REndo (version 2.4.10)

predict.rendo.multilevel: Predict method for Multilevel GMM Estimations

Description

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

Usage

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

Value

predict.rendo.multilevel produces a vector of predictions

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.

See Also

The model fitting function multilevelIV

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