Comput Methods Programs Biomed - A simulation procedure based on copulas to generate clustered multi-state survival data.

Tópicos

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Resumo

Generating survival data with a clustered and multi-state structure is useful to study finite sample properties of multi-state models, competing risks models and frailty models. We propose a simulation procedure based on a copula model for each competing events block, allowing to introduce dependence between times of different transitions and between those of grouped subjects. The effect of simulated frailties and covariates can be added in a proportional hazards way. In order to mimic information from real data, we also propose a method for the tuning of parameters via numerical minimization of a criterion function based on the ratios of target and observed values of median times and of probabilities of competing events. An example is provided on simulation of data mimicking those from a multicenter study on head and neck cancer, where the interest is in studying both time to local relapses and to distant metastases before death. The results demonstrated that data simulated according to our proposed method have characteristics very close to the target values.

Resumo Limpo

generat surviv data cluster multist structur use studi finit sampl properti multist model compet risk model frailti model propos simul procedur base copula model compet event block allow introduc depend time differ transit group subject effect simul frailti covari can ad proport hazard way order mimic inform real data also propos method tune paramet via numer minim criterion function base ratio target observ valu median time probabl compet event exampl provid simul data mimick multicent studi head neck cancer interest studi time local relaps distant metastas death result demonstr data simul accord propos method characterist close target valu

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