Dados
# abra o arquivo direto da internet
con<-url("http://www.labape.com.br/rprimi/SEM/exerc18/ex3b.RData")
load(con)
# explorando a base
names(scores)
## [1] "banco" "cod_suj" "Data de nasc."
## [4] "data.aplic" "Idade0" "idade1"
## [7] "Termo" "sujeito" "serie"
## [10] "escola" "turma" "Sexo"
## [13] "Esc. Mãe" "port" "mat"
## [16] "cloze" "A_o" "C_o"
## [19] "E_o" "N_o" "O_o"
## [22] "A_c" "C_c" "E_c"
## [25] "N_c" "O_c" "A_z"
## [28] "C_z" "E_z" "N_z"
## [31] "O_z" "antonym.rc" "antonym.cntrst_A"
## [34] "antonym.cntrst_C" "antonym.cntrst_E" "antonym.cntrst_N"
## [37] "antonym.cntrst_O" "mean_A" "mean_C"
## [40] "mean_E" "mean_N" "mean_O"
## [43] "sd_A" "sd_C" "sd_E"
## [46] "sd_N" "sd_O" "antonym.rc_A"
## [49] "antonym.rc_C" "antonym.rc_E" "antonym.rc_N"
## [52] "antonym.rc_O" "nse" "A_1_o"
## [55] "C_1_o" "E_1_o" "N_1_o"
## [58] "O_1_o" "A_1_c" "C_1_c"
## [61] "E_1_c" "N_1_c" "O_1_c"
## [64] "A_1_z" "C_1_z" "E_1_z"
## [67] "N_1_z" "O_1_z" "A_0_o"
## [70] "C_0_o" "E_0_o" "N_0_o"
## [73] "O_0_o" "A_0_c" "C_0_c"
## [76] "E_0_c" "N_0_c" "O_0_c"
## [79] "A_0_z" "C_0_z" "E_0_z"
## [82] "N_0_z" "O_0_z" "cexp_o"
## [85] "comlrn_o" "coplrn_o" "cstrat_o"
## [88] "effper_o" "elab_o" "insmot_o"
## [91] "intmat_o" "intrea_o" "memor_o"
## [94] "scacad_o" "scmath_o" "scverb_o"
## [97] "selfef_o" "cexp_c" "comlrn_c"
## [100] "coplrn_c" "cstrat_c" "effper_c"
## [103] "elab_c" "insmot_c" "intmat_c"
## [106] "intrea_c" "memor_c" "scacad_c"
## [109] "scmath_c" "scverb_c" "selfef_c"
## [112] "cexp_z" "comlrn_z" "coplrn_z"
## [115] "cstrat_z" "effper_z" "elab_z"
## [118] "insmot_z" "intmat_z" "intrea_z"
## [121] "memor_z" "scacad_z" "scmath_z"
## [124] "scverb_z" "selfef_z" "means"
## [127] "sd"
vars <- scores %>% select(contains("_c")) %>% select(10:33) %>% names
vars_scales <- names(dic)[c(3, 5, 20:22) ]
dic %>% select(vars_scales) %>% filter((teste == "senna" | teste=="sal") & factor != "chk_0") %>%
group_by(factor) %>% summarise_all("first") %>% arrange(desc(teste),port_text1) %>%
kable()
| A_0 |
senna |
NA |
I care about what happens to other people. |
NA |
| A_1 |
senna |
NA |
i.115.A.Cmp.11__How much do you manage to be nice to other people? |
NA |
| C_0 |
senna |
NA |
I am a dedicated [add: and ambitious/hardworking] student. |
NA |
| C_1 |
senna |
NA |
How well do you manage to put the (necessary) time and effort into your work/necessary to be successful? |
NA |
| E_0 |
senna |
NA |
I am happy and lively |
NA |
| E_1 |
senna |
NA |
i.297.E.Act.11__Do you often do funny things to make your friends laugh? |
NA |
| N_0 |
senna |
NA |
I lose control easily whenever I don’t get what I want. |
NA |
| N_1 |
senna |
NA |
i.449.N.Vol.11__How easily are you able to stay calm, without exploding, when you are provoked? |
NA |
| O_0 |
senna |
NA |
Is interested in various types of art, music, or literature |
NA |
| O_1 |
senna |
NA |
i.482.O.Aes.11__How easily do you find it to create things artistically, like a poem for example? |
