The article explores different methods for estimating the effects of treatments in scientific studies. By using balancing constraints, researchers can improve the accuracy of their estimates. The study found that even with these constraints, it is still important to correctly specify the model used to estimate treatment effects. Additionally, when dealing with a lot of different factors, using a propensity score model can lead to better estimates. This suggests that developing flexible models based on the data is crucial for accurate results.