Re: [R] logistic regression in an incomplete dataset

Of Desmond D Campbell Sent: Monday, April 05, 2010 3:19 PM To: Emmanuel Charpentier Cc: r-help@r-project.org; Desmond Campbell Subject: Re: [R] logistic regression in an incomplete dataset Dear Emmanuel, Thank you. Yes I broadly agree with what you say. I think ML is a better strategy than complete case

Re: [R] logistic regression in an incomplete dataset

Dear Thomas, Thanks for your reply. Yes you are quite right (your example) complete case does not require MCAR, however as well as being a bit less robust than ML it is throwing away data. Missing Data in Clinical Studies, Geert Molenberghs, Michael Kenward, have a nice section in chapter 3

[R] logistic regression in an incomplete dataset

Dear all, I want to do a logistic regression. So far I've only found out how, in a dataset of complete cases. I'd like to do logistic regression via max likelihood, using all the study cases (complete and incomplete). Can you help? I'm using glm() with family=binomial(logit). If any covariate in

[R] logistic regression in an incomplete dataset

Dear all, I want to do a logistic regression. So far I've only found out how to do that in R, in a dataset of complete cases. I'd like to do logistic regression via max likelihood, using all the study cases (complete and incomplete). Can you help? I'm using glm() with family=binomial(logit).

[R] logistic regression in an incomplete dataset

Dear all, I want to do a logistic regression. So far I've only found out how to do that in R, in a dataset of complete cases. I'd like to do logistic regression via max likelihood, using all the study cases (complete and incomplete). Can you help? I'm using glm() with family=binomial(logit).

Re: [R] logistic regression in an incomplete dataset

Hello Desmond, The only way to not drop cases with incomplete data would be some sort of imputation for the missing covariates. JoAnn Desmond Campbell wrote: Dear all, I want to do a logistic regression. So far I've only found out how to do that in R, in a dataset of complete cases. I'd

Re: [R] logistic regression in an incomplete dataset

Dear Desmond, a somewhat analogous question has been posed recently (about 2 weeks ago) on the sig-mixed-model list, and I tried (in two posts) to give some elements of information (and some bibliographic pointers). To summarize tersely : - a model of information missingness (i. e. *why* are

Re: [R] logistic regression in an incomplete dataset

Dear JoAnn, Thank you very much for your reply. If that is the case I am surprised. I would have though ML could incorporate study cases with some missingness in them. Furthermore I believe ML estimates should generally be more robust than complete case based estimates. For unbiased estimates I

Re: [R] logistic regression in an incomplete dataset

Dear Emmanuel, Thank you. Yes I broadly agree with what you say. I think ML is a better strategy than complete case, because I think its estimates will be more robust than complete case. For unbiased estimates I think ML requires the data is MAR, complete case requires the data is MCAR

Re: [R] logistic regression in an incomplete dataset

On Mon, 5 Apr 2010, Desmond D Campbell wrote: Dear Emmanuel, Thank you. Yes I broadly agree with what you say. I think ML is a better strategy than complete case, because I think its estimates will be more robust than complete case. For unbiased estimates I think ML requires the data is MAR,