuela

2012-01-01

during platelet activation in humans and, although vascular expression of DP1 is conserved between humans and mice, platelet DP1 is not present in mice. Despite this, DP1 deletion in mice augmented aneurysm formation and the hypertensive response to Ang II and accelerated atherogenesis and thrombogenesis....... Furthermore, COX inhibitors in humans, as well as platelet depletion, COX-1 knockdown, and COX-2 deletion in mice, revealed that niacin evoked platelet COX-1-derived PGD₂ biosynthesis. Finally, ADP-induced spreading on fibrinogen was augmented by niacin in washed human platelets, coincident with increased...... thromboxane (Tx) formation. However, in platelet-rich plasma, where formation of both Tx and PGD₂ was increased, spreading was not as pronounced and was inhibited by DP1 activation. Thus, PGD₂, like PGI₂, may function as a homeostatic response to thrombogenic and hypertensive stimuli and may have particular...

Development of an empirical model of turbine efficiency using the Taylor expansion and regression analysis

International Nuclear Information System (INIS)

Fang, Xiande; Xu, Yu

2011-01-01

The empirical model of turbine efficiency is necessary for the control- and/or diagnosis-oriented simulation and useful for the simulation and analysis of dynamic performances of the turbine equipment and systems, such as air cycle refrigeration systems, power plants, turbine engines, and turbochargers. Existing empirical models of turbine efficiency are insufficient because there is no suitable form available for air cycle refrigeration turbines. This work performs a critical review of empirical models (called mean value models in some literature) of turbine efficiency and develops an empirical model in the desired form for air cycle refrigeration, the dominant cooling approach in aircraft environmental control systems. The Taylor series and regression analysis are used to build the model, with the Taylor series being used to expand functions with the polytropic exponent and the regression analysis to finalize the model. The measured data of a turbocharger turbine and two air cycle refrigeration turbines are used for the regression analysis. The proposed model is compact and able to present the turbine efficiency map. Its predictions agree with the measured data very well, with the corrected coefficient of determination R c 2 ≥ 0.96 and the mean absolute percentage deviation = 1.19% for the three turbines. -- Highlights: → Performed a critical review of empirical models of turbine efficiency. → Developed an empirical model in the desired form for air cycle refrigeration, using the Taylor expansion and regression analysis. → Verified the method for developing the empirical model. → Verified the model.

Early induction of cytokines/cytokine receptors and Cox2, and activation of NF-κB in 4-nitroquinoline 1-oxide-induced murine oral cancer model

Energy Technology Data Exchange (ETDEWEB)

Liu, Yu-Ching [Department of Medical Research, China Medical University Hospital, Taichung 404, Taiwan (China); Department of Veterinary Medicine, National Chung Hsing University, Taichung 402, Taiwan (China); Ho, Heng-Chien; Lee, Miau-Rong [Department of Biochemistry, China Medical University, Taichung 404, Taiwan (China); Lai, Kuang-Chi [Department of Surgery, China Medical University Beigang Hospital, Yunlin 651, Taiwan (China); School of Medicine, China Medical University, Taichung 404, Taiwan (China); Yeh, Chung-Min; Lin, Yueh-Min [Department of Pathology, Changhua Christian Hospital, Changhua 500, Taiwan (China); Ho, Tin-Yun [School of Chinese Medicine, China Medical University, Taichung 404, Taiwan (China); Hsiang, Chien-Yun, E-mail: cyhsiang@mail.cmu.edu.tw [Department of Microbiology, China Medical University, Taichung 404, Taiwan (China); Chung, Jing-Gung, E-mail: jgchung@mail.cmu.edu.tw [Department of Biological Science and Technology, China Medical University, Taichung 404, Taiwan (China); Department of Biotechnology, Asia University, Taichung 413, Taiwan (China)

2012-07-15

The purpose of this study was to identify the genes induced early in murine oral carcinogenesis. Murine tongue tumors induced by the carcinogen, 4-nitroquinoline 1-oxide (4-NQO), and paired non-tumor tissues were subjected to microarray analysis. Hierarchical clustering of upregulated genes in the tumor tissues revealed an association of induced genes with inflammation. Cytokines/cytokine receptors induced early were subsequently identified, clearly indicating their involvement in oral carcinogenesis. Hierarchical clustering also showed that cytokine-mediated inflammation was possibly linked with Mapk6. Cox2 exhibited the greatest extent (9–18 fold) of induction in the microarray data, and its early induction was observed in a 2 h painting experiment by RT-PCR. MetaCore analysis showed that overexpressed Cox2 may interact with p53 and transcriptionally inhibit expression of several downstream genes. A painting experiment in transgenic mice also demonstrated that NF-κB activates early independently of Cox2 induction. MetaCore analysis revealed the most striking metabolic alterations in tumor tissues, especially in lipid metabolism resulting from the reduction of Pparα and Rxrg. Reduced expression of Mapk12 was noted, and MetaCore analysis established its relationship with decreased efficiency of Pparα phosphorylation. In conclusion, in addition to cytokines/cytokine receptors, the early induction of Cox2 and NF-κB activation is involved in murine oral carcinogenesis.

