[英]Checking parallel regression assumption in ordinal logistic regression
我嘗試使用一個有序分類變量和另外三個分類因變量(N = 43097)構建有序邏輯回歸。 雖然所有系數都很重要,但我對是否滿足平行回歸假設表示懷疑。 盡管brant test
中所有變量和整個模型的概率值完全為零(應該大於 0.05),但測試仍然顯示H0: Parallel Regression Assumption holds
。 我在這里很困惑。 這個模型是否完全符合平行回歸假設的標准?
library(MASS)
table(hh18_u_r$cat_ci_score) # Dependent variable
Extremely Vulnerable Moderate Vulnerable Pandemic Prepared
6143 16341 20613
# Ordinal logistic regression
olr_2 <- polr(cat_ci_score ~ r1_gender + r2_merginalised + r9_religion, data = hh18_u_r, Hess=TRUE)
summary(olr_2)
Call:
polr(formula = cat_ci_score ~ r1_gender + r2_merginalised + r9_religion,
data = hh18_u_r, Hess = TRUE)
Coefficients:
Value Std. Error t value
r1_genderMale 0.3983 0.02607 15.278
r2_merginalisedOthers 0.6641 0.01953 34.014
r9_religionHinduism -0.2432 0.03069 -7.926
r9_religionIslam -0.5425 0.03727 -14.556
Intercepts:
Value Std. Error t value
Extremely Vulnerable|Moderate Vulnerable -1.5142 0.0368 -41.1598
Moderate Vulnerable|Pandemic Prepared 0.4170 0.0359 11.6260
Residual Deviance: 84438.43
AIC: 84450.43
## significance of coefficients and intercepts
summary_table_2 <- coef(summary(olr_2))
pval_2 <- pnorm(abs(summary_table_2[, "t value"]), lower.tail = FALSE)* 2
summary_table_2 <- cbind(summary_table_2, pval_2)
summary_table_2
Value Std. Error t value pval_2
r1_genderMale 0.3982719 0.02606904 15.277583 1.481954e-52
r2_merginalisedOthers 0.6641311 0.01952501 34.014386 2.848250e-250
r9_religionHinduism -0.2432085 0.03068613 -7.925682 2.323144e-15
r9_religionIslam -0.5424992 0.03726868 -14.556436 6.908533e-48
Extremely Vulnerable|Moderate Vulnerable -1.5141502 0.03678710 -41.159819 0.000000e+00
Moderate Vulnerable|Pandemic Prepared 0.4169645 0.03586470 11.626042 3.382922e-31
#Test of parallel regression assumption
library(brant)
brant(olr_2) # Probability supposed to be more than 0.05 as I understand
----------------------------------------------------
Test for X2 df probability
----------------------------------------------------
Omnibus 168.91 4 0
r1_genderMale 12.99 1 0
r2_merginalisedOthers 41.18 1 0
r9_religionHinduism 86.16 1 0
r9_religionIslam 25.13 1 0
----------------------------------------------------
H0: Parallel Regression Assumption holds
# Similar test of parallel regression assumption using car package
library(car)
car::poTest(olr_2)
Tests for Proportional Odds
polr(formula = cat_ci_score ~ r1_gender + r2_merginalised + r9_religion,
data = hh18_u_r, Hess = TRUE)
b[polr] b[>Extremely Vulnerable] b[>Moderate Vulnerable] Chisquare df Pr(>Chisq)
Overall 168.9 4 < 2e-16 ***
r1_genderMale 0.398 0.305 0.442 13.0 1 0.00031 ***
r2_merginalisedOthers 0.664 0.513 0.700 41.2 1 1.4e-10 ***
r9_religionHinduism -0.243 -0.662 -0.147 86.2 1 < 2e-16 ***
r9_religionIslam -0.542 -0.822 -0.504 25.1 1 5.4e-07 ***
---
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
請建議這個模型是否滿足平行回歸假設? 謝謝
它告訴您零假設 (H0) 成立。 您的值具有統計顯着性,這意味着您拒絕原假設 (H0)。 它並沒有向您表明滿足假設,而只是提醒您什么是空值。
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