Modelo de créditos parciais
Ricardo Primi
23 de out de 2019
Bibliotecas
library(tidyverse)
library(sjmisc)
library(TAM)
library(psych)
library(readxl)
library(knitr)
library(RColorBrewer)
#library(xlsx)
source("http://www.labape.com.br/rprimi/R/utils_construct_maps.R")1. Lê/importa banco
# Abre direto da internet (con é um endereço do arquivo)
con<-url("http://www.labape.com.br/rprimi/TRI/2019_slides_exerc/senna_v1_54_ex3.RDS")
sennav1 <- readRDS(con)
con<-url("http://www.labape.com.br/rprimi/TRI/2019_slides_exerc/senna_v1_54_ex3_dic.RDS")
dic <- readRDS(con)2. Examina base e seleciona os itens
names(sennav1)## [1] "i03.NV.NV.10" "i04.A.Cmp.10" "i05.O.Img.10"
## [4] "i06.C.Ord.10" "i07.N.Vol.00" "i09.A.Cmp.10"
## [7] "i10.O.Img.10" "i11.C.Ord.10" "i12.N.Vol.00"
## [10] "i13.NV.NV.10" "i14.A.Tru.10" "i17.N.Anx.00"
## [13] "i24.O.Aes.10" "i25.A.Cmp.10" "i27.N.Dep.00"
## [16] "i29.A.Cmp.10" "i30.O.Int.10" "i32.N.Vol.00"
## [19] "i33.NV.NV.10" "i34.A.Tru.10" "i36.C.Conc.00"
## [22] "i37.N.Anx.10" "i39.A.Cmp.10" "i40.O.Aes.10"
## [25] "i42.N.Anx.00" "i44.A.Pol.00" "i46.C.Conc.00"
## [28] "i48.NV.NV.10" "i49.A.Cmp.10" "i51.C.Ord.00"
## [31] "i52.NV.NV.10" "i53.A.Pol.00" "i54.O.Int.10"
## [34] "i55.E.Act.10" "i56.NV.NV.10" "i60.NV.NV.00"
## [37] "i63.E.Act.10" "i66.O.Int.10" "i67.E.Soc.00"
## [40] "i70.O.Img.11" "i71.E.Soc.10" "i73.E.Soc.00"
## [43] "i74.NV.NV.10" "i75.E.Soc.10" "i76.E.Act.10"
## [46] "i77.C.SD.11" "i79.N.Vol.11" "i82.N.Vol.11"
## [49] "i83.C.Conc.11" "i84.E.Soc.11" "i87.E.Soc.11"
## [52] "i88.N.Dep.11" "i89.C.Achv.11" "i91.C.SD.11"
## [55] "missR" "admiss_missR" "acq_avr"
## [58] "acq_sd" "num_items" "Caderno"
## [61] "age2" "grade" "atrasado"
## [64] "atrasado2" "VL_PROFICIENCIA_LP" "VL_PROFICIENCIA_MT"
## [67] "vign_consist" "vign_consist_count" "F1.Cons"
## [70] "F2.Extr" "F3.EmSt" "F4.Agre"
## [73] "F5.Opns" "F6.NVLoc" "gender"
## [76] "rwn_id" "NM_REGIONAL_ESCOLA" "grade2"
## [79] "grade_5" "grade_9" "grade_10"
## [82] "freq" "cd_esc_grade" "rwn_id2"
## [85] "VL_PROFICIENCIA_LP_r" "VL_PROFICIENCIA_MT_r"dt <- sennav1[ , c(34, 37, 39, 41, 42, 44, 45, 50, 51)]
dic_e <- dic %>% filter(factor == "E")
vars_e <- dic_e$coditem
labels_e <- dic_e$text
dt <- sennav1[ , vars_e]3. Análise psicométrica classica
alpha(dt, check.keys = TRUE)##
