similar to: factanal

I was wondering whether the following inconsistency of the promax rotation function with the results of a promax rotation using SAS should be considered a bug in the promax function of R. Any comments will be highly appreciated. The following is a loading matrix obtained from a varimax rotation in SAS: # Factor loadings after varimax rotation x <- t(array(c(0.78107, 0.35573,

Hi, everyone, This is a little silly, but I cant figure out the algorithm behind lm.fit function used in the context of promax rotation algorithm: The promax function is: promax <- function(x, m = 4) { if(ncol(x) < 2) return(x) dn <- dimnames(x) xx <- varimax(x) x <- xx$loadings Q <- x * abs(x)^(m-1) U <- lm.fit(x, Q)$coefficients d <-

Dear R-devel list members, Ben Fairbank draw it to my attention that factanal() (in the stats package) doesn't report factor correlations for oblique rotations. Looking at the source, I see that factanal also doesn't save the factor-transformation (rotation) matrix from which these correlations can be computed. I've modified the source, attached below, so that the transformation

--=-hiYzUeWcRJ/+kx41aPIZ Content-Type: text/plain; charset="UTF-8" Content-Transfer-Encoding: 8bit Hi, on March 10 I filed a wishlist bug report asking for the inclusion of some changes to factanal() and the associated print method. The changes were originally proposed by John Fox in 2005; they make print.factanal() display factor correlations if factanal() is called with rotation =

I am performing a large (105 variable) factor analysis with factanal, specifying promax rotation. I kow that some loadings over 1.0 are not unsual with that rotation, but I have some as large as 1.2, which seems extreme. I am skirting the assumptions of the model by using responses on a 7-point rating scale as data; I may have to go back and compute polychoric correlations instead of product

Hi, I found a discrepancy between results in R and Stata for a factor analysis with a promax rotation. For Stata: . *rotate, factor(2) promax* (promax rotation) Rotated Factor Loadings Variable | 1 2 Uniqueness -------------+-------------------------------- pfq_amanag~y | -0.17802 0.64161 0.70698 pfq_bwalk_~ø | 0.72569 0.05570

In some documentation for a package I am working on I have > \code{\link[stats]{varimax}} > \code{\link[stats]{promax}} The link to varimax works, but not the one to promax. Promax is an alias under \name{varimax}. This kind of link works within a package, but I'm not sure if it is suppose to work when it is a link to another package. Is this a known limitation or bug, or

Full_Name: conor dolan Version: 1.4.0 OS: windows98 Submission from: (NULL) (146.50.170.247) On the basis of Lawley and Maxwell's explanation in Factor Analysis as a Statistical Method (London: Butterworth, 1971), the following line in the promax routine (library, mva): attr(z, "covariance") <- crossprod(U) should be attr(z, "covariance") <- solve(crossprod(U))

Hi R users, I need some help in the followings: I'm doing factor analysis and I need to extract the loading values and the Proportion Var and Cumulative Var values one by one. Here is what I am doing: > fact <- factanal(na.omit(gnome_freq_r2),factors=5); > fact$loadings Loadings: Factor1 Factor2 Factor3 Factor4 Factor5 b1freqr2 0.246 0.486 0.145

Hi, In a discussion of factor analysis in "Using Multivariate Statistics" by Tabachnick and Fidell, two matrices are singled out as important for interpreting an exploratory factor analysis (EFA) with an oblique promax rotation. One is the "structure matrix". The structure matrix contains the correlations between variables and factors. However, these correlations may be

Hi: How i can make Varimax and Promax Rotation in R 0.63 thanks Jorge M. A. Magalhães -.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.- r-help mailing list -- Read http://www.ci.tuwien.ac.at/~hornik/R/R-FAQ.html Send "info", "help", or "[un]subscribe" (in the "body", not the subject !) To: r-help-request at

Dear R users, I have been doing rotation on Principal components analyse, with varimax function and promax. Following those changes, I cannot find now how to get the spatial evolution and the variance. Indeed, with the function princomp that has been used to get the principal components, arguments such as $scores and $sdev were available to get the spatial evolution and the variance, with

Dear R users, I have been doing some eof analysis using princomp function, then the eof results were rotated with varimax and promax functions. Those functions are working fine. However, after their uses, I cannot find how to obtain the temporal evolution and the variance of the obtain components, as varimax and promax does not have the arguments $scores and $sdev. If any body, know how to

I have data set with binary responses. I would like to conduct polychoric principal component analysis (pPCA). I know there are several packages used in PCA but I could not find one that directly estimate pPCA and graph the individuals and variables maps. I will appreciate any help that expand these reproducible scripts. #How to conduct polychoric principal component analysis pPCA using #either

Hello I seem to find only two types of rotation for the factanal function in R, the Varimax and Promax, but is it possible to run a orthogonal and oblique rotations in R? Thanks in advance Rosario

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Le 29/11/2017 ? 08:26, Sorin Srbu a ?crit?: > If updated, the instrument software will break, like in an atomic mushroom > cloud, rendering critical hardware non-working and lab people standing > outside my office with torches, pitch-forks and all the shebang. > Yupp, unfortunately that's the current state of some lab equipment > manufacturers that use RHEL as a base...

Hi, I make a weibull survival regression using suvreg function. Bu when I try to get the P values from anova, it give me NAs: I'm using R 2.4.0 and survival 2.29 Look: m <- survreg(Surv(tempo,censor)~grupo*peso) anova(m) Df Deviance Resid. Df -2*LL P(>|Chi|) NULL NA NA 148 966.6416 NA grupo -2 25.6334407 146 941.0081 NA

Hi, I make a weibull survival regression using suvreg function. Bu when I try to get the P values from anova, it give me NAs: I'm using R version 2.4.0 Patched (2006-11-25 r39997) and survival 2.30 library Look: m <- survreg(Surv(tempo,censor)~grupo*peso) anova(m) Df Deviance Resid. Df -2*LL P(>|Chi|) NULL NA NA 148 966.6416 NA grupo

Dear all,I am a new user of WinBUGS and need your help. After running the following code, I got parameters of beta0 through beta4 (stats, density), but I don't know how to get the prediction of the last value of h, the variable I set to NA and want to model it using the following code.Does anyone can given me a hint? Any advice would be greatly appreciated.Best