aveEffPlot.RdFor objects of class glm, it calculates the change the average
predicted probability (like the one calculated by glmChange2) for a
hypothetical candidate set of values of a covariate.
aveEffPlot( obj, varname, data, R = 1500, nvals = 25, plot = TRUE, returnSim = FALSE, ... )
| obj | A model object of class |
|---|---|
| varname | Character string giving the variable name for which average effects are to be calculated. |
| data | Data frame used to fit |
| R | Number of simulations to perform. |
| nvals | Number of evaluation points at which the average probability will be calculated. |
| plot | Logical indicating whether plot should be returned, or just data
(if |
| returnSim | Logical indicating whether simulated predicted probabilities should be returned. |
| ... | Other arguments to be passed down to |
A plot or a data frame
The function plots the average effect of a model covariate, for objects of
class glm. The function does not work with poly unless the
coefficients are provided as arguments to the command in the model (see
example below).
data(france) p <- poly(france$lrself, 2) left.mod <- glm(voteleft ~ male + age + retnat + poly(lrself, 2, coefs=attr(p, "coefs")), data=france, family=binomial) aveEffPlot(left.mod, "age", data=france, plot=FALSE)#> s mean lower upper #> 1 15.000 0.6765131 0.6319245 0.7239427 #> 2 18.125 0.6695036 0.6277574 0.7137513 #> 3 21.250 0.6623682 0.6238755 0.7038904 #> 4 24.375 0.6551057 0.6189568 0.6936023 #> 5 27.500 0.6477150 0.6146938 0.6833190 #> 6 30.625 0.6401962 0.6097107 0.6727805 #> 7 33.750 0.6325496 0.6029008 0.6630809 #> 8 36.875 0.6247764 0.5970974 0.6530135 #> 9 40.000 0.6168786 0.5902648 0.6441606 #> 10 43.125 0.6088590 0.5825996 0.6358514 #> 11 46.250 0.6007210 0.5745658 0.6268975 #> 12 49.375 0.5924688 0.5639790 0.6194394 #> 13 52.500 0.5841072 0.5523231 0.6129205 #> 14 55.625 0.5756416 0.5399007 0.6069629 #> 15 58.750 0.5670779 0.5275635 0.6013725 #> 16 61.875 0.5584223 0.5148466 0.5970502 #> 17 65.000 0.5496811 0.5026301 0.5933379 #> 18 68.125 0.5408611 0.4895473 0.5894384 #> 19 71.250 0.5319689 0.4764357 0.5859694 #> 20 74.375 0.5230111 0.4617739 0.5822526 #> 21 77.500 0.5139942 0.4466346 0.5783165 #> 22 80.625 0.5049249 0.4318476 0.5745233 #> 23 83.750 0.4958093 0.4180289 0.5717735 #> 24 86.875 0.4866540 0.4027480 0.5679848 #> 25 90.000 0.4774650 0.3870172 0.5636187