为什么probit在MCMCpack工作，而不是logit？

我试图将二进制结果SECONDARY.LEVEL建模为数据集中其他三个变量的函数。我正在使用MCMCpack包进行贝叶斯建模。有人能解释为什么MCMCprobit有效，而不是McClogit吗？下面给出了代码和输出的前几行

#Read in data
df = read.csv("http://dl.dropbox.com/u/1791181/MCMC.csv")

Probit的工作原理是：

mcmc.probit = MCMCprobit(SECONDARY.LEVEL ~ AGE + SEX + as.factor(DISTRICT), mcmc=1000, data=df)
head(summary(mcmc.probit)$statistics, n=15)
                              Mean          SD     Naive SE Time-series SE
(Intercept)            0.150093347 0.109792702 0.0034719501   0.0059589451
AGE                   -0.035112684 0.005551112 0.0001755416   0.0003118349
SEXMale                0.207912526 0.026288448 0.0008313137   0.0011590922
as.factor(DISTRICT)2   0.004684505 0.068300292 0.0021598449   0.0028876137
as.factor(DISTRICT)3   0.147462569 0.077003268 0.0024350571   0.0036086218
as.factor(DISTRICT)4   0.056207898 0.070746208 0.0022371915   0.0030940116
as.factor(DISTRICT)5   0.262208868 0.074049641 0.0023416553   0.0035314500
as.factor(DISTRICT)6   0.167194019 0.076774267 0.0024278155   0.0037526433
as.factor(DISTRICT)7  -0.030666654 0.079221987 0.0025052192   0.0045243228
as.factor(DISTRICT)8   0.256155556 0.086851907 0.0027464985   0.0043024813
as.factor(DISTRICT)9   0.220563392 0.081925283 0.0025907049   0.0036374888
as.factor(DISTRICT)10  0.048681988 0.084193610 0.0026624357   0.0037311155
as.factor(DISTRICT)11  0.046235838 0.077788116 0.0024598762   0.0041413425
as.factor(DISTRICT)12  0.055248182 0.084691712 0.0026781871   0.0039077209
as.factor(DISTRICT)13  0.180067061 0.077430509 0.0024485677   0.0035813944

但不是罗吉特：

mcmc.logit = MCMClogit(SECONDARY.LEVEL ~ AGE + SEX + as.factor(DISTRICT), mcmc=1000, data=df)
head(summary(mcmc.logit)$statistics, n=15)
                             Mean SD Naive SE Time-series SE
(Intercept)            0.22304927  0        0              0
AGE                   -0.05566763  0        0              0
SEXMale                0.33312032  0        0              0
as.factor(DISTRICT)2   0.01497950  0        0              0
as.factor(DISTRICT)3   0.24880013  0        0              0
as.factor(DISTRICT)4   0.09670442  0        0              0
as.factor(DISTRICT)5   0.42470223  0        0              0
as.factor(DISTRICT)6   0.27617894  0        0              0
as.factor(DISTRICT)7  -0.03446564  0        0              0
as.factor(DISTRICT)8   0.41404924  0        0              0
as.factor(DISTRICT)9   0.35816907  0        0              0
as.factor(DISTRICT)10  0.08551302  0        0              0
as.factor(DISTRICT)11  0.07437629  0        0              0
as.factor(DISTRICT)12  0.09701028  0        0              0
as.factor(DISTRICT)13  0.29723229  0        0              0