NA |
| cexp |
sal |
Auto-conceito |
Self-Belief |
Control Expectation |
| comlrn |
sal |
Competências sociais auto reportadas |
Self-report of social competencies |
Preference for competitive learning |
| coplrn |
sal |
Competências sociais auto reportadas |
Self-report of social competencies |
Preference for co-operative learning |
| scacad |
sal |
Confiança em si |
Self-related beliefs |
Academic self-concept |
| scmath |
sal |
Confiança em si |
Self-related beliefs |
Self-concept of mathematical competencies |
| scverb |
sal |
Confiança em si |
Self-related beliefs |
Self-concept of verbal competencies |
| selfef |
sal |
Confiança em si |
Self-related beliefs |
Self-efficacy |
| cstrat |
sal |
Estratégias de Aprendizagem |
Learning Strategies |
Control Strategies |
| elab |
sal |
Estratégias de Aprendizagem |
Learning Strategies |
Elaboration Strategies |
| memor |
sal |
Estratégias de Aprendizagem |
Learning Strategies |
Memorisation Strategies |
| effper |
sal |
Motivação |
Motivation |
Effort and persistence in learning |
| insmot |
sal |
Motivação |
Motivation |
Instrumental Motivation |
| intmat |
sal |
Motivação |
Motivation |
Interest in math |
| intrea |
sal |
Motivação |
Motivation |
Interest in reading |
Correlação entre as variáveis
scores %>% select(vars) %>% corr.test
## Call:corr.test(x = .)
## Correlation matrix
## A_1_c C_1_c E_1_c N_1_c O_1_c A_0_c C_0_c E_0_c N_0_c O_0_c
## A_1_c 1.00 0.50 0.31 0.33 0.40 0.55 0.28 0.40 0.31 0.33
## C_1_c 0.50 1.00 0.25 0.42 0.50 0.52 0.66 0.48 0.37 0.47
## E_1_c 0.31 0.25 1.00 0.20 0.34 0.18 0.24 0.22 0.12 0.40
## N_1_c 0.33 0.42 0.20 1.00 0.46 0.33 0.20 0.27 0.64 0.32
## O_1_c 0.40 0.50 0.34 0.46 1.00 0.28 0.33 0.32 0.42 0.50
## A_0_c 0.55 0.52 0.18 0.33 0.28 1.00 0.45 0.34 0.34 0.36
## C_0_c 0.28 0.66 0.24 0.20 0.33 0.45 1.00 0.41 0.24 0.32
## E_0_c 0.40 0.48 0.22 0.27 0.32 0.34 0.41 1.00 0.30 0.33
## N_0_c 0.31 0.37 0.12 0.64 0.42 0.34 0.24 0.30 1.00 0.30
## O_0_c 0.33 0.47 0.40 0.32 0.50 0.36 0.32 0.33 0.30 1.00
## cexp_c 0.36 0.53 0.29 0.37 0.38 0.41 0.43 0.36 0.32 0.36
## comlrn_c 0.10 0.22 0.06 0.07 0.14 0.01 0.10 0.03 0.03 0.01
## coplrn_c 0.40 0.46 0.25 0.19 0.36 0.46 0.35 0.28 0.24 0.33
## cstrat_c 0.35 0.58 0.33 0.27 0.40 0.43 0.48 0.34 0.24 0.43
## effper_c 0.38 0.66 0.29 0.33 0.38 0.43 0.49 0.36 0.25 0.38
## elab_c 0.30 0.54 0.28 0.35 0.43 0.35 0.48 0.34 0.32 0.39
## insmot_c 0.27 0.43 0.26 0.20 0.27 0.25 0.26 0.15 0.16 0.36
## intmat_c 0.35 0.60 0.20 0.31 0.35 0.37 0.47 0.28 0.27 0.26
## intrea_c 0.35 0.50 0.29 0.27 0.41 0.43 0.41 0.28 0.22 0.38
## memor_c 0.32 0.54 0.26 0.27 0.33 0.32 0.44 0.31 0.30 0.33
## scacad_c 0.24 0.60 0.15 0.25 0.32 0.38 0.54 0.31 0.24 0.28
## scmath_c 0.25 0.50 0.15 0.13 0.22 0.28 0.43 0.26 0.17 0.24
## scverb_c 0.24 0.49 0.28 0.17 0.30 0.30 0.50 0.28 0.27 0.33
## selfef_c 0.37 0.56 0.27 0.30 0.36 0.36 0.47 0.40 0.25 0.40
## cexp_c