library(psych)
library(readxl)
library(REdaS)
## Loading required package: grid
places <- read.table("C:/multi/activity 2/places.txt", quote="\"", comment.char="")
View(places)
bart_spher(places)
## Bartlett's Test of Sphericity
##
## Call: bart_spher(x = places)
##
## X2 = 1057.162
## df = 45
## p-value < 2.22e-16
KMO(places)
## Kaiser-Meyer-Olkin factor adequacy
## Call: KMO(r = places)
## Overall MSA = 0.7
## MSA for each item =
## V1 V2 V3 V4 V5 V6 V7 V8 V9 V10
## 0.56 0.69 0.69 0.64 0.86 0.73 0.71 0.81 0.38 0.65
fa(places, nfactors = 9, rotate = "oblimin")
## Loading required namespace: GPArotation
## Warning in GPFoblq(L, Tmat = Tmat, normalize = normalize, eps = eps, maxit =
## maxit, : convergence not obtained in GPFoblq. 1000 iterations used.
## Factor Analysis using method = minres
## Call: fa(r = places, nfactors = 9, rotate = "oblimin")
## Standardized loadings (pattern matrix) based upon correlation matrix
## MR1 MR2 MR4 MR6 MR8 MR3 MR5 MR7 MR9 h2 u2 com
## V1 -0.03 0.12 0.09 0.07 0.06 0.65 -0.06 0.01 0.00 0.537 0.463 1.2
## V2 0.05 0.88 -0.03 -0.03 0.01 0.05 0.03 0.00 0.00 0.844 0.156 1.0
## V3 0.81 0.06 0.02 0.12 0.01 -0.02 -0.01 -0.04 -0.15 0.926 0.074 1.1
## V4 0.06 -0.04 0.79 -0.04 0.01 0.05 0.05 0.01 0.00 0.674 0.326 1.0
## V5 0.00 0.11 0.12 0.13 0.12 -0.07 0.60 0.01 -0.02 0.598 0.402 1.4
## V6 0.12 -0.05 -0.06 0.67 -0.02 0.06 0.10 -0.01 -0.01 0.550 0.450 1.2
## V7 0.94 0.01 0.03 -0.04 0.03 0.01 0.02 0.03 0.09 0.881 0.119 1.0
## V8 0.04 -0.02 -0.02 -0.04 0.68 0.04 0.04 0.01 -0.01 0.480 0.520 1.0
## V9 -0.09 0.21 0.21 0.19 0.12 -0.22 -0.18 -0.28 0.19 0.636 0.364 7.2
## V10 -0.12 0.16 0.13 0.17 0.05 -0.06 -0.17 0.31 -0.02 0.083 0.917 3.8
##
## MR1 MR2 MR4 MR6 MR8 MR3 MR5 MR7 MR9
## SS loadings 1.74 0.98 0.79 0.64 0.62 0.55 0.53 0.23 0.14
## Proportion Var 0.17 0.10 0.08 0.06 0.06 0.06 0.05 0.02 0.01
## Cumulative Var 0.17 0.27 0.35 0.41 0.48 0.53 0.58 0.61 0.62
## Proportion Explained 0.28 0.16 0.13 0.10 0.10 0.09 0.08 0.04 0.02
## Cumulative Proportion 0.28 0.44 0.56 0.67 0.77 0.86 0.94 0.98 1.00
##
## With factor correlations of
## MR1 MR2 MR4 MR6 MR8 MR3 MR5 MR7 MR9
## MR1 1.00 0.45 0.38 0.47 0.47 0.20 0.46 0.00 -0.29
## MR2 0.45 1.00 0.19 0.31 0.66 0.33 0.07 -0.22 0.14
## MR4 0.38 0.19 1.00 0.16 0.61 0.10 0.16 -0.21 0.33
## MR6 0.47 0.31 0.16 1.00 0.16 -0.07 0.27 -0.31 -0.13
## MR8 0.47 0.66 0.61 0.16 1.00 0.16 0.39 -0.12 0.22
## MR3 0.20 0.33 0.10 -0.07 0.16 1.00 0.05 0.45 -0.28
## MR5 0.46 0.07 0.16 0.27 0.39 0.05 1.00 0.20 -0.26
## MR7 0.00 -0.22 -0.21 -0.31 -0.12 0.45 0.20 1.00 -0.29
## MR9 -0.29 0.14 0.33 -0.13 0.22 -0.28 -0.26 -0.29 1.00
##
## Mean item complexity = 2
## Test of the hypothesis that 9 factors are sufficient.
