Health Services and Outcomes Research Methodology

, Volume 12, Issue 4, pp 254-272

Open Access This content is freely available online to anyone, anywhere at any time.

Instrumental variable specifications and assumptions for longitudinal analysis of mental health cost offsets

  • A. James O’MalleyAffiliated withDepartment of Health Care Policy, Harvard Medical School Email author 


Instrumental variables (IVs) enable causal estimates in observational studies to be obtained in the presence of unmeasured confounders. In practice, a diverse range of models and IV specifications can be brought to bear on a problem, particularly with longitudinal data where treatment effects can be estimated for various functions of current and past treatment. However, in practice the empirical consequences of different assumptions are seldom examined, despite the fact that IV analyses make strong assumptions that cannot be conclusively tested by the data. In this paper, we consider several longitudinal models and specifications of IVs. Methods are applied to data from a 7-year study of mental health costs of atypical and conventional antipsychotics whose purpose was to evaluate whether the newer and more expensive atypical antipsychotic medications lead to a reduction in overall mental health costs.


Causal inference Exclusion restriction Fixed differences Instrumental variable Longitudinal Mental health costs