Hi There are probably better options but
merge(data.frame(x=1:154),data.frame(x=names(ab.1.fa[[1]]), y=ab.1.fa[[1]]), all.x=T) gives you data frame with NA when there was missing value in the first data.frame. You probably can automate the process a bit with nrow function. Regards Petr > -----Original Message----- > From: Justin Delahunty [mailto:a...@genius.net.au] > Sent: Friday, July 26, 2013 3:34 PM > To: PIKAL Petr; 'Justin Delahunty'; 'Justin Delahunty'; r-help@r- > project.org > Subject: RE: [R] Maintaining data order in factanal with missing data > > Hi Petr, > > So sorry, I accidentally attached the complete data set rather than the > one with missing values. I've attached the correct file to this email. > RE: > init.dfs() being local, I hadn't even thought of that. I've been away > from OOP for close to 15 years now, so it might be time to revise! > > The problem I have is that with missing values the list of factor > scores returned (ab.w1.fa$factor.scores) does not map onto the > originating data frame (ab.w1.df) as it no longer includes the cases > which had missing values. So while the original data set for ab.w1.df > contains 154 ordered cases, the factor analysis contains only 150. > > I am seeking a way to map the values derived from the factor analysis > (ab.w1.fa$factor.scores) back to their original ordered position, so > that these factor score variables may be merged back into the master > data frame (ab.df). A unique ID for each case is available ($dmid) > which I had thought to use when merging the new variables, however I > don't know how to implement this. > > > Thanks for your help, > > Justin > > > -----Original Message----- > From: PIKAL Petr [mailto:petr.pi...@precheza.cz] > Sent: Friday, 26 July 2013 10:59 PM > To: Justin Delahunty; Justin Delahunty; r-help@r-project.org > Subject: RE: [R] Maintaining data order in factanal with missing data > > Hi > > Well, the function init.dfs does nothing as all data frames created > inside it does not propagate to global environment and there is nothing > what the function returns. > > Tha last line (when used outside a function) gives warnings but there > is no sign of error. > > When > > > head(ab.1.df) > dmid g5oab2 g53 g54 g55 g5ovb1 > 1 1 1.418932 1.805227 2.791152 3.624116 3.425586 > 2 2 2.293907 1.187830 1.611237 1.748526 3.816533 > 3 3 2.836536 2.679523 1.279639 2.674986 2.452395 > 4 4 1.872259 3.278359 1.785872 2.458315 1.146480 > 5 5 1.467195 1.180747 3.564127 3.007682 2.109506 > 6 6 3.098512 3.151974 3.969379 3.750571 1.497358 > > head(ab.2.df) > dmid w2oab3 w22 w23 w24 w2ovb1 > 1 1 4.831362 5.522764 7.809366 6.969172 7.398385 > 2 2 6.706346 4.101742 1.434697 5.266775 5.357641 > 3 3 3.653806 2.666885 1.209326 5.125556 4.963374 > 4 4 7.221255 7.649152 6.540398 6.648506 2.576081 > 5 5 1.848023 5.044314 2.761881 3.307220 1.454234 > 6 6 7.606429 4.911766 2.034813 2.638573 2.818834 > > head(ab.3.df) > dmid w3oab3 w3oab4 w3oab7 w3oab8 w3ovb1 > 1 1 5.835609 6.108220 6.587721 2.451461 2.785467 > 2 2 4.973198 1.196815 6.388056 1.110877 4.226463 > 3 3 3.800367 6.697287 5.235345 6.666829 6.319073 > 4 4 1.093141 1.477773 2.269252 3.194978 4.916342 > 5 5 1.975060 7.204516 4.825435 1.775874 3.484027 > 6 6 3.273361 2.243805 5.326547 5.720892 6.118723 > > > > > str(ab.1.fa) > List of 2 > $ rescaled.scores: Named num [1:154] 3.43 3.83 2.43 1.1 2.08 ... > ..- attr(*, "names")= chr [1:154] "1" "2" "3" "4" ... > $ factor.loadings: Named num [1:5] -0.0106 -0.0227 -0.1093 -0.0912 > 0.9975 > ..- attr(*, "names")= chr [1:5] "g5oab2" "g53" "g54" "g55" ... > > str(ab.2.fa) > List of 2 > $ rescaled.scores: Named num [1:154] 6.34 5.24 5.3 1.91 2.16 ... > ..- attr(*, "names")= chr [1:154] "1" "2" "3" "4" ... > $ factor.loadings: Named num [1:5] -0.2042 0.0063 -0.2287 -0.0119 > 0.7138 > ..- attr(*, "names")= chr [1:5] "w2oab3" "w22" "w23" "w24" ... > > str(ab.3.fa) > List of 2 > $ rescaled.scores: Named num [1:154] NaN NaN NaN NaN NaN NaN NaN NaN > NaN NaN ... > ..- attr(*, "names")= chr [1:154] "1" "2" "3" "4" ... > $ factor.loadings: Named num [1:5] -0.1172 0.0128 -0.0968 0.106 0.9975 > ..- attr(*, "names")= chr [1:5] "w3oab3" "w3oab4" "w3oab7" "w3oab8" > ... > > Anyway I have no idea what you consider wrong? > > Regards > Petr > > > > > -----Original Message----- > > From: Justin Delahunty [mailto:a...