Early induction of cytokines/cytokine receptors and Cox2, and activation of NF-κB in 4-nitroquinoline 1-oxide-induced murine oral cancer model

International Nuclear Information System (INIS)

Liu, Yu-Ching; Ho, Heng-Chien; Lee, Miau-Rong; Lai, Kuang-Chi; Yeh, Chung-Min; Lin, Yueh-Min; Ho, Tin-Yun; Hsiang, Chien-Yun; Chung, Jing-Gung

2012-01-01

The purpose of this study was to identify the genes induced early in murine oral carcinogenesis. Murine tongue tumors induced by the carcinogen, 4-nitroquinoline 1-oxide (4-NQO), and paired non-tumor tissues were subjected to microarray analysis. Hierarchical clustering of upregulated genes in the tumor tissues revealed an association of induced genes with inflammation. Cytokines/cytokine receptors induced early were subsequently identified, clearly indicating their involvement in oral carcinogenesis. Hierarchical clustering also showed that cytokine-mediated inflammation was possibly linked with Mapk6. Cox2 exhibited the greatest extent (9–18 fold) of induction in the microarray data, and its early induction was observed in a 2 h painting experiment by RT-PCR. MetaCore analysis showed that overexpressed Cox2 may interact with p53 and transcriptionally inhibit expression of several downstream genes. A painting experiment in transgenic mice also demonstrated that NF-κB activates early independently of Cox2 induction. MetaCore analysis revealed the most striking metabolic alterations in tumor tissues, especially in lipid metabolism resulting from the reduction of Pparα and Rxrg. Reduced expression of Mapk12 was noted, and MetaCore analysis established its relationship with decreased efficiency of Pparα phosphorylation. In conclusion, in addition to cytokines/cytokine receptors, the early induction of Cox2 and NF-κB activation is involved in murine oral carcinogenesis.

Econometric analysis of realized covariation: high frequency based covariance, regression, and correlation in financial economics

DEFF Research Database (Denmark)

Barndorff-Nielsen, Ole Eiler; Shephard, N.

2004-01-01

This paper analyses multivariate high frequency financial data using realized covariation. We provide a new asymptotic distribution theory for standard methods such as regression, correlation analysis, and covariance. It will be based on a fixed interval of time (e.g., a day or week), allowing...... the number of high frequency returns during this period to go to infinity. Our analysis allows us to study how high frequency correlations, regressions, and covariances change through time. In particular we provide confidence intervals for each of these quantities....

Health care: necessity or luxury good? A meta-regression analysis

OpenAIRE

Iordache, Ioana Raluca

2014-01-01

When estimating the influence income per capita exerts on health care expenditure, the research in the field offers mixed results. Studies employ different data, estimation techniques and models, which brings about the question whether these differences in research design play any part in explaining the heterogeneity of reported outcomes. By employing meta-regression analysis, the present paper analyzes 220 estimates of health spending income elasticity collected from 54 studies and finds tha...

Stromal COX-2 signaling activated by deoxycholic acid mediates proliferation and invasiveness of colorectal epithelial cancer cells

International Nuclear Information System (INIS)

Zhu, Yingting; Zhu, Min; Lance, Peter

2012-01-01

Highlights: ► Human colonic cancer associated fibroblasts are major sources of COX-2 and PGE 2 . ► The fibroblasts interact with human colonic epithelial cancer cells. ► Activation of COX-2 signaling in the fibroblasts affects behavior of the epithelia. ► Protein Kinase C controls the activation of COX-2 signaling. -- Abstract: COX-2 is a major regulator implicated in colonic cancer. However, how COX-2 signaling affects colonic carcinogenesis at cellular level is not clear. In this article, we investigated whether activation of COX-2 signaling by deoxycholic acid (DCA) in primary human normal and cancer associated fibroblasts play a significant role in regulation of proliferation and invasiveness of colonic epithelial cancer cells. Our results demonstrated while COX-2 signaling can be activated by DCA in both normal and cancer associated fibroblasts, the level of activation of COX-2 signaling is significantly greater in cancer associated fibroblasts than that in normal fibroblasts. In addition, we discovered that the proliferative and invasive potential of colonic epithelial cancer cells were much greater when the cells were co-cultured with cancer associated fibroblasts pre-treated with DCA than with normal fibroblasts pre-treated with DCA. Moreover, COX-2 siRNA attenuated the proliferative and invasive effect of both normal and cancer associate fibroblasts pre-treated with DCA on the colonic cancer cells. Further studies indicated that the activation of COX-2 signaling by DCA is through protein kinase C signaling. We speculate that activation of COX-2 signaling especially in cancer associated fibroblasts promotes progression of colonic cancer.

Distance Based Root Cause Analysis and Change Impact Analysis of Performance Regressions

Directory of Open Access Journals (Sweden)

Junzan Zhou

2015-01-01

Full Text Available Performance regression testing is applied to uncover both performance and functional problems of software releases. A performance problem revealed by performance testing can be high response time, low throughput, or even being out of service. Mature performance testing process helps systematically detect software performance problems. However, it is difficult to identify the root cause and evaluate the potential change impact. In this paper, we present an approach leveraging server side logs for identifying root causes of performance problems. Firstly, server side logs are used to recover call tree of each business transaction. We define a novel distance based metric computed from call trees for root cause analysis and apply inverted index from methods to business transactions for change impact analysis. Empirical studies show that our approach can effectively and efficiently help developers diagnose root cause of performance problems.

Sparse multivariate factor analysis regression models and its applications to integrative genomics analysis.

