Methods used for assumptions to be checked for statistical methods
REGRESSION
The linear regression models used for the primary analysis assume that residuals are normally distributed. Robust standard errors allow for potential heteroscedasticity according to levels of predictor variables, but do make an assumption of normality conditional on levels of predictor variables. This assumption will be checked by examination of appropriate quantile–quantile plots of standardised residuals. The central limit theorem ensures that results are robust provided that violations of the normality assumptions are not substantial. Minor violations, even if statistically significant, are of little practical consequence. For this reason, formal hypothesis tests of normality assumptions will not be carried out.