Re: [R] In factor analysis in the psych package, how can I work out which factors the columns in $scores relate to? How do I know what each of the scores is scoring?
Dear Professor Carlson Thank you so much! The $Structure command displays the loadings with the same style of column heading as the $scores (i.e. [,1] [,2][,3] [,4][,5] [,6] [,7] [,8] [,9] [,10] [,11]), and makes me so much more confident that the columns in the $scores are displayed in the same order as the columns in $loadings, even though $loadings has different column headings to $scores (the column headings of $loadings are MR4 MR3MR2 MR6 MR7 MR5 MR1 MR8 MR10 MR9 MR11). Thank you! Best wishes Brent -Original Message- From: David L Carlson [mailto:dcarl...@tamu.edu] Sent: Thursday, 6 December 2012 2:45 p.m. To: Brent Caldwell; 'r-help@R-project.org' Cc: 'William R Revelle' Subject: RE: [R] In factor analysis in the psych package, how can I work out which factors the columns in $scores relate to? How do I know what each of the scores is scoring? I think you are safe in assuming that the first factor is used to compute the first factor score column. The factor.scores() procedure is used by fa() to compute the factor scores so it provides details regarding how they are computed beyond the information in the fa() help page. As I understand the help file, the default rotation is oblimin so In the oblique case, the factor loadings are referred to as Pattern coefficients and are related to the Structure coefficients by S = P and thus P = S 1. When estimating factor scores, fa and factanal differ in that fa finds the factors from the Structure matrix and factanal seems to find them from the Pattern matrix. Thus, although in the orthogonal case, fa and factanal agree perfectly in their factor score estimates, they do not agree in the case of oblique factors. Setting oblique.scores = FALSE will produce factor score estimate that match those of factanal. So you might want to look at $Structure. The $scores part of the output is a matrix without column names (they are just numbered). The V1, V2, . . . is added by the write.csv() function and is not part of the actual output from fa(). --- David -Original Message- From: Brent Caldwell [mailto:brent.caldw...@otago.ac.nz] Sent: Wednesday, December 05, 2012 7:08 PM To: dcarl...@tamu.edu; 'r-help@R-project.org' Cc: William R Revelle (reve...@northwestern.edu) Subject: RE: [R] In factor analysis in the psych package, how can I work out which factors the columns in $scores relate to? How do I know what each of the scores is scoring? Dear Prof Carlson Thank you very much. As far as I can tell, factor.scores requires an object from class grm, itm, rason, or tpm; which I think are part of the irt package with which I am unfamiliar. I had used the psych package to do the following factor analysis: fa.11factors.rawdata - fa(WISDMrawdataframe,nfactors=11) # WISDMrawdataframe has 37 columns and 2408 rows, and contain 1051 rows that are NA (having NA in this dataframe allows the raw data to have the same length as my vector of ID numbers so I can work out which participants the data belong to) fa.11factors.rawdata$loadings #on the computer screen this gives me the loadings with column namesMR4MR3MR2MR6MR7MR5 MR1MR8MR10 MR9MR11 fa.11factors.rawdata$scores # on the computer screen this gives me the scores with column names [,1] [,2][,3] [,4][,5] [,6] [,7] [,8] [,9] [,10] [,11] Am I safe in assuming that the scores in the first column relate to the loadings in the column called MR4? If this is a safe assumption, then I can work out which factor the scores relate to, by looking at which items load onto MR4MR3MR2 MR6MR7MR5MR1MR8MR10 MR9MR11 Thank you, I've taken your advice and cc'd this to Prof William Revelle Thank you Best wishes Brent -Original Message- From: David L Carlson [mailto:dcarl...@tamu.edu] Sent: Thursday, 6 December 2012 10:33 a.m. To: Brent Caldwell; 'r-help@R-project.org' Subject: RE: [R] In factor analysis in the psych package, how can I work out which factors the columns in $scores relate to? How do I know what each of the scores is scoring? Without seeing what options you have specified in your call to fa(), it is not possible to answer the question. There are detailed discussions in ?fa and ?factor.scores in the psych package, but for the final word you should probably contact the package maintainer: Package: psych Version: 1.2.8 Date: 2012-08-08 Title: Procedures for Psychological, Psychometric, and Personality Research Author: William Revelle reve...@northwestern.edu Maintainer: William Revelle reve...@northwestern.edu -- David L Carlson Associate Professor of Anthropology
[R] In factor analysis in the psych package, how can I work out which factors the columns in $scores relate to? How do I know what each of the scores is scoring?