comlrn_c coplrn_c cstrat_c effper_c elab_c insmot_c
## A_1_c 0.36 0.10 0.40 0.35 0.38 0.30 0.27
## C_1_c 0.53 0.22 0.46 0.58 0.66 0.54 0.43
## E_1_c 0.29 0.06 0.25 0.33 0.29 0.28 0.26
## N_1_c 0.37 0.07 0.19 0.27 0.33 0.35 0.20
## O_1_c 0.38 0.14 0.36 0.40 0.38 0.43 0.27
## A_0_c 0.41 0.01 0.46 0.43 0.43 0.35 0.25
## C_0_c 0.43 0.10 0.35 0.48 0.49 0.48 0.26
## E_0_c 0.36 0.03 0.28 0.34 0.36 0.34 0.15
## N_0_c 0.32 0.03 0.24 0.24 0.25 0.32 0.16
## O_0_c 0.36 0.01 0.33 0.43 0.38 0.39 0.36
## cexp_c 1.00 0.07 0.48 0.58 0.63 0.61 0.37
## comlrn_c 0.07 1.00 0.10 0.22 0.12 0.13 0.03
## coplrn_c 0.48 0.10 1.00 0.44 0.49 0.45 0.35
## cstrat_c 0.58 0.22 0.44 1.00 0.67 0.74 0.53
## effper_c 0.63 0.12 0.49 0.67 1.00 0.62 0.49
## elab_c 0.61 0.13 0.45 0.74 0.62 1.00 0.49
## insmot_c 0.37 0.03 0.35 0.53 0.49 0.49 1.00
## intmat_c 0.51 0.17 0.53 0.50 0.55 0.50 0.41
## intrea_c 0.49 0.19 0.50 0.49 0.44 0.45 0.31
## memor_c 0.56 0.13 0.45 0.65 0.56 0.67 0.50
## scacad_c 0.60 0.14 0.49 0.59 0.61 0.54 0.39
## scmath_c 0.50 0.14 0.36 0.47 0.56 0.47 0.34
## scverb_c 0.51 0.15 0.38 0.48 0.42 0.34 0.32
## selfef_c 0.67 0.17 0.48 0.63 0.66 0.53 0.40
## intmat_c intrea_c memor_c scacad_c scmath_c scverb_c selfef_c
## A_1_c 0.35 0.35 0.32 0.24 0.25 0.24 0.37
## C_1_c 0.60 0.50 0.54 0.60 0.50 0.49 0.56
## E_1_c 0.20 0.29 0.26 0.15 0.15 0.28 0.27
## N_1_c 0.31 0.27 0.27 0.25 0.13 0.17 0.30
## O_1_c 0.35 0.41 0.33 0.32 0.22 0.30 0.36
## A_0_c 0.37 0.43 0.32 0.38 0.28 0.30 0.36
## C_0_c 0.47 0.41 0.44 0.54 0.43 0.50 0.47
## E_0_c 0.28 0.28 0.31 0.31 0.26 0.28 0.40
## N_0_c 0.27 0.22 0.30 0.24 0.17 0.27 0.25
## O_0_c 0.26 0.38 0.33 0.28 0.24 0.33 0.40
## cexp_c 0.51 0.49 0.56 0.60 0.50 0.51 0.67
## comlrn_c 0.17 0.19 0.13 0.14 0.14 0.15 0.17
## coplrn_c 0.53 0.50 0.45 0.49 0.36 0.38 0.48
## cstrat_c 0.50 0.49 0.65 0.59 0.47 0.48 0.63
## effper_c 0.55 0.44 0.56 0.61 0.56 0.42 0.66
## elab_c 0.50 0.45 0.67 0.54 0.47 0.34 0.53
## insmot_c 0.41 0.31 0.50 0.39 0.34 0.32 0.40
## intmat_c 1.00 0.52 0.48 0.62 0.67 0.42 0.55
## intrea_c 0.52 1.00 0.46 0.50 0.36 0.47 0.50
## memor_c 0.48 0.46 1.00 0.52 0.45 0.48 0.55
## scacad_c 0.62 0.50 0.52 1.00 0.58 0.52 0.59
## scmath_c 0.67 0.36 0.45 0.58 1.00 0.36 0.58
## scverb_c 0.42 0.47 0.48 0.52 0.36 1.00 0.53
## selfef_c 0.55 0.50 0.55 0.59 0.58 0.53 1.00
## Sample Size
## A_1_c C_1_c E_1_c N_1_c O_1_c A_0_c C_0_c E_0_c N_0_c O_0_c
## A_1_c 168 168 168 168 168 168 168 168 168 168
## C_1_c 168 168 168 168 168 168 168 168 168 168
## E_1_c 168 168 168 168 168 168 168 168 168 168
## N_1_c 168 168 168 168 168 168 168 168 168 168
## O_1_c 168 168 168 168 168 168 168 168 168 168
## A_0_c 168 168 168 168 168 168 168 168 168 168
## C_0_c 168 168 168 168 168 168 168 168 168 168
## E_0_c 168 168 168 168 168 168 168 168 168 168
## N_0_c 168 168 168 168 168 168 168 168 168 168
## O_0_c 168 168 168 168 168 168 168 168 168 168
## cexp_c 