Problem 1:
library(psych)## Warning: package 'psych' was built under R version 3.6.2library(dplyr)##
## Attaching package: 'dplyr'## The following objects are masked from 'package:stats':
##
## filter, lag## The following objects are masked from 'package:base':
##
## intersect, setdiff, setequal, unionqtype <- c("E","A","C","N","O", "E","A","C","N","O",
"E","A","C","N","O", "E","A","C","N","O",
"E","A","C","N","O", "E","A","C","N","O",
"E","A","C","N","O", "E","A","C","N","O",
"O","A","C","O")
valence <- c(1,-1,1,1,1, -1,1,-1,-1,1,
1,-1,1,1,1, 1,1,-1,1,1,
-1,1,-1,-1,1, 1,1,-1,-1,-1,
1,-1,1,-1,-1, 1,1,-1,-1,-1,
1,-1,1,-1)
data_raw <- read.csv("bigfive-full.csv")[,4:47]
data_raw[is.na(data_raw)] <- 3
data_raw[1:5,]data <- data_raw
dimC <- select(data,(1:44)[qtype=="C"])
keyC <- valence[qtype=="C"]1 - A:
alpha(data)## Warning in alpha(data): Some items were negatively correlated with the total scale and probably
## should be reversed.
## To do this, run the function again with the 'check.keys=TRUE' option## Some items ( Q2 Q4 Q6 Q8 Q12 Q14 Q18 Q19 Q21 Q23 Q27 Q29 Q31 Q35 Q37 Q39 Q41 Q43 ) were negatively correlated with the total scale and
## probably should be reversed.
## To do this, run the function again with the 'check.keys=TRUE' option##
## Reliability analysis
## Call: alpha(x = data)
##
## raw_alpha std.alpha G6(smc) average_r S/N ase mean sd median_r
## 0.65 0.68 0.79 0.046 2.1 0.016 3.5 0.28 0.04
##
## lower alpha upper 95% confidence boundaries
## 0.62 0.65 0.68
##
## Reliability if an item is dropped:
## raw_alpha std.alpha G6(smc) average_r S/N alpha se var.r med.r
## Q1 0.64 0.67 0.79 0.045 2.0 0.016 0.028 0.039
## Q2 0.64 0.68 0.79 0.047 2.1 0.016 0.029 0.043
## Q3 0.64 0.67 0.79 0.045 2.0 0.016 0.029 0.039
## Q4 0.65 0.68 0.79 0.048 2.1 0.016 0.028 0.042
## Q5 0.63 0.66 0.78 0.044 2.0 0.017 0.028 0.039
## Q6 0.65 0.68 0.79 0.048 2.2 0.016 0.028 0.044
## Q7 0.64 0.67 0.79 0.045 2.0 0.016 0.029 0.039
## Q8 0.64 0.68 0.79 0.047 2.1 0.016 0.029 0.044
## Q9 0.65 0.68 0.79 0.047 2.1 0.016 0.028 0.040
## Q10 0.63 0.66 0.78 0.043 1.9 0.017 0.029 0.038
## Q11 0.64 0.67 0.78 0.045 2.0 0.017 0.028 0.039
## Q12 0.64 0.68 0.79 0.047 2.1 0.016 0.029 0.044
## Q13 0.64 0.67 0.79 0.045 2.0 0.016 0.029 0.039
## Q14 0.64 0.68 0.79 0.046 2.1 0.016 0.028 0.042
## Q15 0.63 0.66 0.78 0.043 2.0 0.017 0.029 0.037
## Q16 0.63 0.67 0.78 0.044 2.0 0.017 0.028 0.039
## Q17 0.64 0.68 0.79 0.046 2.1 0.016 0.029 0.039
## Q18 0.65 0.68 0.80 0.048 2.2 0.016 0.029 0.043
## Q19 0.64 0.68 0.79 0.046 2.1 0.016 0.028 0.042
## Q20 0.63 0.66 0.78 0.043 1.9 0.017 0.029 0.038
## Q21 0.65 0.68 0.79 0.048 2.2 0.016 0.028 0.044
## Q22 0.64 0.67 0.79 0.046 2.1 0.016 0.029 0.039
## Q23 0.65 0.68 0.79 0.048 2.2 0.016 0.028 0.044
## Q24 0.65 0.68 0.79 0.047 2.1 0.016 0.028 0.039
## Q25 0.63 0.66 0.78 0.044 2.0 0.017 0.028 0.039
## Q26 0.64 0.68 0.79 0.046 2.1 0.016 0.029 0.039
## Q27 0.65 0.68 0.79 0.048 2.1 0.016 0.029 0.044
## Q28 0.64 0.67 0.79 0.045 2.0 0.017 0.029 0.039
## Q29 0.65 0.68 0.79 0.048 2.1 0.016 0.028 0.043
## Q30 0.64 0.67 0.78 0.045 2.0 0.017 0.029 0.038
## Q31 0.65 0.68 0.79 0.047 2.1 0.016 0.028 0.044
## Q32 0.64 0.67 0.78 0.045 2.0 0.016 0.028 0.039
## Q33 0.64 0.67 0.79 0.045 2.0 0.016 0.029 0.039
## Q34 0.64 0.68 0.79 0.046 2.1 0.016 0.029 0.040
## Q35 0.65 0.68 0.80 0.048 2.2 0.016 0.029 0.044
## Q36 0.64 0.67 0.79 0.046 2.1 0.016 0.028 0.039
## Q37 0.64 0.68 0.79 0.047 2.1 0.016 0.029 0.043
## Q38 0.64 0.67 0.79 0.045 2.0 0.016 0.029 0.039
## Q39 0.64 0.68 0.79 0.047 2.1 0.016 0.028 0.044
## Q40 0.63 0.66 0.78 0.044 2.0 0.017 0.029 0.038
## Q41 0.66 0.69 0.80 0.049 2.2 0.015 0.029 0.044
## Q42 0.64 0.67 0.79 0.045 2.0 0.016 0.029 0.039
## Q43 0.64 0.68 0.79 0.047 2.1 0.016 0.029 0.043
## Q44 0.64 0.67 0.79 0.045 2.0 0.017 0.029 0.040
##
## Item statistics
## n raw.r std.r r.cor r.drop mean sd
## Q1 1017 0.295 0.306 0.297 0.202 3.4 1.19
## Q2 1017 0.206 0.160 0.109 0.113 2.9 1.15
## Q3 1017 0.293 0.360 0.343 0.229 4.2 0.83
## Q4 1017 0.195 0.134 0.091 0.098 2.3 1.21
## Q5 1017 0.386 0.429 0.431 0.315 3.8 0.98
## Q6 1017 0.123 0.092 0.050 0.026 3.3 1.18
## Q7 1017 0.270 0.329 0.303 0.200 4.0 0.90
## Q8 1017 0.262 0.208 0.170 0.169 3.0 1.17
## Q9 1017 0.135 0.169 0.137 0.039 3.5 1.17
## Q10 1017 0.430 0.480 0.474 0.375 4.4 0.79
## Q11 1017 0.330 0.366 0.359 0.246 3.6 1.10
## Q12 1017 0.201 0.154 0.104 0.114 2.0 1.08
## Q13 1017 0.270 0.339 0.320 0.210 4.4 0.78
## Q14 1017 0.288 0.244 0.214 0.203 3.4 1.09
## Q15 1017 0.431 0.466 0.458 0.363 3.8 0.97
## Q16 1017 0.359 0.397 0.400 0.280 3.6 1.06
## Q17 1017 0.215 0.244 0.205 0.129 3.9 1.08
## Q18 1017 0.159 0.099 0.047 0.052 2.8 1.31
## Q19 1017 0.266 0.220 0.198 0.162 3.3 1.32
## Q20 1017 0.445 0.475 0.478 0.376 4.1 0.99
## Q21 1017 0.126 0.099 0.066 0.024 3.3 1.25
## Q22 1017 0.263 0.286 0.248 0.181 4.0 1.04
## Q23 1017 0.188 0.122 0.074 0.086 3.0 1.26
## Q24 1017 0.126 0.164 0.129 0.031 3.6 1.17
## Q25 1017 0.404 0.440 0.440 0.330 3.7 1.03
## Q26 1017 0.233 0.238 0.204 0.138 3.3 1.18
## Q27 1017 0.189 0.133 0.080 0.090 2.9 1.22
## Q28 1017 0.328 0.375 0.356 0.252 4.0 1.01
## Q29 1017 0.194 0.139 0.091 0.094 3.3 1.24
## Q30 1017 0.329 0.347 0.333 0.244 3.9 1.12
## Q31 1017 0.198 0.151 0.119 0.102 3.4 1.19
## Q32 1017 0.290 0.338 0.326 0.213 4.1 0.99
## Q33 1017 0.304 0.357 0.336 0.233 4.0 0.91
## Q34 1017 0.204 0.238 0.205 0.119 3.7 1.06
## Q35 1017 0.144 0.113 0.047 0.044 3.2 1.23
## Q36 1017 0.254 0.287 0.269 0.162 3.6 1.16
## Q37 1017 0.233 0.173 0.136 0.132 2.7 1.26
## Q38 1017 0.268 0.312 0.285 0.183 3.8 1.08
## Q39 1017 0.223 0.165 0.130 0.122 3.2 1.26
## Q40 1017 0.404 0.439 0.435 0.334 4.0 0.98
## Q41 1017 0.025 -0.012 -0.085 -0.088 2.8 1.38
## Q42 1017 0.279 0.325 0.297 0.206 4.1 0.94
## Q43 1017 0.250 0.207 0.166 0.160 3.5 1.14
## Q44 1017 0.334 0.338 0.317 0.236 3.3 1.28
##
## Non missing response frequency for each item
## 1 2 3 4 5 miss
## Q1 0.07 0.19 0.20 0.35 0.20 0
## Q2 0.12 0.28 0.24 0.28 0.07 0
## Q3 0.01 0.04 0.11 0.44 0.41 0
## Q4 0.32 0.29 0.18 0.17 0.05 0
## Q5 0.02 0.11 0.16 0.48 0.24 0
## Q6 0.08 0.19 0.19 0.40 0.14 0
## Q7 0.01 0.06 0.13 0.48 0.32 0
## Q8 0.11 0.28 0.17 0.37 0.07 0
## Q9 0.06 0.18 0.18 0.38 0.20 0
## Q10 0.00 0.03 0.07 0.37 0.52 0
## Q11 0.03 0.16 0.20 0.38 0.22 0
## Q12 0.44 0.30 0.13 0.11 0.02 0
## Q13 0.00 0.03 0.06 0.33 0.57 0
## Q14 0.05 0.18 0.19 0.44 0.14 0
## Q15 0.01 0.09 0.21 0.42 0.26 0
## Q16 0.03 0.13 0.23 0.38 0.23 0
## Q17 0.03 0.10 0.11 0.41 0.34 0
## Q18 0.20 0.30 0.14 0.24 0.11 0
## Q19 0.11 0.20 0.14 0.33 0.22 0
## Q20 0.02 0.08 0.13 0.39 0.39 0
## Q21 0.10 0.21 0.16 0.36 0.17 0
## Q22 0.03 0.08 0.10 0.41 0.38 0
## Q23 0.14 0.25 0.16 0.34 0.10 0
## Q24 0.05 0.16 0.19 0.35 0.25 0
## Q25 0.02 0.13 0.21 0.43 0.21 0
## Q26 0.08 0.19 0.21 0.37 0.16 0
## Q27 0.16 0.27 0.21 0.29 0.08 0
## Q28 0.02 0.08 0.14 0.40 0.36 0
## Q29 0.10 0.20 0.16 0.38 0.16 0
## Q30 0.04 0.10 0.13 0.37 0.36 0
## Q31 0.08 0.18 0.13 0.45 0.16 0
## Q32 0.02 0.07 0.12 0.37 0.43 0
## Q33 0.01 0.07 0.12 0.46 0.34 0
## Q34 0.03 0.13 0.16 0.44 0.24 0
## Q35 0.10 0.24 0.19 0.32 0.14 0
## Q36 0.04 0.18 0.15 0.38 0.25 0
## Q37 0.22 0.27 0.17 0.29 0.06 0
## Q38 0.03 0.12 0.13 0.43 0.29 0
## Q39 0.10 0.23 0.17 0.34 0.16 0
## Q40 0.03 0.07 0.10 0.46 0.34 0
## Q41 0.24 0.23 0.13 0.29 0.12 0
## Q42 0.02 0.06 0.12 0.44 0.35 0
## Q43 0.05 0.19 0.18 0.40 0.18 0
## Q44 0.11 0.20 0.18 0.33 0.18 0alpha(data,check.keys=TRUE)## Warning in alpha(data, check.keys = TRUE): Some items were negatively correlated with total scale and were automatically reversed.
