Joint Analysis of Zero-heavy Longitudinal Outcomes: Models and Comparison of Study Designs

摘要: Understanding the patterns and mechanisms of process desistance from criminal activity is imperative for development effective sanctions legal policy. Methodological challenges in analysis longitudinal behaviour data include need to develop methods multivariate discrete data, incorporating modulating exposure variables several possible sources zero-inflation. We new tools zero-heavy joint outcome which address these provide novel insights on processes related offending patterns. Comparisons with existing approaches demonstrate benefits utilizing modeling frameworks incorporate distinct zeros. An additional concern this context heaping self-reported counts where recorded are rounded different levels precision. Alternatively, more accurate that less burdensome participants record may be obtained by collecting information presence/absence events at periodic assessments. compare two study designs choice design when expected. The contributions research work following: (i) Developing a general framework multiple zero-inflated count outcomes incorporates variety probabilistic structures zero counts. (ii) Accommodating subgroup subjects who not at-risk engage particular (iii) Incorporating effect time-dependent variable settings some prohibited during treatment. (iv) Illustrating extent counts, arising mechanisms, can introduce bias, impeding identification important risk factors (v) Identifying situations there very little loss efficiency depending partition time records underlying rate events. (vi) Providing recommendations studies concern. (vii) Modeling binary mixture model approach allows differential rates recurrence i events, generating resolve.