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Hi, I have a vector and a list, with data I would like to multiply together. So for instance I have a vector s: [[1]] [1] 44308 [[2]] [1] 4371 Also, I have a list d: [[1]] [1] 1201 6170 2036 2927 1625 1391 2074 1453 3172 3027 4691 3719 1185 320 2071 1027 1046 1186 1403 580 1382 440 8 174 [[2]] [1] 6521 688 2678 3409 3033 1608 3618 1461 1836 2104 879 1095 2630 1591 2986 703 2548

Hello! When I am analyzing proportion data, I usually apply logistic regression using a glm model with binomial family. For example: m <- glm( cbind("not realized", "realized") ~ v1 + v2 , family="binomial") However, sometimes I don't have the number of cases (realized, not realized), but only the proportion and thus cannot compute the binomial model. I just

Well, this would seem to work: e <- data.frame(Score = Score , Country = factor(Country) , Time = Time) ncountry <- nlevels(e$Country) func= function(dat,idx) { if(length(unique(dat[idx,'Country'])) < ncountry) NA else coef(lm(Score~ Time + Country,data = dat[idx,])) } B <- boot(e, func, R=1000) boot.ci(B, index=2, type="perc")

Hi I have data for events in rows, with columns for person and date. Each person may have more than one event; tC <- textConnection(" Person date bob 1/1/00 bob 1/2/00 bob 1/3/00 dave 1/7/00 dave 1/8/00 dave 1/10/00 kevin 1/2/00 kevin 1/3/00 kevin 1/4/00 ") data <- read.table(header=TRUE, tC) close.connection(tC) rm(tC) I would like to add a new column to my dataframe containing