What is one of the basic questions for appraising causal inferences based on empirical studies?

One of the fundamental aspects of appraising causal inferences in empirical studies revolves around the establishment of a control group. A control group serves as a baseline against which the treatment group’s outcomes can be compared. This is crucial because it helps to determine whether the observed effects can indeed be attributed to the treatment or intervention rather than to confounding factors or biases.

The presence of a control group strengthens the internal validity of the study, allowing for a clearer interpretation of the causal relationship between variables. Without a control group, it becomes challenging to disentangle the effects of the intervention from other external influences that could affect the results.

While the other options—sample size, accuracy of outcome measurement, and data analysis techniques—are all important considerations in evaluating the robustness of a study, they do not directly pertain to establishing a causal inference as effectively as the presence of a control group does. Ultimately, having a control group provides a framework that enhances the ability to draw legitimate cause-and-effect conclusions from the data.