Using the Delta Method for Approximate Interval Estimation of Parameter Functions in SEM

By Tenko Raykov, George A. Marcoulides. 2004

243 citations recorded by the source corpus.

Subfields: Management Science and Operations Research, Statistics and Probability

View Paper: https://www.semanticscholar.org/paper/3eb2ff5204fc8c04a8acfd5b0d8c5a2239d42b84

How researchers see this paper

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

In Management Science and Operations Research

1. Alexandre J. S. Morin
2. Marylène Gagné
3. Benjamin Nagengast
4. Herbert W. Marsh
5. T. Asparouhov
6. Joshua L. Howard
7. Tenko Raykov
8. George A. Marcoulides

In Statistics and Probability

1. Alexandre J. S. Morin
2. John P. Meyer
3. Herbert W. Marsh
4. George A. Marcoulides
5. Nicolas Gillet
6. Benjamin Nagengast
7. Franck Biétry
8. Jordane Creusier

Citations in the corpus

• The Big-Fish-Little-Pond Effect in Mathematics (2014, methodology): “Standard errors for confidence intervals and hypothesis tests can be obtained by applying the multivariate delta method (see Raykov & Marcoulides, 2004, for an accessible introduction).”
• Stability, change, and implications of students’ motivation profiles: A latent transition analysis (2017, methodology): “Motivation Profiles 18 We used the MODEL CONSTRAINT command of Mplus to systematically test mean-level differences across pairs of profiles using the multivariate delta method (Kam et al, 2016; Raykov & Marcoulides, 2004).”
• PLS: A Silver Bullet? (2006, methodology): “Unfortunately, finding formulas for standard errors of PLS estimates using the delta or Taylor series expansion method is not a trivial task (Dijkstra 1983), although the recent work by Denham (1997), Raykov and Marcoulides (2004), and Serneels et al. (2004) should prove promising.”
• Evaluation of Scale Reliability With Binary Measures Using Latent Variable Modeling (2010, methodology): “To obtain the interval estimates, one can employ the well-known delta method (e.g., Raykov & Marcoulides, 2004).”
• The big-fish-little-pond effect: Generalizability of social comparison processes over two age cohorts from Western, Asian, and Middle Eastern Islamic countries. (2015, methodology): “The standard error for the contextual effect was obtained with the multivariate delta method (see Raykov & Marcoulides, 2004).”
• Emotional labour profiles: Associations with key predictors and outcomes (2018, methodology): “We used the MODEL CONSTRAINT command of Mplus to systematically test mean-level differences across pairs of profiles using the multivariate delta method (Raykov & Marcoulides, 2004).”
• Multiple-Group Analysis of Similarity in Latent Profile Solutions (2016, methodology): “We used the MODEL CONSTRAINT command of Mplus to systematically test mean-level differences across pairs of profiles (using the multivariate delta method: e.g., Raykov & Marcoulides, 2004; for an application, see Kam et al., 2016).”
• Constructing Approximate Confidence Intervals for Parameters With Structural Equation Models (2009, unknown): “O™/ (e.g., Agresti, 2002; Casella & Berger, 2002; Rice, 1995; see also Raykov & Marcoulides, 2004, for an introduction).”
• Motivation profiles at work: A self-determination theory approach (2016, methodology): “The MODEL CONSTRAINT command of Mplus was used to systematically test mean-level differences across all specific pairs of profiles (using the multivariate delta method: e.g., Raykov & Marcoulides, 2004).”
• Are Commitment Profiles Stable and Predictable? A Latent Transition Analysis (2016, methodology): “…an omnibus Wald chi-square test of mean differences across the profiles (L. K. Muthén & Muthén, 2011), and the Mplus MODEL CONSTRAINT function to systematically test mean-level differences across all specific pairs of profiles (using the multivariate delta method; e.g., Raykov & Marcoulides, 2004).”