## This is indicated by a negative sign for the variable name.##
## Reliability analysis
## Call: alpha(x = data, check.keys = TRUE)
##
## raw_alpha std.alpha G6(smc) average_r S/N ase mean sd median_r
## 0.85 0.86 0.9 0.12 6.1 0.0065 3.5 0.41 0.11
##
## lower alpha upper 95% confidence boundaries
## 0.84 0.85 0.87
##
## Reliability if an item is dropped:
## raw_alpha std.alpha G6(smc) average_r S/N alpha se var.r med.r
## Q1 0.85 0.86 0.9 0.12 6.0 0.0067 0.015 0.11
## Q2- 0.85 0.86 0.9 0.12 6.0 0.0067 0.016 0.11
## Q3 0.85 0.86 0.9 0.12 5.9 0.0067 0.016 0.11
## Q4- 0.85 0.85 0.9 0.12 5.9 0.0068 0.016 0.11
## Q5 0.85 0.85 0.9 0.12 5.9 0.0068 0.016 0.11
## Q6- 0.85 0.86 0.9 0.12 6.0 0.0066 0.015 0.11
## Q7 0.85 0.85 0.9 0.12 5.9 0.0067 0.016 0.11
## Q8- 0.85 0.86 0.9 0.12 6.0 0.0066 0.016 0.11
## Q9 0.85 0.86 0.9 0.12 5.9 0.0068 0.016 0.11
## Q10 0.85 0.86 0.9 0.12 6.0 0.0066 0.016 0.11
## Q11 0.85 0.85 0.9 0.12 5.8 0.0068 0.016 0.11
## Q12- 0.85 0.86 0.9 0.12 6.1 0.0066 0.016 0.11
## Q13 0.85 0.86 0.9 0.12 5.9 0.0067 0.016 0.11
## Q14- 0.85 0.86 0.9 0.12 6.0 0.0067 0.016 0.11
## Q15 0.85 0.86 0.9 0.12 6.0 0.0066 0.016 0.11
## Q16 0.85 0.85 0.9 0.12 5.8 0.0068 0.015 0.11
## Q17 0.85 0.86 0.9 0.12 6.0 0.0066 0.016 0.11
## Q18- 0.85 0.86 0.9 0.12 6.0 0.0066 0.016 0.11
## Q19- 0.85 0.86 0.9 0.12 6.0 0.0067 0.015 0.11
## Q20 0.85 0.86 0.9 0.12 6.0 0.0067 0.016 0.11
## Q21- 0.85 0.86 0.9 0.12 6.1 0.0066 0.015 0.11
## Q22 0.85 0.86 0.9 0.12 6.0 0.0066 0.016 0.11
## Q23- 0.85 0.86 0.9 0.12 5.9 0.0067 0.016 0.11
## Q24 0.85 0.86 0.9 0.12 5.9 0.0068 0.016 0.11
## Q25 0.85 0.86 0.9 0.12 5.9 0.0067 0.016 0.11
## Q26 0.85 0.86 0.9 0.12 6.1 0.0066 0.015 0.11
## Q27- 0.85 0.86 0.9 0.12 6.0 0.0067 0.016 0.11
## Q28 0.85 0.86 0.9 0.12 6.0 0.0067 0.016 0.11
## Q29- 0.85 0.86 0.9 0.12 6.0 0.0067 0.016 0.11
## Q30 0.85 0.86 0.9 0.12 6.1 0.0066 0.015 0.11
## Q31- 0.85 0.86 0.9 0.12 5.9 0.0068 0.016 0.11
## Q32 0.85 0.86 0.9 0.12 5.9 0.0067 0.016 0.11
## Q33 0.85 0.86 0.9 0.12 5.9 0.0067 0.016 0.11
## Q34 0.85 0.86 0.9 0.12 6.0 0.0067 0.016 0.11
## Q35- 0.86 0.86 0.9 0.13 6.2 0.0065 0.016 0.12
## Q36 0.85 0.85 0.9 0.12 5.8 0.0068 0.016 0.11
## Q37- 0.85 0.86 0.9 0.12 6.0 0.0067 0.016 0.11
## Q38 0.85 0.86 0.9 0.12 5.9 0.0067 0.016 0.11
## Q39- 0.85 0.86 0.9 0.12 5.9 0.0068 0.016 0.11
## Q40 0.85 0.86 0.9 0.12 6.0 0.0066 0.016 0.11
## Q41- 0.86 0.86 0.9 0.13 6.2 0.0064 0.016 0.11
## Q42 0.85 0.86 0.9 0.12 5.9 0.0067 0.016 0.11
## Q43- 0.85 0.86 0.9 0.12 6.1 0.0066 0.016 0.11
## Q44 0.85 0.86 0.9 0.12 6.1 0.0065 0.016 0.11
##
## Item statistics
## n raw.r std.r r.cor r.drop mean sd
## Q1 1017 0.37 0.37 0.36 0.31 3.4 1.19
## Q2- 1017 0.36 0.35 0.32 0.30 3.1 1.15
## Q3 1017 0.40 0.44 0.42 0.36 4.2 0.83
## Q4- 1017 0.48 0.46 0.44 0.42 3.7 1.21
## Q5 1017 0.47 0.48 0.47 0.42 3.8 0.98
## Q6- 1017 0.35 0.33 0.31 0.29 2.7 1.18
## Q7 1017 0.44 0.46 0.44 0.40 4.0 0.90
## Q8- 1017 0.33 0.32 0.29 0.27 3.0 1.17
## Q9 1017 0.45 0.44 0.43 0.40 3.5 1.17
## Q10 1017 0.33 0.37 0.35 0.29 4.4 0.79
## Q11 1017 0.53 0.53 0.52 0.48 3.6 1.10
## Q12- 1017 0.26 0.27 0.24 0.21 4.0 1.08
## Q13 1017 0.39 0.42 0.41 0.35 4.4 0.78
## Q14- 1017 0.40 0.37 0.36 0.35 2.6 1.09
## Q15 1017 0.32 0.35 0.33 0.27 3.8 0.97
## Q16 1017 0.54 0.54 0.54 0.50 3.6 1.06
## Q17 1017 0.33 0.34 0.32 0.28 3.9 1.08
## Q18- 1017 0.35 0.34 0.31 0.28 3.2 1.31
## Q19- 1017 0.39 0.36 0.34 0.32 2.7 1.32
## Q20 1017 0.35 0.37 0.36 0.30 4.1 0.99
## Q21- 1017 0.32 0.29 0.28 0.26 2.7 1.25
## Q22 1017 0.30 0.31 0.28 0.25 4.0 1.04
## Q23- 1017 0.43 0.41 0.39 0.37 3.0 1.26
## Q24 1017 0.46 0.45 0.44 0.41 3.6 1.17
## Q25 1017 0.41 0.43 0.42 0.37 3.7 1.03
## Q26 1017 0.29 0.28 0.26 0.23 3.3 1.18
## Q27- 1017 0.38 0.37 0.34 0.32 3.1 1.22
## Q28 1017 0.36 0.39 0.36 0.31 4.0 1.01
## Q29- 1017 0.42 0.40 0.38 0.36 2.7 1.24
## Q30 1017 0.28 0.28 0.26 0.22 3.9 1.12
## Q31- 1017 0.46 0.43 0.42 0.41 2.6 1.19
## Q32 1017 0.39 0.41 0.40 0.34 4.1 0.99
## Q33 1017 0.42 0.44 0.42 0.37 4.0 0.91
## Q34 1017 0.38 0.38 0.36 0.32 3.7 1.06
## Q35- 1017 0.19 0.18 0.14 0.12 2.8 1.23
## Q36 1017 0.51 0.51 0.50 0.46 3.6 1.16
## Q37- 1017 0.37 0.35 0.33 0.30 3.3 1.26
## Q38 1017 0.41 0.42 0.40 0.36 3.8 1.08
## Q39- 1017 0.47 0.45 0.43 0.42 2.8 1.26
## Q40 1017 0.32 0.35 0.33 0.27 4.0 0.98
## Q41- 1017 0.19 0.18 0.15 0.12 3.2 1.38
## Q42 1017 0.40 0.42 0.39 0.35 4.1 0.94
## Q43- 1017 0.30 0.29 0.26 0.24 2.5 1.14
## Q44 1017 0.25 0.25 0.23 0.18 3.3 1.28
##
## Non missing response frequency for each item
## 1 2 3 4 5 miss
## Q1 0.07 0.19 0.20 0.35 0.20 0
## Q2 0.12 0.28 0.24 0.28 0.07 0
## Q3 0.01 0.04 0.11 0.44 0.41 0
## Q4 0.32 0.29 0.18 0.17 0.05 0
## Q5 0.02 0.11 0.16 0.48 0.24 0
## Q6 0.08 0.19 0.19 0.40 0.14 0
## Q7 0.01 0.06 0.13 0.48 0.32 0
## Q8 0.11 0.28 0.17 0.37 0.07 0
## Q9 0.06 0.18 0.18 0.38 0.20 0
## Q10 0.00 0.03 0.07 0.37 0.52 0
## Q11 0.03 0.16 0.20 0.38 0.22 0
## Q12 0.44 0.30 0.13 0.11 0.02 0
## Q13 0.00 0.03 0.06 0.33 0.57 0
## Q14 0.05 0.18 0.19 0.44 0.14 0
## Q15 0.01 0.09 0.21 0.42 0.26 0
## Q16 0.03 0.13 0.23 0.38 0.23 0
## Q17 0.03 0.10 0.11 0.41 0.34 0
## Q18 0.20 0.30 0.14 0.24 0.11 0
## Q19 0.11 0.20 0.14 0.33 0.22 0
## Q20 0.02 0.08 0.13 0.39 0.39 0
## Q21 0.10 0.21 0.16 0.36 0.17 0
## Q22 0.03 0.08 0.10 0.41 0.38 0
## Q23 0.14 0.25 0.16 0.34 0.10 0
## Q24 0.05 0.16 0.19 0.35 0.25 0
## Q25 0.02 0.13 0.21 0.43 0.21 0
## Q26 0.08 0.19 0.21 0.37 0.16 0
## Q27 0.16 0.27 0.21 0.29 0.08 0
## Q28 0.02 0.08 0.14 0.40 0.36 0
## Q29 0.10 0.20 0.16 0.38 0.16 0
## Q30 0.04 0.10 0.13 0.37 0.36 0
## Q31 0.08 0.18 0.13 0.45 0.16 0
## Q32 0.02 0.07 0.12 0.37 0.43 0
## Q33 0.01 0.07 0.12 0.46 0.34 0
## Q34 0.03 0.13 0.16 0.44 0.24 0
## Q35 0.10 0.24 0.19 0.32 0.14 0
## Q36 0.04 0.18 0.15 0.38 0.25 0
## Q37 0.22 0.27 0.17 0.29 0.06 0
## Q38 0.03 0.12 0.13 0.43 0.29 0
## Q39 0.10 0.23 0.17 0.34 0.16 0
## Q40 0.03 0.07 0.10 0.46 0.34 0
## Q41 0.24 0.23 0.13 0.29 0.12 0
## Q42 0.02 0.06 0.12 0.44 0.35 0
## Q43 0.05 0.19 0.18 0.40 0.18 0
## Q44 0.11 0.20 0.18 0.33 0.18 0glb(data)## Warning in ICLUST.cluster(r.mat, ICLUST.options, smc.items): Clusters formed as
## requested do not meet the alpha and beta criteria. Perhaps you should rethink
## the number of cluster settings.## Warning in ICLUST.cluster(r.mat, ICLUST.options, smc.items): Clusters formed as
## requested do not meet the alpha and beta criteria. Perhaps you should rethink
## the number of cluster settings.