168 168 168 168 168 168 168 168 168 168
## comlrn_c 167 167 167 167 167 167 167 167 167 167
## coplrn_c 167 167 167 167 167 167 167 167 167 167
## cstrat_c 168 168 168 168 168 168 168 168 168 168
## effper_c 168 168 168 168 168 168 168 168 168 168
## elab_c 168 168 168 168 168 168 168 168 168 168
## insmot_c 168 168 168 168 168 168 168 168 168 168
## intmat_c 167 167 167 167 167 167 167 167 167 167
## intrea_c 167 167 167 167 167 167 167 167 167 167
## memor_c 168 168 168 168 168 168 168 168 168 168
## scacad_c 167 167 167 167 167 167 167 167 167 167
## scmath_c 167 167 167 167 167 167 167 167 167 167
## scverb_c 167 167 167 167 167 167 167 167 167 167
## selfef_c 168 168 168 168 168 168 168 168 168 168
## cexp_c comlrn_c coplrn_c cstrat_c effper_c elab_c insmot_c
## A_1_c 168 167 167 168 168 168 168
## C_1_c 168 167 167 168 168 168 168
## E_1_c 168 167 167 168 168 168 168
## N_1_c 168 167 167 168 168 168 168
## O_1_c 168 167 167 168 168 168 168
## A_0_c 168 167 167 168 168 168 168
## C_0_c 168 167 167 168 168 168 168
## E_0_c 168 167 167 168 168 168 168
## N_0_c 168 167 167 168 168 168 168
## O_0_c 168 167 167 168 168 168 168
## cexp_c 168 167 167 168 168 168 168
## comlrn_c 167 167 167 167 167 167 167
## coplrn_c 167 167 167 167 167 167 167
## cstrat_c 168 167 167 168 168 168 168
## effper_c 168 167 167 168 168 168 168
## elab_c 168 167 167 168 168 168 168
## insmot_c 168 167 167 168 168 168 168
## intmat_c 167 167 167 167 167 167 167
## intrea_c 167 167 167 167 167 167 167
## memor_c 168 167 167 168 168 168 168
## scacad_c 167 167 167 167 167 167 167
## scmath_c 167 167 167 167 167 167 167
## scverb_c 167 167 167 167 167 167 167
## selfef_c 168 167 167 168 168 168 168
## intmat_c intrea_c memor_c scacad_c scmath_c scverb_c selfef_c
## A_1_c 167 167 168 167 167 167 168
## C_1_c 167 167 168 167 167 167 168
## E_1_c 167 167 168 167 167 167 168
## N_1_c 167 167 168 167 167 167 168
## O_1_c 167 167 168 167 167 167 168
## A_0_c 167 167 168 167 167 167 168
## C_0_c 167 167 168 167 167 167 168
## E_0_c 167 167 168 167 167 167 168
## N_0_c 167 167 168 167 167 167 168
## O_0_c 167 167 168 167 167 167 168
## cexp_c 167 167 168 167 167 167 168
## comlrn_c 167 167 167 167 167 167 167
## coplrn_c 167 167 167 167 167 167 167
## cstrat_c 167 167 168 167 167 167 168
## effper_c 167 167 168 167 167 167 168
## elab_c 167 167 168 167 167 167 168
## insmot_c 167 167 168 167 167 167 168
## intmat_c 167 167 167 167 167 167 167
## intrea_c 167 167 167 167 167 167 167
## memor_c 167 167 168 167 167 167 168
## scacad_c 167 167 167 167 167 167 167
## scmath_c 167 167 167 167 167 167 167
## scverb_c 167 167 167 167 167 167 167
## selfef_c 167 167 168 167 167 167 168
## Probability values (Entries above the diagonal are adjusted for multiple tests.)