Science.gov (United States)

Zhou, Yan; Wang, Pei; Wang, Xianlong; Zhu, Ji; Song, Peter X-K

2017-01-01

The multivariate regression model is a useful tool to explore complex associations between two kinds of molecular markers, which enables the understanding of the biological pathways underlying disease etiology. For a set of correlated response variables, accounting for such dependency can increase statistical power. Motivated by integrative genomic data analyses, we propose a new methodology-sparse multivariate factor analysis regression model (smFARM), in which correlations of response variables are assumed to follow a factor analysis model with latent factors. This proposed method not only allows us to address the challenge that the number of association parameters is larger than the sample size, but also to adjust for unobserved genetic and/or nongenetic factors that potentially conceal the underlying response-predictor associations. The proposed smFARM is implemented by the EM algorithm and the blockwise coordinate descent algorithm. The proposed methodology is evaluated and compared to the existing methods through extensive simulation studies. Our results show that accounting for latent factors through the proposed smFARM can improve sensitivity of signal detection and accuracy of sparse association map estimation. We illustrate smFARM by two integrative genomics analysis examples, a breast cancer dataset, and an ovarian cancer dataset, to assess the relationship between DNA copy numbers and gene expression arrays to understand genetic regulatory patterns relevant to the disease. We identify two trans-hub regions: one in cytoband 17q12 whose amplification influences the RNA expression levels of important breast cancer genes, and the other in cytoband 9q21.32-33, which is associated with chemoresistance in ovarian cancer. © 2016 WILEY PERIODICALS, INC.

Niacin and biosynthesis of PGD2 by platelet COX-1 in mice and humans

Science.gov (United States)

Song, Wen-Liang; Stubbe, Jane; Ricciotti, Emanuela; Alamuddin, Naji; Ibrahim, Salam; Crichton, Irene; Prempeh, Maxwell; Lawson, John A.; Wilensky, Robert L.; Rasmussen, Lars Melholt; Puré, Ellen; FitzGerald, Garret A.

2012-01-01

The clinical use of niacin to treat dyslipidemic conditions is limited by noxious side effects, most commonly facial flushing. In mice, niacin-induced flushing results from COX-1–dependent formation of PGD2 and PGE2 followed by COX-2–dependent production of PGE2. Consistent with this, niacin-induced flushing in humans is attenuated when niacin is combined with an antagonist of the PGD2 receptor DP1. NSAID-mediated suppression of COX-2–derived PGI2 has negative cardiovascular consequences, yet little is known about the cardiovascular biology of PGD2. Here, we show that PGD2 biosynthesis is augmented during platelet activation in humans and, although vascular expression of DP1 is conserved between humans and mice, platelet DP1 is not present in mice. Despite this, DP1 deletion in mice augmented aneurysm formation and the hypertensive response to Ang II and accelerated atherogenesis and thrombogenesis. Furthermore, COX inhibitors in humans, as well as platelet depletion, COX-1 knockdown, and COX-2 deletion in mice, revealed that niacin evoked platelet COX-1–derived PGD2 biosynthesis. Finally, ADP-induced spreading on fibrinogen was augmented by niacin in washed human platelets, coincident with increased thromboxane (Tx) formation. However, in platelet-rich plasma, where formation of both Tx and PGD2 was increased, spreading was not as pronounced and was inhibited by DP1 activation. Thus, PGD2, like PGI2, may function as a homeostatic response to thrombogenic and hypertensive stimuli and may have particular relevance as a constraint on platelets during niacin therapy. PMID:22406532

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

Science.gov (United States)

Marill, Keith A

2004-01-01

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

[Specific inhibitors of cyclooxygenase-2 (COX-2): current knowledge and perspectives].

Science.gov (United States)

Rioda, W T; Nervetti, A

2001-01-01

The Authors summarize the current knowledge on a new class of nonsteroidal anti-inflammatory drugs (NSAIDs), the coxib (celecoxib and rofecoxib), in the treatment of rheumatic diseases. Celecoxib and rofecoxib are selective cyclooxygenase-2 (COX-2) inhibitors which possess the same anti-inflammatory and analgesic activities, but a better gastric tolerability compared to the non-selective COX-1 and COX-2 inhibitors. The Authors also report other possible therapeutic effects of these NSADIs as evidenced by the more recent data of the literature. Celecoxib seems to reduce the incidence of new polyps in patients with familial adenomatous polyposis. It has been suggested the use of celecoxib as a protective drug against the development of colorectal cancer. Other (neoplastic) or pre-neoplastic conditions, such as bladder dysplasia, Barret esophagus, attinic keratosis and Alzheimer's disease seem to have benefit from this class of drugs.

Optimal pricing in retail: a Cox regression approach

NARCIS (Netherlands)

Meijer, R.; Bhulai, S.

2013-01-01

Purpose: The purpose of this paper is to study the optimal pricing problem that retailers are challenged with when dealing with seasonal products. The friction between expected demand and realized demand creates a risk that supply during the season is not cleared, thus forcing the retailer to

No rationale for 1 variable per 10 events criterion for binary logistic regression analysis

Directory of Open Access Journals (Sweden)

Maarten van Smeden

2016-11-01

Full Text Available Abstract Background Ten events per variable (EPV is a widely advocated minimal criterion for sample size considerations in logistic regression analysis. Of three previous simulation studies that examined this minimal EPV criterion only one supports the use of a minimum of 10 EPV. In this paper, we examine the reasons for substantial differences between these extensive simulation studies. Methods The current study uses Monte Carlo simulations to evaluate small sample bias, coverage of confidence intervals and mean square error of logit coefficients. Logistic regression models fitted by maximum likelihood and a modified estimation procedure, known as Firth’s correction, are compared. Results The results show that besides EPV, the problems associated with low EPV depend on other factors such as the total sample size. It is also demonstrated that simulation results can be dominated by even a few simulated data sets for which the prediction of the outcome by the covariates is perfect (‘separation’. We reveal that different approaches for identifying and handling separation leads to substantially different simulation results. We further show that Firth’s correction can be used to improve the accuracy of regression coefficients and alleviate the problems associated with separation. Conclusions The current evidence supporting EPV rules for binary logistic regression is weak. Given our findings, there is an urgent need for new research to provide guidance for supporting sample size considerations for binary logistic regression analysis.

