The bivariate probit model helps researchers understand how two separate processes can lead to a single outcome, like COVID-19 cases being both spread and detected. This model can be used to study various topics, like corporate wrongdoing or new business ventures. By using simulations, researchers found that the bivariate probit model works best with larger sample sizes. They applied this model to analyze COVID-19 reports in the US at the county level. This approach can be useful for studying different organizational outcomes in the future.