Analisa CBT
Winny
August 18, 2016
Item Analysis pada EVALUASI BELAJAR
analisa hasil CBT, output dari eLS (moodle) ujian multiple choice, one correct answer, random number, random choices
- Winny Setyonugroho, MT, PhD
- contact : wsetyonugroho@umy.ac.id
- Medical Informatics Dept
- Medical Education Dept
Faculty of Medicine and Health Sciences, UMY
- sebagian script ramuan dari :
- title: “CTT dan IRT DICHOTOMOUS”
- author: “Heru Wiryanto”
date: “August 4, 2016”
LANGKAH PERTAMA (PERSIAPAN)
- file dari eLS/moodle , bentuk excel, dibersihkan
- delete cell kosong berisi “-” , bersihkan lainnya. trus di export ke csv
- modifikasi script ini, terutama baris kolom
- save as, nama EB nya
LAPORAN
- sertakan csv, print doc yang sudah ditempeli images, plus script nya
ANALISA CTT
-pakai library nya
## Loading required package: multilevel## Loading required package: nlme## Loading required package: MASS## location location_id Surname Grade.75 Grade.. Q1 Q2 Q3 Q4 Q5 Q6 Q7
## 1 kampus 1 20150310001 23 30.7 0 1 0 1 1 0 1
## 2 kampus 1 20150310002 19 25.3 0 0 0 1 0 0 0
## 3 kampus 1 20150310003 40 53.3 1 1 1 1 1 1 1
## 4 kampus 1 20150310004 25 33.3 0 0 0 0 0 0 0
## 5 kampus 1 20150310005 35 46.7 0 0 1 1 1 0 1
## 6 kampus 1 20150310006 36 48.0 1 0 0 1 1 0 1
## Q8 Q9 Q10 Q11 Q12 Q13 Q14 Q15 Q16 Q17 Q18 Q19 Q20 Q21 Q22 Q23 Q24 Q25
## 1 0 1 0 0 1 0 1 0 1 0 0 0 1 0 0 0 0 0
## 2 0 1 1 1 0 0 1 0 1 0 1 0 0 0 1 0 1 1
## 3 0 0 1 0 1 1 1 0 1 0 1 0 0 0 1 1 1 1
## 4 0 1 0 1 0 1 0 1 1 1 0 0 0 0 1 1 0 1
## 5 0 0 1 1 1 1 1 0 1 0 0 0 0 0 1 1 0 1
## 6 0 1 1 1 1 1 1 1 1 0 0 0 0 0 1 0 1 1
## Q26 Q27 Q28 Q29 Q30 Q31 Q32 Q33 Q34 Q35 Q36 Q37 Q38 Q39 Q40 Q41 Q42 Q43
## 1 0 0 1 0 1 0 0 1 0 1 0 1 0 0 1 0 0 0
## 2 0 0 0 0 1 0 0 1 0 0 0 0 0 0 1 0 0 1
## 3 1 1 1 0 0 1 1 0 0 0 1 1 0 0 0 0 0 0
## 4 1 0 0 0 1 1 0 0 0 0 0 1 0 1 0 1 1 1
## 5 1 0 0 1 0 0 0 0 0 0 1 0 0 1 0 0 0 1
## 6 0 1 0 0 0 0 1 0 0 0 0 1 0 0 0 1 0 1
## Q44 Q45 Q46 Q47 Q48 Q49 Q50 Q51 Q52 Q53 Q54 Q55 Q56 Q57 Q58 Q59 Q60 Q61
## 1 0 1 1 0 1 0 0 1 1 0 0 0 0 0 1 0 0 0
## 2 0 0 0 1 0 1 0 0 0 0 0 0 0 0 0 0 0 0
## 3 0 1 1 0 1 0 1 1 1 0 0 1 0 0 0 1 0 1
## 4 0 0 0 0 1 0 0 1 0 0 0 1 0 0 1 0 0 0
## 5 0 1 1 1 1 0 1 1 0 0 1 0 0 1 1 0 0 1
## 6 0 1 1 0 1 0 0 1 0 0 1 0 0 1 1 1 0 1
## Q62 Q63 Q64 Q65 Q66 Q67 Q68 Q69 Q70 Q71 Q72 Q73 Q74 Q75
## 1 1 1 0 0 0 0 0 0 0 0 0 0 0 0
## 2 0 0 0 0 0 0 1 0 0 0 0 1 1 0
## 3 1 1 0 0 0 0 1 1 0 1 0 0 1 1
## 4 1 1 0 0 1 0 0 0 0 0 0 0 1 0
## 5 1 1 1 1 0 1 0 0 1 0 1 0 0 0
## 6 1 1 0 1 0 1 0 0 0 1 0 0 1 1## 'data.frame': 176 obs. of 80 variables:
## $ location : Factor w/ 2 levels "kampus","pku": 1 1 1 1 1 1 1 1 1 1 ...
## $ location_id: int 1 1 1 1 1 1 1 1 1 1 ...
## $ Surname : num 2.02e+10 2.02e+10 2.02e+10 2.02e+10 2.02e+10 ...
## $ Grade.75 : int 23 19 40 25 35 36 50 49 35 26 ...
## $ Grade.. : num 30.7 25.3 53.3 33.3 46.7 48 66.7 65.3 46.7 34.7 ...
## $ Q1 : int 0 0 1 0 0 1 1 0 1 0 ...
## $ Q2 : int 1 0 1 0 0 0 1 1 1 1 ...
## $ Q3 : int 0 0 1 0 1 0 1 0 0 0 ...
## $ Q4 : int 1 1 1 0 1 1 1 1 1 0 ...
## $ Q5 : int 1 0 1 0 1 1 1 1 1 1 ...
## $ Q6 : int 0 0 1 0 0 0 0 1 1 1 ...
## $ Q7 : int 1 0 1 0 1 1 1 1 0 0 ...
## $ Q8 : int 0 0 0 0 0 0 1 1 0 0 ...
## $ Q9 : int 1 1 0 1 0 1 1 1 1 1 ...
## $ Q10 : int 0 1 1 0 1 1 1 1 1 0 ...
## $ Q11 : int 0 1 0 1 1 1 1 1 1 1 ...
## $ Q12 : int 1 0 1 0 1 1 1 1 0 1 ...
## $ Q13 : int 0 0 1 1 1 1 1 1 1 0 ...
## $ Q14 : int 1 1 1 0 1 1 1 1 1 1 ...
## $ Q15 : int 0 0 0 1 0 1 1 1 1 1 ...
## $ Q16 : int 1 1 1 1 1 1 1 1 1 1 ...
## $ Q17 : int 0 0 0 1 0 0 0 0 0 1 ...
## $ Q18 : int 0 1 1 0 0 0 1 0 0 0 ...
## $ Q19 : int 0 0 0 0 0 0 0 0 0 0 ...
## $ Q20 : int 1 0 0 0 0 0 0 1 0 0 ...
## $ Q21 : int 0 0 0 0 0 0 0 0 0 0 ...
## $ Q22 : int 0 1 1 1 1 1 1 1 1 0 ...
## $ Q23 : int 0 0 1 1 1 0 0 1 1 0 ...
## $ Q24 : int 0 1 1 0 0 1 1 1 0 1 ...
## $ Q25 : int 0 1 1 1 1 1 1 1 1 0 ...
## $ Q26 : int 0 0 1 1 1 0 1 1 1 0 ...
## $ Q27 : int 0 0 1 0 0 1 0 1 1 1 ...
## $ Q28 : int 1 0 1 0 0 0 1 1 0 0 ...
## $ Q29 : int 0 0 0 0 1 0 0 0 0 0 ...
## $ Q30 : int 1 1 0 1 0 0 1 1 0 0 ...
## $ Q31 : int 0 0 1 1 0 0 0 0 0 0 ...
## $ Q32 : int 0 0 1 0 0 1 0 1 0 0 ...
## $ Q33 : int 1 1 0 0 0 0 0 1 0 0 ...
## $ Q34 : int 0 0 0 0 0 0 1 0 0 0 ...
## $ Q35 : int 1 0 0 0 0 0 1 0 0 0 ...
## $ Q36 : int 0 0 1 0 1 0 0 0 0 0 ...
## $ Q37 : int 1 0 1 1 0 1 1 1 1 1 ...
## $ Q38 : int 0 0 0 0 0 0 1 0 1 0 ...
## $ Q39 : int 0 0 0 1 1 0 0 0 1 0 ...
## $ Q40 : int 1 1 0 0 0 0 0 1 0 0 ...
## $ Q41 : int 0 0 0 1 0 1 1 1 0 1 ...
## $ Q42 : int 0 0 0 1 0 0 0 0 0 0 ...
## $ Q43 : int 0 1 0 1 1 1 0 1 1 1 ...
## $ Q44 : int 0 0 0 0 0 0 0 1 0 0 ...
## $ Q45 : int 1 0 1 0 1 1 1 1 0 0 ...
## $ Q46 : int 1 0 1 0 1 1 1 1 1 0 ...
## $ Q47 : int 0 1 0 0 1 0 1 1 1 1 ...
## $ Q48 : int 1 0 1 1 1 1 1 1 1 1 ...
## $ Q49 : int 0 1 0 0 0 0 1 1 0 1 ...
## $ Q50 : int 0 0 1 0 1 0 0 1 1 0 ...
## $ Q51 : int 1 0 1 1 1 1 1 1 1 1 ...
## $ Q52 : int 1 0 1 0 0 0 1 1 1 0 ...
## $ Q53 : int 0 0 0 0 0 0 1 1 1 0 ...
## $ Q54 : int 0 0 0 0 1 1 0 0 0 0 ...
## $ Q55 : int 0 0 1 1 0 0 1 1 1 1 ...
## $ Q56 : int 0 0 0 0 0 0 1 1 1 0 ...
## $ Q57 : int 0 0 0 0 1 1 1 1 1 0 ...
## $ Q58 : int 1 0 0 1 1 1 1 1 1 1 ...
## $ Q59 : int 0 0 1 0 0 1 1 0 0 0 ...
## $ Q60 : int 0 0 0 0 0 0 1 0 0 1 ...
## $ Q61 : int 0 0 1 0 1 1 1 1 1 0 ...
## $ Q62 : int 1 0 1 1 1 1 0 0 0 0 ...
## $ Q63 : int 1 0 1 1 1 1 1 1 1 0 ...
## $ Q64 : int 0 0 0 0 1 0 0 0 0 0 ...
## $ Q65 : int 0 0 0 0 1 1 1 0 1 0 ...
## $ Q66 : int 0 0 0 1 0 0 0 0 0 0 ...
## $ Q67 : int 0 0 0 0 1 1 0 0 0 0 ...
## $ Q68 : int 0 1 1 0 0 0 1 0 0 0 ...
## $ Q69 : int 0 0 1 0 0 0 1 0 0 0 ...
