[R] Survey Data - comparing multiple groups
m@vz@@hmed @end|ng |rom utoronto@c@
Fri Aug 16 17:38:02 CEST 2019
Thank you so much for your response and apologies for the delay in responding. This has been helpful.
I have been looking into several other options over the last few weeks and been talking with statisticians as well and SAS seems to have some options that work for survey type of data. At this point, I am still exploring R and if I am able to provide additional feedback on this issue, I will post. I really appreciate your help. Thank you.
From: Abby Spurdle <spurdle.a using gmail.com>
Sent: July 27, 2019 9:39:49 PM
To: Mavra Ahmed <mavz.ahmed using utoronto.ca>
Cc: r-help using r-project.org <r-help using r-project.org>
Subject: Re: [R] Survey Data - comparing multiple groups
> I would like to be able to get p-values between the groups and be able to adjust for multiple comparisons and would appreciate if someone can guide me.
> I did convert my df into a svrepdesign object as follows:
> > df<-svrepdesign (data=df1, scale=1, repweights = df1[, 496:995], type="BRR", combined.weights=TRUE, weight=~WTS_P, na.rm=TRUE)
> therefore, I have called "df" as a svrepdesign however, from the survey package, the svyranktest is shown with svydesign only and not with svrepdesign. I could consider using other tests such as svyglm but am also having issues with it.
This is outside my area.
However, as no one else as responded, I'll offer some more comments.
Firstly, I'm doubtful the Kruskal Wallis test will give you pairwise p-values.
There are other tests for this.
It's also possible to create a matrix of p-values, using an arbitrary test, and then use a correction method.
However, I recommend caution with this.
Secondly, I don't know if the svyranktest() function will work with the svrepdesign object or not.
However, if not, I would assume that other functions in the package would work.
Either way, I'm wondering if you've created the svrepdesign object correctly.
In particular, "weight=~WTS_P" would assign a formula to weights, probably, which doesn't sound right.
And "repweights = df1[, 496:995]" looks questionable, because one, is has hundreds of columns, and two, you've already given that data in the first argument.
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