Lifetime Data Anal - A two-stage estimation in the Clayton-Oakes model with marginal linear transformation models for multivariate failure time data.

Tópicos

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Resumo

This paper considers the analysis of multivariate survival data where the marginal distributions are specified by semiparametric transformation models, a general class including the Cox model and the proportional odds model as special cases. First, consideration is given to the situation where the joint distribution of all failure times within the same cluster is specified by the Clayton-Oakes model (Clayton, Biometrika 65:141-151, l978; Oakes, J R Stat Soc B 44:412-422, 1982). A two-stage estimation procedure is adopted by first estimating the marginal parameters under the independence working assumption, and then the association parameter is estimated from the maximization of the full likelihood function with the estimators of the marginal parameters plugged in. The asymptotic properties of all estimators in the semiparametric model are derived. For the second situation, the third and higher order dependency structures are left unspecified, and interest focuses on the pairwise correlation between any two failure times. Thus, the pairwise association estimate can be obtained in the second stage by maximizing the pairwise likelihood function. Large sample properties for the pairwise association are also derived. Simulation studies show that the proposed approach is appropriate for practical use. To illustrate, a subset of the data from the Diabetic Retinopathy Study is used.

Resumo Limpo

paper consid analysi multivari surviv data margin distribut specifi semiparametr transform model general class includ cox model proport odd model special case first consider given situat joint distribut failur time within cluster specifi claytonoak model clayton biometrika l oak j r stat soc b twostag estim procedur adopt first estim margin paramet independ work assumpt associ paramet estim maxim full likelihood function estim margin paramet plug asymptot properti estim semiparametr model deriv second situat third higher order depend structur left unspecifi interest focus pairwis correl two failur time thus pairwis associ estim can obtain second stage maxim pairwis likelihood function larg sampl properti pairwis associ also deriv simul studi show propos approach appropri practic use illustr subset data diabet retinopathi studi use

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