The International Journal of Biostatistics
Ed. by Chambaz, Antoine / Hubbard, Alan E. / van der Laan, Mark J.
2 Issues per year
IMPACT FACTOR 2016: 0.500
5-year IMPACT FACTOR: 0.862
CiteScore 2016: 0.42
SCImago Journal Rank (SJR) 2016: 0.488
Source Normalized Impact per Paper (SNIP) 2016: 0.467
Mathematical Citation Quotient (MCQ) 2016: 0.09
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.