Current practices in missing data handling for interrupted time series studies performed on individual-level data: A scoping review in health research
Descripción del Articulo
This study was funded by the National Institute for Health Research (NIHR) School for Primary Care Research, project number 444. JCB was sponsored by FONDECYT- CONCYTEC (grant contract number 231-2015- FONDECYT). TPM, TMP and JRC were supported by the Medical Research Council (grant numbers MC_UU_12...
| Autores: | , , , |
|---|---|
| Formato: | revisión |
| Fecha de Publicación: | 2021 |
| Institución: | Consejo Nacional de Ciencia Tecnología e Innovación |
| Repositorio: | CONCYTEC-Institucional |
| Lenguaje: | inglés |
| OAI Identifier: | oai:repositorio.concytec.gob.pe:20.500.12390/2988 |
| Enlace del recurso: | https://hdl.handle.net/20.500.12390/2988 https://doi.org/10.2147/CLEP.S314020 |
| Nivel de acceso: | acceso abierto |
| Materia: | Segmented regression Interrupted time series analysis Missing data Multiple imputation Scoping review https://purl.org/pe-repo/ocde/ford#2.02.04 |
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oai:repositorio.concytec.gob.pe:20.500.12390/2988 |
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| dc.title.none.fl_str_mv |
Current practices in missing data handling for interrupted time series studies performed on individual-level data: A scoping review in health research |
| title |
Current practices in missing data handling for interrupted time series studies performed on individual-level data: A scoping review in health research |
| spellingShingle |
Current practices in missing data handling for interrupted time series studies performed on individual-level data: A scoping review in health research Bazo-Alvarez J.C. Segmented regression Interrupted time series analysis Missing data Multiple imputation Scoping review https://purl.org/pe-repo/ocde/ford#2.02.04 |
| title_short |
Current practices in missing data handling for interrupted time series studies performed on individual-level data: A scoping review in health research |
| title_full |
Current practices in missing data handling for interrupted time series studies performed on individual-level data: A scoping review in health research |
| title_fullStr |
Current practices in missing data handling for interrupted time series studies performed on individual-level data: A scoping review in health research |
| title_full_unstemmed |
Current practices in missing data handling for interrupted time series studies performed on individual-level data: A scoping review in health research |
| title_sort |
Current practices in missing data handling for interrupted time series studies performed on individual-level data: A scoping review in health research |
| author |
Bazo-Alvarez J.C. |
| author_facet |
Bazo-Alvarez J.C. Morris T.P. Carpenter J.R. Petersen I. |
| author_role |
author |
| author2 |
Morris T.P. Carpenter J.R. Petersen I. |
| author2_role |
author author author |
| dc.contributor.author.fl_str_mv |
Bazo-Alvarez J.C. Morris T.P. Carpenter J.R. Petersen I. |
| dc.subject.none.fl_str_mv |
Segmented regression |
| topic |
Segmented regression Interrupted time series analysis Missing data Multiple imputation Scoping review https://purl.org/pe-repo/ocde/ford#2.02.04 |
| dc.subject.es_PE.fl_str_mv |
Interrupted time series analysis Missing data Multiple imputation Scoping review |
| dc.subject.ocde.none.fl_str_mv |
https://purl.org/pe-repo/ocde/ford#2.02.04 |
| description |
This study was funded by the National Institute for Health Research (NIHR) School for Primary Care Research, project number 444. JCB was sponsored by FONDECYT- CONCYTEC (grant contract number 231-2015- FONDECYT). TPM, TMP and JRC were supported by the Medical Research Council (grant numbers MC_UU_12023/ 21 and MC_UU_12023/29). The study sponsors only had a funding role in this research. Thus, the researchers worked with total independence from their sponsors. |
| publishDate |
2021 |
| dc.date.accessioned.none.fl_str_mv |
2024-05-30T23:13:38Z |
| dc.date.available.none.fl_str_mv |
2024-05-30T23:13:38Z |
| dc.date.issued.fl_str_mv |
2021 |
| dc.type.none.fl_str_mv |
info:eu-repo/semantics/review |
| format |
review |
