FitRegression: 'FitRegression'

In Displayr/flipRegression: Estimates standard regression models

FitRegression

Description

Fits a regression model.

Usage

FitRegression(
  .formula,
  .estimation.data,
  .weights,
  type,
  robust.se,
  outlier.prop.to.remove,
  seed = 12321,
  dummy.processed.data = NULL,
  ...
)

Arguments

.formula	An object of class formula (or one that can be coerced to that class): a symbolic description of the model to be fitted. The details of type specification are given under ‘Details’.
.estimation.data	A data.frame.
.weights	An optional vector of sampling weights, or, the name or, the name of a variable in data. It may not be an expression.
type	See Regression.
robust.se	Computes standard errors that are robust to violations of the assumption of constant variance, using the HC1 (degrees of freedom) modification of White's (1980) estimator (Long and Ervin, 2000). This parameter is ignored if weights are applied (as weights already employ a sandwich estimator).
outlier.prop.to.remove	A single numeric value that determines the percentage of data points to remove from the analysis. The data points removed correspond to those in the proportion with the largest residuals. A value of 0 or NULL would denote no points are removed. A value x, with 0 < x < 0.5 (not inclusive) would denote that a percentage between none and 50% of the data points are removed.
seed	A integer seed to generate the surrogate residuals.
dummy.processed.data	A list containing the output from EstimationData when the dummy adjustment for missing data is used. It is only needed when outliers are removed with dummy adjustment. In that situation, the estimation data needs to be recalibrated in case any adjustment variables are redundant or singular when outliers are removed from the data.
...	Arguments to the wrapped functions.

Displayr/flipRegression documentation built on March 2, 2024, 3:51 a.m.