Dear Tim, Thanks. the first vector
y<-c(0,1,1,0,0,1,0,0,1,1,1,0,1,1,1,0,0,0,0,1) is the disease status y=
(1=Case,0=Control). The covariate age, smoking status and hypertension
are independent(uncorrelated). The logistic regression (unconditional)
will used. But I need to compare other models with logistic regression
instead of fitting it directly to logistic regression.
There is no matching on the data to use conditional logistics regression.
Best,
Hana
On 6/15/22, Ebert,Timothy Aaron <teb...@ufl.edu> wrote:
> Disease status is missing from the sample data.
> Are age, disease, smoking, and/or hypertension correlated in any way or are
> they independent (correlation=0)?
> Are the correlations large enough to adversely influence your model?
> Tim
>
> -----Original Message-----
> From: R-help <r-help-boun...@r-project.org> On Behalf Of anteneh asmare
> Sent: Wednesday, June 15, 2022 7:29 AM
> To: r-help@r-project.org
> Subject: [R] Model Comparision for case control studies in R
>
> [External Email]
>
> y<-c(0,1,1,0,0,1,0,0,1,1,1,0,1,1,1,0,0,0,0,1)
> age<-c(45,23,56,67,23,23,28,56,45,47,36,37,33,35,38,39,43,28,39,41)
> smoking<-c(0,1,1,1,0,0,0,0,0,1,1,0,0,1,0,1,1,1,0,1)
> hypertension<-c(1,1,0,1,0,1,0,1,1,0,1,1,1,1,1,1,0,0,1,0)
> data<-data.frame(y,age,smoking,hypertension)
> data
> model<-glm(y~age+factor(smoking)+factor(hypertension), data, family =
> binomial(link = "logit"),na.action = na.omit)
> summary(model)
> from above sample data I want to study a case-control study on male
> individuals with my response variable y, disease status (1=Case,
> 0=Control) with covariates age, smoking status(1=Yes, 0=No)  and
> hypertension, hypertensive (1=Yes, 0=No). I want to fit the model to predict
> the disease status using at least two different methods. And to make model
> comparisons. I think logistic regression will be the best fit for this case
> control study. Do we have other options in addition to logistic regression?
> My objective is to fit the model to predict the disease status using at
> least two different methods.
> Kind regards,
> Hana
>
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