HAIF: Stata module to compute Homoskedastic Adjustment Inflation Factors for model selection
haif calculates homoskedastic adjustment inflation factors (HAIFs) for core variables in the corevarlist, caused by adjustment by the additional variables specified by addvars(). HAIFs are calculated for the variances and standard errors of estimated linear regression parameters corresponding to the core variables. For each variance (or standard error), the HAIF is defined as the ratio between that variance (or standard error) of that parameter, in a model containing both the core variables and the additional variables, to the corresponding variance (or standard error) of the same parameter, in a model containing only the core variables, calculated assuming that the second model is true, and also assuming that the outcome variable is homoskedastic (meaning that it has equal variances in all subpopulations defined by the predictor variables). haifcomp calculates the ratios between the HAIFs for the same core variables caused by adjustment for two alternative lists of additional variables, namely a numerator list and a denominator list. haif and haifcomp are intended for use in model selection, allowing the user to choose a model based on the joint distribution of the exposures and confounders, before estimating the parameters of the model from the data on the outcome variable.
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