2004
DOI: 10.1093/biostatistics/5.3.445
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Analyzing incomplete longitudinal clinical trial data

Abstract: Using standard missing data taxonomy, due to Rubin and co-workers, and simple algebraic derivations, it is argued that some simple but commonly used methods to handle incomplete longitudinal clinical trial data, such as complete case analyses and methods based on last observation carried forward, require restrictive assumptions and stand on a weaker theoretical foundation than likelihood-based methods developed under the missing at random (MAR) framework. Given the availability of flexible software for analyzi… Show more

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Cited by 229 publications
(265 citation statements)
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“…A secondary analysis of the primary outcome variable used a repeated-measures analysis of covariance model (ie, the so-called mixed model repeated measures [MMRM] analysis strategy 22 ) that included treatment group as the factor of interest, center as a stratification factor, and baseline PMD and papilledema grade in the study eye as covariates. The model also included terms for visit (categorical), the interaction between baseline PMD and visit, and the interaction between treatment group and visit.…”
Section: Methodsmentioning
confidence: 99%
“…A secondary analysis of the primary outcome variable used a repeated-measures analysis of covariance model (ie, the so-called mixed model repeated measures [MMRM] analysis strategy 22 ) that included treatment group as the factor of interest, center as a stratification factor, and baseline PMD and papilledema grade in the study eye as covariates. The model also included terms for visit (categorical), the interaction between baseline PMD and visit, and the interaction between treatment group and visit.…”
Section: Methodsmentioning
confidence: 99%
“…Further sensitivity models allowing for missing not-at-random mechanism were also considered. 38 They were based on a pattern mixture approach, considering a large range of possible differences in outcomes between participants who completed the follow-up and those who did not. Mean difference and confidence intervals (CIs) were estimated using the 'rctmiss' 39 user-written command in Stata.…”
Section: Discussionmentioning
confidence: 99%
“…In the primary statistical analyses, we used a repeated measures analysis of covariance model (i.e., the mixed model repeated measures [MMRM] analysis strategy) 22 that included change from baseline in Need Satisfaction with Mentor score as the dependent variable and treatment group as the independent variable of interest. Geographic region and baseline Need Satisfaction with Mentor score were included as covariates.…”
Section: Methodsmentioning
confidence: 99%