## Loading required namespace: GPArotation## Warning in fac(r = r, nfactors = nfactors, n.obs = n.obs, rotate = rotate, : I
## am sorry, to do these rotations requires the GPArotation package to be installed## $beta
## [1] 0.3966681
##
## $beta.factor
## [1] -0.5935149
##
## $alpha.pc
## [1] 0.8486391
##
## $glb.max
## [1] 0.6553752
##
## $glb.IC
## [1] 0.5146044
##
## $glb.Km
## [1] -1.21942
##
## $glb.Fa
## [1] 0.6553752
##
## $r.smc
## [1] 0.7931879
##
## $tenberge
## $tenberge$mu0
## [1] 0.6795968
##
## $tenberge$mu1
## [1] 0.7229027
##
## $tenberge$mu2
## [1] 0.7234902
##
## $tenberge$mu3
## [1] 0.7235253
##
##
## $keys
## IC1 IC2 ICr1 ICr2 K1 K2 F1 F2 f1 f2
## Q1 1 0 0 1 0 1 0 1 1 0
## Q2 -1 0 1 0 1 0 1 0 0 1
## Q3 1 0 1 0 0 1 0 1 1 0
## Q4 -1 0 1 0 1 0 1 0 0 1
## Q5 0 1 1 0 0 1 0 1 1 0
## Q6 -1 0 1 0 1 0 1 0 0 1
## Q7 1 0 1 0 0 1 1 0 1 0
## Q8 -1 0 1 0 1 0 0 1 0 1
## Q9 1 0 1 0 0 1 1 0 1 0
## Q10 0 1 1 0 0 1 0 1 0 1
## Q11 1 0 1 0 0 1 1 0 1 0
## Q12 -1 0 1 0 1 0 0 1 0 1
## Q13 1 0 1 0 0 1 0 1 1 0
## Q14 -1 0 1 0 1 0 0 1 0 1
## Q15 0 1 1 0 0 1 1 0 0 1
## Q16 1 0 1 0 0 1 0 1 1 0
## Q17 1 0 1 0 0 1 0 1 1 0
## Q18 -1 0 1 0 1 0 0 1 0 1
## Q19 -1 0 1 0 1 0 1 0 0 1
## Q20 0 1 1 0 0 1 1 0 0 1
## Q21 -1 0 0 1 1 0 1 0 0 1
## Q22 1 0 1 0 0 1 1 0 1 0
## Q23 -1 0 1 0 1 0 0 1 0 1
## Q24 1 0 1 0 0 1 1 0 1 0
## Q25 0 1 1 0 0 1 1 0 1 0
## Q26 1 0 1 0 0 1 0 1 1 0
## Q27 -1 0 1 0 1 0 0 1 0 1
## Q28 1 0 1 0 0 1 0 1 1 0
## Q29 -1 0 1 0 1 0 1 0 0 1
## Q30 0 1 1 0 0 1 0 1 0 1
## Q31 -1 0 1 0 1 0 1 0 0 1
## Q32 1 0 1 0 0 1 1 0 1 0
## Q33 1 0 1 0 0 1 0 1 1 0
## Q34 1 0 1 0 0 1 1 0 1 0
## Q35 0 -1 1 0 1 0 1 0 0 1
## Q36 1 0 1 0 0 1 0 1 1 0
## Q37 -1 0 1 0 1 0 0 1 0 1
## Q38 1 0 1 0 0 1 1 0 1 0
## Q39 -1 0 1 0 1 0 0 1 0 1
## Q40 0 1 1 0 0 1 1 0 0 1
## Q41 0 -1 1 0 1 0 0 1 1 0
## Q42 1 0 1 0 0 1 0 1 1 0
## Q43 -1 0 1 0 1 0 1 0 0 1
## Q44 0 1 1 0 0 1 1 0 0 1Cor_data<-cor(data)
eigen(Cor_data)## eigen() decomposition
## $values
## [1] 6.6067242 3.6948136 3.4899727 2.4477353 2.3457026 1.9480589 1.6516367
## [8] 1.1717756 1.0783005 0.9057664 0.8926443 0.8230065 0.7836752 0.7567056
## [15] 0.7417932 0.7196240 0.7099749 0.6750394 0.6567385 0.6475501 0.6384098
## [22] 0.6257552 0.6095086 0.5990372 0.5891287 0.5604190 0.5435817 0.5250084
## [29] 0.5099948 0.4951715 0.4806332 0.4538466 0.4427432 0.4347317 0.4324418
## [36] 0.4129808 0.4018597 0.3957799 0.3874425 0.3796720 0.3647115 0.3373966
## [43] 0.3280252 0.3044820
##
## $vectors
## [,1] [,2] [,3] [,4] [,5]
## [1,] -0.15509301 0.090130855 0.317311057 0.178734002 0.063068616
## [2,] 0.12911572 0.131409109 0.078656681 -0.148007725 0.160456796
## [3,] -0.17483139 0.056712489 -0.144693003 0.022511656 0.269135238
## [4,] 0.18862762 0.217503986 -0.010871757 -0.006692325 0.047585477
## [5,] -0.18651518 0.200559195 0.067583758 -0.225327724 -0.029864860
## [6,] 0.13196472 0.055418363 -0.327755992 -0.139946731 0.030127697
## [7,] -0.18030133 0.058314375 -0.140467304 0.155187074 -0.013872724
## [8,] 0.11656627 0.161157062 0.138416009 -0.012761976 -0.138867648
## [9,] -0.18491488 -0.165967346 -0.030154096 -0.262744368 -0.037925558
## [10,] -0.13544829 0.251025693 -0.064615657 -0.097796607 -0.008326188
## [11,] -0.22420614 0.044453073 0.179596866 0.049399625 0.082323483
## [12,] 0.08733390 0.077927477 0.234217764 -0.141652624 0.132895322
## [13,] -0.16760981 0.051971036 -0.177047243 0.085749586 0.261431846
## [14,] 0.14524542 0.242720418 -0.003124966 0.141137144 0.201193514
## [15,] -0.13083064 0.201217088 -0.066933834 -0.217074791 0.103163911
## [16,] -0.22798436 0.091083309 0.207533746 0.108838116 0.050702061
## [17,] -0.13069184 0.004740946 -0.107763002 0.127840225 -0.127469347
## [18,] 0.13246161 0.150252422 0.108635136 -0.036391426 -0.258198644
## [19,] 0.14454089 0.264164278 -0.044940179 0.258467372 0.153517759
## [20,] -0.13658794 0.275853298 0.016033258 -0.167085707 -0.091832851
## [21,] 0.11846819 0.034164429 -0.357669594 -0.164890481 0.041728836
## [22,] -0.12365685 0.004678391 -0.053939535 0.146316000 0.020518480
## [23,] 0.16044646 0.130151930 0.050256369 -0.010362632 -0.193124470
## [24,] -0.18888489 -0.162726366 -0.056892846 -0.198925125 -0.022566297
## [25,] -0.16722491 0.196186151 0.055390628 -0.262391122 -0.011765447
## [26,] -0.11983815 0.028685878 0.282667673 -0.068052171 0.186506537
## [27,] 0.13427769 0.066848973 0.073976474 -0.296445400 0.124762059
## [28,] -0.15061335 0.083804204 -0.175116354 0.013764364 0.171925966
## [29,] 0.15327050 0.165885439 0.091162200 0.091697355 0.216648529
## [30,] -0.08562476 0.279290518 -0.074464943 -0.004299504 -0.218131239
## [31,] 0.16944266 0.093865830 -0.250256877 -0.081044321 0.119131637
## [32,] -0.15232634 0.102425790 -0.217672843 0.211826449 -0.115693058
## [33,] -0.18146180 0.016960903 -0.065359827 -0.063358649 0.294729226
## [34,] -0.15717677 -0.089818172 -0.027383629 -0.291004874 0.027886773
## [35,] 0.04866450 -0.032851991 -0.049189232 0.102502151 0.220656910
## [36,] -0.20991420 0.037793279 0.226060894 0.170086003 0.019362508
## [37,] 0.12137085 0.068035689 0.204245604 -0.179454652 0.237385176
## [38,] -0.16641683 0.051626479 -0.103820331 0.072621028 0.156514506
## [39,] 0.17287895 0.171089854 -0.058220460 0.135020282 0.182454779
## [40,] -0.11849561 0.278048361 -0.074855896 -0.065880104 -0.114711057
## [41,] 0.04212471 -0.182148518 0.050054998 -0.066154720 0.263825126
## [42,] -0.16323010 0.067724489 -0.075907100 0.208062452 -0.050563243
## [43,] 0.10392615 0.171070131 0.117523812 0.015885385 -0.104093684
## [44,] -0.07599267 0.248856434 -0.052076442 -0.073929766 -0.149297371
## [,6] [,7] [,8] [,9] [,10]
## [1,] -0.0697497189 -0.019463738 -0.0447783532 0.084492631 0.087230843
## [2,] 0.0531103017 -0.304513072 0.0926770602 0.037134679 0.062673612
## [3,] 0.0118938138 0.022265576 0.2691388414 0.224697507 -0.029477165
## [4,] 0.0615865983 0.014076543 -0.1972241824 -0.093510669 0.083701788
## [5,] 0.0594476538 0.230762790 -0.0179401267 -0.140579606 0.124481324
## [6,] -0.0720497007 -0.056144815 -0.1134008446 -0.029560589 0.078178013
## [7,] -0.1637051422 0.102012603 0.0465701764 -0.006792418 0.022103411
## [8,] -0.2773900900 -0.251480100 0.0311814200 0.085951451 -0.151451463
## [9,] -0.1964392351 -0.146847876 -0.0898220274 0.111339996 0.014263000
## [10,] -0.0264938576 0.012456112 0.3209327861 0.112562773 -0.070274798
## [11,] -0.1328297032 0.097544327 -0.0802408568 -0.072786437 0.015175396
## [12,] -0.0197774849 -0.220683717 -0.2497453845 -0.106465918 0.037969403
## [13,] 0.0089969097 -0.008345515 0.2357304056 0.102993030 -0.083653145
## [14,] 0.0106915872 -0.083593637 0.0383987845 -0.108774254 0.051570248
## [15,] 0.0296837828 0.058035425 -0.0005098273 -0.145761360 0.298981920
## [16,] -0.1171913720 0.061136438 -0.0695727316 -0.091021609 -0.008074902
## [17,] -0.3322984954 0.181579688 -0.1241186511 -0.150559863 -0.122267257
## [18,] -0.1754958384 -0.149455583 0.1206529349 -0.077461438 0.184638645
## [19,] 0.0372760410 -0.026574032 0.0553231429 -0.058911261 0.090772653
## [20,] -0.0071766592 0.236483531 0.0102703720 0.029454905 0.073437545
## [21,] -0.1234844614 0.016589876 -0.1330074708 -0.098914057 0.005486661
## [22,] -0.3239312076 0.110799349 -0.2630341947 -0.188364306 -0.327912466
## [23,] -0.2807911251 -0.186320035 0.0268842236 0.059118343 0.145258195
## [24,] -0.1972365918 -0.132936222 -0.0219537466 0.151170134 0.068369887
## [25,] 0.0175436145 0.196490061 -0.0055887113 -0.130661082 0.120667939
## [26,] 0.0489658722 -0.053819194 -0.0527394241 -0.115326157 0.013860087
## [27,] -0.1014550044 -0.061005497 -0.0277120702 -0.107758508 -0.226503581
## [28,] 0.0584445304 -0.312947556 -0.0065737966 -0.025458281 -0.034996616
## [29,] -0.0004763241 0.148805196 -0.0418570360 0.152077587 -0.153641887
## [30,] 0.1516220937 -0.013770222 -0.2130664235 0.276990926 -0.139667900
## [31,] -0.2250021621 0.119605627 -0.0013068707 -0.066503640 -0.141693560
## [32,] -0.1224897306 -0.210591051 -0.0294583940 -0.147678752 0.084071497
## [33,] -0.0082826940 -0.004641053 -0.0088950306 0.076123042 -0.114995510
## [34,] -0.1747720012 -0.065321724 0.0997423101 0.217489740 0.093215820
## [35,] -0.1480778175 0.010805135 -0.3993161246 0.449797200 0.405136917
## [36,] -0.0416475139 -0.088386992 -0.0287322306 0.021454372 0.047909642
## [37,] -0.1665393854 -0.032078374 -0.0009253196 0.089817241 -0.436083141
## [38,] 0.1140541707 -0.329659727 -0.1763297776 -0.078572042 -0.001203500
## [39,] -0.1486615352 0.235668756 0.0362254031 0.053672488 0.149528696
## [40,] 0.0970906285 -0.196591458 0.0755503328 -0.230042489 -0.039244291
## [41,] -0.2226095809 0.029462842 -0.0432305426 -0.309317295 0.254950523
## [42,] -0.1488883889 -0.242012999 0.0547724826 -0.030069649 -0.023098203
## [43,] -0.3060232487 0.068612229 0.2502436255 0.239542647 0.090115371
## [44,] 0.1619702482 0.027648983 -0.4137926990 0.239365244 -0.141478886
## [,11] [,12] [,13] [,14] [,15]
## [1,] -0.037583993 -0.0137416188 -0.0216760821 -0.093387003 0.053805230
## [2,] -0.012491791 -0.2295652416 0.1812617040 -0.176403416 0.236356775
## [3,] 0.077548867 0.0605177203 0.0233566846 0.041164597 -0.137852937
## [4,] 0.435269140 0.0082863346 -0.2283589396 -0.028314467 -0.075410853
## [5,] -0.112006755 -0.0429784466 -0.0496675759 0.007192108 -0.140403781
## [6,] -0.174321813 0.1486479265 0.0597411433 -0.143681312 -0.115243862
## [7,] 0.354984617 -0.1485669287 -0.1699089550 -0.108745143 -0.105240191
## [8,] -0.017679023 0.0261077476 -0.0019911936 0.186443548 -0.234142637
## [9,] 0.052367893 0.1273851024 -0.0594531059 -0.127315304 0.091310153
## [10,] 0.078447739 0.2272180050 0.1281402966 0.239843450 0.191685159
## [11,] -0.260706780 0.2691032840 0.0372888784 -0.048952776 -0.033771287
## [12,] 0.088235579 0.1239384457 0.1357377257 0.006052083 0.032985686
## [13,] 0.106790501 -0.0005213965 0.0989439682 0.164554173 -0.047933934
## [14,] -0.061758651 0.0884892149 -0.2087771603 0.182993625 0.217798338
## [15,] 0.173257055 -0.0522987979 0.3997293772 -0.077044383 0.033835517
## [16,] -0.233764651 0.0821201238 -0.0349085828 -0.145136888 -0.140702328
## [17,] 0.145900674 -0.1240807803 0.0655573329 0.149155153 0.009272677
## [18,] 0.162864650 0.0567012940 -0.0332097184 0.207921517 -0.063129123
## [19,] -0.050169955 -0.1086547175 -0.0848705110 -0.154181738 0.175630641
## [20,] -0.103803920 0.0500785081 -0.1321448374 0.197455776 -0.058354134
## [21,] -0.117378088 0.1849341197 0.0394701067 -0.160956001 -0.049808419
## [22,] 0.137121939 -0.0744423483 0.3542709427 0.098168110 0.165670195
## [23,] -0.016276621 -0.1683779320 0.1398568534 -0.055415043 0.008240733
## [24,] -0.150914580 -0.0359786788 -0.1559205340 0.171355484 0.239864978
## [25,] -0.078298963 -0.2453201704 -0.0998094129 0.041820066 -0.112621406
## [26,] 0.125169804 0.1165413679 0.2059775477 -0.164390441 0.005854049
## [27,] -0.024530597 -0.0645299673 -0.3313348472 -0.127997539 -0.309032837
## [28,] -0.046346003 0.1815016110 -0.0343201737 0.246386954 -0.257021103
## [29,] 0.284980363 0.2425469540 -0.0258522429 -0.069198882 -0.174792068
## [30,] 0.022047817 0.1548138167 -0.0263867826 -0.109697118 0.151339992
## [31,] -0.161149127 0.1205186200 0.0015534621 -0.127341901 0.087691882
## [32,] 0.066792499 0.0168513223 -0.0503009752 -0.225894135 -0.114681841
## [33,] 0.003475302 -0.4986334495 -0.1277935591 -0.166555489 0.021128294
## [34,] 0.298239012 0.1843443768 -0.1024636203 -0.250146264 0.172663461
## [35,] -0.052914664 -0.1526526282 0.0115144812 0.287094063 -0.125560753
## [36,] 0.004318271 0.2070003877 -0.1435905322 -0.128184755 0.068108713
## [37,] -0.072001292 -0.1158030038 -0.0120021131 0.130952751 0.093569727
## [38,] -0.106986520 -0.0379766086 0.1977175488 0.034891950 -0.235250038
## [39,] -0.225784979 0.0934405959 -0.0004774675 -0.092341806 0.225950952
## [40,] -0.042983275 -0.1267635381 -0.0443632778 0.158041936 0.185758350
## [41,] 0.126939508 0.0859472533 -0.2200619794 0.221119770 0.180332595
## [42,] -0.103362694 -0.0476431624 -0.2900125179 -0.142376982 0.113909037
## [43,] -0.079760511 -0.1138956406 0.1727162732 -0.172579537 -0.212355949
## [44,] 0.037017088 -0.0435959457 -0.0743106473 0.022717888 0.185286475
## [,16] [,17] [,18] [,19] [,20]
## [1,] 0.101054439 -0.068800150 -0.057827412 0.025653106 -0.067102630
## [2,] 0.239035102 -0.249440633 -0.010322109 0.043454145 -0.339755951
## [3,] 0.074040498 -0.156556285 0.257084457 -0.025437096 -0.187910435
## [4,] 0.038343470 0.103329582 0.206615829 0.090821365 0.004805310
## [5,] -0.177427568 -0.082138380 -0.019906811 -0.120678987 -0.075861139
## [6,] -0.017392351 -0.074334541 -0.060523892 -0.155300991 0.038263670
## [7,] 0.054619141 -0.423957499 -0.229634643 0.007391114 -0.192222752
## [8,] -0.020370542 0.119891404 0.001022534 0.175664392 0.099249080
## [9,] 0.018753308 -0.071972137 0.053761117 0.134260884 0.009224906
## [10,] 0.085887865 0.102616564 -0.089669972 -0.029532071 -0.107153222
## [11,] 0.264018567 0.001888824 0.056778909 0.198002457 0.055733432
## [12,] -0.266157417 -0.397967273 0.025445402 0.349855268 0.011837069
## [13,] 0.145180746 0.048892645 0.045360561 -0.004296391 0.084052314
## [14,] -0.188500084 0.038291897 -0.206464552 0.159513435 0.001584876
## [15,] 0.107130641 0.365609753 0.192038429 0.215984129 -0.075079540
## [16,] 0.169075731 -0.057838043 0.120883932 0.101491773 0.020074826
## [17,] 0.033520676 -0.056610826 0.278639073 0.168933999 0.212959668
## [18,] 0.069924909 -0.126628838 0.255545970 -0.198415910 -0.040994796
## [19,] -0.027658024 0.026534930 0.044448785 -0.049202948 0.116419631
## [20,] -0.040915149 -0.022809703 -0.255610650 0.064111681 -0.104133850
## [21,] -0.088805198 0.058979644 0.118012343 -0.056836561 -0.038738945
## [22,] -0.102669503 0.104536717 -0.162155928 -0.159710680 -0.265955763
## [23,] 0.184250178 0.036618458 -0.125071032 -0.333303291 0.011414785
## [24,] -0.029665563 -0.036447554 -0.105293844 0.002006760 -0.109764421
## [25,] -0.248623527 -0.096336041 0.017879168 -0.160266680 -0.096941749
## [26,] -0.207082100 0.051033846 0.023623797 -0.459449218 0.158780068
## [27,] 0.323215941 0.273480244 -0.051284288 0.006306249 -0.218599148
## [28,] -0.060681544 -0.210991204 0.196178768 -0.220621541 0.152376819
## [29,] -0.094813927 0.060585912 -0.234324781 0.008986627 -0.037882270
## [30,] 0.077348884 -0.025960592 -0.084159450 -0.146864047 0.177636436
## [31,] 0.062223439 -0.104891729 -0.125879426 0.003461637 0.057465332
## [32,] 0.008976685 -0.003120065 -0.125359900 0.062607461 -0.063931847
## [33,] 0.019223832 0.036040376 -0.013770112 -0.001804012 0.367792740
## [34,] -0.190508384 0.113869048 -0.082554412 0.090651272 0.176131471
## [35,] -0.069731889 0.204935795 -0.049176350 0.003588690 -0.098221321
## [36,] 0.086821890 0.185741372 -0.034217154 -0.194448621 -0.049074684
## [37,] -0.131980833 -0.004680913 0.161253490 -0.083595754 -0.022714767
## [38,] 0.023784564 0.014382283 -0.258550944 0.038534392 0.032907037
## [39,] -0.007259207 -0.099357701 0.197218654 0.001542613 -0.020878888
## [40,] 0.010186345 0.127135430 -0.148556418 0.147373668 0.250974578
## [41,] 0.272659831 -0.064676568 -0.106076358 -0.207761063 0.234230856
## [42,] -0.368304189 