A Limited Information Estimator for Dynamic Factor Models

Zachary F. Fisher, Kenneth A. Bollen, Kathleen M. Gates

Research output: Contribution to journalArticlepeer-review

13 Scopus citations


Structural equation modeling (SEM) is an increasingly popular method for examining multivariate time series data. As in cross-sectional data analysis, structural misspecification of time series models is inevitable, and further complicated by the fact that errors occur in both the time series and measurement components of the model. In this article, we introduce a new limited information estimator and local fit diagnostic for dynamic factor models within the SEM framework. We demonstrate the implementation of this estimator and examine its performance under both correct and incorrect model specifications via a small simulation study. The estimates from this estimator are compared to those from the most common system-wide estimators and are found to be more robust to the structural misspecifications considered.

Original languageEnglish (US)
Pages (from-to)246-263
Number of pages18
JournalMultivariate Behavioral Research
Issue number2
StatePublished - Mar 4 2019

All Science Journal Classification (ASJC) codes

  • Statistics and Probability
  • Experimental and Cognitive Psychology
  • Arts and Humanities (miscellaneous)


Dive into the research topics of 'A Limited Information Estimator for Dynamic Factor Models'. Together they form a unique fingerprint.

Cite this