ivregMethods function

Methods for "ivreg" Objects

Various methods for processing "ivreg" objects; for diagnostic methods, see ivregDiagnostics.

## S3 method for class 'ivreg'
coef(object, component = c("stage2", "stage1"), complete = TRUE, ...)

## S3 method for class 'ivreg'
vcov(object, component = c("stage2", "stage1"), complete = TRUE, ...)

## S3 method for class 'ivreg'
bread(x, ...)

## S3 method for class 'ivreg'
estfun(x, ...)

## S3 method for class 'ivreg'
vcovHC(x, ...)

## S3 method for class 'ivreg'
terms(x, component = c("regressors", "instruments", "full"), ...)

## S3 method for class 'ivreg'
model.matrix(
  object,
  component = c("regressors", "projected", "instruments"),
  ...
)

## S3 method for class 'ivreg_projected'
model.matrix(object, ...)

## S3 method for class 'ivreg'
predict(
  object,
  newdata,
  type = c("response", "terms"),
  na.action = na.pass,
  se.fit = FALSE,
  interval = c("none", "confidence", "prediction"),
  df = Inf,
  level = 0.95,
  weights,
  ...
)

## S3 method for class 'ivreg'
print(x, digits = max(3, getOption("digits") - 3), ...)

## S3 method for class 'ivreg'
update(object, formula., ..., evaluate = TRUE)

## S3 method for class 'ivreg'
residuals(
  object,
  type = c("response", "projected", "regressors", "working", "deviance", "pearson",
    "partial", "stage1"),
  ...
)

## S3 method for class 'ivreg'
Effect(focal.predictors, mod, ...)

## S3 method for class 'ivreg'
formula(x, component = c("complete", "regressors", "instruments"), ...)

## S3 method for class 'ivreg'
find_formula(x, ...)

## S3 method for class 'ivreg'
alias(object, ...)

## S3 method for class 'ivreg'
qr(x, ...)

## S3 method for class 'ivreg'
weights(object, type = c("variance", "robustness"), ...)

Arguments

• object, model, mod: An object of class "ivreg".

• component: For terms, "regressors", "instruments", or "full"; for model.matrix, "projected", "regressors", or "instruments"; for formula, "regressors", "instruments", or "complete"; for coef and vcov, "stage2" or "stage1".

• complete: If TRUE, the default, the returned coefficient vector (for coef) or coefficient-covariance matrix (for vcov) includes elements for aliased regressors.

• ...: arguments to pass down.

• x: An object of class "ivreg".

• newdata: Values of predictors for which to obtain predicted values; if missing predicted (i.e., fitted) values are computed for the data to which the model was fit.

• type: For predict, one of "response" (the default) or "terms"; for residuals, one of "response" (the default), "projected", "regressors", "working", "deviance", "pearson", or "partial"; type = "working" and "response" are equivalent, as are type = "deviance" and "pearson"; for weights, "variance" (the default) for invariance-variance weights (which is NULL for an unweighted fit) or "robustness" for robustness weights (available for M or MM estimation).

• na.action: na method to apply to predictor values for predictions; default is na.pass.

• se.fit: Compute standard errors of predicted values (default FALSE).

• interval: Type of interval to compute for predicted values: "none" (the default), "confidence" for confidence intervals for the expected response, or "prediction" for prediction intervals for future observations.

• df: For predict, degrees of freedom for computing t-distribution confidence- or prediction-interval limits; the default, Inf, is equivalent to using the normal distribution; if NULL, df is taken from the residual degrees of freedom for the model. These tests are not to be confused with the regression diagnostics provided elsewhere in the ivreg

  package: see ivregDiagnostics.

• level: for confidence or prediction intervals, default 0.95.

• weights: Either a numeric vector or a one-sided formula to provide weights for prediction intervals when the fit is weighted. If weights and newdata are missing, the weights are those used for fitting the model.

• digits: For printing.

• formula.: To update model.

• evaluate: If TRUE, the default, the updated model is evaluated; if FALSE the updated call is returned.

• focal.predictors: Focal predictors for effect plot, see Effect.

See Also

ivreg, ivreg.fit, ivregDiagnostics