## $ Q70 : int 0 0 0 0 1 0 1 1 0 1 ...
## $ Q71 : int 0 0 1 0 0 1 1 0 0 1 ...
## $ Q72 : int 0 0 0 0 1 0 0 0 0 0 ...
## $ Q73 : int 0 1 0 0 0 0 0 1 0 0 ...
## $ Q74 : int 0 1 1 1 0 1 1 1 0 1 ...
## $ Q75 : int 0 0 1 0 0 1 1 1 0 1 ...## Q1 Q2 Q3 Q4 Q5 Q6 Q7 Q8 Q9 Q10 Q11 Q12 Q13 Q14 Q15 Q16 Q17 Q18 Q19 Q20
## 1 0 1 0 1 1 0 1 0 1 0 0 1 0 1 0 1 0 0 0 1
## 2 0 0 0 1 0 0 0 0 1 1 1 0 0 1 0 1 0 1 0 0
## 3 1 1 1 1 1 1 1 0 0 1 0 1 1 1 0 1 0 1 0 0
## 4 0 0 0 0 0 0 0 0 1 0 1 0 1 0 1 1 1 0 0 0
## 5 0 0 1 1 1 0 1 0 0 1 1 1 1 1 0 1 0 0 0 0
## 6 1 0 0 1 1 0 1 0 1 1 1 1 1 1 1 1 0 0 0 0
## 7 1 1 1 1 1 0 1 1 1 1 1 1 1 1 1 1 0 1 0 0
## 8 0 1 0 1 1 1 1 1 1 1 1 1 1 1 1 1 0 0 0 1
## 9 1 1 0 1 1 1 0 0 1 1 1 0 1 1 1 1 0 0 0 0
## 10 0 1 0 0 1 1 0 0 1 0 1 1 0 1 1 1 1 0 0 0
## 11 0 1 1 0 1 0 0 0 1 1 1 0 1 1 0 1 0 0 0 0
## 12 0 1 0 1 1 0 0 0 1 1 1 1 1 1 1 1 0 0 0 0
## 13 0 0 0 1 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 14 1 1 0 1 1 1 1 0 1 1 1 1 1 1 1 1 0 0 0 0
## 15 0 0 0 1 1 0 1 0 1 1 1 1 1 1 1 1 0 0 0 0
## 16 1 1 0 1 0 1 1 1 0 1 1 0 1 0 1 1 0 0 0 0
## 17 0 0 0 0 1 1 1 0 0 1 1 0 1 1 1 1 0 1 0 0
## 18 1 1 0 1 1 0 1 0 1 1 1 1 1 1 1 1 0 0 0 1
## 19 0 1 0 1 1 1 1 1 0 1 1 0 1 1 1 1 0 0 0 0
## 20 0 0 0 0 1 1 0 1 1 1 0 0 0 0 1 0 0 0 0 0
## 21 0 0 0 1 1 1 0 0 0 1 1 0 1 0 1 1 0 0 0 0
## 22 0 0 0 1 1 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0
## 23 0 1 0 1 1 0 1 0 1 1 1 1 1 1 1 1 0 0 1 1
## 24 0 0 1 0 1 1 0 1 0 0 1 0 1 0 1 1 0 0 0 1
## 25 1 1 0 0 1 0 0 0 1 1 1 1 1 1 1 1 0 0 0 0
## 26 1 1 1 1 1 0 0 0 1 1 1 1 1 1 1 1 0 0 0 0
## 27 0 0 1 1 1 0 0 0 1 0 1 0 1 1 1 0 0 0 0 0
## 28 0 0 0 1 1 0 1 0 1 1 1 1 1 1 1 1 1 0 0 0
## 29 0 1 0 0 1 1 0 0 1 1 1 1 1 1 1 1 0 0 0 0
## 30 0 1 0 1 1 0 1 0 0 1 1 1 1 1 0 1 0 0 0 0
## 31 1 1 0 1 1 1 1 1 1 0 1 1 1 1 1 1 1 1 1 1
## 32 0 0 1 1 1 0 0 0 1 1 1 1 1 1 0 1 0 0 0 0
## 33 0 0 0 1 1 0 1 0 0 1 1 0 1 1 0 1 1 0 0 1
## 34 0 1 1 0 1 1 0 0 0 0 1 0 0 0 1 1 0 0 0 0
## 35 1 1 0 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 0 1
## 36 1 1 0 1 1 0 1 0 1 1 1 1 1 1 0 1 1 0 0 1
## 37 1 1 0 1 1 0 0 0 0 1 1 0 0 1 1 1 0 0 0 0
## 38 1 1 0 0 1 1 1 0 0 0 1 0 1 1 1 1 0 0 0 0
## 39 0 1 1 0 1 0 0 0 1 0 1 1 0 1 1 1 1 0 0 0
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## 41 0 0 0 0 1 1 0 0 1 1 1 1 1 1 0 1 1 0 1 0
## 42 0 0 0 1 1 0 1 0 1 1 1 1 1 1 1 1 0 1 0 0
## 43 1 1 0 0 1 0 1 1 1 1 1 1 1 1 1 1 0 0 0 0
## 44 1 1 1 1 1 0 0 0 1 0 1 0 0 1 1 1 0 0 0 0
## 45 0 1 0 1 1 1 1 0 1 1 1 1 1 1 1 1 0 0 0 0
## 46 1 1 0 1 1 1 1 1 1 1 1 1 1 1 0 1 1 1 0 1
## 47 1 1 0 1 1 0 1 0 1 1 1 1 1 1 1 1 1 1 0 1
## 48 1 1 0 1 1 0 1 0 1 1 1 1 1 1 1 1 0 0 0 1
## 49 1 0 0 1 1 0 1 0 1 1 1 1 1 1 1 1 0 1 1 1
## 50 1 1 0 1 1 1 0 0 1 1 1 0 1 1 1 1 1 0 0 0
## 51 0 0 0 1 1 1 1 0 1 1 1 1 1 1 1 1 1 1 0 1
## 52 0 1 0 1 1 0 1 1 1 1 1 1 1 1 1 1 0 0 0 0
## 53 1 1 0 1 0 0 1 0 1 1 1 1 1 1 1 1 0 1 0 0
## 54 0 1 0 1 1 0 1 1 1 1 1 1 1 1 1 1 0 0 0 0
## 55 0 0 0 0 1 1 1 0 1 1 1 1 1 0 0 1 0 0 0 0
## 56 1 1 0 1 1 1 1 0 0 1 1 0 1 1 1 1 0 0 0 0
## 57 1 1 0 1 1 1 0 0 1 1 1 1 1 1 1 1 0 1 1 0
## 58 0 1 0 1 1 1 1 0 1 1 1 1 1 1 1 1 0 1 0 0
## 59 0 1 0 1 1 1 1 0 0 1 1 0 1 1 1 1 0 0 0 0
## 60 0 0 0 1 1 0 1 0 1 1 1 1 1 1 1 1 0 0 0 0
## 61 1 1 0 1 1 1 1 1 1 1 1 1 1 1 1 1 0 0 1 0
## 62 1 1 0 1 1 1 1 1 1 1 1 1 1 1 1 1 0 0 0 0
## 63 0 0 1 0 1 0 1 0 1 0 1 1 1 1 1 1 0 0 0 1
## 64 0 1 0 1 0 1 0 0 1 1 1 1 1 1 0 1 0 0 0 0
## 65 1 0 0 1 1 1 1 0 1 1 1 1 1 1 1 1 0 1 0 1
## 66 1 1 0 1 1 1 0 1 1 1 1 1 1 0 1 1 0 1 0 0
## 67 0 1 0 1 1 0 0 0 0 0 1 0 0 0 0 1 0 1 0 0
## 68 1 1 0 0 1 1 1 1 0 1 1 1 1 1 0 1 1 0 0 0
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## 71 0 0 0 0 1 0 0 0 1 1 0 0 0 0 1 0 0 0 0 0
## 72 0 1 1 1 1 1 0 0 1 1 1 1 1 0 0 0 0 0 0 0
## 73 0 1 0 1 1 1 0 0 0 1 1 1 1 1 1 1 0 1 0 0
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## 77 0 0 0 1 1 1 1 0 1 1 1 1 1 1 1 1 1 1 0 0
## 78 1 1 0 1 1 0 1 0 1 1 1 1 1 1 1 1 1 0 0 1
## 79 0 1 0 1 1 1 1 1 1 0 1 0 1 1 1 0 1 1 0 0
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## 85 1 1 1 1 1 1 1 0 1 1 1 1 1 1 1 1 0 0 0 1
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## 153 0 0 1 0 1 1 0 0 1 1 1 0 1 1 0 1 0 0 0 0
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## 155 1 1 0 1 1 1 1 0 1 1 1 1 1 1 1 1 0 0 0 0
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## Q21 Q22 Q23 Q24 Q25 Q26 Q27 Q28 Q29 Q30 Q31 Q32 Q33 Q34 Q35 Q36 Q37
## 1 0 0 0 0 0 0 0 1 0 1 0 0 1 0 1 0 1
## 2 0 1 0 1 1 0 0 0 0 1 0 0 1 0 0 0 0
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## 88 1 0 1 0 0 0 1 1 1 0 0 0 0 0 0 0 0
## 89 0 0 1 1 0 0 0 0 0 0 0 1 0 0 0 0 0
## 90 1 0 1 1 0 0 0 1 0 0 1 1 0 0 0 1 1
## 91 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 92 0 0 0 1 0 0 1 0 1 0 0 0 0 1 0 0 0
## 93 1 0 1 0 0 0 0 1 1 0 1 0 0 0 0 0 0
## 94 0 0 0 1 0 0 0 0 0 0 1 0 0 0 0 0 0
## 95 0 0 1 0 0 0 1 1 1 0 0 0 0 0 0 0 0
## 96 0 0 1 1 0 0 0 1 0 0 0 0 0 0 0 1 0
## 97 1 0 1 1 1 0 1 0 1 1 0 0 0 0 0 0 0
## 98 1 0 1 0 0 1 1 1 1 1 0 0 0 1 0 0 0
## 99 0 1 0 0 0 0 0 1 0 0 0 0 0 0 0 0 1
## 100 0 0 1 1 0 0 1 0 1 0 0 0 0 0 0 1 0
## 101 0 1 1 0 0 0 1 1 1 0 1 0 0 1 0 0 0
## 102 1 1 1 1 0 0 1 1 1 1 0 0 0 0 0 1 1
## 103 0 1 0 1 0 0 1 0 1 0 1 0 0 1 0 0 0
## 104 1 0 1 0 0 0 0 1 1 0 1 0 0 0 0 0 0
## 105 1 0 0 0 0 0 0 1 0 1 0 0 1 0 0 0 1
## 106 0 0 0 0 0 0 0 1 1 0 1 0 0 0 0 0 0
## 107 0 0 0 0 0 0 0 0 1 1 0 0 1 0 0 1 0
## 108 1 0 0 0 0 0 1 1 1 0 0 0 0 1 0 0 0
## 109 0 1 0 1 0 1 1 0 1 1 0 0 1 0 0 0 0
## 110 1 0 0 1 0 0 1 0 1 1 1 0 0 0 0 1 0
## 111 1 0 1 0 0 1 1 1 1 1 1 0 0 1 0 0 0
## 112 1 0 1 1 0 0 0 0 1 0 0 0 0 0 0 0 1
## 113 1 0 0 0 0 0 1 0 1 0 0 0 0 1 0 0 1
## 