Análise psicométrica
psicom <- score_tests(data = bd, item_dic = dic, min = 1, max = 5, run_scrub = TRUE)
print.psych(psicom)
## Call: scoreItems(keys = keys, items = data[, rownames(keys)], missing = TRUE,
## impute = "none", digits = 3)
##
## (Standardized) Alpha:
## A C E N NV O
## alpha 0.69 0.73 0.41 0.68 0.45 0.75
##
## Standard errors of unstandardized Alpha:
## A C E N NV O
## ASE 0.015 0.014 0.025 0.015 0.024 0.014
##
## Standardized Alpha of observed scales:
## A C E N NV O
## alpha.observed 0.69 0.73 0.41 0.68 0.45 0.75
##
## Average item correlation:
## A C E N NV O
## average.r 0.18 0.23 0.071 0.17 0.094 0.27
##
## Guttman 6* reliability:
## A C E N NV O
## Lambda.6 0.73 0.77 0.52 0.74 0.52 0.76
##
## Signal/Noise based upon av.r :
## A C E N NV O
## Signal/Noise 2.2 2.7 0.68 2.1 0.83 2.9
##
## Scale intercorrelations corrected for attenuation
## raw correlations below the diagonal, alpha on the diagonal
## corrected correlations above the diagonal:
##
## Note that these are the correlations of the complete scales based on the correlation matrix,
## not the observed scales based on the raw items.
## A C E N NV O
## A 0.69 0.70 0.832 0.51 0.018 0.685
## C 0.50 0.73 0.525 0.62 -0.383 0.481
## E 0.44 0.29 0.406 0.26 0.191 0.944
## N 0.35 0.43 0.136 0.68 -0.652 0.084
## NV 0.01 -0.22 0.082 -0.36 0.453 0.487
## O 0.49 0.36 0.519 0.06 0.283 0.746
##
## In order to see the item by scale loadings and frequency counts of the data
## print with the short option = FALSE
# save_item_psicom(psychObj = psicom, item_dic = dic, filename = "psicom.xlsx")
Análise fatorial exploratória
library(psych)
# Análise paralela
# p <- fa.parallel.poly(bd[ , 5:58], n.iter=20, SMC=TRUE)
m5o <- fa(p$rho, fm="minres", nfactors = 6, cor = "poly", rotate = "oblimin")
## Loading required namespace: GPArotation
m5v <- fa(p$rho, fm="minres", nfactors = 6, cor = "poly", rotate = "varimax")
plot(p)
![](data:image/png;base64,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)
print.psych(m5v, cut = .30)
## Factor Analysis using method = minres
## Call: fa(r = p$rho, nfactors = 6, rotate = "varimax", fm = "minres",
## cor = "poly")
## Standardized loadings (pattern matrix) based upon correlation matrix
## MR1 MR2 MR3 MR4 MR5 MR6 h2 u2 com
## Sv1.003 0.44 0.35 0.34 0.66 2.2
## Sv1.004 0.62 0.51 0.49 1.7
## Sv1.005 0.65 0.54 0.46 1.6
## Sv1.006 0.51 0.55 0.60 0.40 2.3
## Sv1.007 0.83 0.71 0.29 1.1
## Sv1.009 0.57 0.37 0.55 0.45 2.4
## Sv1.010 0.65 0.51 0.49 1.4
## Sv1.011 0.52 0.52 0.57 0.43 2.2
## Sv1.012 0.67 0.46 0.54 1.0
