distrubution of dietary group
library(psych)
describe(food2)
vars n mean sd median trimmed mad min max
rice 1 10041 276.65 162.83 246.36 264.10 130.88 0 1589.60
corn 2 10041 17.49 64.26 0.00 0.49 0.00 0 1886.52
othercereal 3 10041 25.65 32.14 15.51 19.66 23.00 0 436.35
roots 4 10041 12.49 45.96 0.00 2.20 0.00 0 1037.72
Sugar 5 10041 10.95 16.43 5.00 7.61 7.41 0 282.60
beans 6 10041 5.96 18.04 0.00 1.83 0.00 0 416.37
leafy 7 10041 33.23 54.66 15.03 21.69 22.28 0 809.62
othervegetables 8 10041 49.52 70.11 26.19 35.50 38.82 0 1156.18
vitCfruit 9 10041 6.55 51.99 0.00 0.00 0.00 0 2740.00
otherfruit 10 10041 34.10 102.39 0.00 10.79 0.00 0 2285.62
fish 11 10041 109.91 117.82 81.35 91.35 86.97 0 2506.41
meat 12 10041 53.46 86.39 17.25 35.08 25.57 0 1141.59
poultry 13 10041 27.27 56.05 0.00 13.92 0.00 0 835.20
Eggs 14 10041 10.39 18.96 0.00 6.08 0.00 0 261.80
wholemilk 15 10041 11.64 48.71 0.00 0.22 0.00 0 1102.20
milkproducts 16 10041 11.72 91.92 0.00 0.00 0.00 0 2625.00
fats 17 10041 5.87 16.67 3.00 3.68 4.08 0 569.06
beverages 18 10041 42.74 147.37 6.25 14.01 9.27 0 3869.80
condiments 19 10041 1.94 5.27 0.00 0.74 0.00 0 135.00
miscellaneous 20 10041 3.57 28.23 0.00 0.12 0.00 0 945.00
range skew kurtosis se
rice 1589.60 1.09 2.75 1.62
corn 1886.52 6.93 105.73 0.64
othercereal 436.35 2.39 10.03 0.32
roots 1037.72 8.31 105.45 0.46
Sugar 282.60 3.27 20.73 0.16
beans 416.37 7.17 82.33 0.18
leafy 809.62 4.09 28.06 0.55
othervegetables 1156.18 3.32 21.64 0.70
vitCfruit 2740.00 22.82 883.40 0.52
otherfruit 2285.62 7.58 96.70 1.02
fish 2506.41 3.35 31.98 1.18
meat 1141.59 3.27 17.93 0.86
poultry 835.20 3.69 22.12 0.56
Eggs 261.80 2.80 13.06 0.19
wholemilk 1102.20 7.15 75.58 0.49
milkproducts 2625.00 13.65 244.17 0.92
fats 569.06 15.97 352.80 0.17
beverages 3869.80 10.35 166.17 1.47
condiments 135.00 7.75 117.96 0.05
miscellaneous 945.00 15.80 340.46 0.28
sum(complete.cases(food2))
[1] 10041
factor loading
pa6.out <-fa(food2, nfactors =6, scores=T, rotate ="varimax", fm="pa")
print(pa6.out$loadings, cutoff=0, digits=3)
Loadings:
PA1 PA3 PA4 PA2 PA6 PA5
rice 0.944 0.012 0.136 0.081 -0.042 0.065
corn -0.328 -0.037 0.045 -0.001 -0.100 0.293
othercereal -0.013 -0.017 -0.047 0.195 0.439 -0.081
roots -0.046 0.040 0.005 0.018 -0.005 0.144
Sugar 0.056 0.017 -0.005 0.270 0.282 -0.014
beans 0.047 -0.025 -0.070 0.045 0.065 0.045
leafy 0.004 0.004 0.001 -0.106 -0.068 0.497
othervegetables 0.120 0.033 -0.114 -0.050 0.058 0.295
vitCfruit 0.030 0.068 0.003 0.005 0.106 0.048
otherfruit -0.019 0.685 0.024 0.004 0.081 0.059
fish 0.112 0.012 0.757 -0.041 -0.011 -0.053
meat 0.092 0.006 -0.141 0.488 0.126 -0.071
poultry 0.086 0.027 -0.083 0.212 0.152 -0.038
Eggs 0.106 0.012 -0.087 0.047 0.184 -0.047
wholemilk -0.032 0.051 -0.007 -0.027 0.202 -0.005
milkproducts -0.042 0.050 -0.011 0.146 0.188 -0.007
fats 0.034 0.005 0.022 0.055 0.270 0.000
beverages -0.012 -0.004 0.009 0.329 -0.023 0.006
condiments -0.038 -0.005 0.100 0.197 0.126 -0.027
miscellaneous 0.026 0.469 0.001 0.020 0.070 0.046
PA1 PA3 PA4 PA2 PA6 PA5
SS loadings 1.068 0.706 0.659 0.594 0.558 0.474
Proportion Var 0.053 0.035 0.033 0.030 0.028 0.024
Cumulative Var 0.053 0.089 0.122 0.151 0.179 0.203
distrubution of factor score
describe(pa6.out$scores)
vars n mean sd median trimmed mad min max range skew kurtosis
PA1 1 10041 0 0.95 -0.14 -0.06 0.78 -2.35 7.71 10.06 0.96 2.64
PA3 2 10041 0 0.73 -0.20 -0.14 0.07 -1.03 19.41 20.43 9.32 148.79
PA4 3 10041 0 0.77 -0.17 -0.11 0.57 -1.43 15.08 16.51 3.00 27.17
PA2 4 10041 0 0.62 -0.17 -0.10 0.38 -1.64 8.01 9.65 2.82 14.64
PA6 5 10041 0 0.60 -0.14 -0.08 0.43 -2.47 6.99 9.46 2.40 12.63
PA5 6 10041 0 0.61 -0.15 -0.10 0.39 -1.11 9.23 10.34 3.34 22.96
se
PA1 0.01
PA3 0.01
PA4 0.01
PA2 0.01
PA6 0.01
PA5 0.01
