The article compares two types of biases in scientific experiments: post-treatment bias and priming bias. Post-treatment bias happens when variables affected by the treatment influence the results. Priming bias occurs when measuring certain factors before treatment affects how people respond to the treatment. The researchers analyzed three experimental designs to see how measuring moderators before or after treatment impacts the results. They found that measuring moderators before treatment can lead to priming bias, while measuring them after treatment can lead to post-treatment bias. By setting boundaries on these biases, researchers can better understand how their findings might be influenced.