Causal mediation analysis for the Cox proportional hazards model with a smooth baseline hazard estimator
نویسندگان
چکیده
منابع مشابه
The Cox Proportional Hazards Model with a Partially Known Baseline
The Cox proportional hazards regression model has been widely used in the analysis of survival/duration data. It is semiparametric because the model includes a baseline hazard function that is completely unspecified. We study here the statistical inference of the Cox model where some information about the baseline hazard function is available, but it still remains as an infinite dimensional nui...
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We introduce the R package CPHshape, which computes the effect parameters and the nonparametric maximum likelihood estimator of a shape constrained baseline hazard in the Cox proportional hazards model. The functionality of the package is illustrated using reproducible examples which are based on simulated data.
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The aim of fitting a Cox model to time-to-event data is to estimate the effect of covariates on the baseline hazard function. The baseline hazard function, not itself estimated within the model, is the hazard function obtained when all covariate are set to zero. In several applications, it is important to have an explicit, preferably smooth, estimate of the baseline hazard function, or more gen...
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MOTIVATION There has been an increasing interest in expressing a survival phenotype (e.g. time to cancer recurrence or death) or its distribution in terms of a subset of the expression data of a subset of genes. Due to high dimensionality of gene expression data, however, there is a serious problem of collinearity in fitting a prediction model, e.g. Cox's proportional hazards model. To avoid th...
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ژورنال
عنوان ژورنال: Journal of the Royal Statistical Society: Series C (Applied Statistics)
سال: 2016
ISSN: 0035-9254
DOI: 10.1111/rssc.12188