Sparse Regression by Projection and Sparse Discriminant Analysis

KAUST Repository

Qi, Xin; Luo, Ruiyan; Carroll, Raymond J.; Zhao, Hongyu

2015-01-01

predictions. We introduce a new framework, regression by projection, and its sparse version to analyze high-dimensional data. The unique nature of this framework is that the directions of the regression coefficients are inferred first, and the lengths

Stromal COX-2 signaling activated by deoxycholic acid mediates proliferation and invasiveness of colorectal epithelial cancer cells

Energy Technology Data Exchange (ETDEWEB)

Zhu, Yingting, E-mail: yitizhu@yahoo.com [Arizona Cancer Center, The University of Arizona, Tucson, AZ 85724 (United States); Tissue Tech Inc., Miami, FL 33173 (United States); Zhu, Min; Lance, Peter [Arizona Cancer Center, The University of Arizona, Tucson, AZ 85724 (United States)

2012-08-31

Highlights: Black-Right-Pointing-Pointer Human colonic cancer associated fibroblasts are major sources of COX-2 and PGE{sub 2}. Black-Right-Pointing-Pointer The fibroblasts interact with human colonic epithelial cancer cells. Black-Right-Pointing-Pointer Activation of COX-2 signaling in the fibroblasts affects behavior of the epithelia. Black-Right-Pointing-Pointer Protein Kinase C controls the activation of COX-2 signaling. -- Abstract: COX-2 is a major regulator implicated in colonic cancer. However, how COX-2 signaling affects colonic carcinogenesis at cellular level is not clear. In this article, we investigated whether activation of COX-2 signaling by deoxycholic acid (DCA) in primary human normal and cancer associated fibroblasts play a significant role in regulation of proliferation and invasiveness of colonic epithelial cancer cells. Our results demonstrated while COX-2 signaling can be activated by DCA in both normal and cancer associated fibroblasts, the level of activation of COX-2 signaling is significantly greater in cancer associated fibroblasts than that in normal fibroblasts. In addition, we discovered that the proliferative and invasive potential of colonic epithelial cancer cells were much greater when the cells were co-cultured with cancer associated fibroblasts pre-treated with DCA than with normal fibroblasts pre-treated with DCA. Moreover, COX-2 siRNA attenuated the proliferative and invasive effect of both normal and cancer associate fibroblasts pre-treated with DCA on the colonic cancer cells. Further studies indicated that the activation of COX-2 signaling by DCA is through protein kinase C signaling. We speculate that activation of COX-2 signaling especially in cancer associated fibroblasts promotes progression of colonic cancer.

COX-2 Inhibitors for Cancer Treatment in Dogs

Directory of Open Access Journals (Sweden)

Andrigo Barboza De Nardi*, Talita Mariana Morata Raposo1, Rafael Ricardo Huppes1, Carlos Roberto Daleck2 and Renée Laufer Amorim3

2011-10-01

Full Text Available Cancer is one of the main causes of death in canines and felines, and this fact is probably related to the increase in the longevity of these species. The longer the animals live, the higher the exposure to carcinogenic agents will be. With the high incidence of cancer in companion animals, new studies are currently being performed with the aim of finding therapeutic options which make the complete inhibition of the development of neoplasms in animals possible in the future. The correlation of cyclooxygenase-2 (COX-2 whith the development of cancer opens the way for the use of new therapeutic approaches. This relationship has been suggested based on various studies which established an association between the chronic use of nonsteroidal anti-inflammatory drugs (NSAID and a decrease in the incidence of colon carcinoma. As cancer progresses, COX-2 participates in the arachidonic acid metabolism by synthesizing prostaglandins which can mediate various mechanisms related to cancer development such as: increase in angiogenesis, inhibition of apoptosis, suppression of the immune response, acquisition of greater invasion capacity and metastasis. Accordingly, overexpression of this enzyme in tumors has been associated with the most aggressive, poor-prognosis cancer types, especially carcinomas. Therefore, treatments which use COX-2 inhibitors such as coxibs, whether administered as single agents or in combination with conventional antineoplastic chemotherapy, are an alternative for extending the survival of our cancer patients.

Analysis models for variables associated with breastfeeding duration

Directory of Open Access Journals (Sweden)

Edson Theodoro dos S. Neto

2013-09-01

Full Text Available OBJECTIVE To analyze the factors associated with breastfeeding duration by two statistical models. METHODS A population-based cohort study was conducted with 86 mothers and newborns from two areas primary covered by the National Health System, with high rates of infant mortality in Vitória, Espírito Santo, Brazil. During 30 months, 67 (78% children and mothers were visited seven times at home by trained interviewers, who filled out survey forms. Data on food and sucking habits, socioeconomic and maternal characteristics were collected. Variables were analyzed by Cox regression models, considering duration of breastfeeding as the dependent variable, and logistic regression (dependent variables, was the presence of a breastfeeding child in different post-natal ages. RESULTS In the logistic regression model, the pacifier sucking (adjusted Odds Ratio: 3.4; 95%CI 1.2-9.55 and bottle feeding (adjusted Odds Ratio: 4.4; 95%CI 1.6-12.1 increased the chance of weaning a child before one year of age. Variables associated to breastfeeding duration in the Cox regression model were: pacifier sucking (adjusted Hazard Ratio 2.0; 95%CI 1.2-3.3 and bottle feeding (adjusted Hazard Ratio 2.0; 95%CI 1.2-3.5. However, protective factors (maternal age and family income differed between both models. CONCLUSIONS Risk and protective factors associated with cessation of breastfeeding may be analyzed by different models of statistical regression. Cox Regression Models are adequate to analyze such factors in longitudinal studies.

