Using a nonparametric bootstrap to obtain a confidence interval for Pearson's r with cluster randomized data: a case study.
J Prim Prev
; 30(5): 497-512, 2009 Sep.
Article
em En
| MEDLINE
| ID: mdl-19685290
ABSTRACT
A nonparametric bootstrap was used to obtain an interval estimate of Pearson's r, and test the null hypothesis that there was no association between 5th grade students' positive substance use expectancies and their intentions to not use substances. The students were participating in a substance use prevention program in which the unit of randomization was a public middle school. The bootstrap estimate indicated that expectancies explained 21% of the variability in students' intentions (r = 0.46, 95% CI = [0.40, 0.50]). This case study illustrates the use of a nonparametric bootstrap with cluster randomized data and the danger posed if outliers are not identified and addressed. EDITORS' STRATEGIC IMPLICATIONS Prevention researchers will benefit from the authors' detailed description of this nonparametric bootstrap approach for cluster randomized data and their thoughtful discussion of the potential impact of cluster sizes and outliers.
Texto completo:
1
Base de dados:
MEDLINE
Assunto principal:
Análise por Conglomerados
/
Intervalos de Confiança
/
Modelos Estatísticos
/
Estatísticas não Paramétricas
Tipo de estudo:
Clinical_trials
/
Risk_factors_studies
Limite:
Child
/
Humans
País como assunto:
America do norte
Idioma:
En
Ano de publicação:
2009
Tipo de documento:
Article