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

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 i...

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Bibliographic Details
Published in:Statistics in medicine Vol. 39; no. 23; pp. 3195 - 3206
Main Authors: Zhang, Hongbin, Kelvin, Elizabeth A., Carpio, Arturo, Allen Hauser, W.
Format: Journal Article
Language:English
Published: England Wiley Subscription Services, Inc 15.10.2020
Subjects:
Cluster Analysis
Cysts
frailty survival model
Humans
interval‐censoring
Likelihood Functions
Models, Statistical
Monte Carlo Method
multistate joint model
neurocysticercosis
Neurocysticercosis - drug therapy
nonignorable missingness
frailty survival model
interval-censoring
multistate joint model
neurocysticercosis
nonignorable missingness
ISSN:0277-6715, 1097-0258, 1097-0258
Online Access:Get full text
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Summary: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.
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ISSN:0277-6715
1097-0258
1097-0258
DOI:10.1002/sim.8663