Summary of zelig results based on multiply imputed data - Zelig

11 Nov 2012

I tried the following examples from the Zelig manual:

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library(ZeligChoice)

data(immi1, immi2, immi3, immi4, immi5)
z.out <- zelig(as.factor(ipip) ~ wage1992 + prtyid + ideol,
               model = "ologit",
               data = mi(immi1, immi2, immi3, immi4, immi5))
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And got the following:

---------------------------------
...
  summary(z.out) $immi1
Call:
polr(formula = as.factor(as.factor(ipip)) ~ wage1992 + prtyid +
    ideol, data = Data.frame, Hess = TRUE, method = "logistic")

Coefficients:
            Value Std. Error t value
wage1992 -0.47233    0.19834  -2.381
prtyid    0.02219    0.01974   1.124
ideol     0.10878    0.02879   3.779

Intercepts:
    Value    Std. Error t value
1|2  -2.9685   0.1835   -16.1768
2|3  -1.9162   0.1646   -11.6420
3|4   0.3207   0.1570     2.0424
4|5   1.4746   0.1597     9.2359

Residual Deviance: 6696.117
AIC: 6710.117

$immi2
Call:
polr(formula = as.factor(as.factor(ipip)) ~ wage1992 + prtyid +
    ideol, data = Data.frame, Hess = TRUE, method = "logistic")

Coefficients:
            Value Std. Error t value
wage1992 -0.38143    0.19860  -1.921
prtyid    0.02056    0.01979   1.039
ideol     0.07391    0.02898   2.551

Intercepts:
    Value    Std. Error t value
1|2  -3.1490   0.1855   -16.9795
2|3  -2.0003   0.1639   -12.2076
3|4   0.2255   0.1559     1.4459
4|5   1.3535   0.1583     8.5523

Residual Deviance: 6707.571
AIC: 6721.571

$immi3
Call:
polr(formula = as.factor(as.factor(ipip)) ~ wage1992 + prtyid +
    ideol, data = Data.frame, Hess = TRUE, method = "logistic")

Coefficients:
             Value Std. Error t value
wage1992 -0.475120    0.19841 -2.3947
prtyid   -0.002367    0.01998 -0.1185
ideol     0.139663    0.02919  4.7839

Intercepts:
    Value    Std. Error t value
1|2  -3.0410   0.1849   -16.4486
2|3  -1.8938   0.1627   -11.6372
3|4   0.3633   0.1554     2.3381
4|5   1.4932   0.1580     9.4517

Residual Deviance: 6670.636
AIC: 6684.636

$immi4
Call:
polr(formula = as.factor(as.factor(ipip)) ~ wage1992 + prtyid +
    ideol, data = Data.frame, Hess = TRUE, method = "logistic")

Coefficients:
            Value Std. Error t value
wage1992 -0.73006    0.19853  -3.677
prtyid    0.03575    0.01997   1.790
ideol     0.10920    0.02918   3.742

Intercepts:
    Value    Std. Error t value
1|2  -3.2126   0.1877   -17.1201
2|3  -2.0535   0.1645   -12.4860
3|4   0.2400   0.1557     1.5411
4|5   1.4158   0.1582     8.9471

Residual Deviance: 6628.474
AIC: 6642.474

$immi5
Call:
polr(formula = as.factor(as.factor(ipip)) ~ wage1992 + prtyid +
    ideol, data = Data.frame, Hess = TRUE, method = "logistic")

Coefficients:
           Value Std. Error t value
wage1992 -0.5001    0.19919  -2.510
prtyid    0.0225    0.01989   1.131
ideol     0.0967    0.02837   3.408

Intercepts:
    Value    Std. Error t value
1|2  -3.1471   0.1858   -16.9404
2|3  -1.9431   0.1629   -11.9256
3|4   0.2795   0.1554     1.7991
4|5   1.4339   0.1579     9.0808

Residual Deviance: 6699.731
AIC: 6713.731
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My question is: how do I get the combined results? I am using Zelig 4.0-11.

Thanks.

Best,
Shige