0.225961228 0.288854910 -0.031012592 -0.259343739
## [43,] -0.117692102 -0.064100793 -0.065290832 0.056771274 0.304805264
## [44,] 0.247066728 -0.126649607 0.209477824 -0.084351736 0.050539886
## [,21] [,22] [,23] [,24] [,25]
## [1,] -0.171428386 -0.2252488243 0.0809724377 0.122181646 0.0985747199
## [2,] 0.198819449 0.0381601681 -0.1498406266 -0.336656681 -0.3023201421
## [3,] -0.067508186 -0.2235404173 0.0595782073 -0.105856772 0.1872029576
## [4,] -0.172052407 0.0095177809 0.1990253583 -0.062574171 0.0128690535
## [5,] -0.033810153 0.0248344002 -0.0216837675 0.024863422 -0.0514701176
## [6,] -0.007613818 -0.0600307744 -0.0451503572 -0.039470495 0.2188380999
## [7,] 0.119806340 0.1127470490 0.2640808479 0.076964361 -0.0058326958
## [8,] 0.192455928 0.4201946764 -0.1095975218 -0.011950341 -0.0932651353
## [9,] -0.056116735 -0.0733034663 -0.2213740026 -0.062676653 0.0237537046
## [10,] -0.041400766 0.2661193175 0.2737501840 -0.142677160 0.2951432652
## [11,] -0.069879850 0.0125219158 -0.0686642253 -0.149337669 0.0078217681
## [12,] -0.125286301 0.1111395314 0.0922923895 0.245258817 0.2647953197
## [13,] -0.083365288 0.0973367162 -0.2618429248 0.392909588 -0.1509322185
## [14,] 0.301737640 -0.0716369891 -0.0693122130 -0.056857204 0.0186950041
## [15,] 0.058226890 0.0203231791 0.0673334148 0.145325972 -0.0212373424
## [16,] -0.035372722 0.1346596086 -0.1033168820 -0.082585038 0.1224407563
## [17,] 0.209795642 -0.3133218132 0.0206345148 -0.308949958 -0.0218406216
## [18,] -0.217082827 -0.1341940349 -0.3337120382 0.159057262 -0.1778873020
## [19,] 0.028865377 -0.0709446073 -0.1591993866 0.018570695 0.1399956311
## [20,] -0.069292311 0.0651412480 -0.0983007174 0.062478990 -0.1777203690
## [21,] 0.012937093 0.1206728511 -0.0171387358 -0.004365528 -0.0095110049
## [22,] -0.022245923 0.0278948978 -0.0980894462 0.041790995 -0.0423920967
## [23,] -0.221198927 -0.0233135048 -0.0091079588 -0.066511038 0.3822929175
## [24,] 0.084601303 -0.2495471791 0.0006265156 0.295437716 -0.0115138829
## [25,] 0.018544311 0.0244400383 -0.1587019101 -0.227250727 0.0706932924
## [26,] 0.285842828 -0.0641488944 0.0973870978 0.150469195 -0.0810305935
## [27,] 0.184616242 -0.1932816095 0.1511533323 0.147441751 0.0007539024
## [28,] 0.199506702 -0.0399095888 0.0401293180 -0.071883943 0.0052235469
## [29,] -0.174854787 -0.1996881387 -0.3748666993 -0.109252310 -0.0279206693
## [30,] -0.020563932 0.0599078361 0.0550894808 -0.193184036 -0.1376377984
## [31,] -0.155103641 -0.0558465282 0.1029531541 0.140223408 -0.0560353590
## [32,] 0.237000860 0.0632206965 -0.1883102165 0.132882538 0.1104751620
## [33,] -0.128607129 0.2595589547 -0.1805927860 0.033270045 0.1283506143
## [34,] 0.006527692 -0.0503173306 -0.0620270647 -0.150740456 -0.0808890176
## [35,] 0.099132416 -0.0104458680 0.0310944238 -0.078039609 0.0795593877
## [36,] 0.161525119 0.0072782960 0.0321741452 0.020761587 0.0531624912
## [37,] -0.055924664 -0.0437957942 0.0942058906 -0.057162230 0.0521060730
## [38,] -0.341961877 -0.1357950318 0.1947693456 -0.138499348 -0.3472758955
## [39,] 0.043835090 -0.0004998668 0.0440130803 0.102686235 -0.1834565446
## [40,] -0.047462146 -0.3491007272 0.0417032795 0.015547115 0.1022138367
## [41,] -0.126619569 0.2101723447 0.1153387529 -0.114897259 -0.1719321339
## [42,] -0.303739945 0.1228835965 0.1583111495 -0.029084689 -0.1872506015
## [43,] 0.073903747 -0.1031640173 0.2902258576 0.093232054 -0.2441483988
## [44,] 0.071245093 0.0482699561 0.0270105524 0.252026987 -0.0776057893
## [,26] [,27] [,28] [,29] [,30]
## [1,] -8.033697e-02 0.094319983 0.2084064685 -0.018176822 0.13796861
## [2,] -1.925864e-01 0.023573380 -0.0759461830 0.100582025 -0.05667232
## [3,] -8.330080e-02 -0.019987937 -0.0555715284 -0.343592832 -0.01151938
## [4,] -9.389279e-02 0.018846307 0.0093062127 -0.222467957 -0.03486570
## [5,] -1.152331e-01 -0.108512768 0.0070012658 -0.134480633 0.07440798
## [6,] -1.803001e-01 0.362076202 -0.1179905061 0.046202234 0.04464038
## [7,] 3.953985e-01 0.009573614 -0.1184339094 0.055759633 -0.10466380
## [8,] 1.108610e-01 0.189458496 0.1347867946 -0.277756269 -0.13778980
## [9,] 8.364389e-02 -0.078993330 0.1066284836 0.055104220 -0.15039426
## [10,] -3.866072e-02 0.159098305 0.2014421786 0.371416132 0.17568645
## [11,] 2.175935e-01 -0.123552875 -0.2522577598 0.041089758 -0.02206440
## [12,] -2.361067e-01 0.013636057 -0.1480474647 0.080526036 0.06445313
## [13,] -1.379188e-01 0.060791780 -0.4632199862 -0.022944379 -0.03005825
## [14,] 2.421939e-01 -0.106505262 -0.1330115087 -0.139938624 0.15902893
## [15,] 2.184100e-01 -0.050037611 0.1246606638 -0.008856355 -0.12655875
## [16,] 1.126277e-01 -0.023816098 0.0327047297 0.020496598 0.10758891
## [17,] -1.257153e-01 0.357490102 -0.0845041248 0.085217499 0.07106844
## [18,] 1.823577e-01 -0.046005603 -0.0067226120 0.241868201 0.31637699
## [19,] 8.339704e-02 0.032237209 0.0395797118 -0.072964836 0.28562648
## [20,] -2.135156e-01 0.222213828 -0.0402528752 -0.177045608 0.04929635
## [21,] 7.389293e-02 -0.006580940 -0.1149855540 -0.008098603 -0.02939110
## [22,] -1.904728e-01 -0.304911443 0.1050648660 -0.135862630 0.18626997
## [23,] 9.111655e-02 -0.024571899 -0.1072721019 -0.303742800 -0.16142417
## [24,] 1.039046e-01 0.218986761 0.1830636025 -0.082053439 -0.06311540
## [25,] 6.048598e-02 -0.058106885 -0.0367100106 0.070526468 -0.14916497
## [26,] 1.921730e-01 0.299504150 -0.0979279347 0.082135560 -0.00597419
## [27,] -9.740586e-02 -0.037632887 0.0009563031 0.126712979 0.25361215
## [28,] -5.870103e-02 -0.347091500 0.3128916077 0.006157122 -0.02187836
## [29,] 1.730836e-02 0.086631430 0.2239202126 0.235289648 -0.35181433
## [30,] 1.504512e-02 -0.050357726 -0.1612653195 0.023617311 0.14801420
## [31,] 1.526465e-01 -0.179285326 -0.0104669470 0.133480544 -0.05124829
## [32,] -1.688738e-01 0.035868925 0.0942346613 0.079302231 -0.04313616
## [33,] -2.473202e-02 0.043633957 0.1916413935 0.112350244 0.11532348
## [34,] -7.900404e-05 -0.120643524 -0.0278723120 -0.227574230 0.29695038
## [35,] 1.269911e-02 -0.107245643 -0.1583740633 0.241675024 0.04838694
## [36,] -2.602618e-01 -0.054893631 -0.1335277627 -0.051551124 -0.22535221
## [37,] 1.573058e-01 0.037203593 -0.1473010180 -0.036177825 -0.10682113
## [38,] 1.640740e-01 0.211906006 0.0954397021 -0.134952315 0.12736797
## [39,] -4.189852e-02 0.109338518 0.3220092606 -0.142904520 -0.11794901
## [40,] -5.904309e-02 -0.148851172 -0.0968795482 0.094930687 -0.31528043
## [41,] -1.748973e-01 -0.009451204 0.0220916969 0.018267384 -0.11134284
## [42,] -4.741413e-02 0.055416797 -0.1036494439 0.185985824 -0.11294606
## [43,] -2.230702e-01 -0.224670705 -0.0199560387 0.120400165 -0.04226234
## [44,] 1.761620e-02 -0.021514667 0.0743524282 -0.011008308 -0.11189498
## [,31] [,32] [,33] [,34] [,35]
## [1,] -0.100248035 0.0982206236 -0.21893784 0.147250283 -0.019989813
## [2,] -0.091973009 0.1012692976 0.01303996 0.125933798 0.006839564
## [3,] 0.462092526 -0.0795956207 0.12172790 -0.079826238 0.079981237
## [4,] -0.307810297 0.3429716903 0.14243270 0.035786856 0.328009977
## [5,] 0.095069271 0.0661222716 -0.35796076 0.193711501 -0.040531356
## [6,] 0.062886831 0.2390380332 0.09854627 