search for: intercept2

...V1), and so on... V1 V2 "intercept" "coeff" 1 0.6931694 0.05797771 intercept1 coeff1 2 -1.4069786 0.23983307 intercept1 coeff1 3 -1.4901708 0.45079601 intercept1 coeff1 4 0.2215696 1.87888983 intercept1 coeff1 5 -0.5828106 0.90376622 intercept2 coeff2 6 -0.7607985 0.71419938 intercept2 coeff2 7 0.1273495 0.06199312 intercept2 coeff2 8 -0.5612245 1.02223971 intercept2 coeff2 9 -0.1439178 0.92135354 intercept3 coeff3 10 -1.1011662 0.02894731 intercept3 coeff3 11 -0.4098710 -0.01231322 intercept3 coeff3 12...

...c(ifelse(data.mult==0,1,0),ifelse(data.mult==1,1,0),ifelse(data.mult==2,1,0),ifelse(data.mult==3,1,0)) temp<-list(time=2-choice, status=choice, intercept1=c(rep(0,length(data.mult)),rep(1,length(data.mult)),rep(0,length(data.mult)),rep(0,length(data.mult))), intercept2=c(rep(0,length(data.mult)),rep(0,length(data.mult)),rep(1,length(data.mult)),rep(0,length(data.mult))), intercept3=c(rep(0,length(data.mult)),rep(0,length(data.mult)),rep(0,length(data.mult)),rep(1,length(data.mult))), xvar1=c(rep(0,length(data.mult)),rep(1,length(data.mul...

...rix(c(400,80,80,80,80,400,80,80,80,80,400,80,80,80,80,400),4,4 ) mu2<-c(0,0,0) LE<-8^2 #Linking Error Sigma2<-diag(LE,3) sample.size<-5000 N<-100 #Number of datasets #Take a single draw from VL distribution vl.error<-mvrnorm(n=N, mu2, Sigma2) intercept1 <- 0 slope1 <- 0 intercept2 <- 0 slope2 <- 0 for(i in 1:N){ temp <- data.frame(ID=seq(1:sample.size),mvrnorm(n=sample.size, mu,Sigma)) temp$X5 <- temp$X1 temp$X6 <- temp$X2 + vl.error[i,1] temp$X7 <- temp$X3 + vl.error[i,2] temp$X8 <- temp$X4 + vl.error[i,3] long<-reshape(temp, idvar=&quot...

Hi,I have a result from polr which I fit a univariate variable (of ordinal data) with probit function. What I would like to do is to overlay the plot of my fitted values with the different intercept for each level in my ordinal data. I can do something like:lines(rep(intercept1, 1000), seq(from=0,to=max(fit),by=max(fit)/1000))where my intercept1 is, for example, the intercept that breaks between

...were a way to specify that initial covariance values of 0 are to be fixed at 0, then the problem would be solved (I think). For example, with 2 subgroups, the "value" matrix would look like 1 0 r 0 0 1 0 r r 0 1 0 0 r 0 1 Where the corresponding row/column order is Intercept,1 intercept2, slope 1, slope 2. I've been digging through Pinheiro and Bates, as well as these help forums and files, but couldn't find info on writing or modifying pdMat classes. In SAS proc mixed, such a model is specified fairly easily by using the group option: /* SAS CODE FRAGMENT WITHIN PROC MI...