Hi I have used fa() to perform a factor analysis of a psychological battery which is thought to have 11 factors. I can identify which factors the loadings relate to easily enough because I can see which items are loading onto each of the columns in the $loading output. However, how can I identify which items or loadings are being used to create each of the columns in the $scores output? I have used generalised linear models which have shown that some of the scores are significant predictors of treatment outcome, but I can't work out which of the 11 factors they are scoring? when I export to csv the $loadings I get the following columns in this order: MR4, MR3, MR2, MR6, MR7, MR5, MR1, MR8, MR10, MR9, MR11 When I export to csv the $scores I get the following columns in this order: V1, V2, V3, V4, V5, V6, V7, V8, V9, V10,V11 Are the scores in the column V1 derived from the loadings in column MR1 ? Or are the scores in the first column of $scores (ie V1) derived from the loadings in the first column of $loadings (ie MR4)? Thank you very much for your guidance, and your patience with my confusion Best wishes Brent Brent Caldwell, MBChB, DPH, MPH. Research Fellow Department of Medicine University of Otago, Wellington New Zealand U brent.caldw...@otago.ac.nz b 04 918 6041 021 87 22 64 23a Mein Street, PO Box 7343, Newtown, WELLINGTON 6021, NEW ZEALAND brent.ower.caldwell Zonnic study __ 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.
Re: [R] In factor analysis in the psych package, how can I work out which factors the columns in $scores relate to? How do I know what each of the scores is scoring?
Dear Prof Carlson Thank you very much. As far as I can tell, factor.scores requires an object from class grm, itm, rason, or tpm; which I think are part of the irt package with which I am unfamiliar. I had used the psych package to do the following factor analysis: fa.11factors.rawdata - fa(WISDMrawdataframe,nfactors=11) # WISDMrawdataframe has 37 columns and 2408 rows, and contain 1051 rows that are NA (having NA in this dataframe allows the raw data to have the same length as my vector of ID numbers so I can work out which participants the data belong to) fa.11factors.rawdata$loadings #on the computer screen this gives me the loadings with column namesMR4MR3MR2MR6MR7MR5MR1 MR8MR10 MR9MR11 fa.11factors.rawdata$scores # on the computer screen this gives me the scores with column names [,1] [,2][,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10] [,11] Am I safe in assuming that the scores in the first column relate to the loadings in the column called MR4? If this is a safe assumption, then I can work out which factor the scores relate to, by looking at which items load onto MR4MR3MR2MR6MR7 MR5MR1MR8MR10 MR9MR11 Thank you, I've taken your advice and cc'd this to Prof William Revelle Thank you Best wishes Brent -Original Message- From: David L Carlson [mailto:dcarl...@tamu.edu] Sent: Thursday, 6 December 2012 10:33 a.m. To: Brent Caldwell; 'r-help@R-project.org' Subject: RE: [R] In factor analysis in the psych package, how can I work out which factors the columns in $scores relate to? How do I know what each of the scores is scoring? Without seeing what options you have specified in your call to fa(), it is not possible to answer the question. There are detailed discussions in ?fa and ?factor.scores in the psych package, but for the final word you should probably contact the package maintainer: Package: psych Version: 1.2.8 Date: 2012-08-08 Title: Procedures for Psychological, Psychometric, and Personality Research Author: William Revelle reve...@northwestern.edu Maintainer: William Revelle reve...@northwestern.edu -- David L Carlson Associate Professor of Anthropology Texas AM University College Station, TX 77843-4352 -Original Message- From: r-help-boun...