10.6084/m9.figshare.3482039.v1 Brian Neelon Brian Neelon James O'Malley James O'Malley Valerie Smith Valerie Smith Data From: Modeling Zero-Modified Count and Semicontinuous Data in Health Services Research, Part 2: Case Studies Wiley 2016 Health services research Hurdle model Semicontinuous data Two-part model Zero inflation Medicine Statistics 2016-07-12 09:34:44 Dataset https://wiley.figshare.com/articles/dataset/Data_From_Modeling_Zero-Modified_Count_and_Semicontinuous_Data_in_Health_Services_Research_Part_2_Case_Studies/3482039 This article is the second installment of a two-part tutorial on the analysis of zero-modified count and semicontinuous data. Part 1, which appears as a companion piece in this issue of Statistics in Medicine, provides a general background and overview of the topic, with particular emphasis on applications to health services research. Here, we present three case studies highlighting various approaches for the analysis of zero-modified data. The first case study describes methods for analyzing zero-inflated longitudinal count data. Case Study 2 considers the use of hurdle models for the analysis of spatiotemporal count data. The third case study discusses an application of marginalized two-part models to the analysis of semicontinuous health expenditure data.