## Reliability analysis
## Call: alpha(x = dt, check.keys = TRUE)
##
## raw_alpha std.alpha G6(smc) average_r S/N ase mean sd median_r
## 0.7 0.7 0.7 0.21 2.4 0.0043 3.5 0.65 0.2
##
## lower alpha upper 95% confidence boundaries
## 0.69 0.7 0.7
##
## Reliability if an item is dropped:
## raw_alpha std.alpha G6(smc) average_r S/N alpha se var.r
## i67.E.Soc.00- 0.69 0.69 0.68 0.22 2.3 0.0044 0.0097
## i73.E.Soc.00- 0.69 0.70 0.69 0.23 2.3 0.0044 0.0083
## i55.E.Act.10 0.64 0.65 0.64 0.19 1.8 0.0051 0.0075
## i63.E.Act.10 0.67 0.67 0.67 0.20 2.0 0.0048 0.0112
## i76.E.Act.10 0.67 0.67 0.67 0.20 2.1 0.0048 0.0111
## i71.E.Soc.10 0.65 0.66 0.65 0.19 1.9 0.0050 0.0094
## i75.E.Soc.10 0.66 0.67 0.67 0.20 2.0 0.0048 0.0101
## i84.E.Soc.11 0.67 0.68 0.67 0.21 2.1 0.0047 0.0103
## i87.E.Soc.11 0.69 0.70 0.69 0.22 2.3 0.0044 0.0108
## med.r
## i67.E.Soc.00- 0.24
## i73.E.Soc.00- 0.24
## i55.E.Act.10 0.20
## i63.E.Act.10 0.20
## i76.E.Act.10 0.19
## i71.E.Soc.10 0.19
## i75.E.Soc.10 0.20
## i84.E.Soc.11 0.19
## i87.E.Soc.11 0.24
##
## Item statistics
## n raw.r std.r r.cor r.drop mean sd
## i67.E.Soc.00- 10664 0.50 0.47 0.36 0.29 3.2 1.3
## i73.E.Soc.00- 10658 0.46 0.44 0.32 0.26 3.6 1.2
## i55.E.Act.10 10591 0.66 0.67 0.63 0.52 4.0 1.1
## i63.E.Act.10 10714 0.56 0.57 0.48 0.40 3.7 1.1
## i76.E.Act.10 10686 0.58 0.56 0.47 0.39 3.1 1.3
## i71.E.Soc.10 10683 0.62 0.63 0.58 0.47 3.8 1.1
## i75.E.Soc.10 10763 0.57 0.57 0.49 0.40 3.7 1.1
## i84.E.Soc.11 10709 0.52 0.54 0.45 0.37 3.8 1.0
## i87.E.Soc.11 10732 0.46 0.45 0.32 0.26 2.6 1.2
##
## Non missing response frequency for each item
## 1 2 3 4 5 miss
## i67.E.Soc.00 0.19 0.26 0.25 0.16 0.14 0.05
## i73.E.Soc.00 0.30 0.27 0.24 0.11 0.08 0.05
## i55.E.Act.10 0.03 0.08 0.19 0.30 0.40 0.06
## i63.E.Act.10 0.04 0.12 0.24 0.30 0.31 0.05
## i76.E.Act.10 0.14 0.20 0.28 0.23 0.16 0.05
## i71.E.Soc.10 0.03 0.11 0.19 0.33 0.34 0.05
## i75.E.Soc.10 0.05 0.12 0.20 0.34 0.29 0.04
## i84.E.Soc.11 0.03 0.10 0.21 0.41 0.26 0.05
## i87.E.Soc.11 0.21 0.29 0.28 0.16 0.07 0.054. Inverte itens negativos e transforma de 1-5 para 0-4
names(dt)## [1] "i67.E.Soc.00" "i73.E.Soc.00" "i55.E.Act.10" "i63.E.Act.10"
## [5] "i76.E.Act.10" "i71.E.Soc.10" "i75.E.Soc.10" "i84.E.Soc.11"
## [9] "i87.E.Soc.11" dt$i67.E.Soc.00 <- 6 - dt$i67.E.Soc.00
dt$i73.E.Soc.00 <- 6 - dt$i73.E.Soc.00
dt <- map_df(dt, ~.-1)5. Calibra modelo de créditos parciais
tri_e <- tam.mml(resp = dt, irtmodel = "PCM")## ....................................................