##
## The degrees of freedom for the null model are 45 and the objective function was 3.26 with Chi Square of 1057.16
## The degrees of freedom for the model are -9 and the objective function was 0
##
## The root mean square of the residuals (RMSR) is 0
## The df corrected root mean square of the residuals is NA
##
## The harmonic number of observations is 329 with the empirical chi square 0 with prob < NA
## The total number of observations was 329 with Likelihood Chi Square = 0 with prob < NA
##
## Tucker Lewis Index of factoring reliability = 1.045
## Fit based upon off diagonal values = 1
## Measures of factor score adequacy
## MR1 MR2 MR4 MR6 MR8 MR3
## Correlation of (regression) scores with factors 0.97 0.93 0.86 0.81 0.86 0.78
## Multiple R square of scores with factors 0.95 0.86 0.74 0.65 0.74 0.61
## Minimum correlation of possible factor scores 0.89 0.72 0.47 0.30 0.47 0.23
## MR5 MR7 MR9
## Correlation of (regression) scores with factors 0.78 0.69 0.73
## Multiple R square of scores with factors 0.60 0.48 0.53
## Minimum correlation of possible factor scores 0.21 -0.04 0.06
fa(places, nfactors = 3, rotate = "oblimin")
## Warning in fa.stats(r = r, f = f, phi = phi, n.obs = n.obs, np.obs = np.obs, :
## The estimated weights for the factor scores are probably incorrect. Try a
## different factor score estimation method.
## Factor Analysis using method = minres
## Call: fa(r = places, nfactors = 3, rotate = "oblimin")
## Standardized loadings (pattern matrix) based upon correlation matrix
## MR1 MR3 MR2 h2 u2 com
## V1 -0.01 0.00 1.00 0.999 0.0014 1.0
## V2 0.20 0.39 0.23 0.393 0.6067 2.2
## V3 1.03 -0.06 0.00 0.994 0.0065 1.0
## V4 0.10 0.45 0.02 0.257 0.7427 1.1
## V5 0.42 0.25 -0.07 0.325 0.6748 1.7
## V6 0.52 -0.05 -0.07 0.240 0.7605 1.0
## V7 0.79 0.14 0.02 0.764 0.2361 1.1
## V8 0.04 0.62 0.07 0.445 0.5554 1.0
## V9 -0.11 0.50 -0.17 0.201 0.7991 1.4
## V10 -0.04 0.07 0.11 0.017 0.9826 2.1
##
## MR1 MR3 MR2
## SS loadings 2.30 1.20 1.13
## Proportion Var 0.23 0.12 0.11
## Cumulative Var 0.23 0.35 0.46
## Proportion Explained 0.50 0.26 0.24
## Cumulative Proportion 0.50 0.76 1.00
##
## With factor correlations of
## MR1 MR3 MR2
## MR1 1.00 0.49 0.24
## MR3 0.49 1.00 0.24
## MR2 0.24 0.24 1.00
##
## Mean item complexity = 1.4
## Test of the hypothesis that 3 factors are sufficient.
##
## The degrees of freedom for the null model are 45 and the objective function was 3.26 with Chi Square of 1057.16
## The degrees of freedom for the model are 18 and the objective function was 0.33
##
## The root mean square of the residuals (RMSR) is 0.05
## The df corrected root mean square of the residuals is 0.08
##
## The harmonic number of observations is 329 with the empirical chi square 69.02 with prob < 6.6e-08
## The total number of observations was 329 with Likelihood Chi Square = 105.25 with prob < 2.4e-14
##
## Tucker Lewis Index of factoring reliability = 0.783
## RMSEA index = 0.121 and the 90 % confidence intervals are 0.1 0.145
## BIC = 0.93
## Fit based upon off diagonal values = 0.97