A multistate joint model for interval-censored event-history data subject to within-unit clustering and informative missingness, with application to neurocysticercosis research

Hongbin Zhang, Elizabeth A. Kelvin, Arturo Carpio, W. Allen Hauser

Research output: Contribution to journalArticlepeer-review

2 Scopus citations

Abstract

We propose a multistate joint model to analyze interval-censored event-history data subject to within-unit clustering and nonignorable missing data. The model is motivated by a study of the neurocysticercosis (NC) cyst evolution at the cyst-level, taking into account the multiple cysts phases with intermittent missing data and loss to follow-up, as well as the intra-brain clustering of observations made on a predefined data collection schedule. Of particular interest in this study is the description of the process leading to cyst resolution, and whether this process varies by antiparasitic treatment. The model uses shared random effects to account for within-brain correlation and to explain the hidden heterogeneity governing the missing data mechanism. We developed a likelihood-based method using a Monte Carlo EM algorithm for the inference. The practical utility of the methods is illustrated using data from a randomized controlled trial on the effect of antiparasitic treatment with albendazole on NC cysts among patients from six hospitals in Ecuador. Simulation results demonstrate that the proposed methods perform well in the finite sample and misspecified models that ignore the data complexities could lead to substantial biases.

Original languageEnglish
Pages (from-to)3195-3206
Number of pages12
JournalStatistics in Medicine
Volume39
Issue number23
DOIs
StatePublished - Oct 15 2020

Bibliographical note

Funding Information:
This original RCT was supported by the National Institute of Neurological Disorders and Stroke at the National Institutes of Health (R01‐NS39403). The analyses presented here were supported by the City University of New York (PSC‐CUNY ENHC 47). This work was also partially supported by the CUNY (City University of New York) High Performance Computing Center, College of Staten Island, funded in part by the City and State of New York, CUNY Research Foundation, and National Science Foundation Grants CNS‐0958379, CNS‐0855217 , and ACI‐1126113.

Publisher Copyright:
© 2020 John Wiley & Sons, Ltd.

Keywords

  • frailty survival model
  • interval-censoring
  • multistate joint model
  • neurocysticercosis
  • nonignorable missingness

ASJC Scopus subject areas

  • Epidemiology
  • Statistics and Probability

Fingerprint

Dive into the research topics of 'A multistate joint model for interval-censored event-history data subject to within-unit clustering and informative missingness, with application to neurocysticercosis research'. Together they form a unique fingerprint.

Cite this