114 1 0 1 1 0 0 0 1 1 1 1 0 0 1 0 0 0
## 115 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 NA
## 116 1 0 0 0 0 0 0 0 1 0 0 1 0 0 0 0 1
## 117 1 0 1 1 0 0 1 0 1 0 0 0 0 0 0 0 0
## 118 1 0 1 0 0 0 0 0 1 1 1 0 0 1 0 1 1
## 119 1 0 0 1 0 0 0 1 1 1 0 0 0 0 0 0 0
## 120 1 0 0 1 0 0 1 1 1 0 1 0 0 0 1 0 0
## 121 1 1 0 1 0 0 1 0 1 0 0 0 0 0 0 0 0
## 122 1 0 1 0 0 0 1 1 1 0 0 0 0 0 0 0 0
## 123 1 0 1 0 0 0 1 0 1 0 0 0 0 0 0 1 1
## 124 1 0 0 0 0 0 1 1 1 0 0 0 0 0 0 0 0
## 125 1 0 1 0 0 1 1 0 0 1 1 0 0 0 0 0 0
## 126 1 0 1 1 0 0 1 1 1 0 0 0 0 0 1 0 0
## 127 0 0 0 1 0 0 1 0 1 0 1 0 0 0 0 1 0
## 128 1 0 0 1 0 0 0 0 1 0 1 0 0 0 0 0 0
## 129 1 0 0 0 0 0 1 0 1 0 1 0 0 1 0 0 0
## 130 1 1 1 1 1 1 1 0 1 1 0 0 1 0 0 0 0
## 131 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## 132 1 0 1 0 0 0 0 1 1 0 0 0 0 0 0 1 1
## 133 1 0 0 0 0 0 1 0 1 1 1 0 0 0 0 0 0
## 134 0 1 1 1 0 0 0 1 1 0 0 0 0 0 0 0 0
## 135 0 0 1 1 0 1 0 1 1 0 1 0 0 0 0 0 0
## 136 1 0 1 0 0 1 0 0 0 1 1 0 0 0 0 0 0
## 137 1 1 0 1 0 0 0 1 1 0 0 0 0 1 1 0 0
## 138 1 0 1 1 0 0 0 0 1 0 0 0 0 0 0 0 0
## 139 1 1 1 1 1 0 1 0 1 0 1 0 0 1 0 0 0
## 140 1 0 0 1 0 0 0 0 1 1 1 0 0 0 0 0 0
## 141 1 0 1 0 0 0 1 1 1 0 0 0 0 0 0 0 0
## 142 1 0 0 1 0 0 1 1 1 0 0 0 0 0 0 0 1
## 143 1 0 1 1 1 0 1 0 1 0 0 0 1 0 0 0 0
## 144 0 0 0 1 0 0 0 0 1 0 0 0 0 0 0 0 1
## 145 0 1 0 0 0 0 0 1 1 0 0 0 0 0 0 0 0
## 146 1 0 1 0 0 0 1 1 1 0 0 0 0 0 0 0 0
## 147 0 0 1 0 0 0 1 0 1 0 1 0 0 0 1 0 0
## 148 1 0 1 0 0 0 1 0 1 0 1 0 0 0 0 0 0
## 149 1 0 0 1 0 0 0 0 1 0 0 0 0 0 0 0 0
## 150 1 0 0 1 0 0 1 0 0 1 0 0 0 0 0 0 1
## 151 0 0 1 0 0 0 0 1 0 0 0 1 0 0 0 0 1
## 152 1 0 0 1 0 0 0 0 1 0 1 0 0 0 0 0 0
## 153 0 0 1 0 0 0 0 1 1 0 0 0 1 0 0 0 1
## 154 1 0 1 0 0 0 0 1 1 0 1 0 0 1 0 0 1
## 155 1 0 1 0 0 0 1 1 1 0 1 0 0 0 0 0 0
## 156 0 0 1 0 0 0 0 1 1 1 0 0 0 0 0 0 0
## 157 1 0 0 1 0 0 0 1 1 0 0 0 0 0 0 0 0
## 158 0 0 0 0 0 0 1 1 1 0 0 0 1 0 0 0 0
## 159 1 0 1 0 1 0 0 0 1 0 0 0 0 1 1 0 1
## 160 1 0 1 0 0 0 0 1 1 1 0 0 0 0 1 0 0
## 161 0 0 0 1 0 1 0 0 0 1 1 0 0 0 0 0 1
## 162 1 0 1 1 1 0 1 1 1 1 0 0 0 0 0 0 0
## 163 0 0 0 1 0 0 0 0 1 0 0 0 0 0 0 0 0
## 164 1 0 0 0 1 0 1 0 1 1 1 0 1 0 0 0 0
## 165 0 1 0 0 0 0 1 0 1 0 1 0 1 0 0 0 1
## 166 1 0 0 1 0 0 0 0 0 0 1 0 0 0 0 0 0
## 167 1 0 1 0 0 0 0 0 0 1 1 0 1 0 1 0 0
## 168 0 0 0 0 0 1 0 0 1 0 1 0 0 0 0 0 0
## 169 1 1 1 1 1 0 1 0 1 1 1 0 0 1 0 0 0
## 170 1 0 0 0 1 0 1 0 0 1 0 0 0 1 1 1 0
## 171 0 0 1 0 0 1 0 0 0 1 0 0 0 0 0 0 0
## 172 0 0 0 0 0 0 0 1 0 0 0 0 0 1 0 0 0
## 173 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0
## 174 1 0 0 0 0 0 1 1 1 0 0 0 0 0 0 0 0
## 175 0 0 1 1 0 0 0 0 0 0 0 1 0 0 0 0 0
## 176 0 0 0 1 0 1 0 1 0 1 0 0 0 0 1 1 1
## Q72 Q73 Q74 Q75
## 1 0 0 0 0
## 2 0 1 1 0
## 3 0 0 1 1
## 4 0 0 1 0
## 5 1 0 0 0
## 6 0 0 1 1
## 7 0 0 1 1
## 8 0 1 1 1
## 9 0 0 0 0
## 10 0 0 1 1
## 11 0 1 1 0
## 12 0 0 0 1
## 13 0 0 0 0
## 14 0 0 1 1
## 15 0 0 0 1
## 16 0 0 0 1
## 17 0 0 0 1
## 18 0 1 1 1
## 19 0 0 1 0
## 20 0 1 0 0
## 21 0 1 0 0
## 22 0 0 1 0
## 23 0 0 0 1
## 24 0 0 0 0
## 25 0 1 0 0
## 26 0 0 1 1
## 27 0 0 0 1
## 28 0 0 0 1
## 29 0 0 0 0
## 30 0 0 0 1
## 31 0 0 0 1
## 32 0 0 0 0
## 33 0 0 1 1
## 34 0 0 0 1
## 35 0 1 1 1
## 36 0 0 0 1
## 37 0 0 0 0
## 38 0 0 0 0
## 39 0 0 1 0
## 40 0 0 1 1
## 41 0 0 1 1
## 42 0 0 0 1
## 43 0 0 0 1
## 44 0 0 0 0
## 45 0 1 1 1
## 46 0 1 1 1
## 47 0 0 1 1
## 48 0 0 1 1
## 49 0 0 0 1
## 50 0 0 1 1
## 51 0 1 0 1
## 52 0 0 0 1
## 53 0 0 1 1
## 54 0 0 0 1
## 55 0 0 1 1
## 56 0 0 1 1
## 57 0 0 1 1
## 58 1 0 0 1
## 59 0 0 1 1
## 60 0 0 1 1
## 61 0 0 1 0
## 62 0 0 1 1
## 63 0 0 1 1
## 64 1 1 0 1
## 65 0 0 1 1
## 66 0 0 1 1
## 67 0 0 1 1
## 68 1 0 1 1
## 69 0 0 1 1
## 70 0 0 1 1
## 71 0 1 0 0
## 72 0 0 0 1
## 73 0 0 0 1
## 74 0 1 0 0
## 75 0 0 0 1
## 76 0 1 0 0
## 77 0 0 0 1
## 78 1 0 1 1
## 79 0 0 0 1
## 80 0 0 0 1
## 81 0 0 1 0
## 82 0 0 1 0
## 83 1 0 1 0
## 84 0 0 1 0
## 85 0 0 0 1
## 86 0 0 1 1
## 87 0 0 0 1
## 88 0 0 0 1
## 89 0 0 0 1
## 90 0 0 1 0
## 91 0 0 0 1
## 92 0 0 0 1
## 93 1 1 0 0
## 94 0 0 0 0
## 95 1 0 0 1
## 96 0 1 1 0
## 97 0 0 0 1
## 98 0 0 1 1
## 99 1 0 0 0
## 100 0 0 1 1
## 101 0 0 0 1
## 102 0 0 0 1
## 103 0 0 0 1
## 104 0 0 0 1
## 105 1 0 0 0
## 106 0 0 0 1
## 107 0 0 0 1
## 108 0 1 0 1
## 109 1 0 1 1
## 110 0 0 1 1
## 111 0 0 0 1
## 112 0 0 0 1
## 113 1 0 1 1
## 114 0 0 0 0
## 115 0 0 0 0
## 116 0 1 0 1
## 117 0 0 1 1
## 118 0 0 1 1
## 119 0 0 0 1
## 120 0 1 0 1
## 121 0 0 1 1
## 122 0 0 1 1
## 123 0 0 0 1
## 124 0 1 0 1
## 125 0 0 1 1
## 126 0 0 0 1
## 127 1 0 1 0
## 128 1 0 0 1
## 129 0 0 1 1
## 130 0 0 1 1
## 131 0 0 0 0
## 132 0 0 1 1
## 133 0 0 0 1
## 134 0 0 1 0
## 135 1 0 0 1
## 136 0 0 0 0
## 137 0 0 1 1
## 138 0 0 0 1
## 139 0 0 1 1
## 140 0 0 0 1
## 141 0 0 0 1
## 142 0 0 0 1
## 143 0 0 1 1
## 144 0 0 0 0
## 145 0 0 0 1
## 146 0 0 1 1
## 147 0 0 0 1
## 148 0 0 1 0
## 149 0 0 0 0
## 150 0 0 0 1
## 151 0 0 0 1
## 152 1 0 0 0
## 153 0 0 0 0
## 154 0 1 0 1
## 155 0 1 1 1
## 156 1 0 0 0
## 157 0 0 0 0
## 158 0 0 0 1
## 159 1 0 1 1
## 160 0 0 0 1
## 161 0 0 0 1
## 162 1 0 1 0
## 163 0 1 0 1
## 164 0 0 1 1
## 165 1 0 0 1
## 166 0 1 0 0
## 167 1 0 0 0
## 168 0 0 0 0
## 169 0 0 1 1
## 170 0 0 1 1
## 171 0 0 0 1
## 172 0 0 0 0
## 173 0 0 1 1
## 174 0 0 1 1
## 175 0 1 0 0
## 176 0 1 1 0## Sample.SD Item.total Item.Tot.woi Difficulty Discrimination
## Q1 0.4924387 0.448667834 0.395345411 0.40571429 0.53448276
## Q2 0.4962917 0.358041765 0.299900438 0.57142857 0.37931034
## Q3 0.4283086 -0.030279408 -0.085677671 0.24000000 -0.05172414
## Q4 0.4474338 0.391146703 0.340227239 0.72571429 0.39655172
## Q5 