Statistical methods and regression analysis of stratospheric ozone and meteorological variables in Isfahan

Science.gov (United States)

Hassanzadeh, S.; Hosseinibalam, F.; Omidvari, M.

2008-04-01

Data of seven meteorological variables (relative humidity, wet temperature, dry temperature, maximum temperature, minimum temperature, ground temperature and sun radiation time) and ozone values have been used for statistical analysis. Meteorological variables and ozone values were analyzed using both multiple linear regression and principal component methods. Data for the period 1999-2004 are analyzed jointly using both methods. For all periods, temperature dependent variables were highly correlated, but were all negatively correlated with relative humidity. Multiple regression analysis was used to fit the meteorological variables using the meteorological variables as predictors. A variable selection method based on high loading of varimax rotated principal components was used to obtain subsets of the predictor variables to be included in the linear regression model of the meteorological variables. In 1999, 2001 and 2002 one of the meteorological variables was weakly influenced predominantly by the ozone concentrations. However, the model did not predict that the meteorological variables for the year 2000 were not influenced predominantly by the ozone concentrations that point to variation in sun radiation. This could be due to other factors that were not explicitly considered in this study.

A Box-Cox normal model for response times.

Science.gov (United States)

Klein Entink, R H; van der Linden, W J; Fox, J-P

2009-11-01

The log-transform has been a convenient choice in response time modelling on test items. However, motivated by a dataset of the Medical College Admission Test where the lognormal model violated the normality assumption, the possibilities of the broader class of Box-Cox transformations for response time modelling are investigated. After an introduction and an outline of a broader framework for analysing responses and response times simultaneously, the performance of a Box-Cox normal model for describing response times is investigated using simulation studies and a real data example. A transformation-invariant implementation of the deviance information criterium (DIC) is developed that allows for comparing model fit between models with different transformation parameters. Showing an enhanced description of the shape of the response time distributions, its application in an educational measurement context is discussed at length.

A new approach to the Box-Cox transformation

Directory of Open Access Journals (Sweden)

Jorge Iván eVélez

2015-10-01

Full Text Available We propose a new methodology to estimate λ, the parameter of the Box-Cox transformation, as well as an alternative method to determine plausible values for it. The former is accomplished by defining a grid of values for λ and further perform a normality test on the λ -transformed data. The optimum value of λ, say λ * , is such that the p-value from the normality test is the highest. The set of plausible values is determined using the inverse probability method after plotting the p-values against the values of λ on the grid. Our methodology is illustrated with two real-world data sets. Furthermore, a simulation study suggests that our method improves the symmetry, kurtosis and, hence, the normality of data, making it a feasible alternative to the traditional Box-Cox transformation.

Multivariate regression analysis for determining short-term values of radon and its decay products from filter measurements

International Nuclear Information System (INIS)

Kraut, W.; Schwarz, W.; Wilhelm, A.

1994-01-01

A multivariate regression analysis is applied to decay measurements of α-resp. β-filter activcity. Activity concentrations for Po-218, Pb-214 and Bi-214, resp. for the Rn-222 equilibrium equivalent concentration are obtained explicitly. The regression analysis takes into account properly the variances of the measured count rates and their influence on the resulting activity concentrations. (orig.) [de

COX-2 and PPARγ expression are potential markers of recurrence risk in mammary duct carcinoma in-situ

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Wiley Elizabeth L

2008-01-01

Full Text Available Abstract Background In women with duct carcinoma in-situ (DCIS receiving breast conservation therapy (BCT, in-breast recurrences are seen in approximately 10%, but cannot be accurately predicted using clinical and histological criteria. We performed a case-control study to identify protein markers of local recurrence risk in DCIS. Methods Women treated for DCIS with BCT, who later developed in-breast recurrence (cases were matched by age and year of treatment to women who remained free of recurrence (controls. Results A total of 69 women were included in the study, 31 cases and 38 controls. Immunohistochemical evaluation of DCIS tissue arrays was performed for estrogen receptor, progesterone receptor, HER-2/neu, cyclin D1, p53, p21, cycloxygenase-2 (COX-2 and peroxisome proliferator activated receptor γ (PPARγ. Two markers were significantly different between cases and controls on univariate analysis: strong COX-2 expression was associated with increased risk of recurrence, with 67% vs. 24% positivity in cases and controls p = 0.006; and nuclear expression of PPARγ was associated with protection from recurrence with 4% vs. 27% positivity in cases and controls, p = 0.024. In a multivariate model which included size, grade, COX-2 and PPARγ positivity, we found COX-2 positivity to be a strong independent risk factor for recurrence (OR 7.90, 95% CI 1.72–36.23., whereas size and grade were of borderline significance. PPARγ expression continued to demonstrate a protective trend, (OR 0.14, 95% CI 0.06–1.84. Conclusion Our findings suggest that COX-2 and PPARγ should be investigated further as biologic markers to predict DCIS recurrence, particularly since they are also potential therapeutic targets.

