[R] Problem with using flexmix for regression mixtures

Hi there, I would like to conduct a mixture regression analysis with the flexmix Package. Was just playing around with the function stepFlexmix() and did not get a foot into the door. When I run the stepFlexmix-function, I get the following error (actually a list of errors that repeats this sent

Re: [R] Metafor: Differences between two categories of a moderator

Hi Wolfgang that's good news. One further small follow-up question: When I conduct multiple comparisons via the relevel-command: should I adjust the p-value? Thanks in advance, Holger -- View this message in context: http://r.789695.n4.nabble.com/Metafor-Differences-between-two-categories-of-a-

[R] Metafor: Differences between two categories of a moderator

Hi there, when using the metafor package for testing mixed effects models with categorical moderators, I get a regression table reporting betas. These betas are mean differences between a certain category in the effect size to the reference category (intercept). In addition, the QM-tests allows te

Re: [R] Simulating correlations with varying sample sizes

Wow, this was fast and helpful! Thank you very much. Best, Holger -- View this message in context: http://r.789695.n4.nabble.com/Simulating-correlations-with-varying-sample-sizes-tp3526231p3526288.html Sent from the R help mailing list archive at Nabble.com. ___

[R] Simulating correlations with varying sample sizes

Hi there, I would like to draw 10 correlations from a bivariate population - but every draw should be done with a different sample size. I thought I could to this with a loop: r=numeric(10) #Goal vector N = c(1000,100,80,250,125,375,90,211,160,540) #Sample size vector for(i in 1:10) { data <

Re: [R] Hausman Test

Thank you both very much ! This helped me a lot. Best, Holger -- View this message in context: http://r.789695.n4.nabble.com/Hausman-Test-tp3220016p3220123.html Sent from the R help mailing list archive at Nabble.com. __ R-help@r-project.org mailing

Re: [R] Hausman Test

Dear Achim, thank you very much. One follow up question. The Hausman-test always gives me a p-value of 1 - no matter how small the statistic is. I now generated orthogonal regressors (X1-X3) and the test gives me Hausman specification test for consistency of the 3SLS estimation data:

[R] Hausman Test

Hi, can anybody tell me how the Hausman test for endogenty works? I have a simulated model with three correlated predictors (X1-X3). I also have an instrument W for X1 Now I want to test for endogeneity of X1 (i.e., when I omit X2 and X3 from the equation). My current approach: library(system

Re: [R] Hausman test for endogeneity

Dear Arne, this looks promising! Thank you very much. Best, Holger -- View this message in context: http://r.789695.n4.nabble.com/Hausman-test-for-endogeneity-tp2969522p2970564.html Sent from the R help mailing list archive at Nabble.com. __ R-help@

Re: [R] Hausman test for endogeneity

Dear Liviu, thank you very much. After inspecting the options, I *guess* that systemfit is what I need. However, I absolutely don't understand how it works. I searched long for a detailed documentation (beyond the rather cryptic standard documentation) but found none. Has anybody references/adv

[R] Hausman test for endogeneity

Dear folks, can anybody point me in the right direction on how to conduct a hausman test for endogeneity in simultanous equation models? Best, Holger -- View this message in context: http://r.789695.n4.nabble.com/Hausman-test-for-endogeneity-tp2969522p2969522.html Sent from the R help mailing

[R] Eliminating case numbers in a dendrogram

Hi folks, I conducted a hierarchical cluster analysis. As I wanted to illustrate the result, I created a dendrogram with the code plot(as.dendrogram(fit),sub="",xlab="",ylab="Heterogeneity",nodePar = list(lab.cex=.5,pch=NA,xlab="")) However, the dendrogram contains the case numbers and, as I ha

[R] Box-Cox Transformation: Drastic differences when varying added constants

Dear experts, I tried to learn about Box-Cox-transformation but found the following thing: When I had to add a constant to make all values of the original variable positive, I found that the lambda estimates (box.cox.powers-function) differed dramatically depending on the specific constant chos