| dc.identifier.uri.none.fl_str_mv |
https://hdl.handle.net/20.500.12390/2988 |
| dc.identifier.doi.none.fl_str_mv |
https://doi.org/10.2147/CLEP.S314020 |
| dc.identifier.scopus.none.fl_str_mv |
2-s2.0-85111702945 |
| url |
https://hdl.handle.net/20.500.12390/2988 https://doi.org/10.2147/CLEP.S314020 |
| identifier_str_mv |
2-s2.0-85111702945 |
| dc.language.iso.none.fl_str_mv |
eng |
| language |
eng |
| dc.relation.ispartof.none.fl_str_mv |
Clinical Epidemiology |
| dc.rights.none.fl_str_mv |
info:eu-repo/semantics/openAccess |
| dc.rights.uri.none.fl_str_mv |
https://creativecommons.org/licenses/by/4.0/ |
| eu_rights_str_mv |
openAccess |
| rights_invalid_str_mv |
https://creativecommons.org/licenses/by/4.0/ |
| dc.publisher.none.fl_str_mv |
Dove Medical Press Ltd |
| publisher.none.fl_str_mv |
Dove Medical Press Ltd |
| dc.source.none.fl_str_mv |
reponame:CONCYTEC-Institucional instname:Consejo Nacional de Ciencia Tecnología e Innovación instacron:CONCYTEC |
| instname_str |
Consejo Nacional de Ciencia Tecnología e Innovación |
| instacron_str |
CONCYTEC |
| institution |
CONCYTEC |
| reponame_str |
CONCYTEC-Institucional |
| collection |
CONCYTEC-Institucional |
| repository.name.fl_str_mv |
Repositorio Institucional CONCYTEC |
| repository.mail.fl_str_mv |
repositorio@concytec.gob.pe |
| _version_ |
1844883111241842688 |
| spelling |
Publicationrp00647600rp06748600rp06746600rp06747600Bazo-Alvarez J.C.Morris T.P.Carpenter J.R.Petersen I.2024-05-30T23:13:38Z2024-05-30T23:13:38Z2021https://hdl.handle.net/20.500.12390/2988https://doi.org/10.2147/CLEP.S3140202-s2.0-85111702945This study was funded by the National Institute for Health Research (NIHR) School for Primary Care Research, project number 444. JCB was sponsored by FONDECYT- CONCYTEC (grant contract number 231-2015- FONDECYT). TPM, TMP and JRC were supported by the Medical Research Council (grant numbers MC_UU_12023/ 21 and MC_UU_12023/29). The study sponsors only had a funding role in this research. Thus, the researchers worked with total independence from their sponsors.Objective: Missing data can produce biased estimates in interrupted time series (ITS) analyses. We reviewed recent ITS investigations on health topics for determining 1) the data management strategies and statistical analysis performed, 2) how often missing data were considered and, if so, how they were evaluated, reported and handled. Study Design and Setting: This was a scoping review following standard recommendations from the PRISMA Extension for Scoping Reviews. We included a random sample of all ITS studies that assessed any intervention relevant to health care (eg, policies or programmes) with individual-level data, published in 2019, with abstracts indexed on MEDLINE. Results: From 732 studies identified, we finally reviewed 60. Reporting of missing data was rare. Data aggregation, statistical tools for modelling population-level data and complete case analyses were preferred, but these can lead to bias when data are missing at random. Seasonality and other time-dependent confounders were rarely accounted for and, when they were, missing data implications were typically ignored. Very few studies reflected on the consequences of missing data. Conclusion: Handling and reporting of missing data in recent ITS studies performed for health research have many shortcomings compared with best practice. © 2021 Bazo-Alvarez et al.Fondo Nacional de Desarrollo Científico y Tecnológico - FondecytengDove Medical Press LtdClinical Epidemiologyinfo:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by/4.0/Segmented regressionInterrupted time series analysis-1Missing data-1Multiple imputation-1Scoping review-1https://purl.org/pe-repo/ocde/ford#2.02.04-1Current practices in missing data handling for interrupted time series studies performed on individual-level data: A scoping review in health researchinfo:eu-repo/semantics/reviewreponame:CONCYTEC-Institucionalinstname:Consejo Nacional de Ciencia Tecnología e Innovacióninstacron:CONCYTEC#PLACEHOLDER_PARENT_METADATA_VALUE##PLACEHOLDER_PARENT_METADATA_VALUE##PLACEHOLDER_PARENT_METADATA_VALUE##PLACEHOLDER_PARENT_METADATA_VALUE#20.500.12390/2988oai:repositorio.concytec.gob.pe:20.500.12390/29882024-05-30 