## Processing Data 2019-10-29 22:26:11
## * Response Data: 11249 Persons and 9 Items
## * Numerical integration with 21 nodes
## * Created Design Matrices ( 2019-10-29 22:26:11 )
## * Calculated Sufficient Statistics ( 2019-10-29 22:26:11 )
## ....................................................
## Iteration 1 2019-10-29 22:26:11
## E Step
## M Step Intercepts |----
## Deviance = 288147.189
## Maximum item intercept parameter change: 0.792313
## Maximum item slope parameter change: 0
## Maximum regression parameter change: 0
## Maximum variance parameter change: 0.148833
## ....................................................
## Iteration 2 2019-10-29 22:26:11
## E Step
## M Step Intercepts |----
## Deviance = 278114.5414 | Absolute change: 10032.65 | Relative change: 0.0360738
## Maximum item intercept parameter change: 0.691731
## Maximum item slope parameter change: 0
## Maximum regression parameter change: 0
## Maximum variance parameter change: 0.264888
## ....................................................
## Iteration 3 2019-10-29 22:26:11
## E Step
## M Step Intercepts |----
## Deviance = 274784.8535 | Absolute change: 3329.688 | Relative change: 0.01211744
## Maximum item intercept parameter change: 0.455792
## Maximum item slope parameter change: 0
## Maximum regression parameter change: 0
## Maximum variance parameter change: 0.144836
## ....................................................
## Iteration 4 2019-10-29 22:26:12
## E Step
## M Step Intercepts |----
## Deviance = 273731.664 | Absolute change: 1053.189 | Relative change: 0.00384753
## Maximum item intercept parameter change: 0.120218
## Maximum item slope parameter change: 0
## Maximum regression parameter change: 0
## Maximum variance parameter change: 0.073083
## ....................................................
## Iteration 5 2019-10-29 22:26:12
## E Step
## M Step Intercepts |----
## Deviance = 273318.4954 | Absolute change: 413.1686 | Relative change: 0.00151167
## Maximum item intercept parameter change: 0.067482
## Maximum item slope parameter change: 0
## Maximum regression parameter change: 0
## Maximum variance parameter change: 0.040658
## ....................................................
## Iteration 6 2019-10-29 22:26:12
## E Step
## M Step Intercepts |----
## Deviance = 273126.1855 | Absolute change: 192.3099 | Relative change: 0.00070411
## Maximum item intercept parameter change: 0.048367
## Maximum item slope parameter change: 0
## Maximum regression parameter change: 0
## Maximum variance parameter change: 0.024802
## ....................................................
## Iteration 7 2019-10-29 22:26:12
## E Step
## M Step Intercepts |----
## Deviance = 273030.5008 | Absolute change: 95.6847 | Relative change: 0.00035045
## Maximum item intercept parameter change: 0.027411
## Maximum item slope parameter change: 0
## Maximum regression parameter change: 0
## Maximum variance parameter change: 0.015654
## ....................................................
## Iteration 8 2019-10-29 22:26:12
## E Step
## M Step Intercepts |----
## Deviance = 272978.555 | Absolute change: 51.9458 | Relative change: 0.00019029
## Maximum item intercept parameter change: 0.021065
## Maximum item slope parameter change: 0
## Maximum regression parameter change: 0
## Maximum variance parameter change: 0.010643
## ....................................................
## Iteration 9 2019-10-29 22:26:12
## E Step
## M Step Intercepts |----
## Deviance = 272949.6206 | Absolute change: 28.9344 | Relative change: 0.00010601
## Maximum item intercept parameter change: 0.016621
## Maximum item slope parameter change: 0
## Maximum regression parameter change: 0
## Maximum variance parameter change: 0.007406
## ....................................................
## Iteration 10 2019-10-29 22:26:12
## E Step
## M Step Intercepts |----
## Deviance = 272932.8589 | Absolute change: 16.7618 | Relative change: 6.141e-05
## Maximum item intercept parameter change: 0.012857
## Maximum item slope parameter change: 0
## Maximum regression parameter change: 0
## Maximum variance parameter change: 0.005361
## ....................................................