## Sv1.013 0.45 0.46 0.46 0.54 2.3
## Sv1.014 0.53 0.35 0.65 1.5
## Sv1.017 0.79 0.63 0.37 1.0
## Sv1.024 0.37 0.25 0.75 2.8
## Sv1.025 0.23 0.77 3.2
## Sv1.027 0.55 0.33 0.41 0.59 1.7
## Sv1.029 0.31 0.18 0.82 2.8
## Sv1.030 0.62 0.39 0.61 1.1
## Sv1.032 0.70 0.51 0.49 1.1
## Sv1.033 0.11 0.89 3.2
## Sv1.034 0.39 0.26 0.74 2.4
## Sv1.036 0.49 0.38 0.62 2.2
## Sv1.037 0.48 0.36 0.48 0.52 3.2
## Sv1.039 0.58 0.30 0.47 0.53 1.8
## Sv1.040 0.58 0.37 0.63 1.2
## Sv1.042 0.50 0.30 0.70 1.5
## Sv1.044 0.63 0.45 0.55 1.3
## Sv1.046 0.52 -0.37 0.49 0.51 2.5
## Sv1.048 0.46 0.28 0.72 1.7
## Sv1.049 0.62 0.49 0.51 1.7
## Sv1.051 0.38 0.24 0.76 2.2
## Sv1.052 0.37 0.37 0.29 0.71 2.1
## Sv1.053 0.35 0.15 0.85 1.5
## Sv1.054 0.57 0.42 0.58 1.6
## Sv1.055 0.75 0.57 0.43 1.0
## Sv1.056 0.32 0.24 0.76 3.1
## Sv1.060 0.35 0.20 0.80 2.4
## Sv1.063 0.63 0.44 0.56 1.2
## Sv1.066 0.34 0.32 0.24 0.76 2.3
## Sv1.067 0.38 0.26 0.74 2.5
## Sv1.070 0.41 0.25 0.75 2.0
## Sv1.071 0.57 0.38 0.62 1.3
## Sv1.073 0.33 0.21 0.79 2.4
## Sv1.074 0.39 0.25 0.75 2.3
## Sv1.075 0.63 0.43 0.57 1.2
## Sv1.076 0.18 0.82 3.3
## Sv1.077 0.37 0.42 0.37 0.63 2.7
## Sv1.079 0.50 0.27 0.73 1.2
## Sv1.082 0.20 0.80 3.0
## Sv1.083 0.33 0.55 0.48 0.52 2.2
## Sv1.084 0.41 0.32 0.30 0.70 2.3
## Sv1.087 0.14 0.86 2.2
## Sv1.088 0.53 0.32 0.68 1.2
## Sv1.089 0.36 0.46 0.44 0.56 2.9
## Sv1.091 0.31 0.45 0.39 0.61 2.7
##
## MR1 MR2 MR3 MR4 MR5 MR6
## SS loadings 8.16 5.53 2.30 1.62 1.48 0.82
## Proportion Var 0.15 0.10 0.04 0.03 0.03 0.02
## Cumulative Var 0.15 0.25 0.30 0.33 0.35 0.37
## Proportion Explained 0.41 0.28 0.12 0.08 0.07 0.04
## Cumulative Proportion 0.41 0.69 0.80 0.88 0.96 1.00
##
## Mean item complexity = 2
## Test of the hypothesis that 6 factors are sufficient.
##
## The degrees of freedom for the null model are 1431 and the objective function was 19.2
## The degrees of freedom for the model are 1122 and the objective function was 2.42
##
## The root mean square of the residuals (RMSR) is 0.03
## The df corrected root mean square of the residuals is 0.03
##
## Fit based upon off diagonal values = 0.98
## Measures of factor score adequacy
## MR1 MR2 MR3 MR4 MR5
## Correlation of scores with factors 0.94 0.95 0.85 0.80 0.81
## Multiple R square of scores with factors 0.89 0.91 0.71 0.64 0.66
## Minimum correlation of possible factor scores 0.78 0.81 0.43 0.28 0.32
## MR6
## Correlation of scores with factors 0.76
## Multiple R square of scores with factors 0.58
## Minimum correlation of possible factor scores 0.17
print.psych(m5o, cut = .30)
