On May 27, 2015, at 10:10 AM, Kengo Inagaki wrote:
> I am currently working on a health care related project using R. I am
> learning R while working on data analysis.
>
> Below is the part of the data in which i am encountering a problem.
>
>
> Case# Sex Therapy1 Therapy2 Outcome
>
> 1 male no
> no Alive
>
snipped mangled data sent in HTML
>
>
> "Outcome" is the response variable and "Sex", "Therapy1", "Therapy2" are
> predictor variables.
>
> All of the predictors are significantly associated with the outcome by
> univariate analysis.
>
> Logistic regression runs fine with most of the predictors when "Sex" and
> "Therapy1" are not included at the same time (This is a part of table that
> I cut out from a larger table for ease of
>
> presentation and there are more predictors that i tested).
Please examine the data before reaching for ridge regression:
What does this show: ...
with(a, table(Sex, Therapy1) )
I predict you will see a zero cell entry. The read about "complete separation"
and the so-called "Hauck-Donner effect".
--
David.
>
> However, when "Sex" and "Therapy1" are included in logistic regression
> model at the same time, standard error inflates and p value gets close to 1.
>
> The formula used is,
>
>
>
>> Model<-glm(Outcome~Sex+Therapy1,data=a,family=binomial) #I assigned a
> vector "a" to represent above table.
>
>
>
> After doing some reading, I suspect this might be collinearity, as vif
> values (using "vif()" function in car package) were sky high (8,875,841 for
> both "Sex" and "Therapy1").
>
> Learning that ridge regression may be a solution, I attempted using
> logisticRidge {ridge} using the following formula, but i get the
> accomapnying error message.
>
>
>
>> logisticRidge(a$Outcome~a$Sex+a$Therapy1)
>
>
>
> Error in ifelse(y, log(p), log(1 - p)) :
>
> invalid to change the storage mode of a factor
>
>
>
> At this point I do not have an idea how to solve this and would like to
> seek help.
>
> I really really appreciate your input!!!
>
> [[alternative HTML version deleted]]
>
David Winsemius
Alameda, CA, USA
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