## Iteration 11 2019-10-29 22:26:12
## E Step
## M Step Intercepts |----
## Deviance = 272923.0411 | Absolute change: 9.8178 | Relative change: 3.597e-05
## Maximum item intercept parameter change: 0.009803
## Maximum item slope parameter change: 0
## Maximum regression parameter change: 0
## Maximum variance parameter change: 0.003929
## ....................................................
## Iteration 12 2019-10-29 22:26:12
## E Step
## M Step Intercepts |----
## Deviance = 272917.2518 | Absolute change: 5.7893 | Relative change: 2.121e-05
## Maximum item intercept parameter change: 0.007517
## Maximum item slope parameter change: 0
## Maximum regression parameter change: 0
## Maximum variance parameter change: 0.002939
## ....................................................
## Iteration 13 2019-10-29 22:26:12
## E Step
## M Step Intercepts |----
## Deviance = 272913.8353 | Absolute change: 3.4165 | Relative change: 1.252e-05
## Maximum item intercept parameter change: 0.005706
## Maximum item slope parameter change: 0
## Maximum regression parameter change: 0
## Maximum variance parameter change: 0.002223
## ....................................................
## Iteration 14 2019-10-29 22:26:12
## E Step
## M Step Intercepts |----
## Deviance = 272911.8278 | Absolute change: 2.0075 | Relative change: 7.36e-06
## Maximum item intercept parameter change: 0.004342
## Maximum item slope parameter change: 0
## Maximum regression parameter change: 0
## Maximum variance parameter change: 0.001684
## ....................................................
## Iteration 15 2019-10-29 22:26:12
## E Step
## M Step Intercepts |----
## Deviance = 272910.6518 | Absolute change: 1.176 | Relative change: 4.31e-06
## Maximum item intercept parameter change: 0.003315
## Maximum item slope parameter change: 0
## Maximum regression parameter change: 0
## Maximum variance parameter change: 0.001287
## ....................................................
## Iteration 16 2019-10-29 22:26:12
## E Step
## M Step Intercepts |----
## Deviance = 272909.9638 | Absolute change: 0.688 | Relative change: 2.52e-06
## Maximum item intercept parameter change: 0.002533
## Maximum item slope parameter change: 0
## Maximum regression parameter change: 0
## Maximum variance parameter change: 0.000982
## ....................................................
## Iteration 17 2019-10-29 22:26:12
## E Step
## M Step Intercepts |----
## Deviance = 272909.561 | Absolute change: 0.4028 | Relative change: 1.48e-06
## Maximum item intercept parameter change: 0.001934
## Maximum item slope parameter change: 0
## Maximum regression parameter change: 0
## Maximum variance parameter change: 0.000754
## ....................................................
## Iteration 18 2019-10-29 22:26:12
## E Step
## M Step Intercepts |----
## Deviance = 272909.326 | Absolute change: 0.235 | Relative change: 8.6e-07
## Maximum item intercept parameter change: 0.001478
## Maximum item slope parameter change: 0
## Maximum regression parameter change: 0
## Maximum variance parameter change: 0.000576
## ....................................................
## Iteration 19 2019-10-29 22:26:12
## E Step
## M Step Intercepts |----
## Deviance = 272909.1887 | Absolute change: 0.1373 | Relative change: 5e-07
## Maximum item intercept parameter change: 0.001128
## Maximum item slope parameter change: 0
## Maximum regression parameter change: 0
## Maximum variance parameter change: 0.000442
## ....................................................
## Iteration 20 2019-10-29 22:26:12
## E Step
## M Step Intercepts |----
## Deviance = 272909.1086 | Absolute change: 0.0801 | Relative change: 2.9e-07
## Maximum item intercept parameter change: 0.000862
## Maximum item slope parameter change: 0
## Maximum regression parameter change: 0
## Maximum variance parameter change: 0.000338
## ....................................................
