similar to: Editing Partial Correlation Matrix

I am currently working with R's polycor package and I have encountered a problem. I tried to follow the steps as outlined in the sem.pdf file where a CFA model is run using polychoric correlations. Every time I run the command sem(model, data, N=.), I get the following warning message: Warning message: In if (orthogonal) { : the condition has length > 1 and only the first element will be

Dear list members, I've uploaded a new package, called polycor (version 0.5-0), to CRAN. The package has functions for computing polychoric and polyserial correlations, either by maximum-likelihood (in which case, standard errors are available) or by faster approximations. There's also a function to compute "heterogeneous" correlation matrices composed of product-moment,

Dear list members, I've uploaded a new package, called polycor (version 0.5-0), to CRAN. The package has functions for computing polychoric and polyserial correlations, either by maximum-likelihood (in which case, standard errors are available) or by faster approximations. There's also a function to compute "heterogeneous" correlation matrices composed of product-moment,

I am doing Principal Component Analysis (PCA) on assets data for household income prediction. The problem is that the assets data are rank ordered (usually binary ... possess car/don't possess car), so the normal correlation is inappropriate for the calculation of the PCA. Instead one has to use the polychoric correlation coefficient. It uses the "random.polychor.pa" package.

Dear gavin, I think that it's likely that Jim meant the hetcor() function in the polycor package. Best, John -- John Fox, Professor Emeritus McMaster University Hamilton, Ontario, Canada web: https://socialsciences.mcmaster.ca/jfox/ On 2023-02-21 5:42 p.m., gavin duley wrote: > Hi Jim, > > On Tue, 21 Feb 2023 at 22:17, Jim Lemon <drjimlemon at gmail.com> wrote: >>

Hi Sorry for the rather long message. I am trying to use the cfa command in the lavaan package to run a CFA however I am unsure over a couple of issues. I have @25 dichotomous variables, 300 observations and an EFA on a training dataset suggests a 3 factor model. After defining the model I use the command fit.dat <- cfa(model.1, data=my.dat, std.lv = T, estimator="WLSMV",

Hi there, Am I correct to believe that tetrachoric correlation is a special case of polychoric correlation when there are only two levels to the ordered factor? Thus it should be okay to use hetcor from the polycor package to build a matrix of correlations for binary variables? If this is true, how can one estimate 95% confidence intervals for the correlations? My guess would be mat =

I am trying to run a confirmatory factor analysis using the SEM package. My data are ordinal. I have read http://socserv.mcmaster.ca/jfox/Misc/sem/SEM-paper.pdf. When I apply the hetcor function, I receive the following error: Error in checkmvArgs(lower = lower, upper = upper, mean = mean, corr = corr, : at least one element of 'lower' is larger than 'upper' Example:

Hello all, I'd like to calculate the mean correlation within a cluster and understand if it's significantly >0. I'm using packages 'geomorph' and 'paleomorph'. #Simulate an array A <- array ( rep ( 1 : 36 , by = 4 ), dim = c ( 12 , 3 , 4 )) #Load 'geomorph' package and superimpose coordinates test.gpa <- gpagen ( A , print.progress = FALSE ) #Load

I have been using the hetcor function in the polycor package. When I don't specify the use option everything runs smoothly. However, when I specify use either as "pairwise.complete.obs" or "complete.obs" I get this error Error in optim(rho, f, control = control, hessian = TRUE, method = "BFGS") : non-finite value supplied by optim Is this an error in

Hello R Users, While I have attempted to dig into the R help files and I have not identified the answer to these questions, I apologize in advance if my questions were answered in the past. I also recognize that one of my questions unfortunately verges on statistical rather than code territory. I have two rather unrelated questions about using the sem and polycor packages for a relatively

Dear R Experts, I have a query concerning SEMs in a multilevel context. I have an unbalanced panel where children are nested in families, which in turn are nested in districts. The problem is the following: the outcome variable of interest is measured at the child level but the (explanatory) latent variable is at the family level. Most the variables are discrete and I am able to fit the model

Hi I have used the hetcor function on dataset which consists of about 40 variables. Since the output is quite large entire output is not visible on the R screen. Is there a way, I can retrieve the output that is not visible? Thank you Regards Upasna -- --------------------------------------------------------------------- Upasna Sharma Research Scholar Shailesh J. Mehta School of Management,

Dear friends, I'm using R to produce the following Factor Analysis: > matriz.cor<-hetcor(matrix(as.factor(data), ncol=variables, byrow=T))$correlations > factanal(x=data, factors=2, covmat=matriz.cor, scores='regression') Then the screen output shows the following message: Error en factanal(x = data, factors = 2, covmat = matrix, : requested scores without

Hello fellow Rers, I have a no-doubt simple question which is turning into a headache so would be grateful for any help. I want to do a principal components analysis directly on a correlation matrix object rather than inputting the raw data (and specifying cor = TRUE or the like). The reason behind this is I need to use polychoric correlation coefficients calculated with John Fox's

Hi, I'm using the SEM package to estimate a model with a binary variabele as dependent variable. In the literature I have to use then the correlation matrix, made by function hetcor(). Literature also says that the standard errors are not correct then. My question is if somebody knows what the impact is on the estimated coefficients. If I want to calculate the estimated probability I see a

Hello, It has been found that SEM analysis using polychoric correlations + maximum likelihood estimator produces incorrect test statistics and standard errors (e.g., Flora, D. B., & Curran, P. J. (2004). An Empirical Evaluation of Alternative Methods of Estimation for Con?rmatory Factor Analysis With Ordinal Data. Psychological Methods, 9(4), 466-491). Standard errors can be dealt with by

hi merlin, Check out the hetcor package. Jim On Sat, Sep 2, 2017 at 6:25 AM, <merlinverdecia at infomed.sld.cu> wrote: > I would be very grateful if you would tell me how I can find the degree of > correlation between a nominal dependent variable and an independent ordinal > variable. The nominal variable has only two levels: YES and NO. > thank you very much in advance >

Hi Gavin, I can't work through this right now, but I would start by looking at the 'hetcor' package to get the correlations, or if they are already in the return object, build a plot from these. Jim On Wed, Feb 22, 2023 at 4:24 AM gavin duley <gduley at gmail.com> wrote: > > Hi! > > Apologies if this is not the correct place to ask. I am attempting a > MFA

Dear community I'm pretty new to R and I'm trying to do a Point-baserial correlation for a nominal dichotomous variable with a interval scaled variable. It works fine, but the output just shows me the correlation and nothing else (p-Value would be important). I tried it with the following codes: - biseral.cor() - cor.biseral() - I also tried a polyserial() I've found on this