## Factor Analysis using method = minres
## Call: fa(r = p$rho, nfactors = 6, rotate = "oblimin", fm = "minres",
## cor = "poly")
## Standardized loadings (pattern matrix) based upon correlation matrix
## MR2 MR1 MR5 MR6 MR3 MR4 h2 u2 com
## Sv1.003 0.43 0.34 0.66 2.0
## Sv1.004 0.49 0.51 0.49 1.6
## Sv1.005 0.67 0.54 0.46 1.2
## Sv1.006 0.62 0.60 0.40 1.3
## Sv1.007 0.84 0.71 0.29 1.0
## Sv1.009 0.65 0.55 0.45 1.2
## Sv1.010 0.72 0.51 0.49 1.0
## Sv1.011 0.59 0.57 0.43 1.4
## Sv1.012 0.64 0.46 0.54 1.0
## Sv1.013 0.56 0.46 0.54 1.3
## Sv1.014 0.32 0.35 0.65 2.7
## Sv1.017 0.79 0.63 0.37 1.0
## Sv1.024 0.32 0.25 0.75 2.7
## Sv1.025 0.36 0.30 0.23 0.77 2.4
## Sv1.027 0.38 0.41 0.41 0.59 2.0
## Sv1.029 0.31 0.18 0.82 2.1
## Sv1.030 0.52 0.39 0.61 1.3
## Sv1.032 0.70 0.51 0.49 1.1
## Sv1.033 0.11 0.89 2.6
## Sv1.034 0.40 0.26 0.74 1.8
## Sv1.036 -0.31 0.38 0.62 3.8
## Sv1.037 -0.41 0.36 0.48 0.52 3.4
## Sv1.039 0.56 0.47 0.53 1.2
## Sv1.040 0.45 0.37 0.63 1.4
## Sv1.042 0.36 0.30 0.70 2.2
## Sv1.044 0.53 -0.30 0.45 0.55 1.8
## Sv1.046 -0.42 0.34 0.49 0.51 2.8
## Sv1.048 0.32 0.28 0.72 3.3
## Sv1.049 0.44 0.49 0.51 1.9
## Sv1.051 -0.30 0.24 0.76 3.0
## Sv1.052 0.45 0.29 0.71 1.3
## Sv1.053 0.15 0.85 2.2
## Sv1.054 0.40 0.42 0.58 2.1
## Sv1.055 0.59 0.57 0.43 1.4
## Sv1.056 0.24 0.76 3.3
## Sv1.060 0.20 0.80 4.0
## Sv1.063 0.41 0.33 0.44 0.56 2.5
## Sv1.066 0.24 0.76 3.1
## Sv1.067 0.41 0.26 0.74 1.9
## Sv1.070 0.41 0.25 0.75 1.4
## Sv1.071 0.40 0.32 0.38 0.62 2.9
## Sv1.073 0.39 0.21 0.79 1.3
## Sv1.074 0.32 0.25 0.75 2.0
## Sv1.075 0.35 0.33 0.43 0.57 2.2
## Sv1.076 0.18 0.82 2.3
## Sv1.077 0.43 0.37 0.63 1.8
## Sv1.079 0.51 0.27 0.73 1.3
## Sv1.082 0.20 0.80 2.7
## Sv1.083 0.59 0.48 0.52 1.3
## Sv1.084 0.33 0.30 0.70 2.6
## Sv1.087 0.14 0.86 2.1
## Sv1.088 0.57 0.32 0.68 1.0
## Sv1.089 0.45 0.31 0.44 0.56 2.5
## Sv1.091 0.47 0.39 0.61 1.7
##
## MR2 MR1 MR5 MR6 MR3 MR4
## SS loadings 4.11 4.50 3.31 3.46 2.49 2.04
## Proportion Var 0.08 0.08 0.06 0.06 0.05 0.04
## Cumulative Var 0.08 0.16 0.22 0.28 0.33 0.37
## Proportion Explained 0.21 0.23 0.17 0.17 0.12 0.10
## Cumulative Proportion 0.21 0.43 0.60 0.77 0.90 1.00
##
## With factor correlations of
## MR2 MR1 MR5 MR6 MR3 MR4
## MR2 1.00 0.10 -0.27 -0.13 0.38 0.10
## MR1 0.10 1.00 0.42 0.55 0.21 0.37
## MR5 -0.27 0.42 1.00 0.41 -0.10 0.19
## MR6 -0.13 0.55 0.41 1.00 0.05 0.21
## MR3 0.38 0.21 -0.10 0.05 1.00 0.17
## MR4 0.10 0.37 0.19 0.21 0.17 1.00
##
## Mean item complexity = 2
## Test of the hypothesis that 6 factors are sufficient.
##
## The degrees of freedom for the null model are 1431 and the objective function was 19.2
## The degrees of freedom for the model are 1122 and the objective function was 2.42
##
## The root mean square of the residuals (RMSR) is 0.03
## The df corrected root mean square of the residuals is 0.03
##
## Fit based upon off diagonal values = 0.98
## Measures of factor score adequacy
## MR2 MR1 MR5 MR6 MR3
## Correlation of scores with factors 0.94 0.93 0.91 0.91 0.88
## Multiple R square of scores with factors 0.89 0.87 0.84 0.82 0.77
## Minimum correlation of possible factor scores 0.79 0.74 0.67 0.65 0.55
## MR4
## Correlation of scores with factors 0.84
## Multiple R square of scores with factors 0.71
## Minimum correlation of possible factor scores 0.41
save_loadings(psychFaObj = m5o, item_dic = dic,
filename = "senna54xm3.xlsx", digits =2)