0.3509312 0.345471942 0.304368484 0.85714286 0.24137931
## Q6 0.4984706 0.108189074 0.043608499 0.44571429 0.10344828
## Q7 0.4984706 0.429844533 0.374829742 0.55428571 0.55172414
## Q8 0.3922902 0.145688287 0.095280983 0.18857143 0.10344828
## Q9 0.4383129 0.353345382 0.302012538 0.74285714 0.37931034
## Q10 0.3509312 0.305024963 0.262813552 0.85714286 0.22413793
## Q11 0.2807450 0.316049045 0.282644140 0.91428571 0.15517241
## Q12 0.4655629 0.505184822 0.458026315 0.68571429 0.51724138
## Q13 0.3566861 0.412473401 0.372900967 0.85142857 0.32758621
## Q14 0.4173574 0.446429377 0.401415499 0.77714286 0.41379310
## Q15 0.4414486 0.257169801 0.202458748 0.73714286 0.24137931
## Q16 0.3258940 0.462318155 0.428030841 0.88000000 0.29310345
## Q17 0.4720775 0.134855345 0.073965219 0.33142857 0.12068966
## Q18 0.4444882 0.237624362 0.182055216 0.26857143 0.22413793
## Q19 0.2434023 0.284930052 0.255475226 0.06285714 0.13793103
## Q20 0.4444882 0.372081603 0.320727460 0.26857143 0.43103448
## Q21 0.4211174 0.005220600 -0.049459740 0.22857143 -0.10344828
## Q22 0.4978113 0.394920429 0.338241856 0.56000000 0.50000000
## Q23 0.5010334 0.345502587 0.286269394 0.52000000 0.37931034
## Q24 0.4778853 0.207502458 0.147003194 0.65142857 0.24137931
## Q25 0.4874787 0.394840567 0.339375821 0.61714286 0.46551724
## Q26 0.4990632 0.358457046 0.299998187 0.54857143 0.39655172
## Q27 0.4699859 0.117834391 0.057046832 0.67428571 0.17241379
## Q28 0.3388380 0.242562005 0.200473973 0.13142857 0.18965517
## Q29 0.2534491 -0.002408583 -0.035331990 0.06857143 0.00000000
## Q30 0.4283086 0.128443295 0.073179303 0.24000000 0.06896552
## Q31 0.3449852 -0.020862846 -0.065579657 0.13714286 -0.03448276
## Q32 0.4945018 0.402527306 0.346600546 0.41714286 0.46551724
## Q33 0.4094933 0.021704530 -0.031516500 0.21142857 0.06896552
## Q34 0.3876585 0.025349674 -0.025041532 0.18285714 -0.01724138
## Q35 0.3046439 0.157615638 0.118664941 0.10285714 0.10344828
## Q36 0.2215040 -0.033264084 -0.061971997 0.05142857 -0.01724138
## Q37 0.2534491 0.356116634 0.326849295 0.93142857 0.13793103
## Q38 0.3876585 0.115923555 0.065834220 0.18285714 0.12068966
## Q39 0.4383129 -0.072120247 -0.128362030 0.25714286 -0.08620690
## Q40 0.4134837 -0.180230217 -0.231416382 0.21714286 -0.17241379
## Q41 0.5013610 0.143011747 0.078407068 0.49142857 0.12068966
## Q42 0.3388380 0.050747403 0.006710983 0.13142857 0.06896552
## Q43 0.4990632 0.334506305 0.275078321 0.54857143 0.41379310
## Q44 0.4247669 0.317087320 0.266161415 0.23428571 0.27586207
## Q45 0.4984706 0.288033176 0.227030107 0.44571429 0.39655172
## Q46 0.4414486 0.439936937 0.391914238 0.73714286 0.43103448
## Q47 0.4655629 0.421743823 0.370100918 0.68571429 0.37931034
## Q48 0.4011478 0.377674823 0.331668002 0.80000000 0.34482759
## Q49 0.4945018 0.257497308 0.196079190 0.41714286 0.24137931
## Q50 0.4978113 0.445943741 0.391865976 0.56000000 0.51724138
## Q51 0.4474338 0.499674003 0.454117118 0.72571429 0.55172414
## Q52 0.5012300 0.509180298 0.458491900 0.48571429 0.53448276
## Q53 0.4699859 0.249347853 0.190823312 0.32571429 0.27586207
## Q54 0.3566861 -0.259579144 -0.302010298 0.14857143 -0.24137931
## Q55 0.4655629 0.493952380 0.446134772 0.68571429 0.51724138
## Q56 0.3728909 0.180525602 0.133066110 0.16571429 0.08620690
## Q57 0.4990632 0.391500514 0.334513073 0.45142857 0.43103448
## Q58 0.5014265 -0.012404197 -0.077357167 0.50285714 -0.08620690
## Q59 0.2720717 0.285235193 0.252267530 0.08000000 0.17241379
## Q60 0.3119934 0.032619494 -0.007939926 0.10857143 -0.03448276
## Q61 0.4995893 0.500769591 0.449720191 0.45714286 0.62068966
## Q62 0.4978113 0.001260576 -0.063321707 0.44000000 -0.01724138
## Q63 0.4444882 0.543908353 0.501275341 0.73142857 0.60344828
## Q64 0.4530502 0.264539075 0.208555626 0.28571429 0.20689655
## Q65 0.4900990 0.189091678 0.126659813 0.39428571 0.22413793
## Q66 0.2629878 -0.097913421 -0.131582405 0.07428571 -0.08620690
## Q67 0.3566861 0.056681582 0.010332683 0.14857143 0.03448276
## Q68 0.4173574 0.249869937 0.198026050 0.22285714 0.24137931
## Q69 0.2890446 0.102290195 0.064921831 0.09142857 0.05172414
## Q70 0.3566861 0.127892606 0.081926359 0.14857143 0.05172414
## Q71 0.4173574 0.061922821 0.007685834 0.22285714 0.08620690
## Q72 0.3258940 -0.058867167 -0.100887984 0.12000000 -0.01724138
## Q73 0.3622589 -0.034209314 -0.081078475 0.15428571 -0.05172414
## Q74 0.4962917 0.326860951 0.267481813 0.42857143 0.37931034
## Q75 0.4583113 0.534442828 0.489822529 0.70285714 0.60344828
## Item.Criterion Item.Reliab Item.Rel.woi Item.Validity
## Q1 NA 0.2203092491 0.194126354 NA
## Q2 NA 0.1771847224 0.148412228 NA
## Q3 NA -0.0129318243 -0.036591488 NA
## Q4 NA 0.1745115211 0.151793618 NA
## Q5 NA 0.1208899968 0.106506783 NA
## Q6 NA 0.0537747651 0.021675357 NA
## Q7 NA 0.2136517859 0.186306996 NA
## Q8 NA 0.0569885661 0.037270852 NA
## Q9 NA 0.1544327142 0.131997242 NA
## Q10 NA 0.1067365024 0.091965586 NA
## Q11 NA 0.0884753022 0.079123877 NA
## Q12 NA 0.2345223371 0.212629907 NA
## Q13 NA 0.1467025651 0.132628015 NA
## Q14 NA 0.1857874930 0.167054372 NA
## Q15 NA 0.1132024146 0.089119403 NA
## Q16 NA 0.1502356178 0.139093560 NA
## Q17 NA 0.0634800184 0.034817407 NA
## Q18 NA 0.1053190247 0.080689865 NA
## Q19 NA 0.0691541862 0.062005328 NA
## Q20 NA 0.1649126851 0.142151685 NA
## Q21 NA 0.0021921954 -0.020768764 NA
## Q22 NA 0.1960333458 0.167898842 NA
## Q23 NA 0.1726130373 0.143020144 NA
## Q24 NA 0.0988786527 0.070049665 NA
## Q25 NA 0.1919256400 0.164965120 NA
## Q26 NA 