Biostatistical Design and Analysis Using R: A Practical Guide by Murray Logan

Author:Murray Logan [Logan, Murray]
Language: eng
Format: mobi
Publisher: Wiley
Published: 2011-09-23T04:00:00+00:00

(iii) independent of one another - this assumption must be addressed at the design and collection stages and cannot be compensated for laterc.

Violations of these assumptions reduce the reliability of the analysis.

10.5 Robust classification (ANOVA)

There are a number of alternatives to ANOVA that are more robust (less sensitive) to conditions of either non-normality or unequal variance. Welch’s test adjusts the degrees of freedom to maintain test reliability in situations where populations are normally distributed but unequally varied. Alternatively, Randomization tests repeatedly shuffle the observations randomly, each time calculating a specific test statistic so as to build up a unique probability distribution for the test statistic for the collected data and thus make no assumptions about the distribution of the underlying population. Such tests do not assume observations were collected via random sampling, however they do assume that populations are equally varied.

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