The Consequences of Ignoring Variability in Measurement Occasions Within Data Collection Waves in Latent Growth Models

Aydin B., LEITE W. L., ALGINA J.

MULTIVARIATE BEHAVIORAL RESEARCH, cilt.49, sa.2, ss.149-160, 2014 (SCI-Expanded) identifier identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 49 Sayı: 2
  • Basım Tarihi: 2014
  • Doi Numarası: 10.1080/00273171.2014.887901
  • Dergi Adı: MULTIVARIATE BEHAVIORAL RESEARCH
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Social Sciences Citation Index (SSCI), Scopus
  • Sayfa Sayıları: ss.149-160
  • Recep Tayyip Erdoğan Üniversitesi Adresli: Evet

Özet

In longitudinal data collection, it is common that each wave of collection spans several months. However, researchers using latent growth models commonly ignore variability in data collection occasions within a wave. In this study, we investigated the consequences of ignoring within-wave variability in measurement occasions using a Monte Carlo simulation and an empirical study. The results of the simulation study showed that ignoring heterogeneity resulted in biased estimates for some parameters, especially when heterogeneity was large and assessment dates had a skewed distribution. Models constructed on person-specific time points yielded precise estimates and more adequate model fit. In the empirical study, we demonstrated different time coding strategies with a subsample taken from Early Childhood Longitudinal Study Kindergarten Cohort.