Analisa RASCH menggunakan eRm
Heru Wiryanto
Sept 1, 2016
PERSIAPAN DATA
Data 10 soal benar salah
## Warning in read.spss("/home/yg1hw/math66.sav", to.data.frame = T,
## use.value.labels = F): /home/yg1hw/math66.sav: Unrecognized record type 7,
## subtype 18 encountered in system file## re-encoding from CP1252## V1 V2 V3 V4 V5 V6 V7 V8 V9 V10
## 1 1 0 0 1 0 0 0 1 0 1
## 2 1 0 1 0 0 0 1 1 1 1
## 3 1 1 1 1 1 1 1 1 1 0
## 4 1 0 1 1 0 1 0 1 0 1
## 5 1 1 1 1 1 1 0 0 1 1
## 6 1 1 1 1 0 1 1 1 1 1## V1 V2 V3 V4 V5 V6 V7 V8 V9 V10
## 1 1 0 0 1 0 0 0 1 0 1
## 2 1 0 1 0 0 0 1 1 1 1
## 3 1 1 1 1 1 1 1 1 1 0
## 4 1 0 1 1 0 1 0 1 0 1
## 5 1 1 1 1 1 1 0 0 1 1
## 6 1 1 1 1 0 1 1 1 1 1HASIL RASCH MODEL
(Tingkat Kesulitan dan Kemudahan Item)
##
## Results of RM estimation:
##
## Call: RM(X = data)
##
## Conditional log-likelihood: -3115.294
## Number of iterations: 16
## Number of parameters: 9
##
## Item (Category) Difficulty Parameters (eta): with 0.95 CI:
## Estimate Std. Error lower CI upper CI
## V2 0.190 0.075 0.043 0.337
## V3 0.147 0.075 -0.001 0.295
## V4 0.035 0.077 -0.115 0.185
## V5 1.064 0.071 0.924 1.203
## V6 0.184 0.075 0.036 0.331
## V7 0.949 0.071 0.810 1.089
## V8 0.196 0.075 0.049 0.343
## V9 0.141 0.076 -0.007 0.289
## V10 -2.217 0.142 -2.496 -1.938
##
## Item Easiness Parameters (beta) with 0.95 CI:
## Estimate Std. Error lower CI upper CI
## beta V1 0.688 0.088 0.517 0.860
## beta V2 -0.190 0.075 -0.337 -0.043
## beta V3 -0.147 0.075 -0.295 0.001
## beta V4 -0.035 0.077 -0.185 0.115
## beta V5 -1.064 0.071 -1.203 -0.924
## beta V6 -0.184 0.075 -0.331 -0.036
## beta V7 -0.949 0.071 -1.089 -0.810
## beta V8 -0.196 0.075 -0.343 -0.049
## beta V9 -0.141 0.076 -0.289 0.007
## beta V10 2.217 0.142 1.938 2.496PLOTTING ICC dari 10 item
makin posisi grafik ke kanan adalah makin sulit dari grafik ini terlihat item 10 adalah yang termudah dan selanjutnya
PLOT PETA ITEM PETA WRIGHT
Peta Ma[ memperlihatkan item 5 dan 7 adalah yang paling sulit karena posisinya paling kanan dan person parameter menunjukkan orang-orang yang berhasil
## Plot Item Map ## Batas yang hijau adalah untuk menentukan item out fit, ada beberapa item yang outfit item V10, V6 , v7 dan v8 
Berikut Konversi Total Skore ke Logit dan standard errornya
##
## Person Parameters:
##
## Raw Score Estimate Std.Error
## 0 -3.56846213 NA
## 1 -2.53224370 1.1343557
## 2 -1.57274100 0.8650937
## 3 -0.92953434 0.7510711
## 4 -0.41122495 0.6953713
## 5 0.05436205 0.6741169
## 6 0.51022532 0.6809139
## 7 0.99659554 0.7202107
## 8 1.57666100 0.8154282
## 9 2.42662530 1.0722251
## 10 3.34276285 NAItem Parameter untuk Person
## Unconditional (joint) log Lik.: -45.18771 (df=9)## $NAgroup1
## 2.5 % 97.5 %
## P1 -1.7741277 0.9516778
## P2 -0.8243414 1.8447921
## P3 0.3251028 4.5281478
## P4 -0.8243414 1.8447921
## P5 -0.0215490 3.1748710
## P6 0.3251028 4.5281478
## P7 0.3251028 4.5281478
## P8 -0.4149916 2.4081826
## P9 -3.2682935 0.1228115
## P11 -2.4016066 0.5425379
## P12 -0.4149916 2.4081826
## P13 0.3251028 4.5281478
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## P565 -1.7741277 0.9516778
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## P590 -0.0215490 3.1748710
## P591 -3.2682935 0.1228115
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## P593 -0.0215490 3.1748710
