Homoscedascity test for Two-Way ANOVA

Posted by aL3xa on Stack Overflow See other posts from Stack Overflow or by aL3xa
Published on 2010-05-29T00:26:29Z Indexed on 2010/05/29 0:32 UTC
Read the original article Hit count: 629

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r

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test

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variance

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anova

I've been using var.test and bartlett.test to check basic ANOVA assumptions, among others, homoscedascity (homogeniety, equality of variances). Procedure is quite simple for One-Way ANOVA:

bartlett.test(x ~ g)  # where x is numeric, and g is a factor
var.test(x ~ g)

But, for 2x2 tables, i.e. Two-Way ANOVA's, I want to do something like this:

bartlett.test(x ~ c(g1, g2))  # or with list; see latter:
var.test(x ~ list(g1, g2))

Of course, ANOVA assumptions can be checked with graphical procedures, but what about "an arithmetic option"? Is that manageable? How do you test homoscedascity in Two-Way ANOVA?

Homoscedascity test for Two-Way ANOVA

Posted by aL3xa on Stack Overflow See other posts from Stack Overflow or by aL3xa
Published on 2010-05-29T00:24:16Z Indexed on 2010/05/29 0:32 UTC
Read the original article Hit count: 629

Filed under:

r

|

anov

I've been using var.test and bartlett.test to check basic ANOVA assumptions, among others, homoscedascity (homogeniety, equality of variances). Procedure is quite simple for One-Way ANOVA:

bartlett.test(x ~ g)  # where x is numeric, and g is a factor
var.test(x ~ g)

But, for 2x2 tables, i.e. Two-Way ANOVA's, I want to do something like this:

bartlett.test(x ~ c(g1, g2))  # or with list; see latter:
var.test(x ~ list(g1, g2))

Of course, ANOVA assumptions can be checked with graphical procedures, but what about "an arithmetic option"? Is that, at all, manageable? How do you test homoscedascity in Two-Way ANOVA?

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