## A_1_c C_1_c E_1_c N_1_c O_1_c A_0_c C_0_c E_0_c N_0_c O_0_c
## A_1_c 0.00 0 0.00 0.00 0.00 0.00 0.02 0.00 0.00 0.00
## C_1_c 0.00 0 0.05 0.00 0.00 0.00 0.00 0.00 0.00 0.00
## E_1_c 0.00 0 0.00 0.29 0.00 0.51 0.08 0.14 1.00 0.00
## N_1_c 0.00 0 0.01 0.00 0.00 0.00 0.29 0.03 0.00 0.00
## O_1_c 0.00 0 0.00 0.00 0.00 0.02 0.00 0.00 0.00 0.00
## A_0_c 0.00 0 0.02 0.00 0.00 0.00 0.00 0.00 0.00 0.00
## C_0_c 0.00 0 0.00 0.01 0.00 0.00 0.00 0.00 0.07 0.00
## E_0_c 0.00 0 0.00 0.00 0.00 0.00 0.00 0.00 0.01 0.00
## N_0_c 0.00 0 0.12 0.00 0.00 0.00 0.00 0.00 0.00 0.01
## O_0_c 0.00 0 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00
## cexp_c 0.00 0 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00
## comlrn_c 0.21 0 0.46 0.35 0.07 0.90 0.18 0.73 0.67 0.87
## coplrn_c 0.00 0 0.00 0.01 0.00 0.00 0.00 0.00 0.00 0.00
## cstrat_c 0.00 0 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00
## effper_c 0.00 0 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00
## elab_c 0.00 0 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00
## insmot_c 0.00 0 0.00 0.01 0.00 0.00 0.00 0.05 0.04 0.00
## intmat_c 0.00 0 0.01 0.00 0.00 0.00 0.00 0.00 0.00 0.00
## intrea_c 0.00 0 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00
## memor_c 0.00 0 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00
## scacad_c 0.00 0 0.05 0.00 0.00 0.00 0.00 0.00 0.00 0.00
## scmath_c 0.00 0 0.06 0.09 0.00 0.00 0.00 0.00 0.03 0.00
## scverb_c 0.00 0 0.00 0.03 0.00 0.00 0.00 0.00 0.00 0.00
## selfef_c 0.00 0 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00
## cexp_c comlrn_c coplrn_c cstrat_c effper_c elab_c insmot_c
## A_1_c 0.00 1.00 0.00 0.00 0.00 0.01 0.03
## C_1_c 0.00 0.14 0.00 0.00 0.00 0.00 0.00
## E_1_c 0.01 1.00 0.05 0.00 0.01 0.02 0.04
## N_1_c 0.00 1.00 0.38 0.03 0.00 0.00 0.29
## O_1_c 0.00 1.00 0.00 0.00 0.00 0.00 0.02
## A_0_c 0.00 1.00 0.00 0.00 0.00 0.00 0.06
## C_0_c 0.00 1.00 0.00 0.00 0.00 0.00 0.04
## E_0_c 0.00 1.00 0.02 0.00 0.00 0.00 1.00
## N_0_c 0.00 1.00 0.08 0.09 0.06 0.00 0.89
## O_0_c 0.00 1.00 0.00 0.00 0.00 0.00 0.00
## cexp_c 0.00 1.00 0.00 0.00 0.00 0.00 0.00
## comlrn_c 0.38 0.00 1.00 0.14 1.00 1.00 1.00
## coplrn_c 0.00 0.19 0.00 0.00 0.00 0.00 0.00
## cstrat_c 0.00 0.00 0.00 0.00 0.00 0.00 0.00
## effper_c 0.00 0.12 0.00 0.00 0.00 0.00 0.00
## elab_c 0.00 0.09 0.00 0.00 0.00 0.00 0.00
## insmot_c 0.00 0.68 0.00 0.00 0.00 0.00 0.00
## intmat_c 0.00 0.03 0.00 0.00 0.00 0.00 0.00
## intrea_c 0.00 0.01 0.00 0.00 0.00 0.00 0.00
## memor_c 0.00 0.10 0.00 0.00 0.00 0.00 0.00
## scacad_c 0.00 0.07 0.00 0.00 0.00 0.00 0.00
## scmath_c 0.00 0.06 0.00 0.00 0.00 0.00 0.00
## scverb_c 0.00 0.05 0.00 0.00 0.00 0.00 0.00
## selfef_c 0.00 0.02 0.00 0.00 0.00 0.00 0.00
## intmat_c intrea_c memor_c scacad_c scmath_c scverb_c selfef_c
## A_1_c 0.00 0.00 0.00 0.07 0.06 0.07 0.00
## C_1_c 0.00 0.00 0.00 0.00 0.00 0.00 0.00
## E_1_c 0.35 0.01 0.04 1.00 1.00 0.02 0.03
## N_1_c 0.00 0.03 0.03 0.05 1.00 0.78 0.01
## O_1_c 