The treatment of incomplete data: Reporting, analysis, reproducibility, and replicability.
Soc Sci Med
; 209: 169-173, 2018 07.
Article
en En
| MEDLINE
| ID: mdl-29807627
Proper analysis and reporting of incomplete data continues to be a challenging task for practitioners from various research areas. Recently Nguyen, Strazdins, Nicholson and Cooklin (NSNC; 2018) evaluated the impact of complete case analysis and multiple imputation in studies of parental employment and health. Their work joins interdisciplinary efforts to educate and motivate scientists across the research community to use principled statistical methods when analyzing incomplete data. Although we fully support and encourage work in parallel to NSNC's, we also think that further actions should be taken by the research community to improve current practices. In this commentary, we discuss some aspects and misconceptions related to analysis of incomplete data, in particular multiple imputation. In our view, the missing data problem is part of a larger problem of research reproducibility and replicability today. Thus, we believe that improving analysis and reporting of incomplete data will make reproducibility and replicability efforts easier. We also provide a brief checklist of recommendations which could be used by members of the scientific community, including practitioners, journal editors, and reviewers to set higher publication standards.
Palabras clave
Texto completo:
1
Colección:
01-internacional
Base de datos:
MEDLINE
Asunto principal:
Proyectos de Investigación
/
Recolección de Datos
Tipo de estudio:
Guideline
Límite:
Humans
Idioma:
En
Revista:
Soc Sci Med
Año:
2018
Tipo del documento:
Article
País de afiliación:
Estados Unidos
Pais de publicación:
Reino Unido