نتایج جستجو برای: cox proportional hazards models
تعداد نتایج: 1008588 فیلتر نتایج به سال:
Prognostic models are often used to estimate the length of patient survival. The Cox proportional hazards model has traditionally been applied to assess the accuracy of prognostic models. However, it may be suboptimal due to the inflexibility to model the baseline survival function and when the proportional hazards assumption is violated. The aim of this study was to use internal validation to ...
The proportional hazard Cox regression models play a key role in analyzing censored survival data. We use penalized methods in high dimensional scenarios to achieve more efficient models. This article reviews the penalized Cox regression for some frequently used penalty functions. Analysis of medical data namely ”mgus2” confirms the penalized Cox regression performs better than the cox regressi...
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 not been formally evaluated. METHODS We investigated the performance of the polytomous logist...
BeSS: An R Package for Best Subset Selection in Linear, Logistic and Cox Proportional Hazards Models
Quasi score equations derived from corrected mean and variance functions allow for consistent parameter estimation under measure ment error However the practical use of some approaches relying on this general methodological principle was strongly limited by the assumptions underlying them only one covariate was allowed to be measured with non negligible error and additionally this covariate had...
Graphical methods based on the analysis of differences between log cumulative hazard functions are considered for a two-group semi-proportional hazard model which allows for interaction between treatments and covariates. Confidence procedures and test statistics that can be used to test for interaction and for main effects are developed. Their use is illustrated by applying them to the analysis...
Exposure measurement error represents one of the most important sources of uncertainty in epidemiology. When exposure uncertainty is not or only poorly accounted for, it can lead to biased risk estimates and a distortion of the shape of the exposure-response relationship. In occupational cohort studies, the time-dependent nature of exposure and changes in the method of exposure assessment may c...
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