Assess the normality of my data by shapiro wilk but are not normally distributed.

That is not parametric test would you recommend?

- Thread starter speedzeta
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- Tags normal distribution shapiro wilk stata 12

Assess the normality of my data by shapiro wilk but are not normally distributed.

That is not parametric test would you recommend?

Since you have paired samples (i.e., the same people measured at two times

on the same variable), you can use the McNemar test for paired proportions.

The Stata version that works with data in a data set is -mcc-. The Stata

version that works as an "immediate" or "interactive" command with summary

data is -mcci-.

If you are not familiar with the NcNemar test, it similar to Chi-Square, but

Chi-Square can only be used on independent samples. When the samples

are paired (i.e., non-independent), you should use McNemar.

on the same variable), you can use the McNemar test for paired proportions.

The Stata version that works with data in a data set is -mcc-. The Stata

version that works as an "immediate" or "interactive" command with summary

data is -mcci-.

Code:

`help mcc`

Chi-Square can only be used on independent samples. When the samples

are paired (i.e., non-independent), you should use McNemar.

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ssc install emh

An example of its use was posted on Statalist by its author last year.

@bukharin, I agree completely. I read @speedzeta's original post too quickly and thought she had four separate variables rather than a single factor variable with four levels.

The post by @speedzeta was clear, so the misunderstanding about @speedzeta's variable(s) was completely mine.

Both the McNemar test I mentioned and the Friedman test suggested by @bukharin both ignore the apparent ordinal nature of the factor levels in @speedzeta's variable and therefore lose information. To address the ordinal nature of the factor variable, @speedzeta could use that factor as the outcome variable in an ordinal logistic regression (-help ologit- in Stata) and make the time period variable the predictor.

UCLA ATS has good help pages on -ologit- at http://www.ats.ucla.edu/stat/stata/dae/ologit.htm and http://www.ats.ucla.edu/stat/stata/output/stata_ologit_output.htm.

The post by @speedzeta was clear, so the misunderstanding about @speedzeta's variable(s) was completely mine.

Both the McNemar test I mentioned and the Friedman test suggested by @bukharin both ignore the apparent ordinal nature of the factor levels in @speedzeta's variable and therefore lose information. To address the ordinal nature of the factor variable, @speedzeta could use that factor as the outcome variable in an ordinal logistic regression (-help ologit- in Stata) and make the time period variable the predictor.

UCLA ATS has good help pages on -ologit- at http://www.ats.ucla.edu/stat/stata/dae/ologit.htm and http://www.ats.ucla.edu/stat/stata/output/stata_ologit_output.htm.

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- Friedman test can be used for ordinal data

- but since it's a paired comparison you can just use a Wilcoxon signed rank test (-help signrank-). This would be by far the easiest approach

- a typical ordinal logistic regression would not take into account the paired nature of the data

This is not for the current poster but just for the dialogue between us.

You are right about -ologit- ignoring the paired nature of the data,

but I did want to mention that there are models of ordinal logit

that can handle paired comparisons with ordered categorical data.

See for example http://www.jstor.org/discover/10.23...2&uid=70&uid=4&uid=3739256&sid=21102924459057.

This is an interesting discussion, but I do agree that the -signrank- test

will be fine for this poster's needs.