R Dataset / Package psych / Schmid
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dataset-11795.csv | 1020 bytes |
Documentation |
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On this Picostat.com statistics page, you will find information about the Schmid data set which pertains to 12 variables created by Schmid and Leiman to show the Schmid-Leiman Transformation. The Schmid data set is found in the psych R package. Try to load the Schmid data set in R by issuing the following command at the console data("Schmid"). This may load the data into a variable called Schmid. If R says the Schmid data set is not found, you can try installing the package by issuing this command install.packages("psych") and then attempt to reload the data with library("psych") followed by data("Schmid"). Perhaps strangley, if R gives you no output after entering a command, it means the command succeeded. If it succeeded you can see the data by typing Schmid at the command-line which should display the entire dataset. If you need to download R, you can go to the R project website. You can download a CSV (comma separated values) version of the Schmid R data set. The size of this file is about 1,020 bytes. 12 variables created by Schmid and Leiman to show the Schmid-Leiman TransformationDescriptionJohn Schmid and John M. Leiman (1957) discuss how to transform a hierarchical factor structure to a bifactor structure. Schmid contains the example 12 x 12 correlation matrix. schmid.leiman is a 12 x 12 correlation matrix with communalities on the diagonal. This can be used to show the effect of correcting for attenuation. Two additional data sets are taken from Chen et al. (2006). Usagedata(Schmid) DetailsTwo artificial correlation matrices from Schmid and Leiman (1957). One real and one artificial covariance matrices from Chen et al. (2006).
SourceJohn Schmid Jr. and John. M. Leiman (1957), The development of hierarchical factor solutions.Psychometrika, 22, 83-90. F.F. Chen, S.G. West, and K.H. Sousa.(2006) A comparison of bifactor and second-order models of quality of life. Multivariate Behavioral Research, 41(2):189-225, 2006. ReferencesY.-F. Yung, D.Thissen, and L.D. McLeod. (1999) On the relationship between the higher-order factor model and the hierarchical factor model. Psychometrika, 64(2):113-128, 1999. Examplesdata(Schmid) cor.plot(Schmid,TRUE) print(fa(Schmid,6,rotate="oblimin"),cut=0) #shows an oblique solution round(cov2cor(schmid.leiman),2) cor.plot(cov2cor(West),TRUE) -- Dataset imported from https://www.r-project.org. |
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