An Econometric Analysis of Modulated Realised Covariance, Regression and Correlation in Noisy Diffusion Models

DEFF Research Database (Denmark)

Kinnebrock, Silja; Podolskij, Mark

This paper introduces a new estimator to measure the ex-post covariation between high-frequency financial time series under market microstructure noise. We provide an asymptotic limit theory (including feasible central limit theorems) for standard methods such as regression, correlation analysis...... process can be relaxed and how our method can be applied to non-synchronous observations. We also present an empirical study of how high-frequency correlations, regressions and covariances change through time....

A menu-driven software package of Bayesian nonparametric (and parametric) mixed models for regression analysis and density estimation.

Science.gov (United States)

Karabatsos, George

2017-02-01

Most of applied statistics involves regression analysis of data. In practice, it is important to specify a regression model that has minimal assumptions which are not violated by data, to ensure that statistical inferences from the model are informative and not misleading. This paper presents a stand-alone and menu-driven software package, Bayesian Regression: Nonparametric and Parametric Models, constructed from MATLAB Compiler. Currently, this package gives the user a choice from 83 Bayesian models for data analysis. They include 47 Bayesian nonparametric (BNP) infinite-mixture regression models; 5 BNP infinite-mixture models for density estimation; and 31 normal random effects models (HLMs), including normal linear models. Each of the 78 regression models handles either a continuous, binary, or ordinal dependent variable, and can handle multi-level (grouped) data. All 83 Bayesian models can handle the analysis of weighted observations (e.g., for meta-analysis), and the analysis of left-censored, right-censored, and/or interval-censored data. Each BNP infinite-mixture model has a mixture distribution assigned one of various BNP prior distributions, including priors defined by either the Dirichlet process, Pitman-Yor process (including the normalized stable process), beta (two-parameter) process, normalized inverse-Gaussian process, geometric weights prior, dependent Dirichlet process, or the dependent infinite-probits prior. The software user can mouse-click to select a Bayesian model and perform data analysis via Markov chain Monte Carlo (MCMC) sampling. After the sampling completes, the software automatically opens text output that reports MCMC-based estimates of the model's posterior distribution and model predictive fit to the data. Additional text and/or graphical output can be generated by mouse-clicking other menu options. This includes output of MCMC convergence analyses, and estimates of the model's posterior predictive distribution, for selected

Intravenous glutamine enhances COX-2 activity giving cardioprotection.

LENUS (Irish Health Repository)

McGuinness, Jonathan

2009-03-01

Preconditioning, a highly evolutionary conserved endogenous protective response, provides the most powerful form of anti-infarct protection known. We investigated whether acute intravenous glutamine, through an effect on cyclooxygenase (COX)-2 and heat shock protein (HSP) 72, might induce preconditioning.

Regression analysis of mixed recurrent-event and panel-count data.

Science.gov (United States)

Zhu, Liang; Tong, Xinwei; Sun, Jianguo; Chen, Manhua; Srivastava, Deo Kumar; Leisenring, Wendy; Robison, Leslie L

2014-07-01

In event history studies concerning recurrent events, two types of data have been extensively discussed. One is recurrent-event data (Cook and Lawless, 2007. The Analysis of Recurrent Event Data. New York: Springer), and the other is panel-count data (Zhao and others, 2010. Nonparametric inference based on panel-count data. Test 20: , 1-42). In the former case, all study subjects are monitored continuously; thus, complete information is available for the underlying recurrent-event processes of interest. In the latter case, study subjects are monitored periodically; thus, only incomplete information is available for the processes of interest. In reality, however, a third type of data could occur in which some study subjects are monitored continuously, but others are monitored periodically. When this occurs, we have mixed recurrent-event and panel-count data. This paper discusses regression analysis of such mixed data and presents two estimation procedures for the problem. One is a maximum likelihood estimation procedure, and the other is an estimating equation procedure. The asymptotic properties of both resulting estimators of regression parameters are established. Also, the methods are applied to a set of mixed recurrent-event and panel-count data that arose from a Childhood Cancer Survivor Study and motivated this investigation. © The Author 2014. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

[Application of negative binomial regression and modified Poisson regression in the research of risk factors for injury frequency].

Science.gov (United States)

Cao, Qingqing; Wu, Zhenqiang; Sun, Ying; Wang, Tiezhu; Han, Tengwei; Gu, Chaomei; Sun, Yehuan

2011-11-01

To Eexplore the application of negative binomial regression and modified Poisson regression analysis in analyzing the influential factors for injury frequency and the risk factors leading to the increase of injury frequency. 2917 primary and secondary school students were selected from Hefei by cluster random sampling method and surveyed by questionnaire. The data on the count event-based injuries used to fitted modified Poisson regression and negative binomial regression model. The risk factors incurring the increase of unintentional injury frequency for juvenile students was explored, so as to probe the efficiency of these two models in studying the influential factors for injury frequency. The Poisson model existed over-dispersion (P Poisson regression and negative binomial regression model, was fitted better. respectively. Both showed that male gender, younger age, father working outside of the hometown, the level of the guardian being above junior high school and smoking might be the results of higher injury frequencies. On a tendency of clustered frequency data on injury event, both the modified Poisson regression analysis and negative binomial regression analysis can be used. However, based on our data, the modified Poisson regression fitted better and this model could give a more accurate interpretation of relevant factors affecting the frequency of injury.

Direct-to-consumer advertising of COX-2 inhibitors: effect on appropriateness of prescribing.

