ncvTest function

Score Test for Non-Constant Error Variance

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.

ncvTest(model, ...)

## S3 method for class 'lm'
ncvTest(model, var.formula, ...)

## S3 method for class '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.

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.

Returns

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

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.

Author(s)

John Fox jfox@mcmaster.ca , Sandy Weisberg sandy@umn.edu

See Also

hccm, spreadLevelPlot

Examples

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

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