Robust SEs were computed because
of heteroscedasticity.
Not exact matches
White's general
heteroscedasticity test also indicated no presence
of heteroscedastic errors.
The estimator can be used to try to overcome autocorrelation and
heteroscedasticity of the residuals, which can impact the standard errors and thus the calculated t - statistics and p - values.
We also examined differences between experimental and control conditions in style
of response options via repeated measures ANOVA (using a Greenhouse - Geisser correction for
heteroscedasticity as appropriate).