car (version 3.0-10)

# ncvTest: Score Test for Non-Constant Error Variance

## Description

Computes a score test of the hypothesis of constant error variance against the alternative that the error variance changes with the level of the response (fitted values), or with a linear combination of predictors.

## Usage

```ncvTest(model, ...)# S3 method for lm
ncvTest(model, var.formula, ...)# S3 method for glm
ncvTest(model, ...) # to report an error```

## Arguments

model

a weighted or unweighted linear model, produced by `lm`.

var.formula

a one-sided formula for the error variance; if omitted, the error variance depends on the fitted values.

arguments passed down to methods functions; not currently used.

## Value

The function returns a `chisqTest` object, which is usually just printed.

## Details

This test is often called the Breusch-Pagan test; it was independently suggested with some extension by Cook and Weisberg (1983).

`ncvTest.glm` is a dummy function to generate an error when a `glm` model is used.

## References

Breusch, T. S. and Pagan, A. R. (1979) A simple test for heteroscedasticity and random coefficient variation. Econometrica 47, 1287--1294.

Cook, R. D. and Weisberg, S. (1983) Diagnostics for heteroscedasticity in regression. Biometrika 70, 1--10.

Fox, J. (2016) Applied Regression Analysis and Generalized Linear Models, Third Edition. Sage.

Fox, J. and Weisberg, S. (2019) An R Companion to Applied Regression, Third Edition, Sage.

Weisberg, S. (2014) Applied Linear Regression, Fourth Edition, Wiley.

## See Also

`hccm`, `spreadLevelPlot`

## Examples

```# NOT RUN {
ncvTest(lm(interlocks ~ assets + sector + nation, data=Ornstein))

ncvTest(lm(interlocks ~ assets + sector + nation, data=Ornstein),
~ assets + sector + nation, data=Ornstein)
# }
```