## P594 0.3251028 4.5281478
## P595 0.3251028 4.5281478
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## P639 -0.0215490 3.1748710
## P640 -0.0215490 3.1748710
## P641 -3.2682935 0.1228115
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## P643 -1.7741277 0.9516778
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## P646 -2.4016066 0.5425379
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## P648 -2.4016066 0.5425379
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## P650 -0.0215490 3.1748710
## P651 0.3251028 4.5281478
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## P695 -2.4016066 0.5425379
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## P700 0.3251028 4.5281478
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## P718 -0.0215490 3.1748710
## P719 -2.4016066 0.5425379
## P720 -4.7555399 -0.3089475
## P721 -0.0215490 3.1748710
## P722 0.3251028 4.5281478
## P723 0.3251028 4.5281478
## P724 -1.7741277 0.9516778
## P725 -0.8243414 1.8447921
## P726 -1.7741277 0.9516778
## P727 -0.4149916 2.4081826
## P728 0.3251028 4.5281478
## P729 0.3251028 4.5281478
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## P732 -0.8243414 1.8447921
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## P740 0.3251028 4.5281478
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## P745 -0.0215490 3.1748710
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## P750 0.3251028 4.5281478
## P751 -0.0215490 3.1748710
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## P756 0.3251028 4.5281478
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## P760 -1.7741277 0.9516778
## P761 -0.0215490 3.1748710
## P762 0.3251028 4.5281478
## P763 -1.2668828 1.3756069
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## P789 -3.2682935 0.1228115
## P790 -0.0215490 3.1748710
## P791 0.3251028 4.5281478
## P793 0.3251028 4.5281478
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## P796 -1.2668828 1.3756069
## P797 -0.4149916 2.4081826
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## P800 -2.4016066 0.5425379
## P801 -0.8243414 1.8447921
## P802 -0.4149916 2.4081826
## P803 0.3251028 4.5281478
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## P805 -0.0215490 3.1748710
## P806 0.3251028 4.5281478
## P807 -1.2668828 1.3756069
## P808 -0.4149916 2.4081826
## P809 -0.4149916 2.4081826
## P810 -0.4149916 2.4081826
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## P812 -0.0215490 3.1748710
## P813 -0.0215490 3.1748710
## P815 -0.8243414 1.8447921
## P816 -1.7741277 0.9516778
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## P818 -0.0215490 3.1748710
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## P820 0.3251028 4.5281478
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## P824 -2.4016066 0.5425379
## P825 0.3251028 4.5281478
## P826 -0.4149916 2.4081826
## P827 0.3251028 4.5281478
## P830 0.3251028 4.5281478
## P831 -1.2668828 1.3756069
## P832 0.3251028 4.5281478
## P833 -0.0215490 3.1748710
## P834 -0.0215490 3.1748710
## P835 0.3251028 4.5281478
## P836 -0.8243414 1.8447921
## P837 0.3251028 4.5281478
## P838 0.3251028 4.5281478
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## P861 0.3251028 4.5281478
## P862 -1.2668828 1.3756069
## P863 -1.7741277 0.9516778
## P864 0.3251028 4.5281478
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## P870 -0.0215490 3.1748710
