Pool Predictions or Estimated Marginal Means — pool

This function "pools" (i.e. combines) multiple ggeffects objects, in a similar fashion as mice::pool().

Usage

pool_predictions(x, ...)

Arguments

x: A list of ggeffects objects, as returned by predict_response().
...: Currently not used.

Value

A data frame with pooled predictions.

Details

Averaging of parameters follows Rubin's rules (Rubin, 1987, p. 76).

References

Rubin, D.B. (1987). Multiple Imputation for Nonresponse in Surveys. New York: John Wiley and Sons.

Examples

# example for multiple imputed datasets
data("nhanes2", package = "mice")
imp <- mice::mice(nhanes2, printFlag = FALSE)
predictions <- lapply(1:5, function(i) {
  m <- lm(bmi ~ age + hyp + chl, data = mice::complete(imp, action = i))
  predict_response(m, "age")
})
pool_predictions(predictions)
#> # Predicted values of bmi
#> 
#> age   | Predicted |       95% CI
#> --------------------------------
#> 20-39 |     29.42 | 26.87, 31.97
#> 40-59 |     23.96 | 20.95, 26.98
#> 60-99 |     22.60 | 19.32, 25.89
#> 
#> Adjusted for:
#> * hyp =     no
#> * chl = 194.64