American Board of Psychiatry and Neurology (ABPN) Practice Exam

When evaluating the relationship between a binary predictor variable and a continuous outcome variable, the t-test is particularly suitable. This statistical test is designed to compare the means of two groups. In this context, the binary predictor variable can be thought of as defining two groups. By using a t-test, one can determine if there is a statistically significant difference in the means of the continuous outcome variable between these two groups.

This approach is advantageous because it directly assesses how the two categories of the binary variable (often denoted as 0 and 1, or two different groups) influence or relate to the continuous variable. By contrasting the group means, the t-test provides insight into whether any observed difference is likely due to chance or is statistically significant, which is crucial for many fields, including psychology and medicine.

Other statistical methods might be less appropriate in this context. For instance, analysis of variance (ANOVA) is generally used when there are more than two groups to compare, and the chi-square (χ2) test is used for assessing the relationship between two categorical variables. Regression analysis can also be applicable but is typically more complex and might not directly address the hypothesis concerning mean differences between two specific groups. Therefore, the t-test is the most straightforward and relevant