Methods for handling missing data in palliative care research.
Palliat Med
; 20(8): 791-8, 2006 Dec.
Article
em En
| MEDLINE
| ID: mdl-17148533
ABSTRACT
Missing data is a common problem in palliative care research due to the special characteristics (deteriorating condition, fatigue and cachexia) of the population. Using data from a palliative study, we illustrate the problems that missing data can cause and show some approaches for dealing with it. Reasons for missing data and ways to deal with missing data (including complete case analysis, imputation and modelling procedures) are explored. Possible mechanisms behind the missing data are missing completely at random, missing at random or missing not at random. In the example study, data are shown to be missing at random. Imputation of missing data is commonly used (including last value carried forward, regression procedures and simple mean). Imputation affects subsequent summary statistics and analyses, and can have a substantial impact on estimated group means and standard deviations. The choice of imputation method should be carried out with caution and the effects reported.
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Coleções:
01-internacional
Base de dados:
MEDLINE
Assunto principal:
Cuidados Paliativos
/
Coleta de Dados
/
Interpretação Estatística de Dados
/
Modelos Estatísticos
Tipo de estudo:
Clinical_trials
/
Prognostic_studies
/
Risk_factors_studies
Limite:
Adult
/
Aged
/
Aged80
/
Female
/
Humans
/
Male
/
Middle aged
Idioma:
En
Revista:
Palliat Med
Assunto da revista:
SERVICOS DE SAUDE
Ano de publicação:
2006
Tipo de documento:
Article
País de afiliação:
Reino Unido