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Simulations were performed in which we compared bias and variability in parameter estimates between the Cox model and Rizopoulos \(2010\) joint model, concluding that the Cox model is heavily biased when the data is generated according to a joint model. Furthermore, we analysed medical data which recorded the onset time of bipolar/major mood disorder \(in years since birth\) for subjects who were considered at risk. The Cox model and both joint models agreed that a time-varying covariate, the Hamilton anxiety score, had a significant effect \(at a 5% level\) on the risk of bipolar/major mood disorder.</desc---><title--->Comparison of Cox Regression and Discrete Time Survival Models</title---><desc--->A standard analysis of prostate cancer biochemical failure data is done by conducting two approaches in which risk factors or covariates are measured. Cox regression and discrete-time survival models were compared under different attributes: sample size, time periods, and parameters in the model. The person-period data was reconstructed when examining the same data in discrete-time survival model. Twenty-four numerical examples covering a variety of sample sizes, time periods, and number of parameters displayed the closeness of Cox regression and discrete-time survival methods in situations typical of the cancer study.</desc---><title--->A Comparison of Bayesian and Frequentist Inference for Cox Regression Modles with Random Effects</title---><title--->Survival Analysis</title---><title--->A Self-Learning Text</title--->,CRC Press) /Subject (A Comparison Of Cox And Logistic Regression For Use In published by : Springer World Scientific Stata Press Routledge Cambridge University Press Springer Science & Business Media <title--->Comparison of Cox's and Gray's Models in Survival Analysis</title---><title--->Application of Multiple Regression to Survival Data</title---><title--->A Comparison with Cox Regression</title---><title--->A Comparison of Two Survival Models</title---><title--->Cox Proportional Hazards and Frailty</title---><title--->A Comparison of Cox and Joint Models for Time-to-Event Data</title---><desc--->The Cox model has traditionally been used to analyse the relationship between a set of covariates and a time-to-event outcome. However, it has been found to lead to biased estimates when fitting time-varying covariates subject to measurement error. Joint modelling procedures have thus been developed with the purpose of alleviating this problem. Simulations were performed in which we compared bias and variability in parameter estimates between the Cox model and Rizopoulos \(2010\) joint model, concluding that the Cox model is heavily biased when the data is generated according to a joint model. Furthermore, we analysed medical data which recorded the onset time of bipolar/major mood disorder \(in years since birth\) for subjects who were considered at risk. The Cox model and both joint models agreed that a time-varying covariate, the Hamilton anxiety score, had a significant effect \(at a 5% level\) on the risk of bipolar/major mood disorder.</desc---><title--->Comparison of Cox Regression and Discrete Time Survival Models</title---><desc--->A standard analysis of prostate cancer biochemical failure data is done by conducting two approaches in which risk factors or covariates are measured. Cox regression and discrete-time survival models were compared under different attributes: sample size, time periods, and parameters in the model. The person-period data was reconstructed when examining the same data in discrete-time survival model. Twenty-four numerical examples covering a variety of sample sizes, time periods, and number of parameters displayed the closeness of Cox regression and discrete-time survival methods in situations typical of the cancer study.</desc---><title--->A Comparison of Bayesian and Frequentist Inference for Cox Regression Modles with Random Effects</title---><title--->Survival Analysis</title---><title--->A Self-Learning Text</title---> CRC Press) /Keywords (,Comparison of Cox's and Gray's Models in Survival Analysis,Application of Multiple Regression to Survival Data,A Comparison with Cox Regression,A Comparison of Two Survival Models,Cox Proportional Hazards and Frailty,A Comparison of Cox and Joint Models for Time-to-Event Data,Comparison of Cox Regression and Discrete Time Survival Models,A Comparison of Bayesian and Frequentist Inference for Cox Regression Modles with Random Effects,Survival Analysis,A Self-Learning Text,Comparison Between Weibull and Cox Proportional Hazards Models,Comparison of a Traditional and a Multilevel Cox Proportional Hazards Model,Predicting Bank Failures,A Comparison of the Cox Proportional Hazards Model and the Time-varying Covariates Model,Modeling Survival Data: Extending