使用多重插补进行缺失值的处理。All variables that were to be included in the regression analysis we...
Mixed effects logistic regression models for longitudinal ordinal functional response data with multiple-cause drop-out from the longitudinal study of aging In the context of analyzing ordinal functional limitation responses from the Longitudinal Study of Aging, we investigate the association between current...
研究人员调查患者在缺血性中风后退出康复计划的生存时间面临诸多挑战。 每个主体有多个观测值。表示患者病历的变量应用作预测变量。 随着时间的推移,患者可能会经历改变其病历的重大医疗事件。 在这个数据集中,记录了心肌梗塞,缺血性中风或出血性中风的发生,并记录了事件发生的时间。 您可以在过程中创建可计算的依赖于时...
Cox regression, missing data, multiple imputation, restricted cubic spline, time‐varying effectIn Cox regression, it is important to test the proportional hazards assumption and sometimes of interest in itself to study time‐varying effects (TVEs) of covariates. TVEs can be investigated with ...
Background: Polytomous logistic regression models are commonly used in case-control studies of cancer to directly compare the risks associated with an exposure variable across multiple cancer subtypes. However, the validity, accuracy, and efficiency of this approach for prospective cohort studies have no...
Summary This chapter provides a brief overview of logistic regression for the analysis of closed cohort and case-control data, and Cox regression for the analysis of censored survival data. The aim is to demonstrate the connection between these regression methods and the nonregression techniques discu...
Calibration of prediction rules for life-timeoutcomes using prognostic Cox regressionsurvival models and multiple imputations toaccount for missing predictor data withcross-validatory assessment.Mertens, B. J. A. 1May 6, 20211 Medical Statistics, Department of Biomedical Data Sciences, Leiden Uni-versi...
The Cox model can be written as a multiple linear regression of the logarithm of the hazard on the variablesxixi, with the baseline hazard being an ‘intercept’ term that varies with time. The quantitiesexp(bi)exp(bi)are called hazard ratios (HR). A value ofbibigreater than zero, or eq...
then conducted in-depth Cox regression simultaneously fitting both PRS as predictors, and concluded that both PRS are significant predictors for post-menopausal breast cancer. This raises the general question of whether multiple PRS should be used to improve risk prediction obtained from a single PRS...
Overexpression of the oncogene c-erb B2 in primary ovarian cancer: evaluation of the prognostic value in a Cox proportional hazards multiple regression. Ovarian cancer is the leading cause of death in gynecological cancers. To date, there are no prognostic factors in ovarian cancer that adequately ...