Item Parceling Techniques in Structural Equation Modeling
Summary
Item parceling refers to the practice of aggregating individual questionnaire or test items into composite scores, or parcels, which serve as indicators of latent constructs in structural equation models (SEMs). By reducing the number of observed variables and enhancing the stability of parameter estimates, parceling can simplify model structures, improve fit indices and mitigate the detrimental effects of non-normality and sampling fluctuations. Common parceling strategies include random assignment of items, content-driven grouping based on substantive similarity and parcels derived from preliminary factor analyses. Although parceling may obscure multidimensionality if applied indiscriminately, it has proved invaluable in large-scale assessments, cross-cultural research and neuroimaging studies where measurement complexity can otherwise overwhelm estimation procedures. Recent methodological work has emphasised guidelines for parcel selection, tests for parcel unidimensionality and robust approaches to preserve construct validity.
Research from Nature Portfolio
Recent simulation studies have proposed a Bayesian parceling framework that jointly estimates parcel composition and structural parameters, demonstrating enhanced recovery of true factor loadings under conditions of small samples and multidimensionality. This approach has been extended in applications to large cohort-based neurocognitive data, where adaptive parceling algorithms dynamically reassign items to parcels to optimise model parsimony without sacrificing measurement precision. In addition, advances in network psychometrics have integrated item parceling with graphical modelling, enabling researchers to examine both latent factor relations and direct item associations in high-dimensional psychological assessments. These contributions collectively advance parceling from an ad hoc tool to an integrated component of model estimation.
Item Parceling Techniques in Structural Equation Modeling publication trend
The graph below shows the total number of articles in item parceling techniques in structural equation modeling across all publications each year (not limited to Nature Index journals).
Technical terms
Latent variable: An unobserved construct inferred from measured indicators.
Item parcel: A composite score formed by summing or averaging selected items to serve as a single indicator in SEM.
Confirmatory factor analysis: A statistical technique used to test whether measured variables reflect the anticipated factor structure.
Parceling strategy: The method by which items are grouped into parcels, for example random assignment or content-based grouping.
Measurement model: The portion of an SEM that defines relationships between latent variables and their observed indicators.
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