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A randomly truncated sample appears when the independent variables T and L are observable if L < T . The truncated version Kaplan-Meier estimator is known to be the standard estimation method for the marginal distribution of T or L. The inverse probability weighted (IPW) estimator was suggested as an alternative and its agreement to the truncated version Kaplan-Meier estimator has been proved. This paper centers on the weak convergence of IPW estimators and variance decomposition. The paperdoi:10.6339/jds.201210_10(4).0006 fatcat:zywjywvg3zc77lk2wonotcquca