##
## Attaching package: 'dplyr'
## The following objects are masked from 'package:plyr':
##
## arrange, count, desc, failwith, id, mutate, rename, summarise,
## summarize
## The following objects are masked from 'package:stats':
##
## filter, lag
## The following objects are masked from 'package:base':
##
## intersect, setdiff, setequal, union
## Warning in left_join_impl(x, y, by$x, by$y, suffix$x, suffix$y): joining
## character vector and factor, coercing into character vector
## Loading required package: rJava
## Loading required package: xlsxjars
## coditem MR2 MR1 MR5 MR6 MR3 MR4 com h2 rwn factor pole
## 1 Sv1.007 0.84 -0.01 0.03 -0.02 0.03 -0.05 1.01 0.71 5 N 0
## 2 Sv1.017 0.79 -0.04 0.03 0.01 0.03 0.03 1.01 0.63 12 N 0
## 3 Sv1.032 0.70 0.06 -0.05 0.08 0.01 -0.06 1.06 0.51 18 N 0
## 4 Sv1.012 0.64 -0.04 0.01 -0.02 0.08 0.02 1.04 0.46 9 N 0
## 5 Sv1.044 0.53 0.11 -0.01 -0.30 0.05 0.08 1.77 0.45 26 A 0
## 6 Sv1.037 -0.41 0.28 0.16 0.08 0.36 0.11 3.42 0.48 22 N 1
## 7 Sv1.042 0.36 -0.03 0.03 -0.01 0.27 0.14 2.24 0.30 25 N 0
## 8 Sv1.048 0.32 0.22 0.06 -0.16 0.22 0.02 3.26 0.28 28 NV 1
## 9 Sv1.053 0.29 0.12 -0.14 0.02 -0.02 0.11 2.20 0.15 32 A 0
## 10 Sv1.066 0.27 0.22 -0.04 0.14 0.00 0.15 3.13 0.24 38 O 1
## 11 Sv1.010 -0.02 0.72 0.04 -0.05 -0.03 0.05 1.03 0.51 7 O 1
## 12 Sv1.005 -0.03 0.67 0.15 -0.09 0.05 0.05 1.16 0.54 3 O 1
## 13 Sv1.055 -0.03 0.59 -0.01 0.26 -0.08 0.00 1.43 0.57 34 E 1
## 14 Sv1.030 0.05 0.52 -0.04 0.19 0.03 -0.03 1.30 0.39 17 O 1
## 15 Sv1.040 0.01 0.45 0.15 0.12 0.05 -0.04 1.42 0.37 24 O 1
## 16 Sv1.063 0.10 0.41 0.00 0.33 -0.18 0.04 2.47 0.44 37 E 1
## 17 Sv1.070 0.01 0.41 0.03 -0.04 0.04 0.17 1.39 0.25 40 O 1
## 18 Sv1.054 -0.01 0.40 0.23 0.09 0.15 0.04 2.07 0.42 33 O 1
## 19 Sv1.071 0.17 0.40 -0.14 0.32 -0.14 0.05 2.91 0.38 41 E 1
## 20 Sv1.075 0.02 0.35 0.04 0.33 0.05 0.09 2.21 0.43 44 E 1
## 21 Sv1.074 0.09 0.32 -0.03 0.06 0.17 0.11 2.04 0.25 43 NV 1
## 22 Sv1.024 0.00 0.32 0.21 -0.07 0.18 0.08 2.67 0.25 13 O 1
## 23 Sv1.006 -0.02 0.15 0.62 0.14 0.09 -0.05 1.29 0.60 4 C 1
## 24 Sv1.011 0.03 0.20 0.59 0.14 0.07 -0.09 1.43 0.57 8 C 1
## 25 Sv1.083 0.00 -0.03 0.59 0.12 -0.11 0.13 1.27 0.48 49 C 1
## 26 Sv1.091 -0.01 0.08 0.47 -0.03 -0.03 0.28 1.75 0.39 54 C 1
## 27 Sv1.089 0.14 0.12 0.45 0.00 -0.18 0.31 2.52 0.44 53 C 1
## 28 Sv1.077 0.02 0.04 0.43 0.15 -0.11 0.19 1.82 0.37 46 C 1
## 29 Sv1.046 0.21 0.10 -0.42 -0.02 0.34 0.12 2.80 0.49 27 C 0
## 30 Sv1.036 0.24 0.22 -0.31 0.01 0.28 0.05 3.83 0.38 21 C 0
## 31 Sv1.051 0.21 0.08 -0.30 -0.10 0.11 0.13 3.01 0.24 30 C 0
## 32 Sv1.009 -0.08 0.00 0.16 0.65 0.01 -0.03 1.17 0.55 6 A 1
## 33 Sv1.039 0.02 0.07 0.14 0.56 0.03 0.04 1.17 0.47 23 A 1
## 34 Sv1.004 -0.05 0.16 0.18 0.49 0.11 0.03 1.63 0.51 2 A 1
## 35 Sv1.049 -0.10 0.19 0.18 0.44 0.05 0.03 1.88 0.49 29 A 1
## 36 Sv1.034 -0.07 0.04 -0.08 0.40 0.05 0.23 1.82 0.26 20 A 1
## 37 Sv1.025 -0.01 -0.01 -0.16 0.36 0.05 0.30 2.40 0.23 14 A 1
## 38 Sv1.014 -0.06 0.21 0.08 0.32 0.14 0.12 2.73 0.35 11 A 1
## 39 Sv1.029 0.06 -0.03 0.15 0.31 -0.05 0.14 2.06 0.18 16 A 1
## 40 Sv1.060 0.03 0.08 0.15 0.20 0.14 0.14 3.99 0.20 36 NV 0
## 41 Sv1.013 0.16 -0.04 -0.16 0.00 0.56 0.00 1.33 0.46 10 NV 1
## 42 Sv1.052 0.15 -0.04 -0.04 0.00 0.45 0.04 1.27 0.29 31 NV 1
## 43 Sv1.003 0.22 -0.13 -0.05 -0.01 0.43 0.14 1.95 0.34 1 NV 1
## 44 Sv1.067 0.04 0.04 0.20 0.15 0.41 -0.09 1.91 0.26 39 E 0
## 45 Sv1.027 0.38 -0.03 0.00 0.05 0.41 -0.02 2.04 0.41 15 N 0
## 46 Sv1.073 0.09 -0.03 -0.05 0.10 0.39 0.06 1.33 0.21 42 E 0
## 47 Sv1.056 0.14 0.17 -0.02 0.14 0.26 0.09 3.33 0.24 35 NV 1
## 48 Sv1.088 -0.06 0.00 0.01 0.01 -0.02 0.57 1.03 0.32 52 N 1
## 49 Sv1.079 -0.14 -0.06 0.04 0.00 0.11 0.51 1.30 0.27 47 N 1
## 50 Sv1.084 0.08 0.21 0.04 0.16 -0.10 0.33 2.61 0.30 50 E 1
## 51 Sv1.087 0.14 -0.02 -0.13 -0.03 0.08 0.29 2.12 0.14 51 E 1
## 52 Sv1.082 -0.08 0.16 0.17 -0.06 0.06 0.28 2.73 0.20 48 N 1
## 53 Sv1.076 0.12 0.10 0.01 0.06 0.12 0.26 2.35 0.18 45 E 1
## 54 Sv1.033 0.04 0.00 0.03 0.18 0.09 0.19 2.61 0.11 19 NV 1
## item_text
## 1 Eu me irrito com facilidade.
## 2 Fico nervoso(a) com facilidade.
## 3 Fico muito bravo e costumo perder a paciência
## 4 De uma hora para outra eu fico de mau humor.
## 5 Brigo muito. Consigo fazer com que outras pessoas façam o que eu quero
## 6 Sou calmo(a) e controlo bem meu estresse.
## 7 Sou meio tenso(a).
## 8 Meus colegas pegam no meu pé
## 9 Começo bate-bocas com os outros
## 10 Muitos assuntos despertam minha curiosidade
## 11 Tenho uma imaginação bem ativa
## 12 Sou original, tenho ideias novas
## 13 Sou muito alegre e animado(a).
## 14 Gosto de refletir e brincar com minhas idéias
## 15 Gosto de atividades artísticas
## 16 Sou cheio de energia
## 17 Eu consigo facilmente inventar jogos e ou brincadeiras.
## 18 Gosto de pensar profundamente sobre as coisas
## 19 Gosto de conversar.
## 20 Eu gosto de estar na companhia dos outros.
## 21 Você acredita que as pessoas boas nos esportes já nasceram assim?
## 22 Conheço vários tipos de obras de arte, de música e ou de literatura
## 23 Sou um(a) aluno(a) cuidadoso(a) e dedicado(a).
## 24 Sou caprichoso(a) e detalhista nas tarefas escolares.
## 25 Quanto você consegue prestar atenção nas aulas?
## 26 Quanto você consegue estudar um texto para uma prova?
## 27 Quanto você consegue ter um bom desempenho em uma prova?
## 28 Quanto você consegue terminar todo seu dever de casa?
## 29 Sou distraído(a). É difícil ficar concentrado(a) nas aulas.
## 30 Eu desvio minha atenção com muita facilidade
## 31 Costumo ser desorganizado(a).
