我的问题是，为什么Hausman检验显示p值为1？完美1使我担心是正常还是其他问题？
如果正确，应该如何整体解释随机效应模型的输出？
非常感谢。
`> fe.fit = plm(D ~ itr + ip + age + sen + relv + sexdummy + exprdummy + knowdummy, data = merge, family = binomial , index = 'ID', model = "within") summary(fe.fit)`
`> summary(fe.fit) Oneway (individual) effect Within Model`
`Call: plm(formula = D ~ itr + ip + age + sen + relv + sexdummy + exprdummy +
knowdummy, data = merge, model = "within", index = "ID",
family = binomial)`
`Balanced Panel: n = 203, T = 30, N = 6090`
`Residuals:
Min. 1st Qu. Median 3rd Qu. Max.
-1.12022 -0.37350 0.10516 0.31743 1.07604 `
`Coefficients:
Estimate Std. Error t-value Pr(>|t|)
sen -0.00563553 0.00029832 -18.891 < 2.2e-16 ***
relv 0.00407129 0.00033073 12.310 < 2.2e-16 ***`
`Total Sum of Squares: 1194.5
Residual Sum of Squares: 1046.9
R-Squared: 0.12357
Adj. R-Squared: 0.093187
F-statistic: 414.862 on 2 and 5885 DF, p-value: < 2.22e-16`
`> re.fit = plm(D ~ itr + ip + age + sen + relv + sexdummy + exprdummy + knowdummy, data = merge, family = binomial , index = 'ID', model = "random")`
`> summary(re.fit) Oneway (individual) effect Random Effect Model (Swamy-Arora's transformation)`
`Call: plm(formula = D ~ itr + ip + age + sen + relv + sexdummy + exprdummy +
knowdummy, data = merge, model = "random", index = "ID",
family = binomial)`
`Balanced Panel: n = 203, T = 30, N = 6090`
`Effects:
var std.dev share
idiosyncratic 0.17789 0.42177 0.884
individual 0.02334 0.15276 0.116
theta: 0.5499`
`Residuals:
Min. 1st Qu. Median 3rd Qu. Max.
-0.98151 -0.42977 0.15663 0.32311 0.97436 `
`Coefficients:
Estimate Std. Error z-value Pr(>|z|)
(Intercept) 0.36474342 0.14934874 2.4422 0.0145970 *
itr 0.04968868 0.01389861 3.5751 0.0003501 ***
ip -0.00689283 0.01161468 -0.5935 0.5528748
age 0.01078111 0.00553912 1.9464 0.0516119 .
sen -0.00563553 0.00029832 -18.8908 < 2.2e-16 ***
relv 0.00407129 0.00033073 12.3099 < 2.2e-16 ***
sexdummy -0.06338253 0.02629987 -2.4100 0.0159528 *
exprdummy -0.01749713 0.04206798 -0.4159 0.6774648
knowdummy 0.02462112 0.04132943 0.5957 0.5513566 `
`Total Sum of Squares: 1234.9 Residual Sum of Squares: 1081.7 R-Squared: 0.12401 Adj. R-Squared: 0.12286 Chisq: 860.86 on 8 DF, p-value: < 2.22e-16 `
`> phtest(fe.fit, re.fit)`
` Hausman Test`
`data: D ~ itr + ip + age + sen + relv
+ sexdummy + exprdummy + knowdummy
chisq = 2.0691e-11, df = 2, p-value = 1
alternative hypothesis: one model is inconsistent`