Performance of the Longitudinal Actor-Partner Interdependence Model in Case of Large Amounts of Missing Values: Challenges and Possible Alternatives.

ABSTRACT: Researchers interested in dyadic processes increasingly collect intensive longitudinal data (ILD), with the longitudinal actor-partner interdependence model (L-APIM) being a popular modeling approach. However, due to non-compliance and the use of conditional questions, ILD are almost always incomplete. These missing data issues become more prominent in dyadic studies, because partners often miss different measurement occasions or disagree about features that trigger conditional questions. Large amounts of missing data challenge the L-APIM's estimation performance. Specifically, we found that non-convergence occurred when applying the L-APIM to pre-existing dyadic diary data with a lot of missing values. Using a simulation study, we systematically examined the performance of the L-APIM in d

SUBMITTER: Ji Y 

PROVIDER: S-EPMC12483710 | biostudies-literature | 2025 Jun

REPOSITORIES: biostudies-literature