We’re fitting a model that tests the efficacy of a treatment (e.g., a pharmaceutical product). The DV is Recovered, a binary variable (0/1), defined as numeric nominal. The research question is whether the treatment affects the expression of a precondition and thus improves recovery. We expect that people with certain level of the precondition will react differently to the treatment, i.e., an interaction effect. We fit a generalized regression model with binomial distribution. The predictors are 1) whether the person received treatment (Treatment; binary), 2) the variable whose expression should be affected by the treatment (Precondition, continuous), 3-4) two continuous control variables (Period and Q), as well as an 5) interaction term between Treatment and Precondition. The regression equation defaults to calculate the likelihood of Recovered=0, but we’re interested in predicting Recovered=1. How do we change the default? Confusingly, the parameter estimates shows the treatment parameter as “Treatment[0-1]”. Does this mean that this is the effect of no treatment or treatment? A very important distinction, obviously. What’s the right way to interpret the interaction effect? Specifically, what does “-226.24” mean? The output is below. Thanks for your help! Generalized Regression for Recovered = 0 Model Comparison Show Response Distribution Estimation Method Validation Method Nonzero Parameters AICc BIC Generalized RSquare [x] Binomial Logistic Regression None 5 3677.7423 3708.3526 0.1934902 Model Launch Binomial Lasso [ ] Adaptive AICc [ ] Early Stopping Logistic Regression Model Summary Response Recovered Distribution Binomial Estimation Method Logistic Regression Validation Method None Probability Model Link Logit Measure Number of rows 6128 Sum of Frequencies 3380 -LogLikelihood 1833.8622 Number of Parameters 5 BIC 3708.3526 AICc 3677.7423 Generalized RSquare 0.1934902 Parameter Estimates for Original Predictors Term Estimate Std Error Wald ChiSquare Prob > ChiSquare Lower 95% Upper 95% Intercept 0.8755145 0.1101971 63.122825 <.0001* 0.6595322 1.0914968 Treatment[0-1] 0.0643045 0.0696953 0.8512868 0.3562 -0.072296 0.2009047 Period 0.1015936 0.0130748 60.375781 <.0001* 0.0759675 0.1272197 Q 0.0012641 0.0004935 6.5606499 0.0104* 0.0002968 0.0022314 Precondition -0.000095 0.0001314 0.522411 0.4698 -0.000352 0.0001626 (Precondition-226.24)*Treatment[0-1] 0.0009875 0.0003172 9.6914587 0.0019* 0.0003658 0.0016093 (All the variable names are aliases due to confidentiality requirements).
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