0.034725611 0.073657873
## [7,] -0.083669271 -0.1188894948 0.04376985 0.010472468 -0.038253195
## [8,] 0.118634002 -0.1312607772 0.01966091 0.075579932 0.007381140
## [9,] -0.205137656 0.0198073342 0.09799627 -0.218116373 0.083992178
## [10,] -0.044271836 0.0397231918 0.03186040 -0.074622803 0.095521930
## [11,] 0.017313515 0.0807537644 0.24231133 -0.028114946 0.001634762
## [12,] 0.054911547 -0.1838295067 -0.04252816 -0.148497554 -0.161656223
## [13,] -0.238105330 0.0859276330 -0.08832163 -0.025175725 -0.117746412
## [14,] 0.121194983 0.3902755733 -0.15451997 -0.321083266 -0.047032534
## [15,] 0.057044388 -0.0005654559 -0.23293607 0.053336972 -0.127116936
## [16,] -0.023484452 0.2120154290 0.08678238 0.194810310 0.010087802
## [17,] -0.086653231 -0.0498649785 -0.21136981 -0.050676501 -0.158711989
## [18,] 0.100045999 -0.0764050307 -0.02023087 -0.129411153 0.229894040
## [19,] -0.033805181 -0.2824635372 0.11321564 0.264161561 -0.014813632
## [20,] -0.218931615 -0.0950926114 0.23143594 0.113406535 -0.039678056
## [21,] 0.015590850 -0.0465221847 -0.09692249 -0.063672344 0.103472373
## [22,] 0.036827228 0.0757826107 0.21288033 -0.073739743 0.035668980
## [23,] -0.136903439 0.0516924119 -0.05833403 -0.105068549 -0.325838019
## [24,] 0.005755020 0.2326142902 -0.07377597 0.067667035 0.044021905
## [25,] 0.003249134 -0.0743199206 0.03276176 -0.221546526 0.080629156
## [26,] -0.008655215 0.0418356850 0.28622693 0.027230689 -0.026287892
## [27,] 0.018503132 -0.1474070363 0.06112983 -0.167830036 -0.241920790
## [28,] -0.324331682 0.0399362586 -0.02272243 0.113209807 -0.216935421
## [29,] 0.126109777 0.0674566627 -0.06797678 0.034036247 -0.198157958
## [30,] 0.045107231 -0.0749939306 -0.23393300 -0.062432902 -0.139605493
## [31,] -0.111985780 -0.0752068646 -0.15854373 0.178358475 0.123633713
## [32,] 0.205758125 -0.0280252466 -0.08658867 0.187387487 0.233681290
## [33,] 0.008155863 0.0694148276 -0.02476169 -0.239340191 0.078053416
## [34,] 0.003279997 -0.1403197660 0.07290949 0.169235266 -0.072717910
## [35,] -0.021505643 -0.1391819701 0.07805201 0.126842191 0.069166033
## [36,] -0.122982264 -0.2314657945 -0.28836671 -0.263751380 0.346289274
## [37,] -0.014654284 -0.0800287029 -0.19842288 0.278329463 0.285956318
## [38,] 0.038221191 -0.1180699675 -0.06689775 -0.188026684 0.155615125
## [39,] -0.146361620 -0.2671707539 0.11861115 -0.289700271 -0.046147890
## [40,] 0.048651447 -0.1816799767 0.28278763 0.108767705 0.067414389
## [41,] 0.323298063 -0.0101716187 -0.03810079 0.107514022 -0.093947247
## [42,] 0.079759088 0.0944463189 0.06725446 0.042025484 -0.301562875
## [43,] 0.120955651 0.2558083173 0.07408185 -0.080002030 0.098325712
## [44,] 0.290790830 0.1030406674 0.11511975 -0.002075723 -0.052950140
## [,36] [,37] [,38] [,39] [,40]
## [1,] 0.001644127 0.078908532 -0.06736398 -0.221521002 0.3580546010
## [2,] -0.063990379 -0.089148140 -0.02811641 0.115541430 0.0216996262
## [3,] -0.174429626 0.119297677 0.10228300 0.067534260 0.1143075104
## [4,] 0.068045273 -0.026591109 0.09066083 0.067565156 -0.0703322756
## [5,] 0.160498573 0.119709205 -0.10323443 0.557157069 -0.1441372952
## [6,] 0.351628378 -0.026123733 -0.10073654 -0.030658119 0.3904840306
## [7,] 0.134913526 -0.053856470 0.02575474 0.067533799 0.0896058169
## [8,] 0.143301566 0.044316376 -0.09397996 0.142276896 0.2455355552
## [9,] 0.038226720 0.663657867 0.02835228 0.118310288 -0.0364752957
## [10,] 0.025666266 0.013201040 -0.10807231 0.076974322 -0.1907136653
## [11,] 0.116088793 -0.316120313 0.22900727 0.165742267 0.0394985110
## [12,] -0.018474702 -0.071415047 0.06464496 0.007821154 -0.0665384291
## [13,] 0.205126900 0.078792512 -0.14088868 -0.104861559 -0.1303272686
## [14,] -0.141066601 0.112935956 -0.09650292 -0.054461543 0.0497539203
## [15,] 0.013452915 0.012971148 0.14675650 -0.135613765 0.1868944685
## [16,] -0.052436091 0.085226093 -0.19575035 -0.166498418 -0.2285749452
## [17,] -0.125240302 -0.020912479 -0.08845153 0.079235618 -0.0520845687
## [18,] -0.052835495 -0.105768805 0.03418626 0.034453439 0.1059165274
## [19,] 0.204101148 0.139518368 0.09528737 0.150038926 -0.1625338163
## [20,] -0.451087216 0.043857587 0.20493237 -0.110798920 0.0922078837
## [21,] -0.241319921 -0.159536618 0.12834342 0.015576162 -0.1993910828
## [22,] 0.126346202 -0.006940047 0.04731324 0.026883372 0.0817760993
## [23,] -0.161913179 -0.042700851 -0.02908042 0.005995746 -0.1918139673
## [24,] 0.154552037 -0.266469783 0.25979339 0.091256127 -0.1789654394
## [25,] 0.217457507 -0.054789724 -0.14528064 -0.413146924 -0.0044463968
## [26,] -0.191806236 0.127665711 0.02072123 0.103631071 0.0130761474
## [27,] 0.079161705 0.047208624 0.01787096 -0.019718837 -0.0572896812
## [28,] -0.029464608 -0.128151160 0.07206676 -0.059469300 0.0760498911
## [29,] 0.012377320 -0.132019311 0.02120492 0.075305425 -0.1063886773
## [30,] 0.166275901 0.147407428 0.44014160 -0.118837760 0.0894520921
## [31,] -0.279783303 0.067291740 -0.24742191 0.082887818 0.2542307751
## [32,] -0.109380586 0.065962280 0.14821891 -0.250265615 -0.2454999795
## [33,] -0.183649904 -0.167678946 0.14873851 0.171648960 0.1607713983
## [34,] 0.033275323 -0.275917076 -0.30861355 -0.133133268 -0.0288008061
## [35,] -0.037520223 0.064157188 -0.05133779 0.075041618 0.0008905307
## [36,] -0.036427871 -0.167188320 -0.11577492 0.132532088 0.1016983737
## [37,] 0.056383157 0.038107072 0.14359667 -0.237560083 -0.1118753979
## [38,] 0.033078152 0.007281696 -0.15850434 -0.025658229 -0.2118580626
## [39,] 0.186782389 -0.031284162 -0.01742479 -0.062833770 -0.1019008146
## [40,] 0.066801015 -0.010751781 -0.05564397 0.092610867 0.0674363989
## [41,] 0.046589140 0.131858711 0.07232493 -0.120731112 -0.0261566426
## [42,] -0.040314265 0.021167328 -0.01290755 0.036648194 0.0864138540
## [43,] 0.044863158 0.041549253 0.08220188 -0.038828890 -0.1244840770
## [44,] -0.087696248 -0.056214474 -0.37594413 -0.033069979 -0.1040236071
## [,41] [,42] [,43] [,44]
## [1,] 0.17112817 -0.0997196682 -0.235806285 0.458272605
## [2,] 0.04770224 -0.0669650141 0.003039364 0.012917009
## [3,] 0.11534211 -0.1041726090 0.027956375 -0.082884753
## [4,] 0.20426862 -0.0189974703 0.044608160 -0.052369081
## [5,] 0.01383163 0.0987404339 0.150556499 0.177014142
## [6,] -0.28693113 0.0830807776 0.074876697 -0.037225518
## [7,] -0.22402780 -0.0632474899 0.013357848 0.085022934
## [8,] 0.18839428 -0.1268167378 -0.078096493 0.018279941
## [9,] -0.09856825 0.0910363604 -0.122779277 0.048714172
## [10,] 0.05972566 0.0444831872 -0.059375640 0.048253109
## [11,] 0.15077032 0.3712302372 -0.113290914 0.107104252
## [12,] 0.03495583 -0.0352943209 0.014107283 -0.124390213
## [13,] 0.12459271 -0.0446635963 -0.018973690 0.066497200
## [14,] -0.08552374 0.0601699926 0.032246165 0.050855704
## [15,] -0.19775454 0.0428117580 -0.005767644 -0.163972550
## [16,] -0.19207242 -0.4783002851 0.286911905 -0.212849175
## [17,] 0.03718783 0.0274765769 -0.038631712 -0.050110634
## [18,] -0.09950293 -0.0241581794 0.124234385 0.013693984
## [19,] -0.09148476 0.0131702828 -0.457866920 -0.236257806
## [20,] -0.23038131 0.1010648682 -0.061520120 -0.076742099
## [21,] -0.04204243 -0.4099037420 -0.335947892 