Dear Hui-Lin,
S-news asks subscribers to try contacting the author of the add-on
library first. -Thanks
lrm does not accept a frequency weight at present.
Be sure to give modeling functions the basic categorical predictors instead
of deriving dummy variables yourself. So the answer to your question is
to build a data frame that repeats each row of your data up to the needed
frequency, then do lrm(response ~ cheese, data=newdataframe). I'll leave
it to someone else to devise an elegant way to expand the data frame
by the frequency variable. Something along the lines of
newdataframe <- original.data.frame[s,]
will do it once a very long vector s is created (using rep) that has duplicate
row
numbers. The length of s will equal the sum of the frequencies.
lrm does not handle frequency weights because all of my datasets have at least
one continuous variable in them.
-Frank Harrell
-----Original Message-----
From: Hui-Lin Hu <huilin@u.washington.edu>
To: s-news@wubios.wustl.edu <s-news@wubios.wustl.edu>
Date: Monday, March 23, 1998 9:19 PM
Subject: [S] ordinal outcomes
>
>
>Hi there,
>
>This should be easy for those who has ever used Harrell's lrm function.
>It is the first time for me to use this function, but I have not been able
>to make it work. I am not sure what went wrong. Could any of you help me?
>What exactly should be written in () of lrm()?
>
>Here is the cheese data from page 175 of McCullagha and Nelder.
>How to use lrm() to get the logistic treatment effects on page 176 of this
>book?
>
>col 1 (x1) = 1 if Cheese = A
>col 2 (x2) = 1 if Cheese = B
>col 3 (x3) = 1 if Cheese = C
>col 4 (y) : Response category
>col 5 (wt) : Count in each cell of the crosstable "Cheese * Categorical
> Response"
>
> 1 0 0 1 0
> 1 0 0 2 0
> 1 0 0 3 1
> 1 0 0 4 7
> 1 0 0 5 8
> 1 0 0 6 8
> 1 0 0 7 19
> 1 0 0 8 8
> 1 0 0 9 1
> 0 1 0 1 6
> 0 1 0 2 9
> 0 1 0 3 12
> 0 1 0 4 11
> 0 1 0 5 7
> 0 1 0 6 6
> 0 1 0 7 1
> 0 1 0 8 0
> 0 1 0 9 0
> 0 0 1 1 1
> 0 0 1 2 1
> 0 0 1 3 6
> 0 0 1 4 8
> 0 0 1 5 23
> 0 0 1 6 7
> 0 0 1 7 5
> 0 0 1 8 1
> 0 0 1 9 0
> 0 0 0 1 0
> 0 0 0 2 0
> 0 0 0 3 0
> 0 0 0 4 1
> 0 0 0 5 3
> 0 0 0 6 7
> 0 0 0 7 14
> 0 0 0 8 16
> 0 0 0 9 11
>
>
>
>
>
>
>
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