pool_predictions: Pool Predictions or Estimated Marginal Means

In javifar/ggeffects: Create Tidy Data Frames of Marginal Effects for 'ggplot' from Model Outputs

Description

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 ggpredict, ggemmeans or ggeffect.
...	Currently not used.

Details

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

Value

A data frame with pooled predictions.

References

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

Examples

# example for multiple imputed datasets
if (require("mice")) {
  data("nhanes2")
  imp <- mice(nhanes2, printFlag = FALSE)
  predictions <- lapply(1:5, function(i) {
    m <- lm(bmi ~ age + hyp + chl, data = complete(imp, action = i))
    ggpredict(m, "age")
  })
  pool_predictions(predictions)
}

javifar/ggeffects documentation built on Jan. 21, 2022, 12:04 a.m.