The Effects of Model Parsimony and Sampling Error on the Fit of Structural Equation Models

By Gordon W. Cheung, Roger B. Rensvold. 2001

167 citations recorded by the source corpus.

Subfields: Computer Networks and Communications, Management Science and Operations Research, Statistics and Probability

View Paper: https://www.semanticscholar.org/paper/4d8f2c75df0b8fa85f48474ef34753f99426754f

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Computer Networks and Communications

1. Alexandre J. S. Morin
2. Herbert W. Marsh
3. Andrew J. Martin
4. G. Liem
5. T. Asparouhov
6. Benjamin Nagengast
7. B. Muthén
8. O. Lüdtke

In Management Science and Operations Research

1. Alexandre J. S. Morin
2. Herbert W. Marsh
3. Benjamin Nagengast
4. B. Muthén
5. T. Asparouhov
6. O. Lüdtke
7. P. Parker
8. Ulrich Trautwein

In Statistics and Probability

1. Alexandre J. S. Morin
2. Herbert W. Marsh
3. T. Asparouhov
4. B. Muthén
5. Ulrich Trautwein
6. Benjamin Nagengast
7. O. Lüdtke
8. T. Little

Citations in the corpus

• Why the Items versus Parcels Controversy Needn’t Be One (2013, background): “These kinds of population-level errors are referred to as parsimony error, which is different from misspecification error (Cheung & Rensvold, 2001).”
• Reading motivation and reading comprehension in Chinese and English among bilingual students (2011, methodology): “We report five frequently used goodness-of-fit indices: chisquare, the comparable fit index (CFI, Cheung & Rensvold, 2001), Joreskog and Sorbom’s Goodness of Fit (GFI) index, the non-normed fit index (NNFI; Bentler & Bonett, 1980) and the root mean square error of approximation (RMSEA; Steiger,…”
• THE STATE OF STRATEGIC MANAGEMENT RESEARCH AND A VISION OF THE FUTURE (2004, background): “The inadequate sample sizes and inappropriate sample distributions may induce the lack of sufficient power to detect certain effects; even when detected, the effects may be misestimated in terms of magnitude (Cheung & Rensvold, 2001).”
• The Big-Fish-Little-Pond Effect in Mathematics (2014, result): “Usually, a decrease in fit for the more parsimonious model remains below .01 for the CFI and .015 for the RMSEA, is taken to reflect reasonable support for the more parsimonious model (e.g., F. Chen, Curran, Bollen, Kirby, & Paxton, 2008; F. F. Chen, 2007; Cheung & Rensvold, 2001, 2002).”
• Exploratory Structural Equation Modeling (2009, unknown): “Thus, for example, Cheung and Rensvold (2001) and Chen (2007) suggested that if the decrease in fit for the more parsimonious model is less than .01 for incremental fit indexes like the CFI, then there is reasonable support for the more parsimonious model.”
• The reciprocal relations between self-concept, motivation and achievement: juxtaposing academic self-concept and achievement goal orientations for mathematics success (2014, unknown): “For invariance testing across year in school and gender, decreases in fit of less than .01 for fit indices like CFI and TLI indicate that the more parsimonious model is supported (Cheung & Rensvold, 2001).”
• Methodological Measurement Fruitfulness of Exploratory Structural Equation Modeling (ESEM): New Approaches to Key Substantive Issues in Motivation and Engagement (2011, background): “Cheung and Rensvold (2001) and Chen (2007) suggested that if the decrease in fit for the more parsimonious model is less than 0.01 for incrementalfit indices like the CFI, then there is reasonable support for the more parsimonious model.”
• A new look at the big five factor structure through exploratory structural equation modeling. (2010, methodology): “It has been suggested that support for the more parsimonious model requires a change in CFI of less than .01 (Chen, 2007; Cheung & Rensvold, 2001) or a change in RMSEA of less than .015 (Chen, 2007).”
• The Brief State Rumination Inventory (BSRI): Validation and Psychometric Evaluation (2018, methodology): “While comparing nested invariance models, our evaluation criteria were based on guidelines derived from methodological research (Cheung and Rensvold 2001; Chen 2007).”
• Factorial, Convergent, and Discriminant Validity of TIMSS Math and Science Motivation Measures: A Comparison of Arab and Anglo-Saxon Countries (2013, background): “Cheung and Rensvold (2001, 2002) and Chen (2007) suggested that if the decrease in fit for the more parsimonious model is less than .01 for incremental fit indices like the CFI, then there is reasonable support for the more parsimonious model.”