2016-02-12 29 views
0

我從一個離散選擇實驗分析數據,我想不出有什麼重物mlogit使用時,我指定weights對由R使用mlogit

下面的代碼有什麼重物:

mlogit(formula = RES ~ -1 + V1 + V2, data = data, 
    reflevel = 1, rpar = c(V1 = "n", V2 = "n"), weights = Weight1, correlation = FALSE, 
    halton = NA, panel = TRUE, seed = 1234567890, method = "bfgs") 

產生以下估計:

Frequencies of alternatives: 
     1  2 
0.22987 0.77013 

bfgs method 
19 iterations, 0h:15m:34s 
g'(-H)^-1g = 4.29E-08 
gradient close to zero 

Coefficients : 
     Estimate Std. Error t-value Pr(>|t|)  
V1  0.859789 0.019076 45.072 < 2.2e-16 *** 
V2  2.705395 0.039205 69.006 < 2.2e-16 *** 
sd.V1 0.483573 0.023502 20.576 < 2.2e-16 *** 
sd.V2 3.916796 0.062557 62.612 < 2.2e-16 *** 
--- 
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1 

Log-Likelihood: -9297.9 

random coefficients 
     Min. 1st Qu. Median  Mean 3rd Qu. Max. 
V1 -Inf 0.53362451 0.8597892 0.8597892 1.185954 Inf 
V2 -Inf 0.06355681 2.7053955 2.7053955 5.347234 Inf 

然而,當我運行在Stata相同的混合邏輯模型,下面的命令:

mixlogit res [pweight=weight1], group(str) id(id) rand(V1 V2) ln(0) 

給了我下面的估計:

Mixed logit model        Number of obs  =  41,154 
               Wald chi2(2)  =  395.55 
Log likelihood = -9089.7906      Prob > chi2  =  0.0000 

------------------------------------------------------------------------------ 
      |    Robust 
     res |  Coef. Std. Err.  z P>|z|  [95% Conf. Interval] 
-------------+---------------------------------------------------------------- 
Mean   | 
      V1 | 1.207748 .0774815 15.59 0.000  1.055887 1.359608 
      V2 | 4.458814 .2356245 18.92 0.000  3.996998 4.920629 
-------------+---------------------------------------------------------------- 
SD   | 
      V1 | 1.107036 .0765884 14.45 0.000  .9569252 1.257146 
      V2 | 4.444472 .3586858 12.39 0.000  3.741461 5.147483 
------------------------------------------------------------------------------ 

無論權重方案我在Stata使用(pweightiweight,或者fweight),我得到了類似的結果,決不是R給我的結果。

但是,當我在任一程序中運行未加權的混合logit模型時,我得到相同的估計值。這使得我的權重是顯而易見的問題,但我無法弄清楚R在做什麼。

幫助?

回答

0

這隻能由我看到,但如果有人遇到過這種情況,問題不是的權重。事實是R命令(R = 10, tol = 10)中的停止條件過於寬鬆。如果您將R設置爲較大值,將tol設置得較小,則這兩個估計值會收斂。