## Iteration 21 2019-10-29 22:26:12
## E Step
## M Step Intercepts |----
## Deviance = 272909.0618 | Absolute change: 0.0468 | Relative change: 1.7e-07
## Maximum item intercept parameter change: 0.000658
## Maximum item slope parameter change: 0
## Maximum regression parameter change: 0
## Maximum variance parameter change: 0.000259
## ....................................................
## Iteration 22 2019-10-29 22:26:12
## E Step
## M Step Intercepts |----
## Deviance = 272909.0346 | Absolute change: 0.0272 | Relative change: 1e-07
## Maximum item intercept parameter change: 0.000503
## Maximum item slope parameter change: 0
## Maximum regression parameter change: 0
## Maximum variance parameter change: 0.000198
## ....................................................
## Iteration 23 2019-10-29 22:26:12
## E Step
## M Step Intercepts |----
## Deviance = 272909.0187 | Absolute change: 0.0159 | Relative change: 6e-08
## Maximum item intercept parameter change: 0.000383
## Maximum item slope parameter change: 0
## Maximum regression parameter change: 0
## Maximum variance parameter change: 0.000152
## ....................................................
## Iteration 24 2019-10-29 22:26:12
## E Step
## M Step Intercepts |----
## Deviance = 272909.0094 | Absolute change: 0.0092 | Relative change: 3e-08
## Maximum item intercept parameter change: 0.000293
## Maximum item slope parameter change: 0
## Maximum regression parameter change: 0
## Maximum variance parameter change: 0.000116
## ....................................................
## Iteration 25 2019-10-29 22:26:12
## E Step
## M Step Intercepts |----
## Deviance = 272909.004 | Absolute change: 0.0054 | Relative change: 2e-08
## Maximum item intercept parameter change: 0.000223
## Maximum item slope parameter change: 0
## Maximum regression parameter change: 0
## Maximum variance parameter change: 8.9e-05
## ....................................................
## Iteration 26 2019-10-29 22:26:12
## E Step
## M Step Intercepts |----
## Deviance = 272909.0009 | Absolute change: 0.0031 | Relative change: 1e-08
## Maximum item intercept parameter change: 0.000171
## Maximum item slope parameter change: 0
## Maximum regression parameter change: 0
## Maximum variance parameter change: 6.8e-05
## ....................................................
## Iteration 27 2019-10-29 22:26:12
## E Step
## M Step Intercepts |----
## Deviance = 272908.9991 | Absolute change: 0.0018 | Relative change: 1e-08
## Maximum item intercept parameter change: 0.00013
## Maximum item slope parameter change: 0
## Maximum regression parameter change: 0
## Maximum variance parameter change: 5.2e-05
## ....................................................
## Iteration 28 2019-10-29 22:26:12
## E Step
## M Step Intercepts |----
## Deviance = 272908.998 | Absolute change: 0.0011 | Relative change: 0
## Maximum item intercept parameter change: 9.9e-05
## Maximum item slope parameter change: 0
## Maximum regression parameter change: 0
## Maximum variance parameter change: 4e-05
## ....................................................
## Iteration 29 2019-10-29 22:26:12
## E Step
## M Step Intercepts |----
## Deviance = 272908.9974 | Absolute change: 6e-04 | Relative change: 0
## Maximum item intercept parameter change: 7.6e-05
## Maximum item slope parameter change: 0
## Maximum regression parameter change: 0
## Maximum variance parameter change: 3e-05
## ....................................................