## P873 -1.2668828 1.3756069
## P874 -1.7741277 0.9516778
## P875 -0.4149916 2.4081826
## P876 0.3251028 4.5281478
## P877 -0.8243414 1.8447921
## P878 0.3251028 4.5281478
## P879 0.3251028 4.5281478
## P880 -0.0215490 3.1748710
## P881 -0.4149916 2.4081826
## P882 -4.7555399 -0.3089475
## P884 -0.8243414 1.8447921
## P885 -0.4149916 2.4081826
## P886 -1.7741277 0.9516778
## P887 -0.0215490 3.1748710
## P889 -0.8243414 1.8447921
## P891 -1.2668828 1.3756069
## P892 0.3251028 4.5281478
## P893 0.3251028 4.5281478
## P894 -1.2668828 1.3756069
## P895 -1.2668828 1.3756069
## P896 -3.2682935 0.1228115
## P898 -0.0215490 3.1748710
## P899 -2.4016066 0.5425379
## P900 -1.7741277 0.9516778
## P901 -0.0215490 3.1748710
## P902 -1.2668828 1.3756069
## P903 -3.2682935 0.1228115
## P905 0.3251028 4.5281478
## P907 -0.8243414 1.8447921
## P908 -0.4149916 2.4081826
## P909 -1.2668828 1.3756069
## P910 -1.7741277 0.9516778
## P911 -0.8243414 1.8447921
## P912 -0.4149916 2.4081826
## P913 -0.4149916 2.4081826
## P914 -0.0215490 3.1748710
## P915 -4.7555399 -0.3089475
## P916 -1.2668828 1.3756069
## P917 -0.4149916 2.4081826
## P918 -2.4016066 0.5425379
## P919 -0.8243414 1.8447921
## P920 0.3251028 4.5281478
## P921 -0.4149916 2.4081826
## P922 -0.4149916 2.4081826
## P923 -0.0215490 3.1748710
## P924 0.3251028 4.5281478
## P925 -1.2668828 1.3756069
## P926 -0.4149916 2.4081826
## P927 -0.8243414 1.8447921
## P928 -0.8243414 1.8447921
## P929 -1.7741277 0.9516778
## P931 -0.8243414 1.8447921
## P932 0.3251028 4.5281478
## P933 -0.0215490 3.1748710
## P934 0.3251028 4.5281478
## P935 -3.2682935 0.1228115
## P937 -1.7741277 0.9516778
## P938 -0.0215490 3.1748710
## P939 0.3251028 4.5281478
## P940 -0.8243414 1.8447921
## P941 -0.8243414 1.8447921
## P942 -1.2668828 1.3756069
## P943 -0.8243414 1.8447921
## P944 -1.2668828 1.3756069
## P945 -0.4149916 2.4081826
## P946 -0.8243414 1.8447921
## P947 -0.4149916 2.4081826
## P948 -1.2668828 1.3756069
## P949 -0.4149916 2.4081826
## P950 -0.8243414 1.8447921
## P951 -0.8243414 1.8447921
## P952 -0.8243414 1.8447921
## P953 -0.0215490 3.1748710
## P954 -1.7741277 0.9516778
## P955 0.3251028 4.5281478
## P956 -1.2668828 1.3756069
## P957 -0.8243414 1.8447921
## P958 -1.7741277 0.9516778
## P960 0.3251028 4.5281478
## P961 -0.0215490 3.1748710
## P962 0.3251028 4.5281478
## P963 -0.4149916 2.4081826
## P964 -0.4149916 2.4081826
## P965 -0.4149916 2.4081826
## P966 -0.4149916 2.4081826
## P967 -0.0215490 3.1748710
## P968 -0.8243414 1.8447921
## P969 -0.4149916 2.4081826
## P970 -0.0215490 3.1748710
## P971 -0.8243414 1.8447921
## P972 0.3251028 4.5281478
## P973 -0.8243414 1.8447921
## P974 -4.7555399 -0.3089475
## P975 -1.2668828 1.3756069
## P976 -0.4149916 2.4081826
## P977 0.3251028 4.5281478
## P978 -2.4016066 0.5425379
## P979 -3.2682935 0.1228115
## P980 -0.8243414 1.8447921
## P981 -0.8243414 1.8447921
## P982 -0.0215490 3.1748710
## P983 -0.0215490 3.1748710
## P984 -2.4016066 0.5425379
## P985 0.3251028 4.5281478
## P986 0.3251028 4.5281478
## P987 -0.0215490 3.1748710
## P988 0.3251028 4.5281478
## P989 -0.0215490 3.1748710
## P991 -1.7741277 0.9516778
## P992 -0.0215490 3.1748710
## P993 -0.4149916 2.4081826
## P994 -0.8243414 1.8447921
## P995 -1.2668828 1.3756069
## P998 -0.8243414 1.8447921
## P999 -0.8243414 1.8447921
## P1000 0.3251028 4.5281478Plot antara raw Score dan Logit
