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Logistic regression is a statistical method for estimating the contribution of multiple predictor (“independent”) variables, such as demographic and clinical characteristics, to a dichotomous outcome (“dependent”) variable. (A dichotomous outcome variable is one with only 2 possible values, such as dead/alive.) In the study of autism disparities by Harstad et al, the predictors included maternal education and ethnicity and the dichotomous outcome was receipt of an Individualized Education Program (IEP). The main results of a logistic regression are adjusted odds ratios and confidence intervals for each predictor variable included in the model. These results are usually highlighted in the abstract, with the complete model presented in a table.
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