multinomial

问题 Can someone help with JAGS code for a Bayesian multinomial logistic model with one categorical X variable (Dirichlet prior)? My representative sample is the matrix "z" in the code below that represents the 3 outcomes and "site", in the bottom line of code, is the categorical x variable. I can get the code that estimates each of the 3 outcomes but I'm stumped on how to add a categorical X (hospital site). I would like to use the first outcome, z[, 1], as the reference and 'a' as the reference

问题 Can someone help with JAGS code for a Bayesian multinomial logistic model with one categorical X variable (Dirichlet prior)? My representative sample is the matrix "z" in the code below that represents the 3 outcomes and "site", in the bottom line of code, is the categorical x variable. I can get the code that estimates each of the 3 outcomes but I'm stumped on how to add a categorical X (hospital site). I would like to use the first outcome, z[, 1], as the reference and 'a' as the reference

来源： https://stackoverflow.com/questions/59162157/formatting-multiple-models-on-top-of-each-other-in-stargazer

来源： https://stackoverflow.com/questions/59162157/formatting-multiple-models-on-top-of-each-other-in-stargazer

来源： https://stackoverflow.com/questions/59162157/formatting-multiple-models-on-top-of-each-other-in-stargazer

问题 I use the multinom() function from the nnet package to run the multinomial logistic regression in R. The nnet package does not include p-value calculation and t-statistic calculation. I found a way to calculate the p-values using the two tailed z-test from this page. To give one example of calculating a test statistic for a multinom logit (not really a t-stat, but an equivalent) I calculate the Wald's statistic: mm<-multinom(Empst ~ Agegroup + Marst + Education + State, data = temp,weight

问题 I use the multinom() function from the nnet package to run the multinomial logistic regression in R. The nnet package does not include p-value calculation and t-statistic calculation. I found a way to calculate the p-values using the two tailed z-test from this page. To give one example of calculating a test statistic for a multinom logit (not really a t-stat, but an equivalent) I calculate the Wald's statistic: mm<-multinom(Empst ~ Agegroup + Marst + Education + State, data = temp,weight

问题 Problem: I need to estimate a set of multinomial logistic multilevel models and can’t find an appropriate R package. What is the best R package to estimate such models? STATA 13 recently added this feature to their multilevel mixed-effects models – so the technology to estimate such models seems to be available. Details: A number of research questions require the estimation of multinomial logistic regression models in which the outcome variable is categorical. For example, biologists might be

问题 I'm using the function multinom from the nnet package to run a multinomial logistic regression. In multinomial logistic regression, as I understand it, the coefficients are the changes in the log of the ratio of the probability of a response over the probability of the reference response (i.e., ln(P( i )/P( r ))=B 1 +B 2 *X... where i is one response category, r is the reference category, and X is some predictor). However, fitted(multinom(...)) produces estimates for each category, even the

问题 My Problem I just started using the R library 'choicemodelr' and succeded in getting some beta values as a solution. But I wonder how do I assign these values to the specific attribute-levels. As a result I only get values for A1B1, A1B2, A1B3,... etc. How does this generic output generally connect to my Design? Didn't find a hint in the documentation. Neither for the choicemodelr libraray, nor the bayesm library (rhierMnlRwMixture) to which it is connected to. I hope you can help me with