@r-project.org [mailto:r-help-bounces@r- project.org] On Behalf Of Brent Caldwell Sent: Wednesday, December 05, 2012 2:53 PM To: r-help@R-project.org Subject: [R] In factor analysis in the psych package, how can I work out which factors the columns in $scores relate to? How do I know what each of the scores is scoring? Hi I have used fa() to perform a factor analysis of a psychological battery which is thought to have 11 factors. I can identify which factors the loadings relate to easily enough because I can see which items are loading onto each of the columns in the $loading output. However, how can I identify which items or loadings are being used to create each of the columns in the $scores output? I have used generalised linear models which have shown that some of the scores are significant predictors of treatment outcome, but I can't work out which of the 11 factors they are scoring? when I export to csv the $loadings I get the following columns in this order: MR4, MR3, MR2, MR6, MR7, MR5, MR1, MR8, MR10, MR9, MR11 When I export to csv the $scores I get the following columns in this order: V1, V2, V3, V4, V5, V6, V7, V8, V9, V10,V11 Are the scores in the column V1 derived from the loadings in column MR1 ? Or are the scores in the first column of $scores (ie V1) derived from the loadings in the first column of $loadings (ie MR4)? Thank you very much for your guidance, and your patience with my confusion Best wishes Brent Brent Caldwell, MBChB, DPH, MPH. Research Fellow Department of Medicine University of Otago, Wellington New Zealand U brent.caldw...@otago.ac.nz b 04 918 6041 021 87 22 64 23a Mein Street, PO Box 7343, Newtown, WELLINGTON 6021, NEW ZEALAND brent.ower.caldwell Zonnic study __ 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.
[R] trying to understand the names of the loadings and factor scores from fa()
Hi I'm trying to understand the names of the output I get from extracting the loadings and the factor scores from fa() when I export to csv the $loadings I get the following columns in this order: MR4, MR3, MR2, MR6, MR7, MR5, MR1, MR8, MR10, MR9, MR11 When I export to csv the $scores I get the following columns in this order: V1, V2, V3, V4, V5, V6, V7, V8, V9, V10,V11 Are the scores in the column V1 derived from the loadings in column MR1 ? Or are the scores in the first column of $scores (ie V1) derived from the loadings in the first column of $loadings (ie MR4)? Thank you very much for your guidance Best wishes Brent Brent Caldwell, MBChB, DPH, MPH. Research Fellow Department of Medicine University of Otago, Wellington U brent.caldw...@otago.ac.nz b 04 918 6041 021 87 22 64 23a Mein Street, PO Box 7343, Newtown, WELLINGTON 6021, NEW ZEALAND brent.ower.caldwell Zonnic study __ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
Re: [R] Plotting an adjusted survival curve
Dear Terry and David Thank you so much for your rapid and helpful replies! I've changed tack slightly and decided to focus on the effect modifiers which had the greatest effect on the outcome of the trial (HowmanyZonnic_Q and WISDMPDM) I've tried to follow your example on page 16 of the manuscript you emailed me, but I get an error which I think is related to trying to do maths on two matrices which are of different dimensions I think??? This is my code: KM.object.coxph5 - coxph(Surv(whenfailed,failed) ~ strata(Treatment)+HowmanyZonnic_Q+WISDMPDM,survmat) asdist - table(HowmanyZonnic_Q,WISDMPDM) uage - as.numeric(dimnames(asdist)[[1]]) tdata - expand.grid(HowmanyZonnic_Q=uage, WISDMPDM=uage) #This appears to be a table of all the possible combinations of HowmanyZonnic_Q and WISDMPDM par(mfrow=c(1,2)) sfit4a - survfit(KM.object.coxph5, newdata=tdata, se.fit=FALSE) sfit4a$surv - sfit4a$surv %*% c(asdist/sum(asdist)) #Error in sfit4a$surve %*% c(asdist/sum(asdist)) : non-conformable arguments #sfit4a$surv is a table of 10 rows and 25 columns #c(asdist/sum(asdist)) is a vector with a length of 420 I hope I am not sapping your patience with this question Thank you - you guys are awesome Best wishes Brent -Original Message- From: Terry Therneau [mailto:thern...