similar to: factor analysis - constraints

--=-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 =

Hi All, There were lot of diffrences in the R and SPSS results for Exploratory Factor Analysis.why is it so ?I used standard factor analysis functions like:-- factanal(m, factors=3, rotation="varimax") princomp(m, cor = FALSE, scores = TRUE, subset = rep(TRUE, nrow(as.matrix(m)))) print(summary(princomp(m, cor=TRUE),loadings = TRUE, cutoff = 0.2), digits = 2) prcomp(m, scale = TRUE)

Hi, I wonder why factor scores produced by factanal are correlated, and I'd appreciate any hints from people that may help me to get a deeper understanding why that's the case. By the way: I'm a psychologist used to SPSS, so that question my sound a little silly to your ears. Here's my minimal example: *********************************************** v1 <-

Dear R-help, Using R 1.2.1 on Windows98 to run a factor analysis on a 64x150 matrix of data generated from a simulation model, factanal() reported that it failed to find a solution. Looking at the factanal code, I see the immediate condition that triggered the result: if (best == Inf) stop("Unable to optimize from these starting value(s)") So I am sure factanal() is giving

Dear Users, I ran factor analysis using R and SAS. However, I had different outputs from R and SAS. Why they provide different outputs? Especially, the factor loadings are different. I did real dataset(n=264), however, I had an extremely different from R and SAS. Why this things happened? Which software is correct on? Thanks in advance, - TY #R code with example data # A little

Thanks to Brian Ripley for the time and effort put into developing the factanal package for R. I have found it very useful. However, in trying to replicate some results from previous research, I have run into the need for a couple of extensions and was wondering if they might find their way into future implementations. 1. Though maximum likelihood estimates might be more rigorous and

Full_Name: Mike Ulrich Version: 2.9 OS: Mac OSX Submission from: (NULL) (69.169.178.34) The help documentation for loadings() lists more then one parameter. The function call only expects one parameter. The digits, cutoff, and sort parameters are not used in the function. ## S3 method for class 'loadings': print(x, digits = 3, cutoff = 0.1, sort = FALSE, ...) ## S3 method for class

Dear all, The 'make check' step fails for the pacakge mva on IBM AIX. The tail of the Rout log file looks like: > for(factors in 2:4) print(update(Harman23.FA, factors = factors)) Call: factanal(factors = factors, covmat = Harman23.cor) Uniquenesses: height arm.span forearm lower.leg weight 0.170 0.107 0.166

Hi Can anybody please suggest me about the documentation of "factanal.fit.mle()" (Not factanal()------ searching factanal.fit.mle() in R always leads to factanal()). Is there any function for doing principal component factor analysis in R. Regards Souvik Bandyopadhyay JRF, Dept Of Statistics Calcutta University [[alternative HTML version deleted]]

I am having difficulty obtaining the scores from my principal component analysis. I have used this method before and have had no problems. The data set that I am using this time is similar to what I have used in the past. What do I need to do to my dataset in order for me to obtain these scores? R screen says the following message Error in factanal(covmat = pasa.cov, factors = 4) :

Dear list members, I apologize for putting this (probably) very basic question on the mailing list. I have scanned through the R website (using search) but did not found an answer. (code included below) A factor matrix is simply extracted (which can then subsequently be exported using write.table) by FACT$loadings[1:6,]. I would also like to specifically extract and export

Dear list members, Could any expert on factor analysis be so kind to explain how to calculate AIC on the output of factanal. Do I calculate AIC wrong or is factanal$criteria["objective"] not a negative log-likelihood? Best regards Jens Oehlschl?gel The AIC calculated using summary.factanal below don't appear correct to me: n items factors total.df rest.df model.df

Dear list members, Could any expert on factor analysis be so kind to explain how to calculate AIC on the output of factanal. Do I calculate AIC wrong or is factanal$criteria["objective"] not a negative log-likelihood? Best regards Jens Oehlschl?gel The AIC calculated using summary.factanal below don't appear correct to me: n items factors total.df rest.df model.df

Hi, I had a look at the MASS4 scripts in the MASS package, in Ch 11.3 Factor Analysis, there is a section of codes like: data(ability.cov) ability.FA <- factanal(covmat = ability.cov, factors = 1) ability.FA (ability.FA <- update(ability.FA, factors = 2)) #summary(ability.FA) round(loadings(ability.FA) %*% t(loadings(ability.FA)) + diag(ability.FA$uniq), 3)

I am very new to factor analysis as well as R. I am trying to run a factor analysis on the residual returns on common stock (residual to some model) and trying to determine if there are any strong factors remaining. After running factanal, I can obtain the factor loadings but how do I get the values of the factor returns themselves? In other words if the relationship is r = lambda * f I

Dear R users: I'm wondering if it's possible to get the residual correlation matrix when using factanal. Since factanal assumes that the errors are normally distributed and independent (provided the factor model fits the data) this would be useful. Of course you would need to submit the data to the function to get the residuals (not just their correlation matrix), but it should be possible

In R factanal output, I can't find a function to give me residuals e. I mannually got it by using x -lamda1*f1 -lamda2*f2 - ... -lamdan*fn, but the e I got are not uncorrelated with all the f's. What did I do wrong? Please help. Yijun ____________________________________________________________________________________ Be a better friend, newshound, and

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

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

Dear all, i wonder if there?s a command to obtain the actual values of a principal component or a factor (not as.factor, but factanal) . test=princomp(USArrests, cor = TRUE) summary(test) just outputs, standard deviation, Prop of Variance and cumulative proportion of variance. test$loadings offers yet another proportion of variance scheme. why is that? Apart from that: Is there a