0.1783808523 0.149289665 NA
## Q27 NA 0.0552220397 0.026734491 NA
## Q28 NA 0.0819540531 0.067733834 NA
## Q29 NA -0.0006087067 -0.008929240 NA
## Q30 NA 0.0548559644 0.031253646 NA
## Q31 NA -0.0071767794 -0.022559277 NA
## Q32 NA 0.1984809426 0.170904190 NA
## Q33 NA 0.0088624286 -0.012868868 NA
## Q34 NA 0.0097989004 -0.009679788 NA
## Q35 NA 0.0478792494 0.036047111 NA
## Q36 NA -0.0073470470 -0.013687771 NA
## Q37 NA 0.0899991973 0.082602640 NA
## Q38 NA 0.0448101759 0.025448175 NA
## Q39 NA -0.0315207897 -0.056101757 NA
## Q40 NA -0.0743090378 -0.095413128 NA
## Q41 NA 0.0714953657 0.039197773 NA
## Q42 NA 0.0171459474 0.002267430 NA
## Q43 NA 0.1664621202 0.136888662 NA
## Q44 NA 0.1343028271 0.112733081 NA
## Q45 NA 0.1431652557 0.112844026 NA
## Q46 NA 0.1936538561 0.172514961 NA
## Q47 NA 0.1957864578 0.171812233 NA
## Q48 NA 0.1510699291 0.132667201 NA
## Q49 NA 0.1269685501 0.096684081 NA
## Q50 NA 0.2213606515 0.194517155 NA
## Q51 NA 0.2229313701 0.202606001 NA
## Q52 NA 0.2544862133 0.229152361 NA
## Q53 NA 0.1168546546 0.089427649 NA
## Q54 NA -0.0923233500 -0.107414648 NA
## Q55 NA 0.2293078918 0.207109487 NA
## Q56 NA 0.0671237450 0.049477169 NA
## Q57 NA 0.1948244459 0.166465488 NA
## Q58 NA -0.0062019974 -0.038677952 NA
## Q59 NA 0.0773823680 0.068438465 NA
## Q60 NA 0.0101479490 -0.002470117 NA
## Q61 NA 0.2494633191 0.224032556 NA
## Q62 NA 0.0006257334 -0.031432069 NA
## Q63 NA 0.2410691263 0.222173474 NA
## Q64 NA 0.1195065725 0.094215828 NA
## Q65 NA 0.0924084838 0.061898236 NA
## Q66 NA -0.0256763542 -0.034505550 NA
## Q67 NA 0.0201596840 0.003674979 NA
## Q68 NA 0.1039866807 0.082411161 NA
## Q69 NA 0.0294818351 0.018711615 NA
## Q70 NA 0.0454869896 0.029138381 NA
## Q71 NA 0.0257700014 0.003198561 NA
## Q72 NA -0.0191295650 -0.032784714 NA
## Q73 NA -0.0123571712 -0.029287363 NA
## Q74 NA 0.1617542211 0.132369168 NA
## Q75 NA 0.2442403604 0.223848885 NA## [1] 0.7833737## LCL ALPHA UCL
## 1 0.7352741 0.7833737 0.8265934Analisa Rasch Model
## Loading required package: msm## Loading required package: polycor## Loading required package: mvtnorm## Loading required package: sfsmisc##
## Call:
## rasch(data = ebAnalyze, constraint = cbind(ncol(ebAnalyze) +
## 1, 1))
##
## Coefficients:
## Dffclt.Q1 Dffclt.Q2 Dffclt.Q3 Dffclt.Q4 Dffclt.Q5 Dffclt.Q6
## 0.496 -0.232 1.327 -1.003 -1.880 0.318
## Dffclt.Q7 Dffclt.Q8 Dffclt.Q9 Dffclt.Q10 Dffclt.Q11 Dffclt.Q12
## -0.156 1.652 -1.098 -1.880 -2.411 -0.765
## Dffclt.Q13 Dffclt.Q14 Dffclt.Q15 Dffclt.Q16 Dffclt.Q17 Dffclt.Q18
## -1.785 -1.266 -1.034 -2.036 0.843 1.166
## Dffclt.Q19 Dffclt.Q20 Dffclt.Q21 Dffclt.Q22 Dffclt.Q23 Dffclt.Q24
## 2.943 1.166 1.395 -0.181 -0.006 -0.599
## Dffclt.Q25 Dffclt.Q26 Dffclt.Q27 Dffclt.Q28 Dffclt.Q29 Dffclt.Q30
## -0.438 -0.131 -0.708 2.102 2.847 1.327
## Dffclt.Q31 Dffclt.Q32 Dffclt.Q33 Dffclt.Q34 Dffclt.Q35 Dffclt.Q36
## 2.052 0.445 1.501 1.693 2.391 3.160
## Dffclt.Q37 Dffclt.Q38 Dffclt.Q39 Dffclt.Q40 Dffclt.Q41 Dffclt.Q42
## -2.736 1.693 1.229 1.465 0.094 2.103
## Dffclt.Q43 Dffclt.Q44 Dffclt.Q45 Dffclt.Q46 Dffclt.Q47 Dffclt.Q48
## -0.131 1.360 0.319 -1.034 -0.765 -1.411
## Dffclt.Q49 Dffclt.Q50 Dffclt.Q51 Dffclt.Q52 Dffclt.Q53 Dffclt.Q54
## 0.446 -0.206 -0.972 0.143 0.871 1.907
## Dffclt.Q55 Dffclt.Q56 Dffclt.Q57 Dffclt.Q58 Dffclt.Q59 Dffclt.Q60
## -0.765 1.818 0.269 0.069 2.676 2.328
## Dffclt.Q61 Dffclt.Q62 Dffclt.Q63 Dffclt.Q64 Dffclt.Q65 Dffclt.Q66
## 0.269 0.344 -1.003 1.074 0.549 2.759
## Dffclt.Q67 Dffclt.Q68 Dffclt.Q69 Dffclt.Q70 Dffclt.Q71 Dffclt.Q72
## 1.954 1.430 2.526 1.954 1.428 2.211
## Dffclt.Q73 Dffclt.Q74 Dffclt.Q75 Dscrmn
## 1.907 0.394 -0.852 1.000
##
## Log.Lik: -6885.803
##
## Call:
## rasch(data = ebAnalyze, constraint = cbind(ncol(ebAnalyze) +
## 1, 1))
##
## Total Information = 74.98
## Information in (-10, 10) = 74.98 (100%)
## Based on all the items
##
## Item-Fit Statistics and P-values
##
## Call:
## rasch(data = ebAnalyze, constraint = cbind(ncol(ebAnalyze) +
## 1, 1))
##
## Alternative: Items do not fit the model
## Ability Categories: 10
##
## X^2 Pr(>X^2)
## Q1 12.2193 0.2012
## Q2 6.4651 0.6926
## Q3 22.7368 0.0068
## Q4 7.9945 0.5347
## Q5 11.2124 0.2614
## Q6 14.6099 0.1022
## Q7 12.3607 0.1937
## Q8 4.9310 0.8403
## Q9 6.5357 0.6853
## Q10 5.8084 0.7589
## Q11 10.3966 0.3193
## Q12 22.3136 0.0079
## Q13 10.6507 0.3004
## Q14 19.7691 0.0194
## Q15 3.8825 0.919
## Q16 18.8766 0.0263
## Q17 6.5458 0.6843
## Q18 8.9226 0.4445
## Q19 15.3243 0.0824
## Q20 13.2214 0.1528
## Q21 23.3512 0.0055
## Q22 9.5889 0.3848
## Q23 14.6647 0.1006
## Q24 7.1599 0.6205
## Q25 11.3089 0.2551
## Q26 10.6152 0.303
## Q27 10.6275 0.3021
## Q28 8.9729 0.4398
## Q29 12.1401 0.2055
## Q30 11.8256 0.2233
## Q31 15.6453 0.0747
## Q32 15.1867 0.0859
## Q33 20.4889 0.0151
## Q34 13.2128 0.1532
## Q35 9.3192 0.4083
## Q36 12.6244 0.1804
## Q37 26.2441 0.0019
## Q38 5.9907 0.7408
## Q39 27.9750 0.001
## Q40 47.4183 <0.0001
## Q41 12.5713 0.183
## Q42 7.5612 0.5789
## Q43 13.8061 0.1294
## Q44 5.5682 0.7822
## Q45 15.1998 0.0856
## Q46 16.6796 0.054
## Q47 12.0647 0.2097
## Q48 13.8238 0.1287
## Q49 9.3870 0.4023
## Q50 15.0424 0.0898
## Q51 18.3465 0.0314
## Q52 22.0119 0.0088
## Q53 4.0901 0.9054
## Q54 66.4381 <0.0001
## Q55 17.6281 0.0397
## Q56 11.1882 0.263
## Q57 11.8799 0.2202
## Q58 25.9531 0.0021
## Q59 8.0244 0.5317
## Q60 20.6714 0.0142
## Q61 23.7781 0.0047
## Q62 17.4642 0.0419
## Q63 28.0656 0.0009
## Q64 11.6375 0.2345
## Q65 9.2096 0.4182
## Q66 25.7763 0.0022
## Q67 14.1481 0.1172
## Q68 12.4251 