@mayo.edu] Sent: Tuesday, 27 November 2012 4:03 a.m. To: r-help@r-project.org; Brent Caldwell Cc: David Winsemius Subject: Re: Plotting an adjusted survival curve First a statistical issue: The survfit routine will produce predicted survival curves for any requested combination of the covariates in the original model. This is not the same thing as an adjusted survival curve. Confusion on this is prevalent, however. True adjustment requires a population average over the confounding factors and is closely related to the standardized incidence ratio concept found in epidemiology. To answer your technical question: fit - coxph(Surv(. mysurv - survfit(fit, newdata= mydata) This will give a set of predicted curves, one for each observation in mydata. If we assume 2 treatments and 4 ethnicities, this means that there are 8 possible predicted curves. You can certainly take the curves for trt=1, white and trt=2, white, plot them together on one graph, and call this your adjusted survival curves; the mydata data set would have two observations. This is not a correct label but is certainly common. Terry Therneau On 11/26/2012 05:00 AM, r-help-requ...@r-project.org wrote: Dear R-users I am trying to make an adjusted Kaplan-Meier curve (using the Survival package) but I am having difficulty with plotting it so that the plot only shows the curves for the adjusted results. My data come from a randomised controlled trial, and I would like the adjusted Kaplan-Meier curve to only show two curves for the adjusted survival: one for those on treatment (Treatment==1) and another curve for those on placebo (Treatment==0). My problem is that when I plot the survfit of my coxph, I think it displays a curve for every single individual factor in my coxph, whereas I would like it to only display the adjusted curves for when Treatment==1 and Treatment==0. How can I do this? A simplified example of my code with only one effect-modifier is: simple.cox.ethnicity- coxph(Surv(whenfailed,failed) ~ factor(Treatment) + factor(ethnicity)) #I've my data are attached already survfit.simple.cox.ethnicity- survfit(simple.cox.ethnicity,survmat) #survmat is a data.frame that contains Treatment and ethnicity plot(survfit.simple.cox.ethnicity, col=c(red,black), main=survfit.simple.cox, xlab=survival time, ylab=propotion surviving) Thank you so much for your help. Yours gratefully, Brent Caldwell __ 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] Psych package: fa.diagram, how to re-arrange layout so numbers do not over-write each other
Dear R help I have conducted a fa() analysis, and I want to use fa.diagram to assess the extent to which the 11 latent factors predict the 37 items in a psychological battery. However, the display on the screen has very large font size for the coefficients of the relationship between the 11 factors and the 37 items, so the numbers overlap and are therefore illegible. When I output this to a pdf the problem is exacerbated even further (see attachments). I tried to use cex=0.8 and cex=0.4 in the pdf argument but it made no difference - what can I do? The code I used is: fa.diagram(fa.11factors.rawdata) # Start PDF device driver to save output to fa_diagram.pdf pdf(file=I:\\ZAPi\\Tables-of-R-output\\fa_diagram.pdf, height=10, width=5) fa.diagram(fa.11factors.rawdata) #box() # Create box around plot dev.off() # Turn off device driver (to flush output to PDF) pdf(file=I:\\ZAPi\\Tables-of-R-output\\fa_diagram_cex.pdf, height=8, width=5) fa.diagram(fa.11factors.rawdata,cex=0.8) #box() # Create box around plot dev.off() # Turn off device driver (to flush output to PDF) Thank you so much for your time Yours sincerely Brent Caldwell fa_diagram_cex.pdf Description: fa_diagram_cex.pdf fa_diagram.pdf Description: fa_diagram.pdf __ 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.
