similar to: model frame and formula mismatch with latent class analysis poLCA

My problem is I have data with both categorial and numerical data, currently only the categorical number contains missing data, was wondering do I make a new dataframe containing only the categorical columns? How would you use Latent Class Model specifically poLCA to impute the missing data? http://www.sscnet.ucla.edu/polisci/faculty/lewis/pdf/poLCA-JSS-final.pdf The reason why I chose not to

Dear all, I'm an Sri Lankan undergraduate student. I'm also a total newbie to R. My aim is to use the poLCA package to do a latent class analysis. I found the documentation very helpful, but need to make a small clarification that has stumped me awhile. In my work, I need to make provision for conditional dependence. I'm told that poLCA lets you do that. Unfortunately, I

Hi, I am running some latent class models with civariates using poLCA in R, and have a question the meaning of some error messages. My model has 8 y-variables (dichotomous) and 2 x-variables (also dichotomous), and I am trialling different numbers of classes. When I run a 2-class model, the model runs fine without any error messages. I used the nrep = 10 option to avoid local maxima. Class %

Dear all, I have just sent a message asking about poLCA but I thought of another question I wanted to ask. I get the G^2 statistic in my output and want to test for its significance. I get that the degrees of freedom for the test are (S-1-p) where S is the number of different patterns observed and p is the number of estimated parameters. Are these the "residual degrees of freedom" that

Hello, I used a mac G5, R.2.1.1, and G77 3.4.4 and I would like to use and call a fortran subroutine. The trouble is that it seems I am not able to correctly load the compiled code. Here is what I have done: In the terminal this how I compiled my fortran code: R CMD SHLIB ~/Desktop/Fortan_kmeans/kmeans3.f There is the wrapper I have paste inside de kmeans3.f file: c

Hi everyone, I'm using the poLCA module for some analysis work. Basically, Im using the command >poLCA(f, data=response,nclass=2) This returns a poLCA object (a list) >From this data, I need to retrieve certain indexes, such as[[5]] as seen below. [[5]] Pr(1) Pr(2) Pr(3) class 1: 0 1.0 0.0 class 2: 0 0.5

Hello, I want to perform a latent class analysis using poLCA package. My formula is: substances <- cbind(subs1, subs2, subs3, subs4, subs5, subs6) ~ gender+age+education+income+occupation+urban+dbehavior+incarceration+treatment+depression+alcriteria I want to include sample weights in the model, I have read that poLCA does not take into account weights, but when I introduce them, it seems

Hi. I am trying to do a nonlinear regression on a set of data with Monod kinetics and Haldane inhibition. I am using the following commands to do the nonlinear regression: dce<-read.delim("data.txt", header = TRUE, sep = "\t", quote="\"", dec=".", fill = TRUE, comment.char="") dce.m1<-nls(rate~kmax*conc/(Ks+conc+((conc^2)/Ki),data=dce

Duncan, Do a quick check here on x86_64-apple-darwin10 with svn llvm and svn dragon-egg against release gcc 4.5.0, the results from the himenoBMTxpa benchmark compiled at -O3 look pretty good. With stock gcc-4.5.0, we get... Grid-size = M mimax = 128 mjmax = 128 mkmax = 256 imax = 127 jmax = 127 kmax =255 Start rehearsal measurement process. Measure the performance in 3 times. MFLOPS:

Hey there! I got a pseudo code and don't know how to apply it to R, maybe someone can help me: Input: A dataset X, kmax: maximum number of clusters, num_subsamples: number of subsamples. Output: S(i; k) - a distribution of similarities between partitions into k clusters of a reference clustering and clustering of subsamples; i = 1 to num_subsamples Requires: T = cluster(X): A hierarchical

Hi, I am working with -poLCA- which uses the package -scatterplot3d- in order to work. However, I work on a restricted server that is not online. The R-version installed there is 2.6. However, running library(poLCA) after installing the most recent -scatterplot3d- on the server leaves me with R telling me that scatterplot3d needs R-version 2.7 or a more recent versions. Since I cannot install the

Hi there, I have the following problem: I have a package called "polLCA" which has the following syntax: poLCA(formula, data) and needs the following formula definition: formula <- cbind(V1,V2,V3,...) So far so good. What I tried now was the following: #Get "data" with the "read.table" fuction data <- read.table("d:/ .....) #Select cols to use in the

What's the best approach to running latent class analysis with R? I've downloaded both randomLCA and poLCA packages, but I am interesting in running a standard LCA with individual records (not frequency table) as input data. Wen Gu John Jay College of Criminal Justice445 West 59 StreetNew York, NY 10029 wgu@gc.cuny.edu _________________________________________________________________

Dear all Last week, I posted a question and some of you spent their valuable time to respond. Thank you (once again). This time, after doing a lot of homework, I return with  a second question on the issue. I was advised to use poLCA for a Latent Class Analysis with covariates. The software works well, although I feel a bit uncomfortable with the fact that you need to run many times the

Hi Wonsun, can you please provide a testcase. Best wishes, Duncan. > I've noticed that LLVM does a bad job of optimizing array indexing > code for FORTRAN arrays declared using the ALLOCATABLE keyword. > > For example if you have something like the following: > > DOUBLE PRECISION,ALLOCATABLE,DIMENSION(:,:,:,:) :: QAV > ... > ALLOCATE( QAV(

This is my code i don't understand the error message: library(rgenoud) rm(list=ls()) set.seed(666) ######################################################### # As a first step, it is assumed that all input parameters are independent of ageing : ######################################################### InputDim <-20 # Max number of ageings in the inputs CPIRate <- rep(0.02 , InputDim ) #

Hi everyone? Does anybody know how can I estimate a Latent class multinomial (or conditional) logit using R? I have tried flexmix, poLCA, and they do not seem to support this model. thanks in advance adan -- View this message in context: http://r.789695.n4.nabble.com/Latent-class-multinomial-or-conditional-logit-using-R-tp4230083p4230083.html Sent from the R help mailing list archive at

Hi everyones, my function like; e <- rnorm(n=50, mean=0, sd=sqrt(0.5625)) x0 <- c(rep(1,50)) x1 <- rnorm(n=50,mean=2,sd=1) x2 <- rnorm(n=50,mean=2,sd=1) x3 <- rnorm(n=50,mean=2,sd=1) x4 <- rnorm(n=50,mean=2,sd=1) y <- 1+ 2*x1+4*x2+3*x3+2*x4+e x2[1] = 10 #influential observarion y[1] = 10 #influential observarion data.x <- matrix(c(x0,x1,x2,x3,x4),ncol=5) data.y

I've noticed that LLVM does a bad job of optimizing array indexing code for FORTRAN arrays declared using the ALLOCATABLE keyword. For example if you have something like the following: DOUBLE PRECISION,ALLOCATABLE,DIMENSION(:,:,:,:) :: QAV ... ALLOCATE( QAV( -2:IMAX+2,-2:JMAX+2,-2:KMAX+2,ND) ) ... DO L = 1, 5 DO K = K1, K2 DO J = J1, J2 DO I = I1, I2 II = I +

Just found because an old (written for S+) function of mine did label plots wrongly with R. Example --- inspired from example(qqnorm) --- data(precip) qqnorm(precip, ylab = "Precipitation [in/yr] ...") qqnorm(precip, ylab = "Precipitation [in/yr] ...", datax = TRUE) this is all "fine" -- `datax' is a switch that just switches the axes but keeps the