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J Arthroplasty. 2016 Jan;31(1):81-6. doi: 10.1016/j.arth.2015.06.067. Epub 2015 Jul 11.

Analysis of Longitudinal Outcome Data with Missing Values in Total Knee Arthroplasty.

Author information

1
Joint Reconstruction Center, Seoul National University Bundang Hospital, Seongnam-si, South Korea.
2
Department of Statistics, Dan Kook University, Yongin-si, South Korea.
3
Department of Psychology, Princeton University, Princeton, New Jersey.

Abstract

We sought to determine the influence of missing data on the statistical results, and to determine which statistical method is most appropriate for the analysis of longitudinal outcome data of TKA with missing values among repeated measures ANOVA, generalized estimating equation (GEE) and mixed effects model repeated measures (MMRM). Data sets with missing values were generated with different proportion of missing data, sample size and missing-data generation mechanism. Each data set was analyzed with three statistical methods. The influence of missing data was greater with higher proportion of missing data and smaller sample size. MMRM tended to show least changes in the statistics. When missing values were generated by 'missing not at random' mechanism, no statistical methods could fully avoid deviations in the results.

KEYWORDS:

generalized estimating equation; missing data; mixed model repeated measures; repeated measures ANOVA; total knee arthroplasty

PMID:
26248852
DOI:
10.1016/j.arth.2015.06.067
[Indexed for MEDLINE]

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