Introduction of processing methods for missing data in Meta-analysis
YU Ya-yu
XU Yang-peng
HE Qian
WU Jun-yi
FU Wen-jie
TAO Yuan
ZHANG Chao
Abstract：At the beginning of a clinical trial design, and even in the middle and later stages when data is tracked and followed up, partial data may be missed inevitably. However, when the missing data and research results are possibly linked, bias may be induced in a randomized controlled trial (RCT), and the bias risk will also be introduced to the results of Meta-analysis. Due to the status of missing data is very complex, processing methods for missing data should be selected according to actual situation. The aim of this paper is to present missing data mechanism including missing at random (MAR), missing completely at random (MCAR), missing not at random (MAR), and common processing methods.
Keywords：Missing dataAvailable case analysisLast observation carried forwardImputed case analysis
Publication Date：2016-01-01
Online Publishing Date：2025-08-15(First online date of this platform, not the publication date of the document)
Pages：4( 1416-1419 )