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“ERIC ED626847: Which Method Is More Powerful In Testing The Relationship Of Theoretical Construct? A Meta Comparison Of Structural Equation Modeling And Path Analysis With Weighted-Composites Structural Equation Modeling (SEM) Has Been Deemed As A Proper Method When Variables Contain Measurement Errors. In Contrast, Path Analysis With Composite-scores Is Preferred For Prediction And Diagnosis Of Individuals. While Path Analysis With Composite-scores Has Been Criticized For Yielding Biased Parameter Estimates, Recent Literature Pointed Out That The Population Values Of Parameters In A Latent-variable Model Depend On Artificially Assigned Scales. Consequently, Bias In Parameter Estimates Is Not A Well-grounded Concept For Models Involving Latent Constructs. This Article Compares Path Analysis With Composite-scores Against SEM With Respect To Effect Size And Statistical Power In Testing The Significance Of The Path Coefficients, Via The Z- Or T-statistics. The Data Come From Many Sources With Various Models That Are Substantively Determined. Results Show That SEM Is Not As Powerful As Path Analysis Even With Equally-weighted-composites. But Path Analysis With Bartlett-factor- Scores And The Partial-least-squares Approach To SEM Perform The Best With Respect To Effect Size And Power. [This Paper Will Be Published In "Behavior Research Methods." Discrepancy Between The Title Of The Article And Authored Paper.]” Metadata:

• Title: ➤  ERIC ED626847: Which Method Is More Powerful In Testing The Relationship Of Theoretical Construct? A Meta Comparison Of Structural Equation Modeling And Path Analysis With Weighted-Composites Structural Equation Modeling (SEM) Has Been Deemed As A Proper Method When Variables Contain Measurement Errors. In Contrast, Path Analysis With Composite-scores Is Preferred For Prediction And Diagnosis Of Individuals. While Path Analysis With Composite-scores Has Been Criticized For Yielding Biased Parameter Estimates, Recent Literature Pointed Out That The Population Values Of Parameters In A Latent-variable Model Depend On Artificially Assigned Scales. Consequently, Bias In Parameter Estimates Is Not A Well-grounded Concept For Models Involving Latent Constructs. This Article Compares Path Analysis With Composite-scores Against SEM With Respect To Effect Size And Statistical Power In Testing The Significance Of The Path Coefficients, Via The Z- Or T-statistics. The Data Come From Many Sources With Various Models That Are Substantively Determined. Results Show That SEM Is Not As Powerful As Path Analysis Even With Equally-weighted-composites. But Path Analysis With Bartlett-factor- Scores And The Partial-least-squares Approach To SEM Perform The Best With Respect To Effect Size And Power. [This Paper Will Be Published In "Behavior Research Methods." Discrepancy Between The Title Of The Article And Authored Paper.]
• Author: ERIC
• Language: English

“ERIC ED626847: Which Method Is More Powerful In Testing The Relationship Of Theoretical Construct? A Meta Comparison Of Structural Equation Modeling And Path Analysis With Weighted-Composites Structural Equation Modeling (SEM) Has Been Deemed As A Proper Method When Variables Contain Measurement Errors. In Contrast, Path Analysis With Composite-scores Is Preferred For Prediction And Diagnosis Of Individuals. While Path Analysis With Composite-scores Has Been Criticized For Yielding Biased Parameter Estimates, Recent Literature Pointed Out That The Population Values Of Parameters In A Latent-variable Model Depend On Artificially Assigned Scales. Consequently, Bias In Parameter Estimates Is Not A Well-grounded Concept For Models Involving Latent Constructs. This Article Compares Path Analysis With Composite-scores Against SEM With Respect To Effect Size And Statistical Power In Testing The Significance Of The Path Coefficients, Via The Z- Or T-statistics. The Data Come From Many Sources With Various Models That Are Substantively Determined. Results Show That SEM Is Not As Powerful As Path Analysis Even With Equally-weighted-composites. But Path Analysis With Bartlett-factor- Scores And The Partial-least-squares Approach To SEM Perform The Best With Respect To Effect Size And Power. [This Paper Will Be Published In "Behavior Research Methods." Discrepancy Between The Title Of The Article And Authored Paper.]” Subjects and Themes:

• Subjects: ➤  ERIC Archive - ERIC - Deng, Lifang Yuan, Ke-Hai Structural Equation Models - Path Analysis - Weighted Scores - Error of Measurement - Effect Size - Statistical Significance - Least Squares Statistics - Robustness (Statistics)

Edition Identifiers:

• Internet Archive ID: ERIC_ED626847