Parametric assumptions equate to hidden observations: comparing the efficiency of nonparametric and parametric models for estimating time to AIDS or death in a cohort of HIV-positive women.

ABSTRACT:

Background

When conducting a survival analysis, researchers might consider two broad classes of models: nonparametric models and parametric models. While nonparametric models are more flexible because they make few assumptions regarding the shape of the data distribution, parametric models are more efficient. Here we sought to make concrete the difference in efficiency between these two model types using effective sample size.

Methods

We compared cumulative risk of AIDS or death estimated using four survival models - nonparametric, generalized gamma, Weibull, and exponential - and data from 1164 HIV patients who were alive and AIDS-free in 1995. We added pseudo-observations to the sample until the spread of the 95% confidence limits for the nonparametric model became less th

SUBMITTER: Rudolph JE 

PROVIDER: S-EPMC6245810 | biostudies-literature | 2018 Nov

REPOSITORIES: biostudies-literature