Accounting for dropout bias using mixed-effects models

Journal of Biopharmaceutical Statistics

Volumn 11, Issue 1-2, 2001, Pages 9-21

  Mallinckrodt, C H ^a   Clark, W S ^a   David, S R ^a  

^a ELI LILLY AND COMPANY   (United States)

Author keywords

Dropout bias; LOCF; Missing data; Mixed effects models

Indexed keywords

ACCURACY; ANALYTIC METHOD; ARTICLE; CLINICAL TRIAL; CONTROLLED CLINICAL TRIAL; DRUG RESEARCH; MEASUREMENT; PRIORITY JOURNAL; RANDOMIZED CONTROLLED TRIAL; SIMULATION; STATISTICS;

ANALYSIS OF VARIANCE; BIAS (EPIDEMIOLOGY); CONFIDENCE INTERVALS; HUMANS; LONGITUDINAL STUDIES; MODELS, STATISTICAL; PATIENT DROPOUTS; RANDOMIZED CONTROLLED TRIALS;

EID: 0034934721     PISSN: 10543406     EISSN: None     Source Type: Journal    
DOI: 10.1081/BIP-100104194     Document Type: Article

References (19)

1. The analysis of messy data
2. Some conceptual and statistical issues in analysis of longitudinal psychiatric data
3. Missing data in longitudinal studies
4. Clinical trials in psychiatry: Should protocol deviation censor patient data?
5. Using the general linear mixed model to analyze unbalanced repeated measures and longitudinal data
6. A multiple imputation strategy for clinical trials with truncation of patient data
7. A comparison of the random-effects pattern mixture model with Last-Observation-Carried-Forward (LOCF) analysis in longitudinal clinical trials with dropouts
8. Statistical handling of dropouts in longitudinal clinical trials
9. Olanzapine versus haloperidol in the treatment of schizophrenia, schizoaffective, and schizophreniform disorders: Results of an International Collaborative Trial
10. Multiple trait restricted maximum likelihood for simulated measures of ovulation rate with underlying multivariate normal distributions
11. Multiple imputations in health care databases: An overview and some applications