0.00 0.00 0.00 0.00 0.14 0.01 0.00
## A_0_c 0.00 0.00 0.00 0.00 0.02 0.01 0.00
## C_0_c 0.00 0.00 0.00 0.00 0.00 0.00 0.00
## E_0_c 0.02 0.02 0.00 0.00 0.05 0.02 0.00
## N_0_c 0.03 0.15 0.01 0.08 0.82 0.03 0.06
## O_0_c 0.05 0.00 0.00 0.02 0.09 0.00 0.00
## cexp_c 0.00 0.00 0.00 0.00 0.00 0.00 0.00
## comlrn_c 0.78 0.36 1.00 1.00 1.00 1.00 0.66
## coplrn_c 0.00 0.00 0.00 0.00 0.00 0.00 0.00
## cstrat_c 0.00 0.00 0.00 0.00 0.00 0.00 0.00
## effper_c 0.00 0.00 0.00 0.00 0.00 0.00 0.00
## elab_c 0.00 0.00 0.00 0.00 0.00 0.00 0.00
## insmot_c 0.00 0.00 0.00 0.00 0.00 0.00 0.00
## intmat_c 0.00 0.00 0.00 0.00 0.00 0.00 0.00
## intrea_c 0.00 0.00 0.00 0.00 0.00 0.00 0.00
## memor_c 0.00 0.00 0.00 0.00 0.00 0.00 0.00
## scacad_c 0.00 0.00 0.00 0.00 0.00 0.00 0.00
## scmath_c 0.00 0.00 0.00 0.00 0.00 0.00 0.00
## scverb_c 0.00 0.00 0.00 0.00 0.00 0.00 0.00
## selfef_c 0.00 0.00 0.00 0.00 0.00 0.00 0.00
##
## To see confidence intervals of the correlations, print with the short=FALSE option
r <- scores %>% select(vars) %>% corr.test
r$r %>% kable(digits = 2)
| A_1_c |
1.00 |
0.50 |
0.31 |
0.33 |
0.40 |
0.55 |
0.28 |
0.40 |
0.31 |
0.33 |
0.36 |
0.10 |
0.40 |
0.35 |
0.38 |
0.30 |
0.27 |
0.35 |
0.35 |
0.32 |
0.24 |
0.25 |
0.24 |
0.37 |
| C_1_c |
0.50 |
1.00 |
0.25 |
0.42 |
0.50 |
0.52 |
0.66 |
0.48 |
0.37 |
0.47 |
0.53 |
0.22 |
0.46 |
0.58 |
0.66 |
0.54 |
0.43 |
0.60 |
0.50 |
0.54 |
0.60 |
0.50 |
0.49 |
0.56 |
| E_1_c |
0.31 |
0.25 |
1.00 |
0.20 |
0.34 |
0.18 |
0.24 |
0.22 |
0.12 |
0.40 |
0.29 |
0.06 |
0.25 |
0.33 |
0.29 |
0.28 |
0.26 |
0.20 |
0.29 |
0.26 |
0.15 |
0.15 |
0.28 |
0.27 |
| N_1_c |
0.33 |
0.42 |
0.20 |
1.00 |
0.46 |
0.33 |
0.20 |
0.27 |
0.64 |
0.32 |
0.37 |
0.07 |
0.19 |
0.27 |
0.33 |
0.35 |
0.20 |
0.31 |
0.27 |
0.27 |
0.25 |
0.13 |
0.17 |
0.30 |
| O_1_c |
0.40 |
0.50 |
0.34 |
0.46 |
1.00 |
0.28 |
0.33 |
0.32 |
0.42 |
0.50 |
0.38 |
0.14 |
0.36 |
0.40 |
0.38 |
0.43 |
0.27 |
0.35 |
0.41 |
0.33 |
0.32 |
0.22 |
0.30 |
0.36 |
| A_0_c |
0.55 |
0.52 |
0.18 |
0.33 |
0.28 |
1.00 |
0.45 |
0.34 |
0.34 |
0.36 |
0.41 |
0.01 |
0.46 |
0.43 |
0.43 |
0.35 |
0.25 |
0.37 |
0.43 |
0.32 |
0.38 |
0.28 |
0.30 |
0.36 |
| C_0_c |
0.28 |
0.66 |
0.24 |
0.20 |
0.33 |
0.45 |
1.00 |
0.41 |
0.24 |
0.32 |
0.43 |
0.10 |
0.35 |
0.48 |
0.49 |
0.48 |
0.26 |
0.47 |
0.41 |
0.44 |
0.54 |
0.43 |
0.50 |
0.47 |
| E_0_c |
0.40 |
0.48 |
0.22 |
0.27 |
0.32 |
0.34 |
0.41 |
1.00 |
0.30 |
0.33 |
0.36 |
0.03 |
0.28 |
0.34 |
0.36 |
0.34 |
0.15 |
0.28 |
0.28 |
0.31 |
0.31 |
0.26 |
0.28 |
0.40 |
| N_0_c |
0.31 |
0.37 |
0.12 |
0.64 |
0.42 |
0.34 |
0.24 |
0.30 |
1.00 |
0.30 |
0.32 |
0.03 |
0.24 |
0.24 |
0.25 |
0.32 |
0.16 |
0.27 |
0.22 |
0.30 |
0.24 |
0.17 |
0.27 |
0.25 |
| O_0_c |
0.33 |
0.47 |
0.40 |
0.32 |
0.50 |
0.36 |
0.32 |
0.33 |
0.30 |
1.00 |
0.36 |
0.01 |
0.33 |
0.43 |
0.38 |
0.39 |
0.36 |
0.26 |
0.38 |
0.33 |
0.28 |
0.24 |
0.33 |
0.40 |
| cexp_c |
0.36 |
0.53 |
0.29 |