## Item Parameters
## xsi.index xsi.label est
## 1 1 i67.E.Soc.00_Cat1 -0.5005
## 2 2 i67.E.Soc.00_Cat2 -0.5667
## 3 3 i67.E.Soc.00_Cat3 0.0477
## 4 4 i67.E.Soc.00_Cat4 0.5423
## 5 5 i73.E.Soc.00_Cat1 -0.7215
## 6 6 i73.E.Soc.00_Cat2 -1.0372
## 7 7 i73.E.Soc.00_Cat3 -0.1123
## 8 8 i73.E.Soc.00_Cat4 0.0366
## 9 9 i55.E.Act.10_Cat1 -1.5272
## 10 10 i55.E.Act.10_Cat2 -1.0890
## 11 11 i55.E.Act.10_Cat3 -0.5477
## 12 12 i55.E.Act.10_Cat4 -0.1983
## 13 13 i63.E.Act.10_Cat1 -1.4770
## 14 14 i63.E.Act.10_Cat2 -0.9577
## 15 15 i63.E.Act.10_Cat3 -0.2868
## 16 16 i63.E.Act.10_Cat4 0.1424
## 17 17 i76.E.Act.10_Cat1 -0.6444
## 18 18 i76.E.Act.10_Cat2 -0.4508
## 19 19 i76.E.Act.10_Cat3 0.2612
## 20 20 i76.E.Act.10_Cat4 0.6711
## 21 21 i71.E.Soc.10_Cat1 -1.6387
## 22 22 i71.E.Soc.10_Cat2 -0.8036
## 23 23 i71.E.Soc.10_Cat3 -0.5952
## 24 24 i71.E.Soc.10_Cat4 0.0993
## 25 25 i75.E.Soc.10_Cat1 -1.2643
## 26 26 i75.E.Soc.10_Cat2 -0.7856
## 27 27 i75.E.Soc.10_Cat3 -0.5702
## 28 28 i75.E.Soc.10_Cat4 0.3148
## 29 29 i84.E.Soc.11_Cat1 -1.6196
## 30 30 i84.E.Soc.11_Cat2 -1.0294
## 31 31 i84.E.Soc.11_Cat3 -0.7284
## 32 32 i84.E.Soc.11_Cat4 0.6084
## 33 33 i87.E.Soc.11_Cat1 -0.5033
## 34 34 i87.E.Soc.11_Cat2 0.0121
## 35 35 i87.E.Soc.11_Cat3 0.7613
## 36 36 i87.E.Soc.11_Cat4 1.2079
## ...................................
## Regression Coefficients
## [,1]
## [1,] 0
##
## Variance:
## [,1]
## [1,] 0.2477
##
##
## EAP Reliability:
## [1] 0.678
##
## -----------------------------
## Start: 2019-10-29 22:26:11
## End: 2019-10-29 22:26:12
## Time difference of 0.6891789 secs6. Examina ajuste dos itens
fit <- tam.fit(tri_e)## Item fit calculation based on 5 simulations
## |**********|
## |----------| summary(fit)## ------------------------------------------------------------
## TAM 3.1-45 (2019-03-18 16:53:26)
## R version 3.5.1 (2018-07-02) x86_64, darwin15.6.0 | nodename=MacBookPro2018 | login=rprimi
##
## Date of Analysis: 2019-10-29 22:26:13
## Time difference of 0.543447 secs
## Computation time: 0.543447
##
## Item fit statitics (Function 'tam.fit')
## Call:
## tam.fit(tamobj = tri_e)
##
## parameter Outfit Outfit_t Outfit_p Infit Infit_t Infit_p
## 1 i67.E.Soc.00_Cat1 1.396 18.645 0.000 1.054 2.836 0.005
## 2 i67.E.Soc.00_Cat2 1.103 9.516 0.000 1.064 6.010 0.000
## 3 i67.E.Soc.00_Cat3 1.141 17.240 0.000 1.080 9.935 0.000
## 4 i67.E.Soc.00_Cat4 1.240 15.106 0.000 0.996 -0.241 0.809
## 5 i73.E.Soc.00_Cat1 1.875 25.055 0.000 1.062 2.176 0.030
## 6 i73.E.Soc.00_Cat2 1.227 13.837 0.000 1.073 4.645 0.000
## 7 i73.E.Soc.00_Cat3 1.124 15.098 0.000 1.092 11.303 0.000
## 8 i73.E.Soc.00_Cat4 1.156 15.450 0.000 1.032 3.275 0.001
## 9 i55.E.Act.10_Cat1 1.060 1.161 0.246 0.956 -0.874 0.382
## 10 i55.E.Act.10_Cat2 0.795 -10.124 0.000 0.924 -3.565 0.000
## 11 i55.E.Act.10_Cat3 0.844 -16.059 0.000 0.908 -9.276 0.000
## 12 i55.E.Act.10_Cat4 0.907 -13.425 0.000 0.923 -11.113 0.000
## 13 i63.E.Act.10_Cat1 0.990 -0.252 0.801 0.982 -0.416 0.677
## 14 i63.E.Act.10_Cat2 1.011 0.644 0.520 0.989 -0.643 0.520
## 15 i63.E.Act.10_Cat3 0.971 -3.612 0.000 0.981 -2.377 0.017
## 16 i63.E.Act.10_Cat4 0.983 -1.805 0.071 0.978 -2.355 0.019
## 17 i76.E.Act.10_Cat1 1.215 10.773 0.000 1.023 1.203 0.229
## 18 i76.E.Act.10_Cat2 1.016 1.708 0.088 1.007 0.702 0.483
## 19 i76.E.Act.10_Cat3 0.975 -2.995 0.003 0.972 -3.329 0.001
## 20 i76.E.Act.10_Cat4 1.063 3.539 0.000 0.974 -1.499 0.134
## 21 i71.E.Soc.10_Cat1 1.164 3.224 0.001 0.968 -0.674 0.500
## 22 i71.E.Soc.10_Cat2 0.908 -5.191 0.000 0.958 -2.312 0.021
## 23 i71.E.Soc.10_Cat3 0.895 -11.666 0.000 0.932 -7.511 0.000
## 24 i71.E.Soc.10_Cat4 0.922 -9.519 0.000 0.941 -7.144 0.000
## 25 i75.E.Soc.10_Cat1 1.326 7.966 0.000 1.010 0.281 0.778
## 26 i75.E.Soc.10_Cat2 0.993 -0.440 0.660 0.996 -0.234 0.815
## 27 i75.E.Soc.10_Cat3 0.950 -5.914 0.000 0.968 -3.743 0.000
## 28 i75.E.Soc.10_Cat4 0.983 -1.740 0.082 0.977 -2.329 0.020
## 29 i84.E.Soc.11_Cat1 2.097 14.956 0.000 1.003 0.067 0.946
## 30 i84.E.Soc.11_Cat2 1.035 1.659 0.097 0.999 -0.032 0.974
## 31 i84.E.Soc.11_Cat3 0.961 -4.421 0.000 0.980 -2.257 0.024
## 32 i84.E.Soc.11_Cat4 1.012 1.065 0.287 0.978 -1.996 0.046
## 33 i87.E.Soc.11_Cat1 1.238 16.728 0.000 1.073 5.376 0.000
## 34 i87.E.Soc.11_Cat2 1.092 12.507 0.000 1.072 9.794 0.000
## 35 i87.E.Soc.11_Cat3 1.106 7.736 0.000 1.016 1.195 0.232
## 36 i87.E.Soc.11_Cat4 1.677 18.421 0.000 1.006 0.198 0.843 plot(tri_e, ngroups = 24)## Iteration in WLE/MLE estimation 1 | Maximal change 1.8773
