Contents
Does Heteroskedasticity affect t test?
Consequences of Heteroscedasticity The OLS estimators and regression predictions based on them remains unbiased and consistent. Because of the inconsistency of the covariance matrix of the estimated regression coefficients, the tests of hypotheses, (t-test, F-test) are no longer valid.
What is reset test in R?
The RESET test is a popular diagnostic for correctness of functional form. The basic assumption is that under the alternative the model can be written in the form y=X * beta + Z * gamma. Z is generated by taking powers either of the fitted response, the regressor variables, or the first principal component of X .
How do you adjust Heteroskedasticity?
Correcting for Heteroscedasticity One way to correct for heteroscedasticity is to compute the weighted least squares (WLS) estimator using an hypothesized specification for the variance. Often this specification is one of the regressors or its square.
How to obtain heteroskedasticity robust standard errors in R?
Since we already know that the model above suffers from heteroskedasticity, we want to obtain heteroskedasticity robust standard errors and their corresponding t values. In R the function coeftest from the lmtest package can be used in combination with the function vcovHC from the sandwich package to do this.
What does heteroskedasticity mean for Standard Model testing?
This means that standard model testing methods such as t tests or F tests cannot be relied on any longer. This post provides an intuitive illustration of heteroskedasticity and covers the calculation of standard errors that are robust to it.
Is there a RESET test for model misspecification?
Some have argued that RESET is a very general test for model misspecification, including unobserved omitted variables and heteroskedasticity. Unfortunately, such use of RESET is largely misguided.
Which is the Wald function for heteroskedasticity?
For a heteroskedasticity robust F test we perform a Wald test using the waldtest function, which is also contained in the lmtest package. It can be used in a similar way as the anova function, i.e., it uses the output of the restricted and unrestricted model and the robust variance-covariance matrix as argument vcov.