0.1904
## Q69 4.9261 0.8407
## Q70 15.9984 0.0669
## Q71 8.3232 0.5019
## Q72 15.3617 0.0815
## Q73 21.5647 0.0104
## Q74 11.9799 0.2144
## Q75 24.3874 0.0037## [1] -0.40472559 -0.17858266 -0.25313593 -0.97335580 -0.63995709
## [6] -1.43855499 -0.63995709 -1.06132262 -0.25313593 -0.17858266
## [11] 0.61000335 -0.63995710 -0.63995710 0.18498498 -0.03154050
## [16] 0.18498498 -0.88742512 -0.10474458 -0.97335581 -0.48194588
## [21] -0.48194588 -1.86950927 -0.17858266 -0.10474458 0.46895319
## [26] -0.17858266 0.11325422 0.32743719 -0.10474458 -0.17858266
## [31] 0.25635831 0.04110194 0.25635831 0.53950770 -0.10474381
## [36] 0.39828240 0.46895319 -1.54079460 -0.88742512 -0.63995710
## [41] -0.72089467 0.32743719 -0.17858266 0.11325422 0.53950770
## [46] 0.75104632 0.39828240 -0.40472559 0.39828240 -0.80333073
## [51] 0.04110194 -0.72089466 -0.48194588 -0.72089466 -0.10474458
## [56] -0.56024967 -0.48194588 0.04110194 -0.32848725 -0.03154049
## [61] 0.32743719 -0.03154049 -1.15155099 -0.72089466 -1.15155099
## [66] -0.03154048 -0.32848725 -0.32848725 -0.03154049 -0.03154050
## [71] -0.10474458 -0.25313593 -0.63995710 -0.10474458 0.18498498
## [76] -0.17858266 0.04110194 -0.56024967 -0.10474458 0.53950770
## [81] 0.32743719 0.32743719 0.46895319 0.32743719 0.04110194
## [86] -0.17858266 0.18498498 0.75104632 -0.56024967 0.11325422
## [91] 0.96360478 0.68049719 -0.32848725 0.04110194 1.32459756
## [96] -1.06132262 -0.48194588 -0.03154050 0.68049719 -0.56024967
## [101] 0.53950770 0.32743719 -0.10474458 0.46895319 -0.48194588
## [106] -0.97335580 0.04110194 -0.03154049 0.39828240 0.75104632
## [111] 0.68049719 -0.03154049 -0.10474458 0.53950770 0.04110194
## [116] -0.10474458 -0.72089466 -0.25313593 0.68049719 -0.17858266
## [121] -0.03154050 0.11325422 -0.03154049 -0.48194588 -0.03154048
## [126] 0.75104632 0.04110194 -0.25313593 0.18498498 -0.63995710
## [131] 0.61000335 0.25635831 0.53950770 0.32743719 -0.03154048
## [136] -0.10474458 0.39828240 0.89254122 0.68049719 0.68049719
## [141] 0.46895319 0.96360478 0.82170823 0.18498498 0.32743719
## [146] 0.11325422 0.39828240 0.46895319 0.75104632 0.32743719
## [151] 0.53950770 0.61000335 0.39828240 0.53950770 0.61000335
## [156] 0.61000335 1.17880118 1.10666986 0.68049719 0.75104632
## [161] 0.96360478 0.75104632 0.82170823 1.17880118 -0.25313593
## [166] 0.46895319 0.82170823 0.46895319 -0.10474458 -0.03154048
## [171] 0.96360478 0.18498498 1.39841227 0.68049719 0.75104632
## [176] 1.47313920## [1] 0.5876815
-sebenernya kalau datanya dibawah dua ratus biasanya paling Rasch sudah cukup -eh tapi, kalau itemnya banyak, belum tahu juga nih, harus di cek
IRT 1PL
##
## Call:
## rasch(data = ebAnalyze)
##
## Model Summary:
## log.Lik AIC BIC
## -6854.993 13861.99 14102.94
##
## Coefficients:
## value std.err z.vals
## Dffclt.Q1 0.7575 0.2995 2.5289
## Dffclt.Q2 -0.5243 0.2954 -1.7749
## Dffclt.Q3 2.2264 0.3653 6.0939
## Dffclt.Q4 -1.8813 0.3458 -5.4406
## Dffclt.Q5 -3.4290 0.4628 -7.4088
## Dffclt.Q6 0.4443 0.2937 1.5127
## Dffclt.Q7 -0.3906 0.2934 -1.3312
## Dffclt.Q8 2.8040 0.4071 6.8875
## Dffclt.Q9 -2.0487 0.3555 -5.7624
## Dffclt.Q10 -3.4289 0.4628 -7.4087
## Dffclt.Q11 -4.3681 0.5643 -7.7401
## Dffclt.Q12 -1.4629 0.3247 -4.5055
## Dffclt.Q13 -3.2592 0.4470 -7.2907
## Dffclt.Q14 -2.3444 0.3745 -6.2603
## Dffclt.Q15 -1.9365 0.3489 -5.5499
## Dffclt.Q16 -3.7047 0.4901 -7.5593
## Dffclt.Q17 1.3701 0.3196 4.2875
## Dffclt.Q18 1.9409 0.3479 5.5791
## Dffclt.Q19 5.1043 0.6635 7.6929
## Dffclt.Q20 1.9409 0.3479 5.5791
## Dffclt.Q21 2.3468 0.3733 6.2857
## Dffclt.Q22 -0.4352 0.2940 -1.4803
## Dffclt.Q23 -0.1265 0.2911 -0.4345
## Dffclt.Q24 -1.1677 0.3127 -3.7341
## Dffclt.Q25 -0.8884 0.3037 -2.9254
## Dffclt.Q26 -0.3461 0.2929 -1.1817
## Dffclt.Q27 -1.3633 0.3204 -4.2552
## Dffclt.Q28 3.6049 0.4792 7.5224
## Dffclt.Q29 4.9340 0.6389 7.7229
## Dffclt.Q30 2.2265 0.3654 6.0940
## Dffclt.Q31 3.5135 0.4701 7.4734
## Dffclt.Q32 0.6674 0.2975 2.2431
## Dffclt.Q33 2.5353 0.3866 6.5575
## Dffclt.Q34 2.8745 0.4128 6.9635
## Dffclt.Q35 4.1194 0.5347 7.7047
## Dffclt.Q36 5.4922 0.7238 7.5885
## Dffclt.Q37 -4.9457 0.6400 -7.7272
## Dffclt.Q38 2.8747 0.4128 6.9637
## Dffclt.Q39 2.0529 0.3545 5.7913
## Dffclt.Q40 2.4713 0.3820 6.4691
## Dffclt.Q41 0.0484 0.2908 0.1664
## Dffclt.Q42 3.6051 0.4792 7.5225
## Dffclt.Q43 -0.3461 0.2929 -1.1817
## Dffclt.Q44 2.2863 0.3693 6.1912
## Dffclt.Q45 0.4452 0.2937 1.5158
## Dffclt.Q46 -1.9363 0.3489 -5.5495
## Dffclt.Q47 -1.4630 0.3247 -4.5057
## Dffclt.Q48 -2.5990 0.3926 -6.6204
## Dffclt.Q49 0.6691 0.2976 2.2484
## Dffclt.Q50 -0.4798 0.2947 -1.6283
## Dffclt.Q51 -1.8272 0.3428 -5.3302
## Dffclt.Q52 0.1364 0.2910 0.4688
## Dffclt.Q53 1.4194 0.3216 4.4128
## Dffclt.Q54 3.2570 0.4458 7.3052
## Dffclt.Q55 -1.4629 0.3247 -4.5055
## Dffclt.Q56 3.0978 0.4316 7.1770
## Dffclt.Q57 0.3570 0.2926 1.2201
## Dffclt.Q58 0.0042 0.2908 0.0145
## Dffclt.Q59 4.6285 0.5973 7.7496
## Dffclt.Q60 4.0075 0.5220 7.6778
## Dffclt.Q61 0.3562 0.2926 1.2172
## Dffclt.Q62 0.4887 0.2944 1.6601
## Dffclt.Q63 -1.8816 0.3458 -5.4410
## Dffclt.Q64 1.7789 0.3389 5.2484
## Dffclt.Q65 0.8494 0.3018 2.8141
## Dffclt.Q66 4.7760 0.6169 7.7413
## Dffclt.Q67 3.3397 0.4535 7.3645
## Dffclt.Q68 2.4085 0.3776 6.3785
## Dffclt.Q69 4.3599 0.5632 7.7410
## Dffclt.Q70 3.3398 0.4535 7.3646
## Dffclt.Q71 2.4051 0.3775 6.3703
## Dffclt.Q72 3.7984 0.4992 7.6090
## Dffclt.Q73 3.2568 0.4458 7.3051
## Dffclt.Q74 0.5785 0.2958 1.9555
## Dffclt.Q75 -1.6152 0.3318 -4.8676
## Dscrmn 0.5559 0.0383 14.5135
##
## Integration:
## method: Gauss-Hermite
## quadrature points: 21
##
## Optimization:
## Convergence: 0
## max(|grad|): 0.11
## quasi-Newton: BFGS
##
## Call:
## rasch(data = ebAnalyze)
##
## Total Information = 40.9
## Information in (-10, 10) = 40.9 (100%)
## Based on all the items##
## Call:
## rasch(data = ebAnalyze)
##
## Total Information = 40.9
## Information in (0, 10) = 23.74 (58.05%)
## Based on all the items
##
## Item-Fit Statistics and P-values
##
## Call:
## rasch(data = ebAnalyze, constraint = cbind(ncol(ebAnalyze) +
## 1, 1))
##
## Alternative: Items do not fit the model
## Ability Categories: 10
##
## X^2 Pr(>X^2)
## Q1 12.2193 0.2012
## Q2 6.4651 0.6926
## Q3 22.7368 0.0068
## Q4 7.9945 0.5347
## Q5 11.2124 0.2614
## Q6 14.6099 0.1022
## Q7 12.3607 0.1937
## Q8 4.9310 0.8403
## Q9 6.5357 0.6853
## Q10 5.8084 0.7589
## Q11 10.3966 0.3193
## Q12 22.3136 0.0079
## Q13 10.6507 0.3004
## Q14 19.7691 0.0194
## Q15 3.8825 0.919
## Q16 18.8766 0.0263
## Q17 6.5458 0.6843
## Q18 8.9226 0.4445
## Q19 15.3243 0.0824
## Q20 13.2214 0.1528
## Q21 23.3512 0.0055
## Q22 9.5889 0.3848
## Q23 14.6647 0.1006
## Q24 7.1599 0.6205
## Q25 11.3089 0.2551
## Q26 10.6152 0.303
## Q27 10.6275 0.3021
## Q28 8.9729 0.4398
## Q29 12.1401 0.2055
## Q30 11.8256 0.2233
## Q31 15.6453 0.0747
## Q32 15.1867 0.0859
## Q33 20.4889 0.0151
## Q34 13.2128 0.1532
## Q35 9.3192 0.4083
## Q36 12.6244 0.1804
## Q37 26.2441 0.0019
## Q38 5.9907 0.7408
## Q39 27.9750 0.001
## Q40 47.4183 <0.0001
## Q41 12.5713 0.183
## Q42 7.5612 0.5789
## Q43 13.8061 0.1294
## Q44 5.5682 0.7822
## Q45 15.1998 0.0856
## Q46 16.6796 0.054
## Q47 12.0647 0.2097
## Q48 13.8238 0.1287
## Q49 9.3870 0.4023
## Q50 15.0424 0.0898
## Q51 18.3465 0.0314
## Q52 22.0119 0.0088
## Q53 4.0901 0.9054
## Q54 66.4381 <0.0001
## Q55 17.6281 0.0397
## Q56 11.1882 0.263
## Q57 11.8799 0.2202
## Q58 25.9531 0.0021
## Q59 8.0244 0.5317
## Q60 20.6714 0.0142
## Q61 23.7781 0.0047
## Q62 17.4642 0.0419
## Q63 28.0656 0.0009
## Q64 11.6375 0.2345
## Q65 9.2096 0.4182
## Q66 25.7763 0.0022
## Q67 14.1481 0.1172
## Q68 12.4251 0.1904
## Q69 4.9261 0.8407
## Q70 15.9984 0.0669
## Q71 8.3232 0.5019
## Q72 15.3617 0.0815
## Q73 21.5647 0.0104
## Q74 11.9799 0.2144
## Q75 24.3874 0.0037## Min. 1st Qu. Median Mean 3rd Qu. Max.
## -2.769000 -0.485200 -0.035490 0.004904 0.623800 2.159000- dilanjut ke 2 dan 3, atau bahkan 4PL
- tapi untuk mencapai stabil, 2PL biasanya 600 an –> cari citationnya
IRT 2 PL
##
## Call:
## ltm(formula = ebAnalyze ~ z1)
##
## Model Summary:
## log.Lik AIC BIC
## -6577.842 13455.68 13931.26
##
## Coefficients:
## value std.err z.vals
## Dffclt.Q1 0.4555 0.2277 2.0010
## Dffclt.Q2 -0.5359 0.2796 -1.9165
## Dffclt.Q3 -4.0261 2.4622 -1.6352
## Dffclt.Q4 -1.2873 0.2849 -4.5186
## Dffclt.Q5 -2.5275 0.6848 -3.6908
## Dffclt.Q6 1.0594 1.1247 0.9419
## Dffclt.Q7 -0.3247 0.1895 -1.7140
## Dffclt.Q8 7.9999 8.5880 0.9315
## Dffclt.Q9 -1.4270 0.3158 -4.5185
## Dffclt.Q10 -2.1855 0.4888 -4.4712
## Dffclt.Q11 -2.1308 0.3743 -5.6931
## Dffclt.Q12 -0.7955 0.1614 -4.9286
## Dffclt.Q13 -1.7033 0.2832 -6.0145
## Dffclt.Q14 -1.2522 0.2081 -6.0176
## Dffclt.Q15 -1.9025 0.6037 -3.1515
## Dffclt.Q16 -1.4533 0.1520 -9.5622
## Dffclt.Q17 3.2975 2.6508 1.2440
## Dffclt.Q18 2.0988 0.8171 2.5684
## Dffclt.Q19 2.7998 0.7399 3.7839
## Dffclt.Q20 1.2616 0.3273 3.8541
## Dffclt.Q21 -15.3031 34.8095 -0.4396
## Dffclt.Q22 -0.3852 0.2161 -1.7820
## Dffclt.Q23 -0.2094 0.3174 -0.6598
## Dffclt.Q24 -1.8444 0.9233 -1.9976
## Dffclt.Q25 -0.6849 0.2290 -2.9908
## Dffclt.Q26 -0.4296 0.3166 -1.3567
## Dffclt.Q27 -3.8386 3.3682 -1.1397
## Dffclt.Q28 3.1964 1.1586 2.7588
## Dffclt.Q29 -8.4714 8.2189 -1.0307
## Dffclt.Q30 9.8901 15.2993 0.6464
## Dffclt.Q31 -10.2198 12.6350 -0.8088
## Dffclt.Q32 0.4062 0.2303 1.7640
## Dffclt.Q33 -25.0766 89.4372 -0.2804
## Dffclt.Q34 -6.6903 5.8635 -1.1410
## Dffclt.Q35 6.4035 4.6408 1.3798
## Dffclt.Q36 -6.0279 4.1434 -1.4548
## Dffclt.Q37 -2.0706 0.3140 -6.5947
## Dffclt.Q38 8.6406 9.8546 0.8768
## Dffclt.Q39 -4.4360 3.1730 -1.3980
## Dffclt.Q40 -2.4574 0.8220 -2.9897
## Dffclt.Q41 0.0869 1.0141 0.0857
## Dffclt.Q42 10.1771 12.3861 0.8217
## Dffclt.Q43 -0.3560 0.2458 -1.4487
## Dffclt.Q44 1.7051 0.4751 3.5887
## Dffclt.Q45 0.3656 0.3116 1.1730
## Dffclt.Q46 -1.0525 0.1871 -5.6268
## Dffclt.Q47 -1.1238 0.2923 -3.8446
## Dffclt.Q48 -1.4648 0.2564 -5.7128
## Dffclt.Q49 0.6963 0.4187 1.6628
## Dffclt.Q50 -0.3822 0.1922 -1.9889
## Dffclt.Q51 -1.0616 0.2058 -5.1576
## Dffclt.Q52 -0.0143 0.1503 -0.0952
## Dffclt.Q53 1.5810 0.6610 2.3920
## Dffclt.Q54 -2.0167 0.4287 -4.7044
## Dffclt.Q55 -0.7931 0.1618 -4.9029
## Dffclt.Q56 3.4723 1.4925 2.3265
## Dffclt.Q57 0.1936 0.2282 0.8485
## Dffclt.Q58 -0.0640 1.2189 -0.0525
## Dffclt.Q59 2.6928 0.6979 3.8585
## Dffclt.Q60 -22.4072 58.8428 -0.3808
## Dffclt.Q61 0.1154 0.1645 0.7020
## Dffclt.Q62 -29.4912 533.6951 -0.0553
## Dffclt.Q63 -0.8824 0.1425 -6.1923
## Dffclt.Q64 1.8842 0.7232 2.6055
## Dffclt.Q65 2.2599 2.0714 1.0910
## Dffclt.Q66 -7.3204 6.0415 -1.2117
## Dffclt.Q67 7.5065 6.9012 1.0877
## Dffclt.Q68 2.3132 0.8059 2.8703
## Dffclt.Q69 12.0355 16.5599 0.7268
## Dffclt.Q70 13.5006 22.5294 0.5992
## Dffclt.Q71 -63.8070 608.2788 -0.1049
## Dffclt.Q72 -8.8674 9.1729 -0.9667
## Dffclt.Q73 -9.9202 12.2306 -0.8111
## Dffclt.Q74 0.4384 0.2868 1.5285
## Dffclt.Q75 -0.8065 0.1472 -5.4798
## Dscrmn.Q1 0.8799 0.2019 4.3581
## Dscrmn.Q2 0.6514 0.1823 3.5731
## Dscrmn.Q3 -0.2992 0.1882 -1.5894
## Dscrmn.Q4 0.9770 0.2317 4.2173
## Dscrmn.Q5 0.8304 