## Iteration in WLE/MLE estimation 2 | Maximal change 1.2791
## Iteration in WLE/MLE estimation 3 | Maximal change 0.6499
## Iteration in WLE/MLE estimation 4 | Maximal change 0.3254
## Iteration in WLE/MLE estimation 5 | Maximal change 0.1171
## Iteration in WLE/MLE estimation 6 | Maximal change 0.0478
## Iteration in WLE/MLE estimation 7 | Maximal change 0.0184
## Iteration in WLE/MLE estimation 8 | Maximal change 0.0072
## Iteration in WLE/MLE estimation 9 | Maximal change 0.0028
## Iteration in WLE/MLE estimation 10 | Maximal change 0.0011
## Iteration in WLE/MLE estimation 11 | Maximal change 4e-04
## Iteration in WLE/MLE estimation 12 | Maximal change 2e-04
## Iteration in WLE/MLE estimation 13 | Maximal change 1e-04
## ----
## WLE Reliability= 0.658
## ....................................................
## Plots exported in png format into folder:
## /Users/rprimi/Dropbox (Personal)/TRI/2019_slides_exerc/Plots7. Examina curva dos itens
summary(tri_e)## ------------------------------------------------------------
## TAM 3.1-45 (2019-03-18 16:53:26)
## R version 3.5.1 (2018-07-02) x86_64, darwin15.6.0 | nodename=MacBookPro2018 | login=rprimi
##
## Date of Analysis: 2019-10-29 22:26:12
## Time difference of 0.6891789 secs
## Computation time: 0.6891789
##
## Multidimensional Item Response Model in TAM
##
## IRT Model: PCM
## Call:
## tam.mml(resp = dt, irtmodel = "PCM")
##
## ------------------------------------------------------------
## Number of iterations = 29
## Numeric integration with 21 integration points
##
## Deviance = 272909
## Log likelihood = -136454.5
## Number of persons = 11249
## Number of persons used = 11082
## Number of items = 9
## Number of estimated parameters = 37
## Item threshold parameters = 36
## Item slope parameters = 0
## Regression parameters = 0
## Variance/covariance parameters = 1
##
## AIC = 272983 | penalty = 74 | AIC=-2*LL + 2*p
## AIC3 = 273020 | penalty = 111 | AIC3=-2*LL + 3*p
## BIC = 273254 | penalty = 344.58 | BIC=-2*LL + log(n)*p
## aBIC = 273136 | penalty = 226.99 | aBIC=-2*LL + log((n-2)/24)*p (adjusted BIC)
## CAIC = 273291 | penalty = 381.58 | CAIC=-2*LL + [log(n)+1]*p (consistent AIC)
## AICc = 272983 | penalty = 74.25 | AICc=-2*LL + 2*p + 2*p*(p+1)/(n-p-1) (bias corrected AIC)
##
## ------------------------------------------------------------
## EAP Reliability
## [1] 0.678
## ------------------------------------------------------------
## Covariances and Variances
## [,1]
## [1,] 0.248
## ------------------------------------------------------------
## Correlations and Standard Deviations (in the diagonal)
## [,1]
## [1,] 0.498
## ------------------------------------------------------------
## Regression Coefficients
## [,1]
## [1,] 0
## ------------------------------------------------------------
## Item Parameters -A*Xsi
## item N M xsi.item AXsi_.Cat1 AXsi_.Cat2
## i67.E.Soc.00 i67.E.Soc.00 10664 2.200 -0.119 -0.501 -1.067
## i73.E.Soc.00 i73.E.Soc.00 10658 2.616 -0.459 -0.722 -1.759
## i55.E.Act.10 i55.E.Act.10 10591 2.957 -0.841 -1.527 -2.616
## i63.E.Act.10 i63.E.Act.10 10714 2.718 -0.645 -1.477 -2.435
## i76.E.Act.10 i76.E.Act.10 10686 2.070 -0.041 -0.644 -1.095
## i71.E.Soc.10 i71.E.Soc.10 10683 2.825 -0.735 -1.639 -2.442
## i75.E.Soc.10 i75.E.Soc.10 10763 2.707 -0.576 -1.264 -2.050
## i84.E.Soc.11 i84.E.Soc.11 10709 2.770 -0.692 -1.620 -2.649
## i87.E.Soc.11 i87.E.Soc.11 10732 1.580 0.369 -0.503 -0.491
## AXsi_.Cat3 AXsi_.Cat4 B.Cat1.Dim1 B.Cat2.Dim1 B.Cat3.Dim1
## i67.E.Soc.00 -1.020 -0.477 1 2 3
## i73.E.Soc.00 -1.871 -1.834 1 2 3
## i55.E.Act.10 -3.164 -3.362 1 2 3
## i63.E.Act.10 -2.722 -2.579 1 2 3
## i76.E.Act.10 -0.834 -0.163 1 2 3
## i71.E.Soc.10 -3.038 -2.938 1 2 3
