# Alternatives to balance tables to examine selection bias

I was wondering if someone has ideas to statistically examine selection into programme participation? For example, would it make sense to present the results of a propensity score analysis?

Thank you

For goal 1), a balance table does exactly what you want. It is literally a table displaying how the participants and non-participants differ from each other. This is important to let readers know what the goal of an analysis is that seeks to remove confounding (e.g., propensity score or regression analysis). Readers can examine the balance table before and after adjustment and decide for themselves if enough variables have been accounted for and if balance is sufficient to warrant trust in the effect estimate. A balance table doesn't describe how participation is selected, but just describes the consequences of non-random selection into participation. That is, it describes the consequences of the treatment assignment mechanism. In terms of visual display, if you want to avoid a table, you can look into making a Love plot. The R package cobalt makes these easily and has examples in its documentation.