@genius.net.au] > > Sent: Friday, July 26, 2013 2:22 PM > > To: PIKAL Petr; 'Justin Delahunty'; r-help@r-project.org > > Subject: RE: [R] Maintaining data order in factanal with missing data > > > > Hi Petr, > > > > Thanks for the quick response. Unfortunately I cannot share the data > I > > am working with, however please find attached a suitable R workspace > > with generated data. It has the appropriate variable names, only the > > data has been changed. > > > > The last function in the list (init.dfs()) I call to subset the > > overall data set into the three waves, then conduct the factor > > analysis on each > > (1 factor CFA); it's just in a function to ease re-typing in a new > > workspace. > > > > > > Thanks, > > > > Justin > > > > -----Original Message----- > > From: PIKAL Petr [mailto:petr.pi...@precheza.cz] > > Sent: Friday, 26 July 2013 7:35 PM > > To: Justin Delahunty; r-help@r-project.org > > Subject: RE: [R] Maintaining data order in factanal with missing data > > > > Hi > > > > You provided functions, so far so good. But without data it would be > > quite difficult to understand what the functions do and where could > be > > the issue. > > > > I suspect combination of complete cases selection together with > subset > > and factor behaviour. But I can be completely out of target too. > > > > Petr > > > > > -----Original Message----- > > > From: r-help-boun...@r-project.org [mailto:r-help-bounces@r- > > > project.org] On Behalf Of s00123...@myacu.edu.au > > > Sent: Friday, July 26, 2013 9:35 AM > > > To: r-help@r-project.org > > > Subject: [R] Maintaining data order in factanal with missing data > > > > > > Hi, > > > > > > > > > > > > I'm new to R, so sorry if this is a simple answer. I'm currently > > > trying to collapse some ordinal variables into a composite; the > > > program ideally should take a data frame as input, perform a factor > > > analysis, compute factor scores, sds, etc., and return the rescaled > > > scores and loadings. The difficulty I'm having is that my data set > > > contains a number of NA, which I am excluding from the analysis > > > using complete.cases(), and thus the incomplete cases are > "skipped". > > > These functions are for a longitudinal data set with repeated waves > > > of > > data, > > > so the final rescaled scores from each wave need to be saved as > > > variables grouped by a unique ID (DMID). The functions I'm trying > to > > > implement are as follows: > > > > > > > > > > > > weighted.sd<-function(x,w){ > > > > > > sum.w<-sum(w) > > > > > > sum.w2<-sum(w^2) > > > > > > mean.w<-sum(x*w)/sum(w) > > > > > > > > > x.sd.w<-sqrt((sum.w/(sum.w^2-sum.w2))*sum(w*(x-mean.w)^2)) > > > > > > return(x.sd.w) > > > > > > } > > > > > > > > > > > > re.scale<-function(f.scores, raw.data, loadings){ > > > > > > > > > fz.scores<-(f.scores+mean(f.scores))/(sd(f.scores)) > > > > > > > > > means<-apply(raw.data,1,weighted.mean,w=loadings) > > > > > > > > > sds<-apply(raw.data,1,weighted.sd,w=loadings) > > > > > > grand.mean<-mean(means) > > > > > > grand.sd<-mean(sds) > > > > > > > > > final.scores<-((fz.scores*grand.sd)+grand.mean) > > > > > > return(final.scores) > > > > > > } > > > > > > > > > > > > get.scores<-function(data){ > > > > > > > > > fact<- > > > factanal(data[complete.cases(data),],factors=1,scores="regression") > > > > > > f.scores<-fact$scores[,1] > > > > > > f.loads<-fact$loadings[,1] > > > > > > rescaled.scores<-re.scale(f.scores, > > > data[complete.cases(data),], f.loads) > > > > > > output.list<-list(rescaled.scores, > > > f.loads) > > > > > > names(output.list)<- > > > c("rescaled.scores", > > > "factor.loadings") > > > > > > return(output.list) > > > > > > } > > > > > > > > > > > > init.dfs<-function(){ > > > > > > > > > ab.1.df<-subset(ab.df,,select=c(dmid,g5oab2:g5ovb1)) > > > > > > > > > ab.2.df<-subset(ab.df,,select=c(dmid,w2oab3:w2ovb1)) > > > > > > > > > ab.3.df<-subset(ab.df,,select=c(dmid, > > > w3oab3, w3oab4, w3oab7, w3oab8, w3ovb1)) > > > > > > > > > > > > ab.1.fa<-get.scores(ab.1.df[-1]) > > > > > > ab.2.fa<-get.scores(ab.2.df[-1]) > > > > > > ab.3.fa<-get.scores(ab.3.df[-1]) > > > > > > > > > } > > > > > > > > > > > > Thanks for your help, > > > > > > > > > > > > Justin > > > > > > > > > [[alternative HTML version deleted]] > > > > > > ______________________________________________ > > > R-help@r-project.org mailing list > > > https://stat.ethz.ch/mailman/listinfo/r-help > > > PLEASE do read the posting guide http://www.R-project.org/posting- > > > guide.html and provide commented, minimal, self-contained, > > > reproducible code. > > > > ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