the Cox Model,A Comparison of Statistical Tests for Assessing the Proportional Hazards Assumption for the Cox Model,A Comparison of Smoothing Techniques for a Covariate Measured with Error in a Time-dependent Cox Proportional Hazards Model,A Comparison of Test Statistics for Proportionality of the Hazards in the Cox Regression Model,A Comparison of Test Statistics for Assessing the Proportional Hazards Assumption of Cox's Model,Analytical Comparison of Contrasting Approaches to Estimating Competing Risks Models,Regression Modeling Strategies,With Applications to Linear Models, Logistic Regression, and Survival Analysis,Comparison of Variance Estimates for Parameter Estimators in Cox Regression,Carbon-Ion Radiotherapy,Principles, Practices, and Treatment Planning,A Comparison of the Generalized Box-Cox and Fourier Functional Forms,An Application to the North Carolina Residential Time-of-use Electricity Pricing Experiment,A Comparison of Particle Size Models Using the Method of D.R. Cox,Comparison of V-fold Data Splitting with the Jackknife \(leave-one-out\) Procedure for the Cross Validated Likelihood Function in the Cox Proportional Hazards Model,A Comparison of the Specific Deterrent Effects of Official Sanctions Across Drug and Non-drug Cohorts of Offenders in New York City Between 1983 and 1988, Using a Cox Proportional Hazards Survival Model,Multiple Event Analysis of Injuries Using Adaptations to the Cox Proportional Hazards Model,Report for ...,Bayesian Survival Analysis,Modelling Survival Data in Medical Research, Second Edition,Applied Statistics - Principles and Examples,A Comparison of Accurate Malnutrition Diagnoses by the Cox Medical System Before and After Physician Education,Comparison of Time-dependent Sequential Logit and Cox Proportional Hazards Models for Hurricane Evacuation with a Focus on the Use of Evolving Forecast Information,Report,A Comparison of Categorical Models for Right-censored Data,Survival Analysis Using S,Analysis of Time-to-Event Data,A Comparison of the Box-Cox Maximum Likelihood Estimator and the Nonlinear Two-stage Least Squares Estimator,Artificial Intelligence in Medicine,17th Conference on Artificial Intelligence in Medicine, AIME 2019, Poznan, Poland, June 26 29, 2019, Proceedings,An Introduction to Survival Analysis Using Stata, Second Edition,Advanced Mathematical & Computational Tools in Metrology VII,Goodness-of-Fit Tests and Model Validity,Principles of Statistical Inference,MODELLING DEFAULT AMONG MALAYSIAN CONSUMER LOANS,COMPARISON BETWEEN LOGISTIC REGRESSION AND COX PROPORTIONAL HAZARD REGRESSION) /Creator (Acrobat Elements 9.0.0 \(Windows\)) /Producer (FrameMaker 10.0.2|x|Acrobat Distiller 10.0.0 \(Windows\)) /CreationDate (D:20211205213248+00'00') /ModDate (D:20211205213248+00'00') /Trapped /False >>
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A Comparison Of Cox And Logistic Regression For Use In Epdf Read
Springer,World Scientific,Stata Press,Routledge,Cambridge University Press,Springer Science & Business Media,<title--->Comparison of Cox's and Gray's Models in Survival Analysis</title---><title--->Application of Multiple Regression to Survival Data</title---><title--->A Comparison with Cox Regression</title---><title--->A Comparison of Two Survival Models</title---><title--->Cox Proportional Hazards and Frailty</title---><title--->A Comparison of Cox and Joint Models for Time-to-Event Data</title---><desc--->The Cox model has traditionally been used to analyse the relationship between a set of covariates and a time-to-event outcome. However, it has been found to lead to biased estimates when fitting time-varying covariates subject to measurement error. Joint modelling procedures have thus been developed with the purpose of alleviating this problem. Simulations were performed in which we compared bias and variability in parameter estimates between the Cox model and Rizopoulos (2010) joint model, concluding that the Cox model is heavily biased when the data is generated according to a joint model. Furthermore, we analysed medical data which recorded the onset time of bipolar/major mood disorder (in years since birth) for subjects who were considered at risk. The Cox model and both joint models agreed that a time-varying covariate, the Hamilton anxiety score, had a significant effect (at a 5% level) on the risk of bipolar/major mood disorder.</desc---><title--->Comparison of Cox Regression and Discrete Time Survival Models</title---><desc--->A standard analysis of prostate cancer biochemical failure data is done by conducting two approaches in which risk factors or covariates are measured. Cox regression and discrete-time survival models were compared under different attributes: sample size, time periods, and parameters in the model. The person-period data was reconstructed when examining the same data in discrete-time survival model. Twenty-four numerical examples covering a variety of sample sizes, time periods, and number of parameters displayed the closeness of Cox regression and discrete-time survival methods in situations typical of the cancer study.</desc---><title--->A Comparison of Bayesian and Frequentist Inference for Cox Regression Modles with Random Effects</title---><title--->Survival Analysis</title---><title--->A Self-Learning Text</title--->,CRC Press