15:26:11.323https://creativecommons.org/licenses/by/4.0/info:eu-repo/semantics/openAccesshttp://purl.org/coar/access_right/c_14cbinfo:eu-repo/semantics/closedAccessmetadata only accesshttps://repositorio.concytec.gob.peRepositorio Institucional CONCYTECrepositorio@concytec.gob.pe#PLACEHOLDER_PARENT_METADATA_VALUE##PLACEHOLDER_PARENT_METADATA_VALUE##PLACEHOLDER_PARENT_METADATA_VALUE##PLACEHOLDER_PARENT_METADATA_VALUE#<Publication xmlns="https://www.openaire.eu/cerif-profile/1.1/" id="624984ce-2233-4d95-b941-0d19bb8775f1"> <Type xmlns="https://www.openaire.eu/cerif-profile/vocab/COAR_Publication_Types">http://purl.org/coar/resource_type/c_1843</Type> <Language>eng</Language> <Title>Current practices in missing data handling for interrupted time series studies performed on individual-level data: A scoping review in health research</Title> <PublishedIn> <Publication> <Title>Clinical Epidemiology</Title> </Publication> </PublishedIn> <PublicationDate>2021</PublicationDate> <DOI>https://doi.org/10.2147/CLEP.S314020</DOI> <SCP-Number>2-s2.0-85111702945</SCP-Number> <Authors> <Author> <DisplayName>Bazo-Alvarez J.C.</DisplayName> <Person id="rp00647" /> <Affiliation> <OrgUnit> </OrgUnit> </Affiliation> </Author> <Author> <DisplayName>Morris T.P.</DisplayName> <Person id="rp06748" /> <Affiliation> <OrgUnit> </OrgUnit> </Affiliation> </Author> <Author> <DisplayName>Carpenter J.R.</DisplayName> <Person id="rp06746" /> <Affiliation> <OrgUnit> </OrgUnit> </Affiliation> </Author> <Author> <DisplayName>Petersen I.</DisplayName> <Person id="rp06747" /> <Affiliation> <OrgUnit> </OrgUnit> </Affiliation> </Author> </Authors> <Editors> </Editors> <Publishers> <Publisher> <DisplayName>Dove Medical Press Ltd</DisplayName> <OrgUnit /> </Publisher> </Publishers> <License>https://creativecommons.org/licenses/by/4.0/</License> <Keyword>Segmented regression</Keyword> <Keyword>Interrupted time series analysis</Keyword> <Keyword>Missing data</Keyword> <Keyword>Multiple imputation</Keyword> <Keyword>Scoping review</Keyword> <Abstract>Objective: Missing data can produce biased estimates in interrupted time series (ITS) analyses. We reviewed recent ITS investigations on health topics for determining 1) the data management strategies and statistical analysis performed, 2) how often missing data were considered and, if so, how they were evaluated, reported and handled. Study Design and Setting: This was a scoping review following standard recommendations from the PRISMA Extension for Scoping Reviews. We included a random sample of all ITS studies that assessed any intervention relevant to health care (eg, policies or programmes) with individual-level data, published in 2019, with abstracts indexed on MEDLINE. Results: From 732 studies identified, we finally reviewed 60. Reporting of missing data was rare. Data aggregation, statistical tools for modelling population-level data and complete case analyses were preferred, but these can lead to bias when data are missing at random. Seasonality and other time-dependent confounders were rarely accounted for and, when they were, missing data implications were typically ignored. Very few studies reflected on the consequences of missing data. Conclusion: Handling and reporting of missing data in recent ITS studies performed for health research have many shortcomings compared with best practice. © 2021 Bazo-Alvarez et al.</Abstract> <Access xmlns="http://purl.org/coar/access_right" > </Access> </Publication> -1 |
| score |
13.904966 |
Nota importante:
La información contenida en este registro es de entera responsabilidad de la institución que gestiona el repositorio institucional donde esta contenido este documento o set de datos. El CONCYTEC no se hace responsable por los contenidos (publicaciones y/o datos) accesibles a través del Repositorio Nacional Digital de Ciencia, Tecnología e Innovación de Acceso Abierto (ALICIA).
La información contenida en este registro es de entera responsabilidad de la institución que gestiona el repositorio institucional donde esta contenido este documento o set de datos. El CONCYTEC no se hace responsable por los contenidos (publicaciones y/o datos) accesibles a través del Repositorio Nacional Digital de Ciencia, Tecnología e Innovación de Acceso Abierto (ALICIA).
