Parameter Recovery and Model Fit Using Multidimensional Composites: A Comparison of Four Empirical Parceling Algorithms

By W. Rogers, Neal Schmitt. 2004

357 citations recorded by the source corpus.

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In Statistics and Probability

Citations in the corpus

Psychosocial causes and consequences of pathological gaming (2011, methodology): “The items from each scale were distributed over two parcels using the factorial algorithm (see Rogers & Schmitt, 2004, for a description of this procedure).”
The Impact of Person–Job Fit on Job Satisfaction: The Mediator Role of Self Efficacy (2015, methodology): “The value of the parcel used as an indicator or observed variable was the average scores of several conceptually similar items (Rogers and Schmitt 2004; Zhang et al. 2014).”
Reciprocal associations between shyness, self-esteem, loneliness, depression and Internet addiction in Chinese adolescents (2020, methodology): “A previous study proposed that one dimension variables could use the parceling strategy of the factorial algorithm to simplify their structures (Rogers and Schmitt 2004).”
Four Research Designs and a Comprehensive Analysis Strategy for Investigating Common Method Variance with Self-Report Measures Using Latent Variables (2016, methodology): “We included items from each of the three dimensions within every parcel, using a factorial algorithm (Rogers and Schmitt 2004).”
Small Sample Size Solutions (2020, background): “A first option would be to assign items that correlate the most strongly with each other to the same parcel (Landis, Beal, & Tesluk, 2000; Rogers & Schmitt, 2004).”
Problems With Item Parceling for Confirmatory Factor Analytic Tests of Measurement Invariance (2006, methodology): “In addition, parcels were formed for each group in which responses to groups of four items were summed to create parcel scores (cf. Rogers & Schmitt, 2004), allowing the use of either items or parcels for analysis.”
Item Parceling in Structural Equation Modeling: A Primer (2008, background): “When a given scale consists of eight items, say, parcels can be formed by creating several aggregate scores by combining two or more items in a random or nonrandom manner, or aggregating all eight items into one composite score ( Little et al, 2002 ; Rogers & Schmitt, 2004 ).”
Why the Items versus Parcels Controversy Needn’t Be One (2013, methodology): “…can lead to biased estimates of other model parameters (e.g., structural parameters; Bandalos & Finney, 2001; Hall et al., 1999; Kim & Hagtvet, 2003; Landis, Beal, & Tesluk, 2000; Little et al., 2002; Matsunaga, 2008; Meade & Kroustalis, 2006; Rogers & Schmitt, 2004; Sass & Smith, 2006).”
Informal digital learning of English and L2 willingness to communicate: roles of emotions, gender, and educational stage (2021, methodology): “Exploratory factor analysis was conducted for each measure, based on which composite variables were computed (i.e. item par-celling technique, Rogers and Schmitt 2004), which were used as observable indicators of latent factors in subsequent measurement and structural models.”
12 Structural Equation Modeling in Management Research: A Guide for Improved Analysis (2009, background): “It should be noted that while our emphasis is on models with multiple indicators for each latent variable, models with only a single indicator are available (referred to as total aggregation with reliability correction models—see Rogers and Schmitt (2004)).”