Science.gov (United States)

Spence, Michele M; Teleki, Stephanie S; Cheetham, T Craig; Schweitzer, Stuart O; Millares, Mirta

2005-10-01

Spending on direct-to-consumer advertising (DTCA) of prescription drugs has increased dramatically in the past several years. An unresolved question is whether such advertising leads to inappropriate prescribing. In this study, the authors use survey and administrative data to determine the association of DTCA with the appropriate prescribing of cyclooxygenase-2 (COX-2) inhibitors for 1,382 patients. Treatment with either a COX-2 or a traditional nonsteroidal anti-inflammatory drug (NSAID) was defined as appropriate or not according to three different definitions of gastrointestinal risk. Patients who saw or heard a COX-2 advertisement and asked their physician about the advertised drug were significantly more likely to be prescribed a COX-2 (versus a NSAID, as recommended by evidence-based guidelines) than all other patients. Findings also suggest that some patients may benefit from DTCA. The authors discuss the need for balanced drug information for consumers, increased physician vigilance in prescribing appropriately, and further study of DTCA.

Forecasting Model for IPTV Service in Korea Using Bootstrap Ridge Regression Analysis

Science.gov (United States)

Lee, Byoung Chul; Kee, Seho; Kim, Jae Bum; Kim, Yun Bae

The telecom firms in Korea are taking new step to prepare for the next generation of convergence services, IPTV. In this paper we described our analysis on the effective method for demand forecasting about IPTV broadcasting. We have tried according to 3 types of scenarios based on some aspects of IPTV potential market and made a comparison among the results. The forecasting method used in this paper is the multi generation substitution model with bootstrap ridge regression analysis.

Marital status integration and suicide: A meta-analysis and meta-regression.

Science.gov (United States)

Kyung-Sook, Woo; SangSoo, Shin; Sangjin, Shin; Young-Jeon, Shin

2018-01-01

Marital status is an index of the phenomenon of social integration within social structures and has long been identified as an important predictor suicide. However, previous meta-analyses have focused only on a particular marital status, or not sufficiently explored moderators. A meta-analysis of observational studies was conducted to explore the relationships between marital status and suicide and to understand the important moderating factors in this association. Electronic databases were searched to identify studies conducted between January 1, 2000 and June 30, 2016. We performed a meta-analysis, subgroup analysis, and meta-regression of 170 suicide risk estimates from 36 publications. Using random effects model with adjustment for covariates, the study found that the suicide risk for non-married versus married was OR = 1.92 (95% CI: 1.75-2.12). The suicide risk was higher for non-married individuals aged analysis by gender, non-married men exhibited a greater risk of suicide than their married counterparts in all sub-analyses, but women aged 65 years or older showed no significant association between marital status and suicide. The suicide risk in divorced individuals was higher than for non-married individuals in both men and women. The meta-regression showed that gender, age, and sample size affected between-study variation. The results of the study indicated that non-married individuals have an aggregate higher suicide risk than married ones. In addition, gender and age were confirmed as important moderating factors in the relationship between marital status and suicide. Copyright © 2017 Elsevier Ltd. All rights reserved.

Driven Factors Analysis of China’s Irrigation Water Use Efficiency by Stepwise Regression and Principal Component Analysis

Directory of Open Access Journals (Sweden)

Renfu Jia

2016-01-01

Full Text Available This paper introduces an integrated approach to find out the major factors influencing efficiency of irrigation water use in China. It combines multiple stepwise regression (MSR and principal component analysis (PCA to obtain more realistic results. In real world case studies, classical linear regression model often involves too many explanatory variables and the linear correlation issue among variables cannot be eliminated. Linearly correlated variables will cause the invalidity of the factor analysis results. To overcome this issue and reduce the number of the variables, PCA technique has been used combining with MSR. As such, the irrigation water use status in China was analyzed to find out the five major factors that have significant impacts on irrigation water use efficiency. To illustrate the performance of the proposed approach, the calculation based on real data was conducted and the results were shown in this paper.

A regression analysis of the effect of energy use in agriculture

International Nuclear Information System (INIS)

Karkacier, Osman; Gokalp Goktolga, Z.; Cicek, Adnan

2006-01-01

This study investigates the impacts of energy use on productivity of Turkey's agriculture. It reports the results of a regression analysis of the relationship between energy use and agricultural productivity. The study is based on the analysis of the yearbook data for the period 1971-2003. Agricultural productivity was specified as a function of its energy consumption (TOE) and gross additions of fixed assets during the year. Least square (LS) was employed to estimate equation parameters. The data of this study comes from the State Institute of Statistics (SIS) and The Ministry of Energy of Turkey

Histamine, carbachol, and serotonin induce hyperresponsiveness to ATP in guinea pig tracheas: involvement of COX-2 pathway.

Science.gov (United States)

Montaño, Luis M; Carbajal, Verónica; Vargas, Mario H; García-Hernández, Luz M; Díaz-Hernández, Verónica; Checa, Marco; Barajas-López, Carlos

