similar to: Error messages when attempting to calculate polychoric correlation matrices

Dear Professor Fox, Apologies for my oversight relating to the polychor command and thank you for your advice. I turned to the polychor command when trying to find an equivalent for the polychoric command found in the psych package (I am following a procedure outlined in Gadermann, Guhn & Zumbo, 2012 that uses this command rather than the polycor package) . The polychoric command is returning

Hello, I am running polychoric correlations on a dataset composed of 12 ordinal and binary variables (N =384), using the polycor package. One of the association (between 2 dichotomous variables) is very high using the 2-step estimate (0.933 when polychoric run only between the two variables; but 0.801 when polychoric run on the 12 variables). The same correlation run with ML estimate returns a

Hello. Using the polychor function > polychor(data[c(s1,s2)] ) for polychoric correlations of two ordinal variables in R takes a long time for N=7000 (20 minutes+) and significantly slows down my computer. Now, I have a pretty old computer, but it takes about 20 seconds for MPLUS to print out the complete polychoric correlation matrix for all 16 variables, while I am running the R function

Hi, I'm running this for a simulation study, so many combinations of parameter produce many predictions that I need to correlate with data. The problem ---------------- I'm using rating data with 3 to 5 categories (e.g., too low, correct, too high). The underlying continuous scales should be normal, so I chose the polychoric correlation. I'm using library(polychor) in its

Hi All, I produced a barplot and made a horizontal legend below the graph. Because the results are from a survey, there are three levels, namely strongly disagree/disagree, neutral and strongly agree/agree. > rownames(survey)[1] "Strongly disagree/disagree" "Neutral" "Strongly agree/agree" As in the output above, there is a large space

I am working on modifying a REDCap survey. The data dictionary column for the response field has the following value. 1, Strongly disagree | 2, Disagree | 3, Agree | 4, Strongly Agree | 5, Don't Know | 6, Refuse to Answer | 7, Not Applicable I am wanting to convert this so that it looks as follows: 1, A. Strongly disagree | 2, B. Disagree | 3, C. Agree | 4, D. Strongly Agree | 5, E.

Hi. Does anyone know whether the following error is a result of a bug or a feature? I can eliminate the error by making ML=F, but I would like to see the values of the cut-points and their variance. tmp.vec<-c(0, 0, 0 , 0 ,0 , 1, 0, 2, 0 , 0, 5 ,5 ,3 ,1, 0 , 1, 5, 10, 27, 20, 9, 0, 1, 1, 12, 29, 57, 34, 0, 0, 1, 2, 11, 31, 32) tmp.mat<-matrix(tmp.vec, nrow=7)

Hello, I am attempting to create a bar plot that contains a range of possible response values on the x-axis of 1 to 5 and contains barplots for the number of responses even in the event that there are 0 responses. For example, I have a data set that contains values of 2, 3, 4, and 5 but I would also like my graph to show that there are no 1's. I have attached the resulting graph. The

Hi I have used a polycor package for categorical correlation coefficients. I run the following script. But there were no results. Could you tell me how to correct the script? Thanks in advance, vars <- names(sdi) for (i in 1:length(vars)) { for (j in 1:length(vars)) { paste(vars[i]," and ", vars[j]) polychor(vars[i], vars[j]) # corr } } -- Kum-Hoe Hwang, Ph.D.Phone :

Hi, Is there any R library/package that calculates tetrachoric correlations from given marginals and Pearson correlations among ordinal variables? Inputs to polychor function in polycor package are either contingency tables or ordinal data themselves. I am looking for something that takes marginal distributions and Pearson correlation as inputs. For example, Y1=(1,2,3) with P(Y1=1)=0.3,

Dear all, I get a strange error when I find polychoric correlations with the ML method, which I have been able to reproduce using randomly-generated data. What is wrong? I realize that the data that I generated randomly is a bit strange, but it is the only way that I duplicate the error message. > n<-100 > test.x<-rnorm(n, mean=0, sd=1) > test.c<-test.x + rnorm(n, mean=0,

Hi, I have probably overlooked something obvious, but could anybody help me with following, please? Trying to make regression analysis. I have a huge dataframe with results from National Opinion Survey on Crime and Justice (www.abacon.com/fox/) with two variables G5 and N3 which are imported to R as ordered factors: > levels(noscj$G5) [1] "Strongly agree" "Agree"

I am having trouble generating a graph. I want to know the % of respondents who answered that they "strongly agree" or "agree" the "America owes R's ethnic group a better chance" (BTTRCHNC) and I want to organize it by racial group (RACESHRT). "BTTRCHNC" is organized ordinally from 1 through 5 with 1=Strongly Agree, 5=Strongly Disagree

About two years ago there was a thread about this which suggested that at that time nobody had these coefficients ready to go. (a) has anyone in the meanwhile programmed them? (b) I think I can see how to do the tetrachoric one with mvtnorm on similar lines to an example on the help page so will try that if nobody else already has (c) looking at the polychoric one makes me realise yet again

I have a 96x34 array of Likert scale data (96 cases, 34 items) of ordered factors (strongly disagree, disagree, neutral, agree, strongly agree) that are coded numerically (1 through 5). I cannot seem to convert this array (in any class) into ordered vectors. I have all the cases as vectors of ordered factors, but any which way I reassemble those vectors loses the ordered factors and converts

hi all, I am having a hard time trying to find out what''s wrong with my setup. It used to work smoothly until I decided out of the blue to do a selfupdate and upgrade outdated on MacPort, then things started going south very quickily. Since MacPort kinda broke, I pull it all out and re-install the ports I have before, which went pretty smoothly. Then to my surprise any command I

On Wed, Jun 1, 2016 at 7:22 PM, Hal Finkel <hfinkel at anl.gov> wrote: > > ________________________________ > > From: "C Bergström" <cbergstrom at pathscale.com> > To: "Hal Finkel" <hfinkel at anl.gov> > Cc: "llvm-dev" <llvm-dev at lists.llvm.org>, "cfe-dev" > <cfe-dev at lists.llvm.org>,

Hi All, I'm working on a class example that demonstrates one way to deal with factors and their labels. I create a function called myLabeler and apply it with lapply. It works on the whole data frame when I subscript it as in lapply( myQFvars[ ,myQFnames ], myLabeler ) but does not work if I leave the [] subscripts off. I would appreciate it if anyone could tell me why. The program below

Has anyone tried using erb and builder in the same file? Either .rxml or .rhtml? I''m wanting to do some think like the following: xml.div(''id''=>''menu'') {|xml| link_to "create race", :controller=>"derby", :action=>"new" } Thanks, -- Tom. -- "Nothing will ever be attempted, if all possible objections must

Help with survey data: Hello R colleagues, I hope this is an appropriate place to direct this question. It relates specifically to the comparability of a 5-point likert to a 4- point likert scale. One question in my dataset asks "How much should be done to reduce the gap between rich and poor" Much more, somewhat more, about the same, somewhat less and much less. The second