Re: [R] Psych package: fa.diagram, how to re-arrange layout so numbers do not over-write each other
Dear Bill Wow! Thank you so much for your rapid reply - you are such a kind person, thank you! I'll try fa.rgraph - thanks Thanks Best wishes Brent -Original Message- From: William R Revelle [mailto:reve...@northwestern.edu] Sent: Tuesday, 27 November 2012 5:54 p.m. To: Brent Caldwell Cc: r-help@R-project.org Subject: Re: [R] Psych package: fa.diagram, how to re-arrange layout so numbers do not over-write each other Brent, No, cex doesn't work (as you have discovered). That is a bug. I will work on it. In the meantime, try Rgraphviz called from fa.rgaph or use the output from fa.graph which produces a dot file for processing with any graphic package (including graphviz) which handles the dot language. Bill On Nov 26, 2012, at 10:08 PM, Brent Caldwell brent.caldw...@otago.ac.nz wrote: Dear R help I have conducted a fa() analysis, and I want to use fa.diagram to assess the extent to which the 11 latent factors predict the 37 items in a psychological battery. However, the display on the screen has very large font size for the coefficients of the relationship between the 11 factors and the 37 items, so the numbers overlap and are therefore illegible. When I output this to a pdf the problem is exacerbated even further (see attachments). I tried to use cex=0.8 and cex=0.4 in the pdf argument but it made no difference - what can I do? The code I used is: fa.diagram(fa.11factors.rawdata) # Start PDF device driver to save output to fa_diagram.pdf pdf(file=I:\\ZAPi\\Tables-of-R-output\\fa_diagram.pdf, height=10, width=5) fa.diagram(fa.11factors.rawdata) #box() # Create box around plot dev.off() # Turn off device driver (to flush output to PDF) pdf(file=I:\\ZAPi\\Tables-of-R-output\\fa_diagram_cex.pdf, height=8, width=5) fa.diagram(fa.11factors.rawdata,cex=0.8) #box() # Create box around plot dev.off() # Turn off device driver (to flush output to PDF) Thank you so much for your time Yours sincerely Brent Caldwell fa_diagram_cex.pdffa_diagram.pdf__ 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. William Revellehttp://personality-project.org/revelle.html Professor http://personality-project.org Department of Psychology http://www.wcas.northwestern.edu/psych/ Northwestern Universityhttp://www.northwestern.edu/ Use R for psychology http://personality-project.org/r It is 5 minutes to midnighthttp://www.thebulletin.org __ 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] Plotting an adjusted kaplan-meier curve
Dear R-users I am trying to make an adjusted Kaplan-Meier curve (using the Survival package) but I am having difficulty with plotting it so that the plot only shows the curves for the adjusted results. My data come from a randomised controlled trial, and I would like the adjusted Kaplan-Meier curve to only show two curves for the adjusted survival: one for those on treatment (Treatment==1) and another curve for those on placebo (Treatment==0). My problem is that when I plot the survfit of my coxph, I think it displays a curve for every single individual factor in my coxph, whereas I would like it to only display the adjusted curves for when Treatment==1 and Treatment==0. How can I do this? A simplified example of my code with only one effect-modifier is: simple.cox.ethnicity - coxph(Surv(whenfailed,failed) ~ factor(Treatment) + factor(ethnicity)) #I've my data are attached already survfit.simple.cox.ethnicity - survfit(simple.cox.ethnicity,survmat) #survmat is a data.frame that contains Treatment and ethnicity plot(survfit.simple.cox.ethnicity, col=c(red,black), main=survfit.simple.cox, xlab=survival time, ylab=propotion surviving) Thank you so much for your help. Yours gratefully, Brent Caldwell __ 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.
