[R] calculate response probabilities using sem-analysis

Hi everyone, I just conducted a structural equation model for estimating a response model. This model should predict the probability that someone is responding to a direct mailing. I used the sem package for this. When I have my coefficients I want to know how well my model predicts the probabilit

[R] calculate response probabilities using sem-analysis

Hi everyone, I just conducted a structural equation model for estimating a response model. This model should predict the probability that someone is responding to a direct mailing. I used the sem package for this. When I have my coefficients I want to know how well my model predicts the probabili

[R] Confidence/prediction interval for choice probabilities mlogit

Hi, I have estimated a multinomial logit model with use of the mlogit-package for my choice data. I predicted the probabilities for each choice, using the formula: pred1 <- exp(B1*X1.1 + B2*X2.1 + B3*X3.1) pred2 <- exp(B1*X1.2 + B2*X2.2 + B3*X3.2) pred3 <- exp(B1*X1.3 + B2*X2.3 + B3*X3.3) sumpred

[R] Difference MNP-package and rmnpGibbs from bayesm-package

Hi all, For my research I have to use a Multinomial Probit model. I saw that there are two packages, that include a method to estimate my parameters. The first one is the MNP-package of Imai and van Dyk. The second one is part of the bayesm-package of Rossi. The results for both packages are not t

[R] LCA (e1071 package): error

Hello, I will use the lca method in the e1071 package. But I get the following error: Error in pas[j, ] <- drop(exp(rep(1, nvar) %*% log(mp))) : number of items to replace is not a multiple of replacement length Does anybody know this error and knows what this means? Kind regards, Tryntsje _

[R] Output mlogit package (multinomial logisti c regression)‏

Hello, For my master thesis I conducted a conjoint analysis. Using the mlogit-package of Yves Croissant I should be able to analyse my choice data. I read the whole program of mlogit, but I do not understand how my coefficients must be interpreted. Are they a result of P(Y=i) or are they P(Y=i)/P(