- 前のデータで順序なしカテゴリであるx4を被説明変数にしてy.2を順序ありカテゴリの説明変数にする
fat.out0 <- vgam(x4 ~ 1,family = cumulative(parallel = TRUE, reverse = TRUE))
head(coef(fat.out0,matrix=TRUE),10)
head(coef(summary(fat.out0)),10)
fat.out1 <- vglm(x4 ~ x1+x2+x3+y.2,family = cumulative(parallel = TRUE, reverse = TRUE))
colSums(fat.out1@y)
head(coef(fat.out1,matrix=TRUE),10)
head(coef(summary(fat.out1)),10)
pchisq(deviance(fat.out0)-deviance(fat.out1),df=df.residual(fat.out0)-df.residual(fat.out1),lower.tail=FALSE)
fat.out2 <- vglm(y.2 ~ x1+x2+x3+x4,family = cumulative(parallel = FALSE ~ 1+x4, reverse = TRUE))
head(coef(fat.out2,matrix=TRUE),10)
head(coef(summary(fat.out2)),10)
pchisq(deviance(fat.out1)-deviance(fat.out2),df=df.residual(fat.out1)-df.residual(fat.out2),lower.tail=FALSE)
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> fat.out0 <- vgam(x4 ~ 1,family = cumulative(parallel = TRUE, reverse = TRUE))
警告メッセージ:
In model.matrix.default(mt, mf, contrasts) :
variable 'x4' converted to a factor
> head(coef(fat.out0,matrix=TRUE),10)
logit(P[Y>=2]) logit(P[Y>=3]) logit(P[Y>=4]) logit(P[Y>=5])
(Intercept) 1.463058 0.4599402 -0.4599402 -1.482832
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> head(coef(summary(fat.out0)),10)
(Intercept):1 (Intercept):2 (Intercept):3 (Intercept):4
1.4630584 0.4599402 -0.4599402 -1.4828323
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> fat.out1 <- vglm(x4 ~ x1+x2+x3+y.2,family = cumulative(parallel = TRUE, reverse = TRUE))
警告メッセージ:
In model.matrix.default(mt, mf, contrasts) :
variable 'x4' converted to a factor
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> colSums(fat.out1@y)
A B C D E
188 199 226 202 185
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> head(coef(fat.out1,matrix=TRUE),10)
logit(P[Y>=2]) logit(P[Y>=3]) logit(P[Y>=4]) logit(P[Y>=5])
(Intercept) 1.8816656095 0.8754619270 -0.0475793864 -1.0724638363
x1 0.4572981994 0.4572981994 0.4572981994 0.4572981994
x2 -0.0064020316 -0.0064020316 -0.0064020316 -0.0064020316
x3 -0.0003846138 -0.0003846138 -0.0003846138 -0.0003846138
y.2 0.0009281906 0.0009281906 0.0009281906 0.0009281906
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> head(coef(summary(fat.out1)),10)
Value Std. Error t value
(Intercept):1 1.8816656095 0.307879495 6.11169513
(Intercept):2 0.8754619270 0.302953928 2.88975268
(Intercept):3 -0.0475793864 0.301653599 -0.15772856
(Intercept):4 -1.0724638363 0.304455951 -3.52255829
x1 0.4572981994 0.300156547 1.52353231
x2 -0.0064020316 0.009480932 -0.67525340
x3 -0.0003846138 0.000325561 -1.18138791
y.2 0.0009281906 0.061208467 0.01516441
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> pchisq(deviance(fat.out0)-deviance(fat.out1),df=df.residual(fat.out0)-df.residual(fat.out1),lower.tail=FALSE)
[1] 0.3965315
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> fat.out2 <- vglm(y.2 ~ x1+x2+x3+x4,family = cumulative(parallel = FALSE ~ 1+x4, reverse = TRUE))
警告メッセージ:
In model.matrix.default(mt, mf, contrasts) :
variable 'x4' converted to a factor
> head(coef(fat.out2,matrix=TRUE),10)
logit(P[Y>=2]) logit(P[Y>=3]) logit(P[Y>=4])
(Intercept) -3.468009222 -5.057181562 -7.770261183
x1 1.083793033 1.083793033 1.083793033
x2 0.072781576 0.072781576 0.072781576
x3 0.002867438 0.002867438 0.002867438
x4B 0.145736083 0.104751298 0.454973687
x4C 1.200523387 1.974227617 3.579792821
x4D 0.017035933 -0.259397806 0.243186015
x4E 0.038567630 0.172056690 -0.045528562
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> head(coef(summary(fat.out2)),10)
Value Std. Error t value
(Intercept):1 -3.468009222 0.4182957827 -8.2908061
(Intercept):2 -5.057181562 0.4327272985 -11.6867634
(Intercept):3 -7.770261183 0.5281333590 -14.7126877
x1 1.083793033 0.3663289848 2.9585238
x2 0.072781576 0.0115986302 6.2750148
x3 0.002867438 0.0003716743 7.7149203
x4B:1 0.145736083 0.2432247429 0.5991828
x4B:2 0.104751298 0.2419113476 0.4330152
x4B:3 0.454973687 0.4021672687 1.1313046
x4C:1 1.200523387 0.2759482980 4.3505374
> pchisq(deviance(fat.out1)-deviance(fat.out2),df=df.residual(fat.out1)-df.residual(fat.out2),lower.tail=FALSE)
[1] 0.0031684
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