The International Journal of Biostatistics
Ed. by Chambaz, Antoine / Hubbard, Alan E. / van der Laan, Mark J.
IMPACT FACTOR 2018: 1.309
CiteScore 2018: 1.11
SCImago Journal Rank (SJR) 2018: 1.325
Source Normalized Impact per Paper (SNIP) 2018: 0.715
Mathematical Citation Quotient (MCQ) 2018: 0.03
The Kaplan-Meier and closely related Lynden-Bell estimators are used to provide nonparametric estimation of the distribution of a left-truncated random variable. These estimators assume that the left-truncation variable is independent of the time-to-event. This paper proposes a semiparametric method for estimating the marginal distribution of the time-to-event that does not require independence. It models the conditional distribution of the time-to-event given the truncation variable using Cox's model for left truncated data, and uses inverse probability weighting. We report the results of simulations and illustrate the method using a survival study.
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