search for: oldvar

Hello everyone, I have a variable with several categories and I want to convert this into dummy variables and do logistic regression on it. I used model.matrix to create dummy variables but it always picked the smallest one as the reference. For example, model.matrix(~.,data=as.data.frame(letters[1:5])) will code 'a' as '0 0 0 0'. But I want to code another category as

Hi, I've been trying to sort this out for the past week. I had a RedHat 7.3 desktop install with a disk dying on it. The desktop has two disks on it - one configured with /, /usr and /boot (this was the bad disk) and the second had /var and /home. I obtained a replacement disk and initially tried copying the /, /usr and /boot filesystems to the new disk but this ended up being a problem. In

I have a rather large data set (about 30 predictor variables) I need to preform a logistic regression on this data. My response variable is binary. My code looks like this: mylogit <- glm(Enrolled ~ A + B + C + ... + EE, data = data, family = binomial(link="logit")) with A,B,C, ... as my predictor variables. Some categorical, some continuous, some binary. I run the code and get

...-12 23:00:00" Now what I would like is to have more readable labels, such as 2010-W01 for the first week of 2010, 2009-W34 for the 34th week in 2009, etc....is there an easier way to achieve that than having to write out the all recode sintax: library(car) dataset$newvar <- recode(dataset$oldvar, " c('2009-03-30 00:00:00')='2009-W13'; c('2009-04-06 00:00:00')='2009-W14'; # etc... c('2010-12-05 23:00:00')='2009-W48'; c('2010-12-12 23:00:00')='2009-W49'; # etc...this part should be updated with time unless I'll find...