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2006 Feb 01
1
glm-logistic on discrete-time methods with individual and aggregated data
...rm(list = ls()) # working one timesIND <- c(rep(1:4, 3), 1, rep(1:2,2), rep(1:3 , 2), rep(1:4, 2)) statusIND <- c(rep(0 ,12), 1, rep(0:1,2), rep(c(0,0,1), 2), rep(c(0,0,0,1),2)) datiIND <- as.data.frame(cbind(timesIND, statusIND)) datiIND$timesIND <- as.factor(datiIND$timesIND) timesAGG <- c( 1:4, 1, 1:2, 1:3, 1:4) statusAGG <- c(rep(0,4), 1, 0:1, c(0,0,1), c(0,0,0,1)) weightAGG <- c(rep(3,4), 1, rep(2,2), rep(2,3), rep(2,4)) datiAGG <- as.data.frame(cbind(timesAGG, statusAGG, weightAGG)) datiAGG$timesAGG <- as.factor(datiAGG$timesAGG) coe...