## 32 Eu trato meus colegas com carinho.
## 33 Se um colega tem dificuldade eu o ajudo.
## 34 Sou amável e legal com quase todo mundo
## 35 Não sou egoísta e gosto de ajudar os outros
## 36 Eu confio nos outros.
## 37 Eu deixo que os outros usem minhas coisas.
## 38 Tenho facilidade em perdoar
## 39 Gosto de cooperar com os outros
## 40 Você acredita que pode mudar o que acontecerá com voce amanhã pelo que faz hoje?
## 41 Você sente que é inútil se esforçar na escola porque a maioria dos outros alunos é mais inteligente que você?
## 42 Você sente que muitas vezes não vale a pena se esforçar porque, de qualquer modo, as coisas nunca dão certo mesmo?
## 43 Costumo acreditar que sou um fracasso
## 44 Sou reservado(a), fico mais na minha.
## 45 De uma hora para outra eu fico triste.
## 46 Sou tímido(a), inibido(a).
## 47 Quando faz alguma coisa errada, voce sente que existe muito pouco que você pode fazer para consertar?
## 48 Quanto você consegue evitar pensamentos desagradáveis?
## 49 Quanto você consegue evitar ficar nervoso(a)?
## 50 Quanto você consegue permanecer amigo(a) de outras crianças jovens?
## 51 Quanto você consegue bater um papo com uma pessoa desconhecida?
## 52 Quanto você consegue controlar seus sentimentos?
## 53 Contagio os outros com meu entusiasmo
## 54 Você sente que a melhor maneira de lidar com os problemas é apenas não pensar neles?
## order2 facet coditem2
## 1 5 Vol i07N.Vol.00
## 2 12 Anx i17N.Anx.00
## 3 18 Vol i32N.Vol.00
## 4 9 Vol i12N.Vol.00
## 5 26 Cmp i44A.Cmp.00
## 6 22 Anx i37N.Anx.10
## 7 25 Anx i42N.Anx.00
## 8 28 NV i48NV.NV.10
## 9 32 Pol i53A.Pol.00
## 10 38 Int i66O.Int.10
## 11 7 Img i10O.Img.10
## 12 3 Img i05O.Img.10
## 13 34 Act i55E.Act.10
## 14 17 Int i30O.Int.10
## 15 24 Aes i40O.Aes.10
## 16 37 Act i63E.Act.10
## 17 40 Img i70O.Img.11
## 18 33 Int i54O.Int.10
## 19 41 Soc i71E.Soc.10
## 20 44 Soc i75E.Soc.10
## 21 43 NV i74NV.NV.10
## 22 13 Aes i24O.Aes.10
## 23 4 Ord i06C.Ord.10
## 24 8 Ord i11C.Ord.10
## 25 49 SD i83C.SD.11
## 26 54 SD i91C.SD.11
## 27 53 SD i89C.SD.11
## 28 46 SD i77C.SD.11
## 29 27 SD i46C.SD.00
## 30 21 SD i36C.SD.00
## 31 30 Ord i51C.Ord.00
## 32 6 Cmp i09A.Cmp.10
## 33 23 Cmp i39A.Cmp.10
## 34 2 Cmp i04A.Cmp.10
## 35 29 Cmp i49A.Cmp.10
## 36 20 Tru i34A.Tru.10
## 37 14 Cmp i25A.Cmp.10
## 38 11 Tru i14A.Tru.10
## 39 16 Cmp i29A.Cmp.10
## 40 36 NV i60NV.NV.00
## 41 10 NV i13NV.NV.10
## 42 31 NV i52NV.NV.10
## 43 1 NV i03NV.NV.10
## 44 39 Soc i67E.Soc.00
## 45 15 Dep i27N.Dep.00
## 46 42 Soc i73E.Soc.00
## 47 35 NV i56NV.NV.10
## 48 52 Vol i88N.Vol.11
## 49 47 Anx i79N.Anx.11
## 50 50 Soc i84E.Soc.11
## 51 51 Soc i87E.Soc.11
## 52 48 Vol i82N.Vol.11
## 53 45 Act i76E.Act.10
## 54 19 NV i33NV.NV.10