## i75.E.Soc.10 -2.620 -2.305 1 2 3
## i84.E.Soc.11 -3.378 -2.769 1 2 3
## i87.E.Soc.11 0.270 1.478 1 2 3
## B.Cat4.Dim1
## i67.E.Soc.00 4
## i73.E.Soc.00 4
## i55.E.Act.10 4
## i63.E.Act.10 4
## i76.E.Act.10 4
## i71.E.Soc.10 4
## i75.E.Soc.10 4
## i84.E.Soc.11 4
## i87.E.Soc.11 4
##
## Item Parameters Xsi
## xsi se.xsi
## i67.E.Soc.00_Cat1 -0.500 0.030
## i67.E.Soc.00_Cat2 -0.567 0.023
## i67.E.Soc.00_Cat3 0.048 0.021
## i67.E.Soc.00_Cat4 0.542 0.026
## i73.E.Soc.00_Cat1 -0.721 0.038
## i73.E.Soc.00_Cat2 -1.037 0.027
## i73.E.Soc.00_Cat3 -0.112 0.021
## i73.E.Soc.00_Cat4 0.037 0.023
## i55.E.Act.10_Cat1 -1.527 0.060
## i55.E.Act.10_Cat2 -1.089 0.033
## i55.E.Act.10_Cat3 -0.548 0.023
## i55.E.Act.10_Cat4 -0.198 0.021
## i63.E.Act.10_Cat1 -1.477 0.051
## i63.E.Act.10_Cat2 -0.958 0.028
## i63.E.Act.10_Cat3 -0.287 0.021
## i63.E.Act.10_Cat4 0.142 0.022
## i76.E.Act.10_Cat1 -0.644 0.030
## i76.E.Act.10_Cat2 -0.451 0.022
## i76.E.Act.10_Cat3 0.261 0.022
## i76.E.Act.10_Cat4 0.671 0.028
## i71.E.Soc.10_Cat1 -1.639 0.056
## i71.E.Soc.10_Cat2 -0.804 0.029
## i71.E.Soc.10_Cat3 -0.595 0.022
## i71.E.Soc.10_Cat4 0.099 0.022
## i75.E.Soc.10_Cat1 -1.264 0.046
## i75.E.Soc.10_Cat2 -0.786 0.028
## i75.E.Soc.10_Cat3 -0.570 0.022
## i75.E.Soc.10_Cat4 0.315 0.023
## i84.E.Soc.11_Cat1 -1.620 0.059
## i84.E.Soc.11_Cat2 -1.029 0.031
## i84.E.Soc.11_Cat3 -0.728 0.022
## i84.E.Soc.11_Cat4 0.608 0.023
## i87.E.Soc.11_Cat1 -0.503 0.025
## i87.E.Soc.11_Cat2 0.012 0.021
## i87.E.Soc.11_Cat3 0.761 0.025
## i87.E.Soc.11_Cat4 1.208 0.040
##
## Item Parameters in IRT parameterization
## item alpha beta tau.Cat1 tau.Cat2 tau.Cat3 tau.Cat4
## 1 i67.E.Soc.00 1 -0.119 -0.381 -0.447 0.167 0.662
## 2 i73.E.Soc.00 1 -0.459 -0.263 -0.579 0.346 0.495
## 3 i55.E.Act.10 1 -0.841 -0.687 -0.248 0.293 0.642
## 4 i63.E.Act.10 1 -0.645 -0.832 -0.313 0.358 0.787
## 5 i76.E.Act.10 1 -0.041 -0.604 -0.410 0.302 0.712
## 6 i71.E.Soc.10 1 -0.735 -0.904 -0.069 0.139 0.834
## 7 i75.E.Soc.10 1 -0.576 -0.688 -0.209 0.006 0.891
## 8 i84.E.Soc.11 1 -0.692 -0.927 -0.337 -0.036 1.301
## 9 i87.E.Soc.11 1 0.369 -0.873 -0.357 0.392 0.838 plot(tri_e, type = "items")## Iteration in WLE/MLE estimation 1 | Maximal change 1.8773
## Iteration in WLE/MLE estimation 2 | Maximal change 1.2791
## Iteration in WLE/MLE estimation 3 | Maximal change 0.6499
## Iteration in WLE/MLE estimation 4 | Maximal change 0.3254
## Iteration in WLE/MLE estimation 5 | Maximal change 0.1171
## Iteration in WLE/MLE estimation 6 | Maximal change 0.0478
## Iteration in WLE/MLE estimation 7 | Maximal change 0.0184
## Iteration in WLE/MLE estimation 8 | Maximal change 0.0072
## Iteration in WLE/MLE estimation 9 | Maximal change 0.0028
## Iteration in WLE/MLE estimation 10 | Maximal change 0.0011
## Iteration in WLE/MLE estimation 11 | Maximal change 4e-04
## Iteration in WLE/MLE estimation 12 | Maximal change 2e-04
## Iteration in WLE/MLE estimation 13 | Maximal change 1e-04
## ----
## WLE Reliability= 0.658
## ....................................................
## Plots exported in png format into folder:
## /Users/rprimi/Dropbox (Personal)/TRI/2019_slides_exerc/Plots7. Mapa de construto: tentativa 3
person_item_map_v2(
item_tresh = tam.threshold(tri_e),
coditem = names(dt),
item_text = dic_e$text,
pole = c(1,1,0, 1, 0, 1, 1,1,1),
theta = tri_e$person$EAP
)
describe_likert5_items(
data = dt,
item_tresh = tam.threshold(tri_e),
coditem = names(dt),
item_text = names(dt),
pole = c(1,1,0, 1, 0, 1, 1,1,1)
)
##### 8. Mapa de construto: tentativa 4
person_item_map_v3( size_bar = 4,
size_categ_label = 3,
item_text_max = 32,
item_tresh = tam.threshold(tri_e),
coditem = dic_e$coditem,
item_text = dic_e$text,
pole = dic_e$pole,
theta = tri_e$person$EAP
)