2013-08-01

Extracellular ATP promotes an indirect contraction of airway smooth muscle via the secondary release of thromboxane A2 (TXA2) from airway epithelium. Our aim was to evaluate if common contractile agonists modify this response to ATP. Tracheas from sensitized guinea pigs were used to evaluate ATP-induced contractions before and after a transient contraction produced by histamine, carbachol, or serotonin. Epithelial mRNA for COX-1 and COX-2 was measured by RT-PCR and their expression assessed by immunohistochemistry. Compared with the initial response, ATP-induced contraction was potentiated by pretreatment with histamine, carbachol, or serotonin. Either suramin (antagonist of P2X and P2Y receptors) plus RB2 (antagonist of P2Y receptors) or indomethacin (inhibitor of COX-1 and COX-2) annulled the ATP-induced contraction, suggesting that it was mediated by P2Y receptor stimulation and TXA2 production. When COX-2 was inhibited by SC-58125 or thromboxane receptors were antagonized by SQ-29548, just the potentiation was abolished, leaving the basal response intact. Airway epithelial cells showed increased COX-2 mRNA after stimulation with histamine or carbachol, but not serotonin, while COX-1 mRNA was unaffected. Immunochemistry corroborated this upregulation of COX-2. In conclusion, we showed for the first time that histamine and carbachol cause hyperresponsiveness to ATP by upregulating COX-2 in airway epithelium, which likely increases TXA2 production. Serotonin-mediated hyperresponsiveness seems to be independent of COX-2 upregulation, but nonetheless is TXA2 dependent. Because acetylcholine, histamine, and serotonin can be present during asthmatic exacerbations, their potential interactions with ATP might be relevant in its pathophysiology.

Selection of the optimal Box-Cox transformation parameter for modelling and forecasting age-specific fertility

OpenAIRE

Shang, Han Lin

2015-01-01

The Box-Cox transformation can sometimes yield noticeable improvements in model simplicity, variance homogeneity and precision of estimation, such as in modelling and forecasting age-specific fertility. Despite its importance, there have been few studies focusing on the optimal selection of Box-Cox transformation parameters in demographic forecasting. A simple method is proposed for selecting the optimal Box-Cox transformation parameter, along with an algorithm based on an in-sample forecast ...

Integrated proteomics identified novel activation of dynein IC2-GR-COX-1 signaling in neurofibromatosis type I (NF1) disease model cells.

Science.gov (United States)

Hirayama, Mio; Kobayashi, Daiki; Mizuguchi, Souhei; Morikawa, Takashi; Nagayama, Megumi; Midorikawa, Uichi; Wilson, Masayo M; Nambu, Akiko N; Yoshizawa, Akiyasu C; Kawano, Shin; Araki, Norie

2013-05-01

Neurofibromatosis type 1 (NF1) tumor suppressor gene product, neurofibromin, functions in part as a Ras-GAP, and though its loss is implicated in the neuronal abnormality of NF1 patients, its precise cellular function remains unclear. To study the molecular mechanism of NF1 pathogenesis, we prepared NF1 gene knockdown (KD) PC12 cells, as a NF1 disease model, and analyzed their molecular (gene and protein) expression profiles with a unique integrated proteomics approach, comprising iTRAQ, 2D-DIGE, and DNA microarrays, using an integrated protein and gene expression analysis chart (iPEACH). In NF1-KD PC12 cells showing abnormal neuronal differentiation after NGF treatment, of 3198 molecules quantitatively identified and listed in iPEACH, 97 molecules continuously up- or down-regulated over time were extracted. Pathway and network analysis further revealed overrepresentation of calcium signaling and transcriptional regulation by glucocorticoid receptor (GR) in the up-regulated protein set, whereas nerve system development was overrepresented in the down-regulated protein set. The novel up-regulated network we discovered, "dynein IC2-GR-COX-1 signaling," was then examined in NF1-KD cells. Validation studies confirmed that NF1 knockdown induces altered splicing and phosphorylation patterns of dynein IC2 isomers, up-regulation and accumulation of nuclear GR, and increased COX-1 expression in NGF-treated cells. Moreover, the neurite retraction phenotype observed in NF1-KD cells was significantly recovered by knockdown of the dynein IC2-C isoform and COX-1. In addition, dynein IC2 siRNA significantly inhibited nuclear translocation and accumulation of GR and up-regulation of COX-1 expression. These results suggest that dynein IC2 up-regulates GR nuclear translocation and accumulation, and subsequently causes increased COX-1 expression, in this NF1 disease model. Our integrated proteomics strategy, which combines multiple approaches, demonstrates that NF1-related neural

Prediction of hearing outcomes by multiple regression analysis in patients with idiopathic sudden sensorineural hearing loss.

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Suzuki, Hideaki; Tabata, Takahisa; Koizumi, Hiroki; Hohchi, Nobusuke; Takeuchi, Shoko; Kitamura, Takuro; Fujino, Yoshihisa; Ohbuchi, Toyoaki

2014-12-01

This study aimed to create a multiple regression model for predicting hearing outcomes of idiopathic sudden sensorineural hearing loss (ISSNHL). The participants were 205 consecutive patients (205 ears) with ISSNHL (hearing level ≥ 40 dB, interval between onset and treatment ≤ 30 days). They received systemic steroid administration combined with intratympanic steroid injection. Data were examined by simple and multiple regression analyses. Three hearing indices (percentage hearing improvement, hearing gain, and posttreatment hearing level [HLpost]) and 7 prognostic factors (age, days from onset to treatment, initial hearing level, initial hearing level at low frequencies, initial hearing level at high frequencies, presence of vertigo, and contralateral hearing level) were included in the multiple regression analysis as dependent and explanatory variables, respectively. In the simple regression analysis, the percentage hearing improvement, hearing gain, and HLpost showed significant correlation with 2, 5, and 6 of the 7 prognostic factors, respectively. The multiple correlation coefficients were 0.396, 0.503, and 0.714 for the percentage hearing improvement, hearing gain, and HLpost, respectively. Predicted values of HLpost calculated by the multiple regression equation were reliable with 70% probability with a 40-dB-width prediction interval. Prediction of HLpost by the multiple regression model may be useful to estimate the hearing prognosis of ISSNHL. © The Author(s) 2014.