A consistent estimator for logistic mixed effect models

Yizheng Wei, Yanyuan Ma, Tanya P. Garcia, Samiran Sinha

Research output: Contribution to journalArticle

Abstract

We propose a consistent and locally efficient method of estimating the model parameters of a logistic mixed effect model with random slopes. Our approach relaxes two typical assumptions: the random effects being normally distributed, and the covariates and random effects being independent of each other. Adhering to these assumptions is particularly difficult in health studies where, in many cases, we have limited resources to design experiments and gather data in long-term studies, while new findings from other fields might emerge, suggesting the violation of such assumptions. So it is crucial to have an estimator that is robust to such violations; then we could make better use of current data harvested using various valuable resources. Our method generalizes the framework presented in Garcia & Ma (2016) which also deals with a logistic mixed effect model but only considers a random intercept. A simulation study reveals that our proposed estimator remains consistent even when the independence and normality assumptions are violated. This contrasts favourably with the traditional maximum likelihood estimator which is likely to be inconsistent when there is dependence between the covariates and random effects. Application of this work to a study of Huntington's disease reveals that disease diagnosis can be enhanced using assessments of cognitive performance. The Canadian Journal of Statistics 47: 140–156; 2019

Original languageEnglish (US)
Pages (from-to)140-156
Number of pages17
JournalCanadian Journal of Statistics
Volume47
Issue number2
DOIs
StatePublished - Jun 1 2019

Fingerprint

Mixed Effects Model
Consistent Estimator
Logistics
Random Effects
Covariates
Resources
Intercept
Normality
Inconsistent
Maximum Likelihood Estimator
Slope
Health
Likely
Simulation Study
Statistics
Estimator
Generalise
Random effects
Experiment
Violations

All Science Journal Classification (ASJC) codes

  • Statistics and Probability
  • Statistics, Probability and Uncertainty

Cite this

Wei, Yizheng ; Ma, Yanyuan ; Garcia, Tanya P. ; Sinha, Samiran. / A consistent estimator for logistic mixed effect models. In: Canadian Journal of Statistics. 2019 ; Vol. 47, No. 2. pp. 140-156.
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A consistent estimator for logistic mixed effect models. / Wei, Yizheng; Ma, Yanyuan; Garcia, Tanya P.; Sinha, Samiran.

In: Canadian Journal of Statistics, Vol. 47, No. 2, 01.06.2019, p. 140-156.

Research output: Contribution to journalArticle

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