A Comparison Of Cox And Logistic Regression For Use In published by : Springer World Scientific Stata Press Routledge Cambridge University Press Springer Science & Business Media <title--->Comparison of Cox's and Gray's Models in Survival Analysis</title---><title--->Application of Multiple Regression to Survival Data</title---><title--->A Comparison with Cox Regression</title---><title--->A Comparison of Two Survival Models</title---><title--->Cox Proportional Hazards and Frailty</title---><title--->A Comparison of Cox and Joint Models for Time-to-Event Data</title---><desc--->The Cox model has traditionally been used to analyse the relationship between a set of covariates and a time-to-event outcome. However, it has been found to lead to biased estimates when fitting time-varying covariates subject to measurement error. Joint modelling procedures have thus been developed with the purpose of alleviating this problem. Simulations were performed in which we compared bias and variability in parameter estimates between the Cox model and Rizopoulos (2010) joint model, concluding that the Cox model is heavily biased when the data is generated according to a joint model. Furthermore, we analysed medical data which recorded the onset time of bipolar/major mood disorder (in years since birth) for subjects who were considered at risk. The Cox model and both joint models agreed that a time-varying covariate, the Hamilton anxiety score, had a significant effect (at a 5% level) on the risk of bipolar/major mood disorder.</desc---><title--->Comparison of Cox Regression and Discrete Time Survival Models</title---><desc--->A standard analysis of prostate cancer biochemical failure data is done by conducting two approaches in which risk factors or covariates are measured. Cox regression and discrete-time survival models were compared under different attributes: sample size, time periods, and parameters in the model. The person-period data was reconstructed when examining the same data in discrete-time survival model. Twenty-four numerical examples covering a variety of sample sizes, time periods, and number of parameters displayed the closeness of Cox regression and discrete-time survival methods in situations typical of the cancer study.</desc---><title--->A Comparison of Bayesian and Frequentist Inference for Cox Regression Modles with Random Effects</title---><title--->Survival Analysis</title---><title--->A Self-Learning Text</title---> CRC Press
,Comparison of Cox's and Gray's Models in Survival Analysis,Application of Multiple Regression to Survival Data,A Comparison with Cox Regression,A Comparison of Two Survival Models,Cox Proportional Hazards and Frailty,A Comparison of Cox and Joint Models for Time-to-Event Data,Comparison of Cox Regression and Discrete Time Survival Models,A Comparison of Bayesian and Frequentist Inference for Cox Regression Modles with Random Effects,Survival Analysis,A Self-Learning Text,Comparison Between Weibull and Cox Proportional Hazards Models,Comparison of a Traditional and a Multilevel Cox Proportional Hazards Model,Predicting Bank Failures,A Comparison of the Cox Proportional Hazards Model and the Time-varying Covariates Model,Modeling Survival Data: Extending the Cox Model,A Comparison of Statistical Tests for Assessing the Proportional Hazards Assumption for the Cox Model,A Comparison of Smoothing Techniques for a Covariate Measured with Error in a Time-dependent Cox Proportional Hazards Model,A Comparison of Test Statistics for Proportionality of the Hazards in the Cox Regression Model,A Comparison of Test Statistics for Assessing the Proportional Hazards Assumption of Cox's Model,Analytical Comparison of Contrasting Approaches to Estimating Competing Risks Models,Regression Modeling Strategies,With Applications to Linear Models, Logistic Regression, and Survival Analysis,Comparison of Variance Estimates for Parameter Estimators in Cox Regression,Carbon-Ion Radiotherapy,Principles, Practices, and Treatment Planning,A Comparison of the Generalized Box-Cox and Fourier Functional Forms,An Application to the North Carolina Residential Time-of-use Electricity Pricing Experiment,A Comparison of Particle Size Models Using the Method of D.R. Cox,Comparison of V-fold Data Splitting with the Jackknife (leave-one-out) Procedure for the Cross Validated Likelihood Function in the Cox Proportional Hazards Model,A Comparison