[R] how to use the EV AND condEV from BMA's results?

From: zhijie zhang <epistat_at_gmail.com>
Date: Thu 03 Aug 2006 - 22:53:49 EST


Dear friends,
In R, the help of "bic.glm" tells the difference between postmean(the posterior mean of each coefficient from model averaging) and condpostmean(the posterior mean of each coefficient conditional on the variable being included in the model), But it's still unclear about the results explanations, and the artile of Rnews in 2005 on BMA still don't give more detail on it.
Suppose my results of logistic regression analyzed by bic.glm (BMA) as follows:(dataset is birthwt(MASS) and i include the interaction)

                  p!=0      EV      SD     condEV  cond SD    model 1   model
2 model 3 model 4 model 5
Intercept         100     0.1841  1.2204   0.184    1.220        1.017
1.175    -0.853    -1.057     0.532

age                17.8   -0.0113  0.0285  -0.063    0.036         .
.         .         .       -0.071

lwt               50.0   -0.0079  0.0093   -0.016   0.007       -0.017    -
0.017      .         .         .

smokeTRUE          9.5   0.0469  0.1798   0.496    0.345         .
    .

. . .
ptdTRUE 99.4 1.5161 0.4751 1.526 0.461 1.407 1.596 1.732 1.463 1.608 htTRUE 54.4 0.9477 1.0269 1.742 0.744 1.894 1.930 . . . uiTRUE 13.3 0.0976 0.2987 0.731 0.453 . . . . . ftv 12.3
.1 -0.0257 0.5117 -0.209 2.438 .
. -0.867 . .
.2+ 0.7470 2.1277 6.081 3.371 .
. 6.024 . . age.ftv1 33.7 -0.0136 0.0278 -0.040 0.035 . - 0.036 . . . age.ftv2. 15.9 -0.0340 0.0950 -0.214 0.135 . . -0.271 . . smokeTRUE.uiTRUE 2.4 0.0103 0.1209 0.422 0.652 .
.
. . .
nVar 3 4 3 1 2 post prob 0.117 0.086 0.083 0.061 0.044
  1. how should I write my final logistic model?
  2. Which parameter estimation should be used, condEV OR EV? How should I use the two different parameter estimations correctly? Thanks for your precious time!
-- 
Kind Regards,
Zhi Jie,Zhang

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Received on Thu Aug 03 22:59:26 2006

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