similar to: replacement has 13665 rows, data has 13664

Hello. I am trying to pull out one country from a time series of 5 waves. For example I need Norway from the 5th wave. This is new to me. Typically, I work with country specific surveys. data = norway I have attached a .tiff of the codebook showing the variable names for Norway and the wave. They appear to be Norway = v218 and wave = v15. But perhaps I am wrong and this is part of the

Hello, I have a dataset which I am calling RB09. I am trying to match the questions in the code book with variable codes. It is not very intuitive. example: names(RB09) [1] "ea1" "eaf1" "eaf1a" "eaf2" "eaf2_7" [6] "eaf3" "eafimpun" "eafunpun" "evimpmar"

Hi everyone, Does anyone here has experience using MICE to impute missing value? I am having problem to pool the imputed dataset for a MANOVA test, could you give me some advice please? Here is my code: > library(mice) >

Hello, I am VERY new to R (one week) and I am trying to run a multinomial logit model. The model I am using is > model1 <- multinom(Y ~ X1 + X2 + , ..., Xn) if I put in > summary(model1) I get #Error in function (classes, fdef, mtable) : unable to find an inherited method for function "fitted", for signature "multinom" and if I put in > coef(model1)

Hello, all. I've been working on this for sometime and was almost at the end/ last chunk of code i would need.... When I received an error. Rather than go to bed and think about it in the morning, I messed with my data and now I am not getting anything. I was up until 4am trying to fix this. Zip files of my data are attached (the data which ends in 'a' matches with wvsA and the

Hi!! This is my first time with llvm. I'm still learning and really need help. I wrote only one Function Pass, which uses another Function Pass (blockNrs), and registered this: RegisterPass<FunctionAnalysis> X("gasched", "Genom Scheduling Pass"); When I compile my sourcecode, everything was okay. But when I tried to test it, i got this error Message: nicole at

Dear All: I am interested in multinomial logit models (function multinon, library nnet) but I'm having troubles in choose whether to define the predictors as factors or not. I had posted earlier this example (thanks for the reply ronggui): worms<- data.frame(year= rep(2000:2004, c(3,3,3,3,3)),age=rep(1:3,5),

Hi I would like to eliminate a large number of lines of the dataframe df1 The lines to delete are given here by the values of Mat (ex : 2,4,7,10). but I have a large number (300) values of Mat dput(df1) structure(list(Mat = c(1, 1, 1, 1, 1, 1, 2, 2, 2, 2, 3, 3, 3, 3, 3, 4, 4, 4, 4, 4, 5, 5, 5, 5, 5, 5, 6, 6, 6, 6, 6, 6, 7, 7, 7, 7, 7, 7, 7, 8, 8, 8, 8, 8, 8, 8, 9, 9, 9, 9, 9, 9, 10, 10, 10, 11,

If one estimates a model using multinom, is it possible to perform the omnibus LR test ( the analogue to omnibus F in linear models ) using the output from multinom ? The residual deviance is there but I was hoping I could somehow pull out the deviance based on just using an intercept ? Sample code is below from the CAR book but I wasn't sure how to do it based on that example. Thanks

All: I am new to R and would like your help in identifying the appropriate process to follow in order to modify the output from an existing package. I've had difficulty finding an answer online, perhaps because I am using incorrect terminology. A package that I am using (mmlcr) invokes another package (multinom). An output of multinom is the standard errors, but this output is not

Dear R users, The nnet package includes the multinom method for the confint function. The R Help file (?confint) for the generic function in the stats package and the help files for the glm and nls methods in the MASS package indicate that one can use the "parm" argument as "a specification of which parameters are to be given confidence intervals, either a vector of numbers or

Hello, I am working with s.multinom() from the ade4package. I tried to plot the results of my %PCA (via the function dudi.pca()) followed by a MCOA (mcoa()). But when I give my variables to s.multinom() I get the following Error message: Error in FUN(1:14[[1L]], ...) : number 1 profile without data I know that it has to do with one (or two?) of the first arguments (kpca,sglmarkerfrq) but I just

I have RedHat linux 9 with R 1.8. I'm estimating models with multinom with a dependent variable that has 3 different values. Sometimes the models run fine and I can understand the results. Sometimes when I put in another variable, I see an indication that the estimation did work, but then I can't get the summary method to work. It's like this: > votemn1 <-

I am trying to create a LaTex table based on a multinom (nnet) object using the stargazer command. I have created a small data frame to demonstration the problem: data <- data.frame(age=1:21, hight=20:40, ed=c(1,2,3,1,2,3,1,2,3,1,2,3,1,2,3,1,2,3,1,2,3)) data$ed <- as.factor(data$ed) I then make a multinomial model using the command multinom from the nnet package: model <- multinom(ed ~

Hello, I apologize if this seems like an obvious question, but I have been looking everywhere and have yet to find an answer. I am doing a multinomial regression with multinom() in the nnet package. I have a 3 level ordered response (ordered()) variable and 4 predictors, 3 of which are numerical and one which is an ordered factor (also ordered()) with 5 levels (a, b, c, d, e). My question is in

Hi!! It's me again. I guess that there is a problem in the Makefile of my source code. But I don't know where. Could you please verify it? The Makefile is written like this: # Makefile for Genetic Algorithm Pass CXXFLAGS = -Wall -I/iss/fpga3/nicole/galib247/ LDFLAGS= -L/iss/fpga3/nicole/galib247/ga/ -lga -Wl,-E # Path to top level of LLVM heirarchy LEVEL=../../../ # Name of the

Hello List and thanks in advance for all of your help, I am trying implement a permutation test of a multinomial logistic regression ('multinom' within the nnet package). In the end I want to compare the parameter estimate from my data to the distribution of randomized parameter estimates. I have figured out how to permute my dependent variable (MNNUM) x number of times, apply

Hi, I am searching for methods to compare regression models with an ordered categorical response variable (polr versus multinom). The pattern of predictions of both methods (using the same predictor variables) is quite different and the AIC is smaller for the multinom approach. I guess polr has more strict premises for the structure of the response variable, which methods can be used to test for

Is anyone aware of a way to check whether multinom has converged by checking a component of the output ? I'm not familar with nnet but, since multinom calls nnet , maybe there is an extra argument once can send to multinom to capture this information. Thanks.

Dear all, I'm fitting a multinom function to my dataset (multinom(outcome~age+K+D)) and I need to present my results on a poster. Does someone know a nice way of doing that? I think I saw in an archive that you cannot plot a multinom.object, is it true? Thank you by advance for your help, Cheers Camille