14.6 Factor Scores

  • Can be used as dependent or independent variables in other analyses
  • Each \(X\) is a function of \(F\)’s
  • Factor Scores are the reverse: Each \(F\) is a function of the \(X\)’s
  • Can be generated by adding the scores="regression" option to factanal(), or scores=TRUE in principal()
  • Each record in the data set with no missing data will have a corresponding factor score.
    • principal() also has a missing argument that if set to TRUE it will impute missing values.

To merge these scores back onto the original data set providing there is no missing data you can use the bind_cols() function in dplyr.

X1 X2 X3 X4 X5 Factor1 Factor2
-0.8236763 -0.1210726 -0.5970760 -1.4752693 -1.2355056 -1.4917431 0.0036129
1.4013214 1.0733569 0.7681035 -0.0509857 0.0180061 -0.2625472 1.0908647
0.2781468 0.7574632 0.6445954 0.6765583 0.7532815 0.5551604 0.6311199
0.1819544 -1.3228227 -1.0847105 -0.9574722 -1.3719843 -1.2102868 -1.2812405
-1.6147171 -1.4254411 0.3519605 -0.0124497 -0.2523487 -0.0485221 -1.5756915
0.8251470 0.6245702 -1.2923348 -0.6345633 -0.0885945 -0.5376877 0.6611383