Longitudinal Meta-Analysis Estimates when Mean from Median Estimation is Necessary
Abstract Number:
3040
Submission Type:
Contributed Abstract
Contributed Abstract Type:
Paper
Participants:
Harlan Sayles (1), Lynette Smith (1), Christopher Wichman (1)
Institutions:
(1) University of Nebraska Medical Center, N/A
Co-Author(s):
First Author:
Presenting Author:
Abstract Text:
Patient reported outcomes, such as quality of life (QOL), are commonly collected in oncology studies, and are increasingly common in meta-analyses. We currently have a meta-analysis data set where studies of QOL among cancer patients receiving radiation therapy have reported been reported longitudinally as correlated continuous repeated measures. While most studies of QOL have reported means and standard deviations, some studies have reported medians with ranges, interquartile ranges (IQR), or both. It is unknown how existing methods for mean from median estimation may affect results of a meta-analysis when data are from longitudinal studies reporting correlated repeated measures. In a simulation study, we varied the underlying distributions, numbers of studies and subjects within studies, data reported (medians with range, IQR or both), and proportion of studies reporting medians. Results show that bias and coverage problems tend to arise as the proportion of studies reporting medians increases and as the underlying distributions become more skewed.
Keywords:
Meta-Analysis|Simulation|Quality of Life|Cancer|Longitudinal|
Sponsors:
Section for Statistical Programmers and Analysts
Tracks:
Best practices for programming and analysis
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