[R] logistic regression enquiry
John Fox
jfox at mcmaster.ca
Sun Jun 4 12:59:33 CEST 2006
Dear Bob,
If I follow this properly, this is just a binomial logistic regression,
where, for each of your 26 observations, you have a certain number of
"successes" (positive instances) and "failures" (negative ones).
Fitting a binomial logit model is easily accommodated by the glm()
function. Probably the simplest approach is to prepare one observation
for each study which has the number of successes and failures for that
study, and put these together as the columns of a two-column matrix on
the left-hand side of the model; on the right-hand-side you'd have the
usual specification for a model formula. Thus, something like
model <- glm(cbind(successes, failures) ~ ..., family=binomial,
data=Dataset)
(where the ... represents the RHS of your model) should do the trick.
I hope this helps,
John
On Sun, 04 Jun 2006 20:39:29 +1000
Bob Green <bgreen at dyson.brisnet.org.au> wrote:
> I am hoping for some advie regarding the following scenario.
>
> I have data from 26 studies that I wanted to analyse using logistic
> regression. Given the data was from studies and not individuals I was
>
> unsure how I would perform this in R. When analysed in SPSS,
> weighting was
> used so that each study was included twice. Where "use" occurred, a
> value
> of 1 was assigned and was weighted by the value for the variable
> "positive". In the second instance, where use did not occur a value
> of 0
> was assigned and was weighted by the variable "negative". Taking the
> first
> study below, use = 1 would be weighted by 28 and use =0, it would be
> weighted by 117 (the total study N =145). If this data is scrambled
> in
> transmission I can send a csv version.
>
> My questions:
>
> 1. is change required to the data format or is modification of the
> usual
> code required?
> 2. what is the best R package for performing logistic regression?
>
>
> Any assistance is much appreciated
>
> regards
>
> Bob Green
>
>
>
>
> In SPSS, each study was included I weighted the , though am unsure
> how I
> would format the data
>
>
> medyear where who dxbroad firstep standard age sex positive negative
> 89 3 2 1 0 0 31.5 71 28 117.00
> 98 2 2 1 0 1 48.0 62 15 72.00
> 98 4 1 1 0 0 45.2 61 42 57.00
> 89 3 0 1 0 1 28.7 63 19 48.00
> 99 2 2 1 0 1 34.7 73 27 73.00
> 88 3 0 1 0 1 30.6 58 26 57.00
> 94 1 1 1 0 1 36.3 81 70 124.00
> 96 3 1 1 0 1 40.0 57 27 40.00
> 96 2 2 1 0 1 33.1 64 9 41.00
> 88 2 0 1 1 0 29.5 47 30 202.00
> 98 1 2 0 0 1 39.3 60 246 734.00
> 97 4 0 0 0 1 38.4 67 17 85.00
> 92 3 0 1 0 1 34.3 67 15 127.00
> 88 2 0 1 0 1 46 9 90.00
> 85 3 0 1 0 1 30.3 64 58 87.00
> 94 3 0 1 0 1 38.8 47 47 126.00
> 88 3 0 1 0 1 33.8 54 25 134.00
> 92 3 0 1 1 1 67 157.00
> 90 3 0 1 1 1 26.0 52 17 101.00
> 90 3 0 1 0 0 39 32.00
> 90 2 0 1 0 1 36.1 38 10 173.00
> 90 2 0 1 0 1 38.9 53 64 383.00
> 97 2 0 1 0 1 31.5 61 12 52.00
> 99 1 1 1 0 1 25 56.00
> 100 4 1 1 0 1 45.0 62 46 270.00
> 101 2 0 1 0 1 32.4 100 33 92.00
>
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--------------------------------
John Fox
Department of Sociology
McMaster University
Hamilton, Ontario, Canada
http://socserv.mcmaster.ca/jfox/
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