0.439098308
## [22,] -0.02849267 -0.0755069287 -0.009193595 -0.018410593
## [23,] 0.01601128 0.1164521263 0.067763111 0.005913644
## [24,] 0.14119948 -0.1867080141 -0.052254449 -0.251231215
## [25,] 0.31785570 -0.0240190330 -0.223817155 -0.139036005
## [26,] 0.19492839 -0.0229973617 0.079333176 0.029964657
## [27,] 0.03672236 0.0003113707 0.031416452 0.010268098
## [28,] -0.08324729 0.0776878891 -0.044817489 -0.022411067
## [29,] -0.06005707 -0.0511783875 -0.027593516 -0.035935382
## [30,] 0.16061078 -0.1877582745 0.190391360 -0.083204928
## [31,] 0.36729972 0.0398788313 0.046104824 -0.331756122
## [32,] 0.21017839 0.3312266955 0.196774501 0.099225979
## [33,] -0.04180715 0.0140768651 0.103059072 0.046452555
## [34,] -0.02843631 0.0600337596 0.096926642 0.066042918
## [35,] 0.05777688 -0.0384236105 0.121420373 0.051555173
## [36,] -0.22030940 -0.0562117076 -0.093533137 -0.219454978
## [37,] -0.27178614 0.2224127435 0.106154234 0.115293399
## [38,] -0.04032618 0.0755318480 -0.039108699 -0.053159109
## [39,] 0.02607930 0.0428478374 0.369663841 0.175501576
## [40,] -0.03192919 -0.2470236731 0.180007560 0.218945818
## [41,] -0.03179649 -0.0274344734 -0.077389751 -0.003630865
## [42,] -0.02143874 0.0667870045 -0.004939242 -0.055387133
## [43,] -0.11496432 -0.0055780702 -0.185686163 -0.061248487
## [44,] -0.10736591 0.1737366580 -0.194844628 0.0197179531 -B :
Cordataset<-data.frame(Cor_data)
data_means<-colMeans(Cordataset)
sorted<-sort(data_means,decreasing = TRUE)[1:5]
sorted## Q10 Q20 Q15 Q25 Q40
## 0.1249910 0.1236756 0.1211648 0.1144871 0.1142559print(fiveQs<-Cordataset[c(10,20,15,25,40)])## Q10 Q20 Q15 Q25 Q40
## Q1 0.097370780 0.161638523 0.053648490 0.145569521 0.06162700
## Q2 0.010071845 -0.057795472 0.062849351 -0.016906137 0.04843845
## Q3 0.287232124 0.130155066 0.227205859 0.159530221 0.11194118
## Q4 -0.029273669 0.020559029 0.055209967 -0.059591105 0.04853183
## Q5 0.301090565 0.514155002 0.382201665 0.576723483 0.28624928
## Q6 0.005591696 -0.043877498 0.025588812 -0.085212015 0.01940527
## Q7 0.203290990 0.168757169 0.121600323 0.162164142 0.11748895
## Q8 0.046275245 0.042455610 -0.079049574 -0.068597510 0.04347001
## Q9 0.058407614 0.049686985 0.124944798 0.164155383 0.02171631
## Q10 1.000000000 0.382422146 0.334777347 0.289872210 0.34567695
## Q11 0.164601096 0.234898245 0.177993878 0.256793093 0.10734880
## Q12 -0.079280078 -0.030756836 0.007765349 0.013732026 -0.01237997
## Q13 0.249563387 0.128269456 0.226899065 0.077982551 0.14369419
## Q14 0.053047706 0.011538666 -0.003685989 -0.072050581 0.12225088
## Q15 0.334777347 0.306584340 1.000000000 0.363701523 0.31060828
## Q16 0.176040837 0.253342865 0.153230609 0.289454747 0.11741388
## Q17 0.084396571 0.115787046 0.065335754 0.097711770 0.09158503
## Q18 0.017844276 0.045749960 -0.058765330 -0.012320369 0.07787023
## Q19 0.027954894 -0.025835182 -0.013511494 -0.123171049 0.12655338
## Q20 0.382422146 1.000000000 0.306584340 0.477071547 0.33488868
## Q21 -0.008256181 -0.040274198 0.101829565 -0.067981259 -0.02310540
## Q22 0.072119029 0.068774003 0.070871092 0.058856727 0.02456177
## Q23 -0.016632408 -0.041703795 -0.089400099 -0.095884077 0.03900254
## Q24 0.083009642 0.083334709 0.084662235 0.133330896 0.05372057
## Q25 0.289872210 0.477071547 0.363701523 1.000000000 0.30455903
## Q26 0.057210849 0.081118300 0.165255902 0.215368340 0.01992914
## Q27 -0.049398020 0.013481078 0.038894812 0.038721552 -0.02860678
## Q28 0.219329568 0.063703063 0.170839916 0.111193716 0.25804333
## Q29 -0.021204381 0.004074728 -0.053157311 -0.081535897 -0.10544947
## Q30 0.307980000 0.346417389 0.163673567 0.209954809 0.34766321
## Q31 0.008135709 -0.032787639 -0.001385649 -0.128167313 -0.02850891
## Q32 0.172694402 0.097346145 0.129989135 0.037761061 0.28607746
## Q33 0.147742343 0.110304360 0.224562268 0.251933144 0.11462525
## Q34 0.158814664 0.119029739 0.199506616 0.191534316 0.03064611
## Q35 -0.135570870 -0.104551767 -0.032204840 -0.118206315 -0.21683008
## Q36 0.136706665 0.136096037 0.054772145 0.146054737 0.11875617
## Q37 -0.029386172 -0.046001126 -0.058460989 0.033038160 -0.10809208
## Q38 0.115998982 0.058276239 0.186051766 0.070237125 0.25175485
## Q39 -0.012225025 0.012882909 -0.017251858 -0.102542841 -0.12197296
## Q40 0.345676955 0.334888678 0.310608276 0.304559035 1.00000000
## Q41 -0.171830708 -0.190321846 -0.074286778 -0.108171045 -0.24040635
## Q42 0.165323005 0.066482181 0.045435216 0.065700941 0.21489671
## Q43 0.066944711 0.098043627 -0.035243045 0.004987494 0.00683121
## Q44 0.205123808 0.318306087 0.211166006 0.230077845 0.30478760alpha(fiveQs)##
## Reliability analysis
## Call: alpha(x = fiveQs)
##
## raw_alpha std.alpha G6(smc) average_r S/N ase mean sd median_r
## 0.9 0.9 0.9 0.65 9.2 0.024 0.12 0.17 0.63
##
## lower alpha upper 95% confidence boundaries
## 0.86 0.9 0.95
##
## Reliability if an item is dropped:
## raw_alpha std.alpha G6(smc) average_r S/N alpha se var.r med.r
## Q10 0.88 0.88 0.86 0.64 7.2 0.030 0.0081 0.62
## Q20 0.87 0.87 0.84 0.62 6.6 0.033 0.0029 0.62
## Q15 0.89 0.89 0.87 0.66 7.8 0.028 0.0073 0.65
## Q25 0.88 0.88 0.84 0.64 7.1 0.031 0.0021 0.63
## Q40 0.89 0.89 0.88 0.67 8.3 0.026 0.0053 0.66
##
## Item statistics
## n raw.r std.r r.cor r.drop mean sd
## Q10 44 0.85 0.85 0.81 0.76 0.12 0.19
## Q20 44 0.89 0.88 0.87 0.82 0.12 0.20
## Q15 44 0.82 0.83 0.76 0.73 0.12 0.18
## Q25 44 0.87 0.86 0.84 0.78 0.11 0.21
## Q40 44 0.81 0.81 0.74 0.70 0.11 0.20glb(fiveQs)## Loading required namespace: GPArotation## Warning in fac(r = r, nfactors = nfactors, n.obs = n.obs, rotate = rotate, : I
## am sorry, to do these rotations requires the GPArotation package to be installed## Warning in fac(r = r, nfactors = nfactors, n.obs = n.obs, rotate = rotate, : An
## ultra-Heywood case was detected. Examine the results carefully## $beta
## [1] 0.8694207
##
## $beta.factor
## [1] NaN
##
## $alpha.pc
## [1] 0.7218343
##
## $glb.max
## [1] 0.9349485
##
## $glb.IC
## [1] 0.930006
##
## $glb.Km
## [1] 0.9349485
##
## $glb.Fa
## [1] 0.8744227
##
## $r.smc
## [1] 0.8955804
##
## $tenberge
## $tenberge$mu0
## [1] 0.9019261
##
## $tenberge$mu1
## [1] 0.9029154
##
## $tenberge$mu2
## [1] 0.9033335
##
## $tenberge$mu3
## [1] 0.9035189
##
##
## $keys
## IC1 IC2 ICr1 ICr2 K1 K2 F1 F2 f1 f2
## Q10 1 0 1 0 0 1 1 0 1 0
## Q20 0 1 0 1 1 0 1 0 1 0
## Q15 1 0 0 1 1 0 0 1 1 0
## Q25 0 1 1 0 0 1 0 1 1 0
## Q40 1 0 1 0 1 0 1 0 1 0Problem 2:
2-A:
tr <- read.csv("TaskRatings.csv")
data <- tr
merged <- c(data[,3],data[,11], data[,19])
subject <- as.factor(rep(1:3,each=nrow(data)))
task <- rep(data$Task,3)
frame.gm <- data.frame(task,subject,merged)
library(knitr)
library(ggplot2)##
## Attaching package: 'ggplot2'## The following objects are masked from 'package:psych':
##
## %+%, alphalibrary(GGally) ## Warning: package 'GGally' was built under R version 3.6.2## Registered S3 method overwritten by 'GGally':
## method from
## +.gg ggplot2##
## Attaching package: 'GGally'## The following object is masked from 'package:dplyr':
##
## nasalibrary(reshape2)
cor(tr[3:10],method = "pearson")## GM.1 FM.1 R.1 V.1 LTM.1 WM.1
