  Ecological momentary assessment (EMA) data have a broad base of application
in the study of time trends and relations. In EMA studies, there are a number
of design considerations which influence the analysis of the data. One general
modeling framework is particularly well-suited for these analyses: state-space
modeling. Here, we present the state-space modeling framework with
recommendations for the considerations that go into modeling EMA data. These
recommendations can account for the issues that come up in EMA data analysis
such as idiographic versus nomothetic modeling, missing data, and stationary
versus non-stationary data. In addition, we suggest R packages in order to
implement these recommendations in practice. Overall, well-designed EMA studies
offer opportunities for researchers to handle the momentary minutiae in their
assessment of psychological phenomena.
