Cautionary note on "Semiparametric modeling of grouped current duration data with preferential reporting'"

TL;DR

This paper examines the impact of right censoring on semiparametric models for grouped current duration data, highlighting potential biases and conditions for reliable application.

Contribution

It evaluates the methods of MSTL under type I censoring through simulations, clarifies when the model is correctly specified, and discusses sources of bias.

Findings

Bias can occur with right censoring in simulations.

Certain settings allow the method to perform well despite censoring.

The paper clarifies the implications of model assumptions under censoring.

Abstract

This report is designed to clarify a few points about the article "Semiparametric modeling of grouped current duration data with preferential reporting" by McLain, Sundaram, Thoma and Louis in Statistics in Medicine (McLain et al., 2014, hereafter MSTL) regarding using the methods under right censoring. In simulation studies, it has been found that bias can occur when right censoring is present. Current duration data normally does not have censored values, but censoring can be induced at a value, say tau, after which the data values are thought to be unreliable. As noted in MSTL, some right censored data require an assumption on the parametric form of the data beyond {\tau}. While this assumption was given in MSTL, the implications of the assumption were not sufficiently explored. Here we present simulations and evaluate the methods of MSTL under type I censoring, give some settings under which the method works well even in presence of censoring, state when the model is correctly specified and discuss the reasons of the bias.