predict.rendo.multilevel function

Predict method for Multilevel GMM Estimations

Predicted values based on multilevel models employing the GMM approach for hierarchical data with endogenous regressors.

## S3 method for class 'rendo.multilevel'
predict(
  object,
  newdata,
  model = c("REF", "FE_L2", "FE_L3", "GMM_L2", "GMM_L3"),
  ...
)

Arguments

• object: Object of class inheriting from "rendo.multilevel"
• newdata: An optional data frame in which to look for variables with which to predict. If omitted, the fitted values for the specified model are returned.
• model: character string to indicate for which fitted model predictions are made. Possible values are: "REF", "FE_L2", "FE_L3", "GMM_L2", or "GMM_L3".
• ...: ignored, for consistency with the generic function.

Returns

predict.rendo.multilevel produces a vector of predictions

Examples

data("dataMultilevelIV")

# Two levels
res.ml.L2 <- multilevelIV(y ~ X11 + X12 + X13 + X14 + X15 + X21 + X22 + X23 + X24 + X31 +
                          X32 + X33 + (1|SID) | endo(X15),
                          data = dataMultilevelIV, verbose = FALSE)
predict(res.ml.L2, model = "FE_L2")

# using the data used for fitting also for predicting,
#    correctly results in fitted values
all.equal(predict(res.ml.L2, dataMultilevelIV, model = "GMM_L2"),
          fitted(res.ml.L2, model = "GMM_L2")) # TRUE

See Also

The model fitting function multilevelIV