## GM.1 1.0000000 0.26255692 -0.2531784 0.2184429 -0.25185870 0.1616224
## FM.1 0.2625569 1.00000000 -0.1085015 0.1555248 -0.08726778 0.5029053
## R.1 -0.2531784 -0.10850149 1.0000000 0.2769584 0.55874923 0.2299233
## V.1 0.2184429 0.15552485 0.2769584 1.0000000 0.31968530 0.4067361
## LTM.1 -0.2518587 -0.08726778 0.5587492 0.3196853 1.00000000 0.4961803
## WM.1 0.1616224 0.50290529 0.2299233 0.4067361 0.49618034 1.0000000
## Att.1 -0.1239599 0.01285981 0.6333898 0.4060387 0.64111888 0.4789322
## EC.1 -0.1170045 0.15403826 0.5652861 0.3610463 0.60677415 0.5639856
## Att.1 EC.1
## GM.1 -0.12395987 -0.1170045
## FM.1 0.01285981 0.1540383
## R.1 0.63338976 0.5652861
## V.1 0.40603873 0.3610463
## LTM.1 0.64111888 0.6067742
## WM.1 0.47893224 0.5639856
## Att.1 1.00000000 0.7181948
## EC.1 0.71819482 1.0000000cor(tr[3],tr[11])## GM.2
## GM.1 0.6638527cor(tr[4],tr[12])## FM.2
## FM.1 0.7475984cor(tr[5],tr[13])## R.2
## R.1 0.5319479cor(tr[6],tr[14])## V.2
## V.1 0.6848928cor(tr[7],tr[15])## LTM.2
## LTM.1 0.3883135cor(tr[8],tr[16])## WM.2
## WM.1 0.01468169cor(tr[9],tr[17])## Att.2
## Att.1 0.6104159cor(tr[10],tr[18])## EC.2
## EC.1 0.51769042-B:
merged1 <- c(data[,4],data[,12], data[,20])
subject1 <- as.factor(rep(1:3,each=nrow(data)))
task1 <- rep(data$Task,3)
frame.fm <- data.frame(task1,subject1,merged1)
merged2 <- c(data[,5],data[,13], data[,21])
subject2 <- as.factor(rep(1:3,each=nrow(data)))
task2 <- rep(data$Task,3)
frame.r <- data.frame(task2,subject2,merged2)
merged3 <- c(data[,6],data[,14], data[,22])
subject3 <- as.factor(rep(1:3,each=nrow(data)))
task3 <- rep(data$Task,3)
frame.v <- data.frame(task3,subject3,merged3)
merged4 <- c(data[,7],data[,15], data[,23])
subject4 <- as.factor(rep(1:3,each=nrow(data)))
task4 <- rep(data$Task,3)
frame.ltm <- data.frame(task4,subject4,merged4)
merged5 <- c(data[,8],data[,16], data[,24])
subject5 <- as.factor(rep(1:3,each=nrow(data)))
task5 <- rep(data$Task,3)
frame.wm <- data.frame(task5,subject5,merged5)
merged6 <- c(data[,9],data[,17], data[,25])
subject6 <- as.factor(rep(1:3,each=nrow(data)))
task6 <- rep(data$Task,3)
frame.att <- data.frame(task6,subject6,merged6)
merged7 <- c(data[,10],data[,18], data[,26])
subject7 <- as.factor(rep(1:3,each=nrow(data)))
task7 <- rep(data$Task,3)
frame.ec <- data.frame(task7,subject7,merged7)
require(ICC)## Loading required package: ICClibrary(reshape2)
library(dplyr)
library(ICC)
ICC_GM<-ICCest(x=task,y=merged,data=frame.gm)
ICC_FM<-ICCest(x=task1,y=merged1,data=frame.fm)
ICC_R<-ICCest(x=task2,y=merged2,data=frame.r)
ICC_V<-ICCest(x=task3,y=merged3,data=frame.v)
ICC_LTM<-ICCest(x=task4,y=merged4,data=frame.ltm)
ICC_WM<-ICCest(x=task5,y=merged5,data=frame.wm)
ICC_ATT<-ICCest(x=task6,y=merged6,data=frame.att)
ICC_EC<-ICCest(x=task7,y=merged7,data=frame.ec)
ICC_GM## $ICC
## [1] 0.212527
##
## $LowerCI
## [1] 0.09429839
##
## $UpperCI
## [1] 0.3395611
##
## $N
## [1] 107
##
## $k
## [1] 3
##
## $varw
## [1] 2.962617
##
## $vara
## [1] 0.799565ICC_FM## $ICC
## [1] 0.6057337
##
## $LowerCI
## [1] 0.5055756
##
## $UpperCI
## [1] 0.6963667
##
## $N
## [1] 107
##
## $k
## [1] 3
##
## $varw
## [1] 1.442368
##
## $vara
## [1] 2.215992ICC_R## $ICC
## [1] 0.4227881
##
## $LowerCI
## [1] 0.3053517
##
## $UpperCI
## [1] 0.5379009
##
## $N
## [1] 107
##
## $k
## [1] 3
##
## $varw
## [1] 1.274143
##
## $vara
## [1] 0.9332667ICC_V## $ICC
## [1] 0.4800731
##
## $LowerCI
## [1] 0.3662877
##
## $UpperCI
## [1] 0.5888517
##
## $N
## [1] 107
##
## $k
## [1] 3
##
## $varw
## [1] 1.476636
##
## $vara
## [1] 1.363448ICC_LTM## $ICC
## [1] -0.150081
##
## $LowerCI
## [1] -0.2288591
##
## $UpperCI
## [1] -0.0508192
##
## $N
## [1] 107
##
## $k
## [1] 3
##
## $varw
## [1] 3.423676
##
## $vara
## [1] -0.446776ICC_WM## $ICC
## [1] 0.2243142
##
## $LowerCI
## [1] 0.105634
##
## $UpperCI
## [1] 0.3511783
##
## $N
## [1] 107
##
## $k
## [1] 3
##
## $varw
## [1] 1.859813
##
## $vara
## [1] 0.537824ICC_ATT## $ICC
## [1] 0.4328725
##
## $LowerCI
## [1] 0.3159669
##
## $UpperCI
## [1] 0.5469615
##
## $N
## [1] 107
##
## $k
## [1] 3
##
## $varw
## [1] 1.003115
##
## $vara
## [1] 0.7656498ICC_EC## $ICC
## [1] 0.3486409
##
## $LowerCI
## [1] 0.2287275
##
## $UpperCI
## [1] 0.4700486
##
## $N
## [1] 107
##
## $k
## [1] 3
##
## $varw
## [1] 1.186916
##
## $vara
## [1] 0.63529852 - C:
library(psych)
a1<-frame.gm$subject[1:107]
b1<-frame.gm$subject[108:214]
cohen.kappa(cbind(a1,b1))## Call: cohen.kappa1(x = x, w = w, n.obs = n.obs, alpha = alpha, levels = levels)
##
## Cohen Kappa and Weighted Kappa correlation coefficients and confidence boundaries
## lower estimate upper
## unweighted kappa 0 0 0
## weighted kappa 0 0 0
##
## Number of subjects = 107a2<-frame.fm$subject1[1:107]
b2<-frame.fm$subject1[108:214]
cohen.kappa(cbind(a2,b2))## Call: cohen.kappa1(x = x, w = w, n.obs = n.obs, alpha = alpha, levels = levels)
##
## Cohen Kappa and Weighted Kappa correlation coefficients and confidence boundaries
## lower estimate upper
## unweighted kappa 0 0 0
## weighted kappa 0 0 0
##
## Number of subjects = 107a3<-frame.r$subject2[1:107]
b3<-frame.r$subject2[108:214]
cohen.kappa(cbind(a3,b3))## Call: cohen.kappa1(x = x, w = w, n.obs = n.obs, alpha = alpha, levels = levels)
##
## Cohen Kappa and Weighted Kappa correlation coefficients and confidence boundaries
## lower estimate upper
## unweighted kappa 0 0 0
## weighted kappa 0 0 0
##
## Number of subjects = 107a4<-frame.v$subject3[1:107]
b4<-frame.v$subject3[108:214]
cohen.kappa(cbind(a4,b4))## Call: cohen.kappa1(x = x, w = w, n.obs = n.obs, alpha = alpha, levels = levels)
##
## Cohen Kappa and Weighted Kappa correlation coefficients and confidence boundaries
## lower estimate upper
## unweighted kappa 0 0 0
## weighted kappa 0 0 0
##
## Number of subjects = 107a5<-frame.ltm$subject4[1:107]
b5<-frame.ltm$subject4[108:214]
cohen.kappa(cbind(a5,b5))## Call: cohen.kappa1(x = x, w = w, n.obs = n.obs, alpha = alpha, levels = levels)
##
## Cohen Kappa and Weighted Kappa correlation coefficients and confidence boundaries
## lower estimate upper
## unweighted kappa 0 0 0
## weighted kappa 0 0 0
##
## Number of subjects = 107a6<-frame.wm$subject5[1:107]
b6<-frame.wm$subject5[108:214]
cohen.kappa(cbind(a6,b6))## Call: cohen.kappa1(x = x, w = w, n.obs = n.obs, alpha = alpha, levels = levels)
##
## Cohen Kappa and Weighted Kappa correlation coefficients and confidence boundaries
## lower estimate upper
## unweighted kappa 0 0 0
## weighted kappa 0 0 0
##
## Number of subjects = 107a7<-frame.att$subject6[1:107]
b7<-frame.att$subject6[108:214]
cohen.kappa(cbind(a7,b7))## Call: cohen.kappa1(x = x, w = w, n.obs = n.obs, alpha = alpha, levels = levels)
##
## Cohen Kappa and Weighted Kappa correlation coefficients and confidence boundaries
## lower estimate upper
## unweighted kappa 0 0 0
## weighted kappa 0 0 0
##
## Number of subjects = 107a8<-frame.ec$subject7[1:107]
b8<-frame.ec$subject7[108:214]
cohen.kappa(cbind(a6,b6))## Call: cohen.kappa1(x = x, w = w, n.obs = n.obs, alpha = alpha, levels = levels)
##
## Cohen Kappa and Weighted Kappa correlation coefficients and confidence boundaries
## lower estimate upper
## unweighted kappa 0 0 0
## weighted kappa 0 0 0
##
## Number of subjects = 107