These advantages, however, are not realized in all applications of IDA and, as with any tool for conducting pooled data analysis, IDA is not appropriate for every multi-study application. For example, in our experience, limitations in deriving comparable measures across studies and in identifying age overlap for studies pooled through cohort sequential methods may make IDA infeasible or at least indefensible for some questions. One difficulty in stating when IDA may or may not be useful is that we view IDA as a methodological framework for pooled data analysis rather than a set of specific techniques or analyses. In part, this is because the specific techniques and analyses used in IDA depend on the application at hand. The IDA framework is relevant to testing a variety of questions within clinical psychology, including those about measurement, cross-sectional associations, longitudinal prediction, and treatment effects. Just as we may use a variety of statistical techniques and analyses to answer questions about these issues in a single study, the IDA framework provides a set of guidelines that may also be widely applied across a
