Focus on qualitative methods. Uses and abuses of the analysis of covariance.
OBJECTIVE: The analysis of covariance (ANCOVA) has two primary purposes: (a) to improve the power of a statistical analysis by reducing error variance, and (b) to statistically 'equate' comparison groups. In this article, we review the merits and demerits of these claims for ANCOVA. We recommend tha...
| Publicado en: | Research in Nursing & Health Vol. 21; no. 6; pp. 557 - 563 |
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| Autores principales: | , |
| Formato: | tables/charts Journal Article |
| Publicado: |
Wiley-Blackwell
1998
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| Acceso en línea: | Ver este registro en EBSCOhost |
| Sumario: | OBJECTIVE: The analysis of covariance (ANCOVA) has two primary purposes: (a) to improve the power of a statistical analysis by reducing error variance, and (b) to statistically 'equate' comparison groups. In this article, we review the merits and demerits of these claims for ANCOVA. We recommend that the method be limited primarily to randomized designs. We also recommend that researchers report tests of ANCOVA assumptions. That statistical packages make assumption tests challenging is not a good reason to avoid them entirely. And it is easy, not challenging, to report the simple correlations between covariates and dependent variables. In the case where the correlations are tiny, then there is no gain whatsoever to using ANCOVA. DESIGN: NA SETTING: NA POPULATION: NA INTERVENTIONS: AN MAIN OUTCOME MEASURE(S): NA RESULTS/CONCLUSIONS: NA [CINAHL abstract] |
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