0.37 |
0.38 |
0.41 |
0.43 |
0.36 |
0.32 |
0.36 |
1.00 |
0.07 |
0.48 |
0.58 |
0.63 |
0.61 |
0.37 |
0.51 |
0.49 |
0.56 |
0.60 |
0.50 |
0.51 |
0.67 |
| comlrn_c |
0.10 |
0.22 |
0.06 |
0.07 |
0.14 |
0.01 |
0.10 |
0.03 |
0.03 |
0.01 |
0.07 |
1.00 |
0.10 |
0.22 |
0.12 |
0.13 |
0.03 |
0.17 |
0.19 |
0.13 |
0.14 |
0.14 |
0.15 |
0.17 |
| coplrn_c |
0.40 |
0.46 |
0.25 |
0.19 |
0.36 |
0.46 |
0.35 |
0.28 |
0.24 |
0.33 |
0.48 |
0.10 |
1.00 |
0.44 |
0.49 |
0.45 |
0.35 |
0.53 |
0.50 |
0.45 |
0.49 |
0.36 |
0.38 |
0.48 |
| cstrat_c |
0.35 |
0.58 |
0.33 |
0.27 |
0.40 |
0.43 |
0.48 |
0.34 |
0.24 |
0.43 |
0.58 |
0.22 |
0.44 |
1.00 |
0.67 |
0.74 |
0.53 |
0.50 |
0.49 |
0.65 |
0.59 |
0.47 |
0.48 |
0.63 |
| effper_c |
0.38 |
0.66 |
0.29 |
0.33 |
0.38 |
0.43 |
0.49 |
0.36 |
0.25 |
0.38 |
0.63 |
0.12 |
0.49 |
0.67 |
1.00 |
0.62 |
0.49 |
0.55 |
0.44 |
0.56 |
0.61 |
0.56 |
0.42 |
0.66 |
| elab_c |
0.30 |
0.54 |
0.28 |
0.35 |
0.43 |
0.35 |
0.48 |
0.34 |
0.32 |
0.39 |
0.61 |
0.13 |
0.45 |
0.74 |
0.62 |
1.00 |
0.49 |
0.50 |
0.45 |
0.67 |
0.54 |
0.47 |
0.34 |
0.53 |
| insmot_c |
0.27 |
0.43 |
0.26 |
0.20 |
0.27 |
0.25 |
0.26 |
0.15 |
0.16 |
0.36 |
0.37 |
0.03 |
0.35 |
0.53 |
0.49 |
0.49 |
1.00 |
0.41 |
0.31 |
0.50 |
0.39 |
0.34 |
0.32 |
0.40 |
| intmat_c |
0.35 |
0.60 |
0.20 |
0.31 |
0.35 |
0.37 |
0.47 |
0.28 |
0.27 |
0.26 |
0.51 |
0.17 |
0.53 |
0.50 |
0.55 |
0.50 |
0.41 |
1.00 |
0.52 |
0.48 |
0.62 |
0.67 |
0.42 |
0.55 |
| intrea_c |
0.35 |
0.50 |
0.29 |
0.27 |
0.41 |
0.43 |
0.41 |
0.28 |
0.22 |
0.38 |
0.49 |
0.19 |
0.50 |
0.49 |
0.44 |
0.45 |
0.31 |
0.52 |
1.00 |
0.46 |
0.50 |
0.36 |
0.47 |
0.50 |
| memor_c |
0.32 |
0.54 |
0.26 |
0.27 |
0.33 |
0.32 |
0.44 |
0.31 |
0.30 |
0.33 |
0.56 |
0.13 |
0.45 |
0.65 |
0.56 |
0.67 |
0.50 |
0.48 |
0.46 |
1.00 |
0.52 |
0.45 |
0.48 |
0.55 |
| scacad_c |
0.24 |
0.60 |
0.15 |
0.25 |
0.32 |
0.38 |
0.54 |
0.31 |
0.24 |
0.28 |
0.60 |
0.14 |
0.49 |
0.59 |
0.61 |
0.54 |
0.39 |
0.62 |
0.50 |
0.52 |
1.00 |
0.58 |
0.52 |
0.59 |
| scmath_c |
0.25 |
0.50 |
0.15 |
0.13 |
0.22 |
0.28 |
0.43 |
0.26 |
0.17 |
0.24 |
0.50 |
0.14 |
0.36 |
0.47 |
0.56 |
0.47 |
0.34 |
0.67 |
0.36 |
0.45 |
0.58 |
1.00 |
0.36 |
0.58 |
| scverb_c |
0.24 |
0.49 |
0.28 |
0.17 |
0.30 |
0.30 |
0.50 |
0.28 |
0.27 |
0.33 |
0.51 |
0.15 |
0.38 |
0.48 |
0.42 |
0.34 |
0.32 |
0.42 |
0.47 |
0.48 |
0.52 |
0.36 |
1.00 |
0.53 |
| selfef_c |
0.37 |
0.56 |
0.27 |
0.30 |
0.36 |
0.36 |
0.47 |
0.40 |
0.25 |
0.40 |
0.67 |
0.17 |
0.48 |
0.63 |
0.66 |
0.53 |
0.40 |
0.55 |
0.50 |
0.55 |
0.59 |
0.58 |
0.53 |
1.00 |
library(d3heatmap)
scores %>%
select(vars) %>%
cor(use="pair") %>%
d3heatmap(
symn= TRUE,
symm = TRUE,
k_row = 5,
k_col = 5
)
Análise paralela e EFA
scores %>% select(vars) %>% fa.parallel(fa = "fa" )
## Parallel analysis suggests that the number of factors = 2 and the number of components = NA
scores %>% select(vars) %>% fa(nfactors = 3) %>% print.psych(cut =.28, sort = TRUE)
