dc.contributor.author |
Malla L, Perera-Salazar R, McFadden E, Ogero M, Stepniewska K, English M. |
|
dc.date.accessioned |
2024-08-09T08:15:59Z |
|
dc.date.available |
2024-08-09T08:15:59Z |
|
dc.date.issued |
2018-03 |
|
dc.identifier.uri |
http://dx.doi.org/10.2217/cer-2017-0071 |
|
dc.identifier.uri |
http://repository.kemri.go.ke:8080/xmlui/handle/123456789/873 |
|
dc.description.abstract |
Aim: Even though systematic reviews have examined how aspects of propensity score
methods are used, none has reviewed how the challenge of missing data is addressed
with these methods. This review therefore describes how missing data are addressed with
propensity score methods in observational comparative effectiveness studies.
Methods: Published articles on observational comparative effectiveness studies were
extracted from MEDLINE and EMBASE databases.
Results: Our search yielded 167 eligible articles. Majority of these studies (114; 68%)
conducted complete case analysis with only 53 of them stating this in the methods. Only
16 articles reported use of multiple imputation.
Conclusion: Few researchers use correct methods for handling missing data or reported
missing data methodology which may lead to reporting biased findings. |
en_US |
dc.language.iso |
en |
en_US |
dc.publisher |
Journal of Comparative Effectiveness Research |
en_US |
dc.title |
Handling missing data in propensity score estimation in comparative effectiveness evaluations: a systematic review. |
en_US |
dc.type |
Article |
en_US |