TY  - RPRT
        AU  - Berg, Gerard J. van den
AU  - Drepper, Bettina
        TI  - Inference for Shared-Frailty Survival Models with Left-Truncated Data
        PY  - 2011/Oct/
        PB  - Institute of Labor Economics (IZA)
        CY  - Bonn
        T2  - IZA Discussion Paper
        IS  - 6031
        UR  - https://www.iza.org/index.php/publications/dp6031
        AB  - Shared-frailty survival models specify that systematic unobserved determinants of duration outcomes are identical within groups of individuals. We consider random-effects likelihood-based statistical inference if the duration data are subject to left-truncation. Such inference with left-truncated data can be performed in the Stata software package. We show that with left-truncated data, the commands ignore the weeding-out process before the left-truncation points, affecting the distribution of unobserved determinants among group members in the data, that is, among the group members who survive until their truncation points. We critically examine studies in the statistical literature on this issue as well as published empirical studies that use the commands. Simulations illustrate the size of the (asymptotic) bias and its dependence on the degree of truncation. We provide a Stata command file that maximizes the likelihood function that properly takes account of the interplay between truncation and dynamic selection.
        KW  - left-truncation
KW  - likelihood function
KW  - dynamic selection
KW  - hazard rate
KW  - unobserved heterogeneity
KW  - duration analysis
KW  - stata
KW  - twin data
        ER  -