Latent variable GIMME using model implied instrumental variables (MIIVs).

ABSTRACT: Researchers across many domains of psychology increasingly wish to arrive at personalized and generalizable dynamic models of individuals' processes. This is seen in psychophysiological, behavioral, and emotional research paradigms, across a range of data types. Errors of measurement are inherent in most data. For this reason, researchers typically gather multiple indicators of the same latent construct and use methods, such as factor analysis, to arrive at scores from these indices. In addition to accurately measuring individuals, researchers also need to find the model that best describes the relations among the latent constructs. Most currently available data-driven searches do not include latent variables. We present an approach that builds from the strong foundations of group iterativ

SUBMITTER: Gates KM 

PROVIDER: S-EPMC6933098 | biostudies-literature | 2020 Apr

REPOSITORIES: biostudies-literature