setwd("~/Documents/Dropbox/Research/Bernd")
abot<-read.csv ("abot_database_robot_list_final.csv", header=T, sep=",")
abot<-subset(abot, select=c(3:21))
library(psych)
## Warning: package 'psych' was built under R version 3.2.5
fit <- principal(abot, nfactors=2, rotate="varimax") #get factor loadings
fit
## Principal Components Analysis
## Call: principal(r = abot, nfactors = 2, rotate = "varimax")
## Standardized loadings (pattern matrix) based upon correlation matrix
## RC1 RC2 h2 u2 com
## Apparel 0.64 0.23 0.466 0.53 1.3
## Arms 0.04 0.93 0.862 0.14 1.0
## Eyebrows 0.77 -0.14 0.606 0.39 1.1
## Eyelashes 0.84 -0.07 0.718 0.28 1.0
## Eye.s. 0.51 0.09 0.269 0.73 1.1
## Face 0.64 0.23 0.458 0.54 1.3
## Finger.s. 0.09 0.88 0.788 0.21 1.0
## Gender 0.79 0.25 0.687 0.31 1.2
## Gripper -0.14 0.87 0.785 0.22 1.1
## Hand.s. 0.10 0.94 0.891 0.11 1.0
## Head 0.44 0.55 0.489 0.51 1.9
## Head.hair 0.78 0.01 0.605 0.39 1.0
## Leg.s. -0.05 0.69 0.472 0.53 1.0
## Mouth 0.69 -0.02 0.470 0.53 1.0
## Nose 0.77 0.07 0.593 0.41 1.0
## Skin 0.74 -0.01 0.544 0.46 1.0
## Torso 0.11 0.90 0.821 0.18 1.0
## Treads.tracks -0.33 0.13 0.129 0.87 1.3
## Wheels -0.28 -0.04 0.077 0.92 1.0
##
## RC1 RC2
## SS loadings 5.64 5.08
## Proportion Var 0.30 0.27
## Cumulative Var 0.30 0.56
## Proportion Explained 0.53 0.47
## Cumulative Proportion 0.53 1.00
##
## Mean item complexity = 1.1
## Test of the hypothesis that 2 components are sufficient.
##
## The root mean square of the residuals (RMSR) is 0.11
## with the empirical chi square 840.92 with prob < 7.9e-103
##
## Fit based upon off diagonal values = 0.91