Affordable Access

deepdyve-link deepdyve-link
Publisher Website

Analysis of counts with two latent classes, with application to risk assessment based on physician-visit records of cancer survivors.

Authors
Type
Published Article
Journal
Biostatistics (Oxford, England)
Publication Date
Volume
15
Issue
2
Pages
384–397
Identifiers
DOI: 10.1093/biostatistics/kxt052
PMID: 24297607
Source
Medline
Keywords
License
Unknown

Abstract

Motivated by a cancer survivorship program, this paper explores event counts from two categories of individuals with unobservable membership. We formulate the counts using a latent class model and consider two likelihood-based inference procedures, the maximum likelihood estimation (MLE) and a pseudo-MLE procedure. The pseudo-MLE utilizes additional information on one of the latent classes. It yields reduced computational intensity and potentially increased estimation efficiency. We establish the consistency and asymptotic normality of the proposed pseudo-MLE, and we present an extended Huber sandwich estimator as a robust variance estimator for the pseudo-MLE. The finite-sample properties of the two-parameter estimators along with their variance estimators are examined by simulation. The proposed methodology is illustrated by physician-claim data from the cancer program.

Statistics

Seen <100 times