of the Specific Deterrent Effects of Official Sanctions Across Drug and Non-drug Cohorts of Offenders in New York City Between 1983 and 1988, Using a Cox Proportional Hazards Survival Model,Multiple Event Analysis of Injuries Using Adaptations to the Cox Proportional Hazards Model,Report for ...,Bayesian Survival Analysis,Modelling Survival Data in Medical Research, Second Edition,Applied Statistics - Principles and Examples,A Comparison of Accurate Malnutrition Diagnoses by the Cox Medical System Before and After Physician Education,Comparison of Time-dependent Sequential Logit and Cox Proportional Hazards Models for Hurricane Evacuation with a Focus on the Use of Evolving Forecast Information,Report,A Comparison of Categorical Models for Right-censored Data,Survival Analysis Using S,Analysis of Time-to-Event Data,A Comparison of the Box-Cox Maximum Likelihood Estimator and the Nonlinear Two-stage Least Squares Estimator,Artificial Intelligence in Medicine,17th Conference on Artificial Intelligence in Medicine, AIME 2019, Poznan, Poland, June 26–29, 2019, Proceedings,An Introduction to Survival Analysis Using Stata, Second Edition,Advanced Mathematical & Computational Tools in Metrology VII,Goodness-of-Fit Tests and Model Validity,Principles of Statistical Inference,MODELLING DEFAULT AMONG MALAYSIAN CONSUMER LOANS,COMPARISON BETWEEN LOGISTIC REGRESSION AND COX PROPORTIONAL HAZARD REGRESSION
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,Comparison of Cox's and Gray's Models in Survival Analysis,Application of Multiple Regression to Survival Data,A Comparison with Cox Regression,A Comparison of Two Survival Models,Cox Proportional Hazards and Frailty,A Comparison of Cox and Joint Models for Time-to-Event Data,Comparison of Cox Regression and Discrete Time Survival Models,A Comparison of Bayesian and Frequentist Inference for Cox Regression Modles with Random Effects,Survival Analysis,A Self-Learning Text,Comparison Between Weibull and Cox Proportional Hazards Models,Comparison of a Traditional and a Multilevel Cox Proportional Hazards Model,Predicting Bank Failures,A Comparison of the Cox Proportional Hazards Model and the Time-varying Covariates Model,Modeling Survival Data: Extending the Cox Model,A Comparison of Statistical Tests for Assessing the Proportional Hazards Assumption for the Cox Model,A Comparison of Smoothing Techniques for a Covariate Measured with Error in a Time-dependent Cox Proportional Hazards Model,A Comparison of Test Statistics for Proportionality of the Hazards in the Cox Regression Model,A Comparison of Test Statistics for Assessing the Proportional Hazards Assumption of Cox's Model,Analytical Comparison of Contrasting Approaches to Estimating Competing Risks Models,Regression Modeling Strategies,With Applications to Linear Models, Logistic Regression, and Survival Analysis,Comparison of Variance Estimates for Parameter Estimators in Cox Regression,Carbon-Ion Radiotherapy,Principles, Practices, and Treatment Planning,A Comparison of the Generalized Box-Cox and Fourier Functional Forms,An Application to the North Carolina Residential Time-of-use Electricity Pricing Experiment,A Comparison of Particle Size Models Using the Method of D.R. Cox,Comparison of V-fold Data Splitting with the Jackknife (leave-one-out) Procedure for the Cross Validated Likelihood Function in the Cox Proportional Hazards Model,A Comparison of the Specific Deterrent Effects of Official Sanctions Across Drug and Non-drug Cohorts of Offenders in New York City Between 1983 and 1988, Using a Cox Proportional Hazards Survival Model,Multiple Event Analysis of Injuries Using Adaptations to the Cox Proportional Hazards Model,Report for ...,Bayesian Survival Analysis,Modelling Survival Data in Medical Research, Second Edition,Applied Statistics - Principles and Examples,A Comparison of Accurate Malnutrition Diagnoses by the Cox Medical System Before and After Physician Education,Comparison of Time-dependent Sequential Logit and Cox Proportional Hazards Models for Hurricane Evacuation with a Focus on the Use of Evolving Forecast Information,Report,A Comparison of Categorical Models for Right-censored Data,Survival Analysis Using S,Analysis of Time-to-Event Data,A Comparison of the Box-Cox Maximum Likelihood Estimator and the Nonlinear Two-stage Least Squares Estimator,Artificial Intelligence in Medicine,17th Conference on Artificial Intelligence in Medicine, AIME 2019, Poznan, Poland, June 26–29, 2019, Proceedings,An Introduction to Survival Analysis Using Stata, Second Edition,Advanced Mathematical & Computational Tools in Metrology VII,Goodness-of-Fit Tests and Model Validity,Principles of Statistical Inference,MODELLING DEFAULT AMONG MALAYSIAN CONSUMER LOANS,COMPARISON BETWEEN LOGISTIC REGRESSION AND COX PROPORTIONAL HAZARD REGRESSION
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