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1 R ,,,,,, &. (2011).., 59(3),
2 A. 57 A1. A2. A3. A4. A5. A6. A7. A8. A9. C. 51 C1. C2. C3. C4. C5. C6. C7. C8. C9. B. 39 B1. B2. B3. B4. B5. D. 52 D1. D2. D3. D4. D5. 4
3 6-3-2/3 / R Testdata.csv ( 2027 ) A1~A9 B1~B5 C1~C9 D1~D
4 6-4-2 Testdata < read.csv("testdata.csv") head(testdata) library(psych) describe(testdata) mean (sd) attach(testdata) TotalA< A1+A2+A3+A4+A5+A6+A7+A8+A9 TotalB< B1+B2+B3+B4+B5 TotalC< C1+C2+C3+C4+C5+C6+C7+C8+C9 TotalD< D1+D2+D3+D4+D5+D6+D7+D8+D9 Total< TotalA+TotalB+TotalC+TotalD attach Testdata Totaldata< cbind(totala,totalb,totalc,totald,total) # 5 describe(totaldata) 8
5 (kurtosis): Ku>0 Ku=0 Ku<0 (skewness): Sk>0 Sk=0 Sk< (reliability) internal consistency : Cronbach 10
6 R install.packages("psych") #psych alpha(testdata[,2:10]) #2 10 alpha(testdata[,11:15]) #11 15 alpha(testdata[,16:24]) #16 24 alpha(testdata[,25:33]) #25 33 alpha(testdata[,2:33]) #
7 R omega(testdata[,2:10]) #2 10 omega(testdata[,11:15]) #11 15 omega(testdata[,16:24]) #16 24 omega(testdata[,25:33]) #25 33 omega(testdata[,2:33]) #
8 total= 15 e.g. 1 2 ( ) 16
9 6-4-5 validity criterion related validity e.g Testdataneeds.csv 560 Testdataneeds < read.csv("testdataneeds.csv") head(testdataneeds) describe(testdataneeds)
10 detach(testdata) attach(testdataneeds) TotalAneeds< A1+A2+A3+A4+A5+A6+A7+A8+A9 TotalBneeds< B1+B2+B3+B4+B5 TotalCneeds< C1+C2+C3+C4+C5+C6+C7+C8+C9 TotalDneeds< D1+D2+D3+D4+D5+D6+D7+D8+D9 Totalneeds< TotalAneeds+TotalBneeds+TotalCneeds+TotalDneeds Totaldataneeds<cbind(TotalAneeds,TotalBneeds,TotalCneeds,TotalDneeds,Totalneeds) describe(totaldataneeds) 19 20
11 ROW< nrow(totaldata) ROWneeds< nrow(totaldataneeds) GROUP< c(rep(1,row),rep(0,rowneeds)) Totaldata Totadataneeds rep DataAALL < c (Totaldata[,1], Totaldataneeds[,1])#1 cor.test(dataaall, GROUP) x p GROUP GROUP1 22
12 DataAALL < c (Totaldata[,2], Totaldataneeds[,2]) DataAALL < c (Totaldata[,3], Totaldataneeds[,3]) DataAALL < c (Totaldata[,4], Totaldataneeds[,4]) DataAALL < c (Totaldata[,5], Totaldataneeds[,5]) [0.391, 0.454] [0.412, 0.474] [0.399, 0.462] [0.382, 0.446] [0.403, 0.466] 23 Grade < Testdata[,1]#Testdata.csv Grade plot(grade, Totaldata[,1]) # Grade 24
13 cor.test(grade,totaldata[,1]) # cor.test(grade,totaldata[,2]) # cor.test(grade,totaldata[,3]) # cor.test(grade,totaldata[,4]) # cor.test(grade,totaldata[,5]) # [0.758, 0.793] [0.731, 0.769] [0.762, 0.797] [0.767, 0.800] [0.778, 0.810] e.g
14 2 33 A1~D9 FA< factanal(testdata[,2:33],factors=2,rotation="promax") * print(fa, cutoff = 0) #cutoff Factor1 Factor2 Factor2 Factor2 A1 B1 B5 28
15 1 library(lavaan) Testdata.model < " Total=~A1+A2+A3+A4+A5+A6+A7+A8+A9+B1+B2+B3+B4+B5+C1+C2+C 3+C4+C5+C6+C7+C8+C9+D1+D2+D3+D4+D5+D6+D7+D8+D9 fit < cfa (Testdata.model, data=testdata) summary(fit, fit.measures=true) 29 Check! 30
16 2 Testdata.model < ' First=~A2+A4+A5+A6+A7+A8+A9+B2+B3+B4+C1+C2+C3+C4+C5+C6+C7 +C8+C9+D1+D2+D3+D4+D5+D6+D7+D8+D9 Second=~A1+A3+B1+B5 ' fit < cfa (Testdata.model, data=testdata) summary(fit, fit.measures=true) 31 Check! 32
17 3 Testdata.model < ' First=~A2+A4+A5+A6+A7+A8+A9+B2+B3+B4+C1+C2+C3+C4+C5+C6+C7 +C8+C9+D1+D2+D3+D4+D5+D6+D7+D8+D9 Second=~A1+A3+B5 Third=~B1 ' fit < cfa (Testdata.model, data=testdata) summary(fit, fit.measures=true) 33 Check! 34
18 (4 ) Testdata.model < L=~A1+A2+A3+A4+A5+A6+A7+A8+A9 D=~B1+B2+B3+B4+B5 S=~C1+C2+C3+C4+C5+C6+C7+C8+C9 P=~D1+D2+D3+D4+D5+D6+D7+D8+D9 fit < cfa (Testdata.model, data=testdata) summary(fit, fit.measures=true) 35 Check! 36
19
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企業費用・利益総合保険_平成27年10月_損保ジャパン日本興亜
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