Cargando…
Handling missing data in propensity score estimation in comparative effectiveness evaluations: a systematic review
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 there-fore describes how missing data are addressed with propensity score methods in observational comp...
Autores principales: | , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
2017
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6478118/ https://www.ncbi.nlm.nih.gov/pubmed/28980833 http://dx.doi.org/10.2217/cer-2017-0071 |
_version_ | 1783413128547008512 |
---|---|
author | Malla, Lucas Perera-Salazar, Rafael McFadden, Emily Ogero, Morris Stepniewska, Kasia English, Mike |
author_facet | Malla, Lucas Perera-Salazar, Rafael McFadden, Emily Ogero, Morris Stepniewska, Kasia English, Mike |
author_sort | Malla, Lucas |
collection | PubMed |
description | 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 there-fore 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. |
format | Online Article Text |
id | pubmed-6478118 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
record_format | MEDLINE/PubMed |
spelling | pubmed-64781182019-04-23 Handling missing data in propensity score estimation in comparative effectiveness evaluations: a systematic review Malla, Lucas Perera-Salazar, Rafael McFadden, Emily Ogero, Morris Stepniewska, Kasia English, Mike J Comp Eff Res Article 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 there-fore 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. 2017-10-05 2018-03 /pmc/articles/PMC6478118/ /pubmed/28980833 http://dx.doi.org/10.2217/cer-2017-0071 Text en http://creativecommons.org/licenses/by-nc-nd/4.0/ This work is licensed under the Attribution-NonCommercial-NoDerivatives 4.0 Unported License. To view a copy of this license, visit http://creativecommons.org/licenses/by-nc-nd/4.0/ |
spellingShingle | Article Malla, Lucas Perera-Salazar, Rafael McFadden, Emily Ogero, Morris Stepniewska, Kasia English, Mike Handling missing data in propensity score estimation in comparative effectiveness evaluations: a systematic review |
title | Handling missing data in propensity score estimation in comparative effectiveness evaluations: a systematic review |
title_full | Handling missing data in propensity score estimation in comparative effectiveness evaluations: a systematic review |
title_fullStr | Handling missing data in propensity score estimation in comparative effectiveness evaluations: a systematic review |
title_full_unstemmed | Handling missing data in propensity score estimation in comparative effectiveness evaluations: a systematic review |
title_short | Handling missing data in propensity score estimation in comparative effectiveness evaluations: a systematic review |
title_sort | handling missing data in propensity score estimation in comparative effectiveness evaluations: a systematic review |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6478118/ https://www.ncbi.nlm.nih.gov/pubmed/28980833 http://dx.doi.org/10.2217/cer-2017-0071 |
work_keys_str_mv | AT mallalucas handlingmissingdatainpropensityscoreestimationincomparativeeffectivenessevaluationsasystematicreview AT pererasalazarrafael handlingmissingdatainpropensityscoreestimationincomparativeeffectivenessevaluationsasystematicreview AT mcfaddenemily handlingmissingdatainpropensityscoreestimationincomparativeeffectivenessevaluationsasystematicreview AT ogeromorris handlingmissingdatainpropensityscoreestimationincomparativeeffectivenessevaluationsasystematicreview AT stepniewskakasia handlingmissingdatainpropensityscoreestimationincomparativeeffectivenessevaluationsasystematicreview AT englishmike handlingmissingdatainpropensityscoreestimationincomparativeeffectivenessevaluationsasystematicreview |