## Factor Analysis using method = minres
## Call: fa(r = ., nfactors = 3)
## Standardized loadings (pattern matrix) based upon correlation matrix
## item MR1 MR3 MR2 h2 u2 com
## scacad_c 21 0.74 0.66 0.34 1.1
## intmat_c 18 0.73 0.60 0.40 1.0
## scmath_c 22 0.71 0.54 0.46 1.1
## C_0_c 7 0.57 0.46 0.54 1.2
## C_1_c 2 0.55 0.38 0.70 0.30 1.8
## selfef_c 24 0.47 0.35 0.61 0.39 1.9
## scverb_c 23 0.40 0.38 0.62 1.7
## coplrn_c 13 0.38 0.40 0.60 1.9
## intrea_c 19 0.36 0.42 0.58 2.2
## comlrn_c 12 0.04 0.96 1.2
## cstrat_c 14 0.78 0.74 0.26 1.1
## elab_c 16 0.70 0.64 0.36 1.0
## insmot_c 17 0.64 0.39 0.61 1.0
## memor_c 20 0.61 0.57 0.43 1.2
## E_1_c 3 0.47 0.24 0.76 1.8
## O_0_c 10 0.47 0.41 0.43 0.57 2.2
## effper_c 15 0.40 0.43 0.63 0.37 2.0
## cexp_c 11 0.36 0.38 0.57 0.43 2.2
## N_1_c 4 0.67 0.45 0.55 1.0
## N_0_c 9 0.65 0.41 0.59 1.0
## O_1_c 5 0.29 0.54 0.47 0.53 1.6
## A_1_c 1 0.51 0.39 0.61 1.2
## A_0_c 6 0.37 0.46 0.42 0.58 2.0
## E_0_c 8 0.39 0.30 0.70 1.7
##
## MR1 MR3 MR2
## SS loadings 4.57 4.02 2.87
## Proportion Var 0.19 0.17 0.12
## Cumulative Var 0.19 0.36 0.48
## Proportion Explained 0.40 0.35 0.25
## Cumulative Proportion 0.40 0.75 1.00
##
## With factor correlations of
## MR1 MR3 MR2
## MR1 1.00 0.71 0.41
## MR3 0.71 1.00 0.49
## MR2 0.41 0.49 1.00
##
## Mean item complexity = 1.5
## Test of the hypothesis that 3 factors are sufficient.
##
## The degrees of freedom for the null model are 276 and the objective function was 13.44 with Chi Square of 2125.3
## The degrees of freedom for the model are 207 and the objective function was 2.08
##
## The root mean square of the residuals (RMSR) is 0.04
## The df corrected root mean square of the residuals is 0.05
##
## The harmonic number of observations is 168 with the empirical chi square 182.25 with prob < 0.89
## The total number of observations was 168 with Likelihood Chi Square = 324.25 with prob < 3.4e-07
##
## Tucker Lewis Index of factoring reliability = 0.914
## RMSEA index = 0.064 and the 90 % confidence intervals are 0.046 0.07
## BIC = -736.41
## Fit based upon off diagonal values = 0.99
## Measures of factor score adequacy
## MR1 MR3 MR2
## Correlation of (regression) scores with factors 0.95 0.95 0.90
## Multiple R square of scores with factors 0.90 0.89 0.81
## Minimum correlation of possible factor scores 0.80 0.79 0.63
scores %>% select(vars) %>% fa(nfactors = 5) %>% print.psych(cut =.21, sort = TRUE)
## Factor Analysis using method = minres
## Call: fa(r = ., nfactors = 5)
## Standardized loadings (pattern matrix) based upon correlation matrix
## item MR1 MR5 MR2 MR3 MR4 h2 u2 com
## scacad_c 21 0.74 0.673 0.33 1.1
## intmat_c 18 0.72 0.611 0.39 1.1
## scmath_c 22 0.69 0.543 0.46 1.2
## C_0_c 7 0.61 0.477 0.52 1.3
## scverb_c 23 0.59 0.24 0.440 0.56 1.3
## C_1_c 2 0.56 0.692 0.31 1.6
## selfef_c 24 0.53 0.26 0.619 0.38 1.5
## intrea_c 19 0.45 0.23 0.453 0.55 1.7
## coplrn_c 13 0.31 0.25 0.415 0.58 2.8
## comlrn_c 12 0.30 0.064 0.94 1.6
## E_0_c 8 0.25 0.294 0.71 3.6
## elab_c 16 0.80 0.710 0.29 1.1
## cstrat_c 14 0.73 0.735 0.27 1.1
## insmot_c 17 0.64 0.397 0.60 1.0
## memor_c 20 0.61 0.587 0.41 1.2
## effper_c 15 0.32 0.46 0.644 0.36 1.9
## cexp_c 11 0.35 0.36 0.574 0.43 2.3
## N_1_c 4 0.86 0.739 0.26 1.0
## N_0_c 9 0.72 0.550 0.45 1.0
## A_0_c 6 0.94 0.868 0.13 1.0
## A_1_c 1 0.46 0.22 0.442 0.56 1.6
## E_1_c 3 0.23 0.50 0.343 0.66 1.5
## O_0_c 10 0.24 0.49 0.487 0.51 1.7
## O_1_c 5 0.37 0.43 0.526 0.47 2.2
##
## MR1 MR5 MR2 MR3 MR4
## SS loadings 4.54 3.39 1.80 1.76 1.40
## Proportion Var 0.19 0.14 0.07 0.07 0.06
## Cumulative Var 0.19 0.33 0.41 0.48 0.54
## Proportion Explained 0.35 0.26 0.14 0.14 0.11
## Cumulative Proportion 0.35 0.62 0.75 0.89 1.00
##
## With factor correlations of
## MR1 MR5 MR2 MR3 MR4
## MR1 1.00 0.74 0.35 0.49 0.29
## MR5 0.74 1.00 0.38 0.42 0.36
## MR2 0.35 0.38 1.00 0.42 0.32
## MR3 0.49 0.42 0.42 1.00 0.33
## MR4 0.29 0.36 0.32 0.33 1.00
##
## Mean item complexity = 1.6
## Test of the hypothesis that 5 factors are sufficient.
##
## The degrees of freedom for the null model are 276 and the objective function was 13.44 with Chi Square of 2125.3
## The degrees of freedom for the model are 166 and the objective function was 1.46
##
## The root mean square of the residuals (RMSR) is 0.03
## The df corrected root mean square of the residuals is 0.04
##
## The harmonic number of observations is 168 with the empirical chi square 100.14 with prob < 1
## The total number of observations was 168 with Likelihood Chi Square = 225.32 with prob < 0.0015
##
## Tucker Lewis Index of factoring reliability = 0.945
## RMSEA index = 0.053 and the 90 % confidence intervals are 0.029 0.061
## BIC = -625.25
## Fit based upon off diagonal values = 0.99
## Measures of factor score adequacy
## MR1 MR5 MR2 MR3 MR4
## Correlation of (regression) scores with factors 0.95 0.95 0.91 0.95 0.82
## Multiple R square of scores with factors 0.91 0.90 0.83 0.90 0.68
## Minimum correlation of possible factor scores 0.82 0.79 0.66 0.79 0.36