Missing Data A Systematic Review of How They Are Reported and Handled

被引:154
作者
Eekhout, Iris [1 ,2 ,3 ]
de Boer, Michiel R. [3 ,4 ]
Twisk, Jos W. R. [1 ,2 ,3 ]
de Vet, Henrica C. W. [1 ,2 ]
Heymans, Martijn W. [1 ,2 ,3 ]
机构
[1] Vrije Univ Amsterdam, Med Ctr, Dept Epidemiol & Biostat, NL-1081 BT Amsterdam, Netherlands
[2] EMGO Inst Hlth & Care Res, Amsterdam, Netherlands
[3] Vrije Univ Amsterdam, Inst Hlth Sci, Fac Earth & Life Sci, Dept Methodol & Appl Biostat, NL-1081 BT Amsterdam, Netherlands
[4] Univ Groningen, Univ Med Ctr Groningen, Dept Publ Hlth, NL-9713 AV Groningen, Netherlands
关键词
ITEM SCORES; IMPUTATION;
D O I
10.1097/EDE.0b013e3182576cdb
中图分类号
R1 [预防医学、卫生学];
学科分类号
1004 ; 120402 ;
摘要
Background: The objectives of this systematic review are to examine how researchers report missing data in questionnaires and to provide an overview of current methods for dealing with missing data. Methods: We included 262 studies published in 2010 in 3 leading epidemiologic journals. Information was extracted on how missing data were reported, types of missing, and methods for dealing with missing data. Results: Seventy-eight percent of the studies lacked clear information about the measurement instruments. Missing data in multi-item instruments were not handled differently from other missing data. Complete-case analysis was most frequently reported (81% of the studies), and the selectivity of missing data was seldom examined. Conclusions: Although there are specific methods for handling missing data in item scores and in total scores of multi-item instruments, these are seldom applied. Researchers mainly use complete-case analysis for both types of missing, which may seriously bias the study results.
引用
收藏
页码:729 / 732
页数:4
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