0.2708 3.0666
## Dscrmn.Q6 0.2055 0.1566 1.3122
## Dscrmn.Q7 1.0222 0.2158 4.7373
## Dscrmn.Q8 0.1833 0.1968 0.9315
## Dscrmn.Q9 0.9415 0.2317 4.0629
## Dscrmn.Q10 1.0171 0.2894 3.5144
## Dscrmn.Q11 1.5221 0.4279 3.5570
## Dscrmn.Q12 1.6062 0.3037 5.2889
## Dscrmn.Q13 1.4290 0.3381 4.2260
## Dscrmn.Q14 1.4714 0.3093 4.7566
## Dscrmn.Q15 0.5966 0.1985 3.0052
## Dscrmn.Q16 3.0561 0.8003 3.8185
## Dscrmn.Q17 0.2138 0.1654 1.2928
## Dscrmn.Q18 0.4945 0.1858 2.6608
## Dscrmn.Q19 1.1582 0.4061 2.8522
## Dscrmn.Q20 0.8984 0.2199 4.0852
## Dscrmn.Q21 -0.0804 0.1839 -0.4374
## Dscrmn.Q22 0.8612 0.2006 4.2925
## Dscrmn.Q23 0.5145 0.1708 3.0122
## Dscrmn.Q24 0.3534 0.1702 2.0760
## Dscrmn.Q25 0.9011 0.2085 4.3216
## Dscrmn.Q26 0.5429 0.1729 3.1390
## Dscrmn.Q27 0.1899 0.1672 1.1361
## Dscrmn.Q28 0.6291 0.2466 2.5508
## Dscrmn.Q29 -0.3165 0.3182 -0.9948
## Dscrmn.Q30 0.1170 0.1801 0.6496
## Dscrmn.Q31 -0.1830 0.2300 -0.7958
## Dscrmn.Q32 0.8456 0.1991 4.2468
## Dscrmn.Q33 -0.0529 0.1894 -0.2795
## Dscrmn.Q34 -0.2297 0.2061 -1.1148
## Dscrmn.Q35 0.3439 0.2553 1.3471
## Dscrmn.Q36 -0.5103 0.3792 -1.3457
## Dscrmn.Q37 2.0241 0.6051 3.3452
## Dscrmn.Q38 0.1740 0.1984 0.8769
## Dscrmn.Q39 -0.2481 0.1811 -1.3701
## Dscrmn.Q40 -0.5807 0.2108 -2.7544
## Dscrmn.Q41 0.1514 0.1550 0.9770
## Dscrmn.Q42 0.1864 0.2278 0.8184
## Dscrmn.Q43 0.7218 0.1886 3.8272
## Dscrmn.Q44 0.7618 0.2144 3.5537
## Dscrmn.Q45 0.5704 0.1753 3.2550
## Dscrmn.Q46 1.4832 0.2969 4.9949
## Dscrmn.Q47 0.8445 0.2100 4.0208
## Dscrmn.Q48 1.2950 0.2922 4.4324
## Dscrmn.Q49 0.4780 0.1692 2.8261
## Dscrmn.Q50 1.0133 0.2140 4.7350
## Dscrmn.Q51 1.3054 0.2681 4.8696
## Dscrmn.Q52 1.5075 0.2739 5.5048
## Dscrmn.Q53 0.4722 0.1762 2.6793
## Dscrmn.Q54 -1.0700 0.2933 -3.6478
## Dscrmn.Q55 1.6191 0.3096 5.2300
## Dscrmn.Q56 0.4828 0.2151 2.2448
## Dscrmn.Q57 0.7955 0.1910 4.1641
## Dscrmn.Q58 -0.1242 0.1544 -0.8045
## Dscrmn.Q59 1.0684 0.3529 3.0274
## Dscrmn.Q60 -0.0947 0.2500 -0.3787
## Dscrmn.Q61 1.2864 0.2473 5.2015
## Dscrmn.Q62 -0.0085 0.1548 -0.0552
## Dscrmn.Q63 2.3107 0.4346 5.3169
## Dscrmn.Q64 0.5037 0.1837 2.7418
## Dscrmn.Q65 0.1906 0.1591 1.1983
## Dscrmn.Q66 -0.3564 0.3076 -1.1589
## Dscrmn.Q67 0.2343 0.2169 1.0802
## Dscrmn.Q68 0.5681 0.2002 2.8381
## Dscrmn.Q69 0.1917 0.2652 0.7227
## Dscrmn.Q70 0.1297 0.2164 0.5992
## Dscrmn.Q71 -0.0196 0.1870 -0.1048
## Dscrmn.Q72 -0.2295 0.2428 -0.9454
## Dscrmn.Q73 -0.1745 0.2183 -0.7991
## Dscrmn.Q74 0.6491 0.1816 3.5752
## Dscrmn.Q75 1.9898 0.3722 5.3467
##
## Integration:
## method: Gauss-Hermite
## quadrature points: 21
##
## Optimization:
## Convergence: 0
## max(|grad|): 0.011
## quasi-Newton: BFGS
##
## Call:
## ltm(formula = ebAnalyze ~ z1)
##
## Total Information = 51.92
## Information in (-10, 10) = 51.92 (100%)
## Based on all the items
##
## Item-Fit Statistics and P-values
##
## Call:
## ltm(formula = ebAnalyze ~ z1)
##
## Alternative: Items do not fit the model
## Ability Categories: 10
##
## X^2 Pr(>X^2)
## Q1 2.1506 0.976
## Q2 7.4437 0.4896
## Q3 7.7887 0.4544
## Q4 5.5267 0.7001
## Q5 10.3036 0.2444
## Q6 9.1171 0.3325
## Q7 2.2576 0.9721
## Q8 9.3797 0.3113
## Q9 3.2771 0.9158
## Q10 12.4041 0.1341
## Q11 16.2375 0.0391
## Q12 7.4398 0.49
## Q13 4.4284 0.8166
## Q14 14.3886 0.0722
## Q15 5.7906 0.6707
## Q16 7.8994 0.4434
## Q17 5.4277 0.711
## Q18 8.5523 0.3815
## Q19 9.7391 0.2838
## Q20 13.9184 0.0839
## Q21 7.4896 0.4848
## Q22 9.8854 0.2732
## Q23 16.5382 0.0353
## Q24 5.3611 0.7184
## Q25 7.5370 0.48
## Q26 18.3478 0.0188
## Q27 4.6291 0.7964
## Q28 10.4673 0.2337
## Q29 4.3064 0.8285
## Q30 10.6686 0.2212
## Q31 12.3933 0.1345
## Q32 6.6202 0.5781
## Q33 7.0700 0.5291
## Q34 12.1731 0.1436
## Q35 9.3819 0.3111
## Q36 5.0765 0.7494
## Q37 5.2920 0.726
## Q38 7.0315 0.5332
## Q39 15.0379 0.0584
## Q40 5.2422 0.7314
## Q41 6.5555 0.5853
## Q42 5.3002 0.7251
## Q43 15.3919 0.052
## Q44 5.6761 0.6835
## Q45 12.0716 0.148
## Q46 5.4774 0.7055
## Q47 6.0691 0.6395
## Q48 9.2245 0.3237
## Q49 6.2812 0.6158
## Q50 6.8639 0.5514
## Q51 4.2678 0.8322
## Q52 6.0697 0.6394
## Q53 4.1873 0.8398
## Q54 8.5014 0.3861
## Q55 4.1216 0.846
## Q56 7.5443 0.4792
## Q57 7.8001 0.4532
## Q58 9.5714 0.2964
## Q59 5.2848 0.7267
## Q60 8.1094 0.4229
## Q61 7.7473 0.4585
## Q62 12.6283 0.1253
## Q63 11.4285 0.1786
## Q64 7.6909 0.4642
## Q65 4.5671 0.8027
## Q66 8.3915 0.3962
## Q67 15.0464 0.0582
## Q68 6.4073 0.6017
## Q69 7.5105 0.4827
## Q70 5.8672 0.6621
## Q71 3.8805 0.8677
## Q72 9.3422 0.3143
## Q73 9.1210 0.3322
## Q74 11.0864 0.1969
## Q75 3.9596 0.8607
## Min. 1st Qu. Median Mean 3rd Qu. Max.
## -2.12000 -0.86990 -0.11550 -0.07829 0.70340 2.69900PERBANDINGAN 2 MODEL
##
## Call:
## rasch(data = ebAnalyze)
##
## Total Information = 40.9
## Information in (-10, 10) = 40.9 (100%)
## Based on all the items##
## Call:
## ltm(formula = ebAnalyze ~ z1)
##
## Total Information = 51.92
## Information in (-10, 10) = 51.92 (100%)
## Based on all the items===========================================================================
ANOVA 3 MODEL
- digunakan untuk melihat apakah kita bisa menggunakan level yang lebih tinggi -jika observation nya sedikit, biasanya pengukuran dengan level 2 atau diatasnya tidak akan stabil
##
## Likelihood Ratio Table
## AIC BIC log.Lik LRT df p.value
## ebrasch 13921.61 14159.39 -6885.80
## ebIRT.1pl 13861.99 14102.94 -6854.99 61.62 1 <0.001##
## Likelihood Ratio Table
## AIC BIC log.Lik LRT df p.value
## ebIRT.1pl 13861.99 14102.94 -6854.99
## ebIRT.2pl 13455.68 13931.26 -6577.84 554.3 74 <0.001