[R] Power test binominal GLM model

[davide cortellino]

Dear All


I have run the following GLM binominal model on a dataset composed by the
following variables:

TRAN_DURING_CAMP_FLG enviados bono_recibido
                 0        1     benchmark
                 0        1     benchmark
                 0        1     benchmark
                 0        1     benchmark
                 0        1     benchmark
                 0        1     benchmark


   - tran_during_flag= redemption yes/no (1/0)
   - enviados= counter variables, all 1's
   - bono_recibido= benchmark(control group) or test groups (two type of
   test groups)

The model used has been

glm(TRAN_DURING_CAMP_FLG~bono_recibido,exp2,family="binomial")

                          Estimate Std. Error     z value
Pr(>|z|)(Intercept)             -1.4924117 0.01372190 -108.761315
0.000000e+00
bono_recibidoBONO3EUROS -0.8727739 0.09931119   -8.788274 1.518758e-18
bono_recibidoBONO6EUROS  0.1069435 0.02043840    5.232480 1.672507e-07

The scope for this model was to test if there was significative difference
in the redemption rate between control group and test groups. Now, applying
the post hoc test:

> Treat.comp<-glht(mod.binposthoc,mcp(bono_recibido='Tukey'))> summary(Treat.comp) # el modelo se encuentra en  log odds aqui

     Simultaneous Tests for General Linear Hypotheses
Multiple Comparisons of Means: Tukey Contrasts

Fit: glm(formula = TRAN_DURING_CAMP_FLG ~ bono_recibido, family = "binomial",
    data = exp2)
Linear Hypotheses:
                             Estimate Std. Error z value Pr(>|z|)
BONO3EUROS - benchmark == 0  -0.87277    0.09931  -8.788  < 1e-09 ***
BONO6EUROS - benchmark == 0   0.10694    0.02044   5.232 3.34e-07 ***
BONO6EUROS - BONO3EUROS == 0  0.97972    0.09952   9.845  < 1e-09
***---Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’
1(Adjusted p values reported -- single-step method)

It confirm that the differences are significatively differents, however, I
would check the power of the model in assessing these differences. I have
checked several time both on cross validates and on the web but it seems
there is no pre-made function which enable the user to compute the power of
glm models. Is it the case? Does anyone know of available packages or
methodologies to achive a power test in a glm binominal model?

Bests

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