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If I wanted to fit a logit model and account for clustering of observations, I would do something like: library(Design) f <- lrm(Y1 ~ X1 + X2, x=TRUE, y=TRUE, data=d) g <- robcov(f, d$st.year) What would I do if I wanted to do the same thing with a probit model? ?robcov says the input model must come from the Design package, but the Design package appears not to do probit? Thanks very

Dear list, I have an irregular time series saved and exported as a zoo object. What is the trick to force zoo to ignore the missing dates when reading it back in? Thanks. > str(g) ?zoo? series from 1948-11-02 to 2012-11-06 Data: num [1:14881, 1:8] 1 0 0 0 0 0 0 0 0 0 ... - attr(*, "dimnames")=List of 2 ..$ : NULL ..$ : chr [1:8] "session" "midterm"

Can someone please show me how to smooth time series data that I have in the form of a zoo object? I have a monthly economies series and all I really need is to see a less jagged line when I plot it. If I do something like s <- smooth.spline(d.zoo$Y, spar = 0.2) plot(predict(s,index(d.zoo)), xlab = "Year") # not defined for Date objects and if I do something like

I have a data frame containing monthly observations of the 'density' of each US state, recorded in variables named "density.AL", "density.AK", "density.AZ", and so on for all 50 states. The data frame (called d) also contains a variable called "Date" which is encoded as a string in the format "Jan-09", "Feb-09", etc. I also have

What's the neat way to create a dummy from a list? The code below is not replicable, but hopefully self-explanatory... d$treatment<-rep(1,length(d)) notreat<-c("AR", "DE", "MS", "NY", "TN", "AK", "LA", "MD", "NC", "OK", "UT", "VA") #i would really like this to work:

Dear list, I am trying to replicate some Stata results but having a tough time doing it in R. The goal is to obtain a difference-in-difference estimate in a model with simple state fixed effects. The "state" variable is a factor, but some levels are missing. It appears that Stata automatically recognizes this and works around it. It also automatically pick "ME" as the base