Performance of a mixed effects logistic regression model for binary outcomes with unequal cluster size

Moonseong Heo, Andrew C. Leon

Research output: Contribution to journalArticle

18 Citations (Scopus)

Abstract

When a clustered randomized controlled trial is considered at a design stage of a clinical trial, it is useful to consider the consequences of unequal cluster size (i.e., sample size per cluster). Furthermore, the assumption of independence of observations within cluster does not hold, of course, because the subjects share the same cluster. Moreover, when the clustered outcomes are binary, a mixed effect logistic regression model is applicable. This article compares the performance of a maximum likelihood estimation of the mixed effects logistic regression model with equal and unequal cluster sizes. This was evaluated in terms of type I error rate, power, bias, and standard error through computer simulations that varied treatment effect, number of clusters, and intracluster correlation coefficients. The results show that the performance of the mixed effects logistic regression model is very similar, regardless of inequality in cluster size. This is illustrated using data from the Prevention Of Suicide in Primary care Elderly: Collaborative Trial (PROSPECT) study.

Original languageEnglish (US)
Pages (from-to)513-526
Number of pages14
JournalJournal of Biopharmaceutical Statistics
Volume15
Issue number3
DOIs
StatePublished - 2005
Externally publishedYes

Fingerprint

Mixed Effects
Binary Outcomes
Logistic Regression Model
Unequal
Logistic Models
Intracluster Correlation
Primary Care
Randomized Controlled Trial
Type I Error Rate
Treatment Effects
Number of Clusters
Standard error
Maximum Likelihood Estimation
Correlation coefficient
Clinical Trials
Computer Simulation
Sample Size
Suicide
Primary Health Care
Randomized Controlled Trials

Keywords

  • Bias
  • Clustered binary observations
  • Clustered randomized controlled trials
  • ICC
  • Power
  • Type I error rate

ASJC Scopus subject areas

  • Pharmacology (medical)
  • Pharmacology, Toxicology and Pharmaceutics(all)

Cite this

Performance of a mixed effects logistic regression model for binary outcomes with unequal cluster size. / Heo, Moonseong; Leon, Andrew C.

In: Journal of Biopharmaceutical Statistics, Vol. 15, No. 3, 2005, p. 513-526.

Research output: Contribution to journalArticle

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