Testing in binary response index models

In the context of binary response index models, "testing" typically refers to the statistical methods used to evaluate hypotheses about the relationships between independent variables and a binary dependent variable. Binary response models, such as the logistic regression model or the probit model, are commonly used to model situations where the outcome of interest can take on one of two discrete values (e.g., success/failure, yes/no, or 1/0).