Melissa M. Garrido Ph.D., Partha Deb Ph.D., James F. Burgess Ph.D., Joan D. Penrod Ph.D.
To compare methods of analyzing endogenous treatment effect models for nonlinear outcomes and illustrate the impact of model specification on estimates of treatment effects such as health care costs.
Secondary data on cost and utilization for inpatients hospitalized in five eterans ffairs acute care facilities in 2005–2006.
We compare results from analyses with full information maximum simulated likelihood (); control function () approaches employing different types and functional forms for the residuals, including the special case of two‐stage residual inclusion; and two‐stage least squares (2). As an example, we examine the effect of an inpatient palliative care () consultation on direct costs of care per day.
Data Collection/Extraction Methods
We analyzed data for 3,389 inpatients with one or more life‐limiting diseases.
The distribution of average treatment effects on the treated and local average treatment effects of a consultation depended on model specification. and estimates were more similar to each other than to 2 estimates. estimates were sensitive to choice and functional form of residual.
When modeling cost or other nonlinear data with endogeneity, one should be aware of the impact of model specification and treatment effect choice on results.