factload {DandEFA} | R Documentation |
This function produces a factor loading matrix given by the specified factor extraction method, number of factors and rotation method. R-mode Exploratory Factor Analysis is based on the factorization of the variables. See "References" for more details.
factload(data, cormeth = "spearman", data.cor,
method = "pc", nfac = 1, rotation = "varimax")
data |
Dataset to be analyzed for R-mode Exploratory Factor Analysis |
cormeth |
Correlation coefficient. Type |
data.cor |
Given correlation matrix. However, if |
method |
Factor extraction method. Type |
nfac |
The number of factors |
rotation |
Rotation method. Type |
Returns a loadings class factor loading matrix
Reyment, R., Joreskog, K.G., 1993. Applied Factor Analysis in the Natural Sciences. Cambridge University Press, Cambridge, United Kingdom.
Klinke, S., Wagner, C., 2008. Visualizing exploratory factor analysis models, in: Paulo, B. (Ed.), Compstat 2008: Proceedings in Computational Statistics: 18th Symposium Held in Porto, Portugal, 2008.
Harman, Harry H., and Wayne H. Jones. "Factor analysis by minimizing residuals (minres)." Psychometrika 31.3 (1966): 351-368.
data(timss2011)
timss2011 <- na.omit(timss2011)
factload(timss2011,nfac=5,method="prax",cormeth="spearman")
factload(timss2011,nfac=8,method="pc",cormeth="pearson",rotation="promax")
timsscor <- cor(timss2011)
factload(data.cor=timsscor,nfac=10,method="mle")