These tools will no longer be maintained as of December 31, 2024. Archived website can be found here. PubMed4Hh GitHub repository can be found here. Contact NLM Customer Service if you have questions.
132 related articles for article (PubMed ID: 38427288)
1. Power analyses for measurement model misspecification and response shift detection with structural equation modeling. Verdam MGE Qual Life Res; 2024 May; 33(5):1241-1256. PubMed ID: 38427288 [TBL] [Abstract][Full Text] [Related]
2. Analytical power calculations for structural equation modeling: A tutorial and Shiny app. Jak S; Jorgensen TD; Verdam MGE; Oort FJ; Elffers L Behav Res Methods; 2021 Aug; 53(4):1385-1406. PubMed ID: 33140375 [TBL] [Abstract][Full Text] [Related]
3. A tutorial on assessing statistical power and determining sample size for structural equation models. Jobst LJ; Bader M; Moshagen M Psychol Methods; 2023 Feb; 28(1):207-221. PubMed ID: 34672644 [TBL] [Abstract][Full Text] [Related]
4. On congruence and incongruence of measures of fit in structural equation modeling. Moshagen M; Auerswald M Psychol Methods; 2018 Jun; 23(2):318-336. PubMed ID: 28301200 [TBL] [Abstract][Full Text] [Related]
5. We need to change how we compute RMSEA for nested model comparisons in structural equation modeling. Savalei V; Brace JC; Fouladi RT Psychol Methods; 2024 Jun; 29(3):480-493. PubMed ID: 36622720 [TBL] [Abstract][Full Text] [Related]
6. semPower: General power analysis for structural equation models. Moshagen M; Bader M Behav Res Methods; 2024 Apr; 56(4):2901-2922. PubMed ID: 37950114 [TBL] [Abstract][Full Text] [Related]
7. Population performance of SEM parceling strategies under measurement and structural model misspecification. Rhemtulla M Psychol Methods; 2016 Sep; 21(3):348-368. PubMed ID: 26828780 [TBL] [Abstract][Full Text] [Related]
8. Using Structural Equation Modeling to Assess Functional Connectivity in the Brain: Power and Sample Size Considerations. Sideridis G; Simos P; Papanicolaou A; Fletcher J Educ Psychol Meas; 2014 Oct; 74(5):733-758. PubMed ID: 25435589 [TBL] [Abstract][Full Text] [Related]
9. The Noncentral Chi-square Distribution in Misspecified Structural Equation Models: Finite Sample Results from a Monte Carlo Simulation. Curran PJ; Bollen KA; Paxton P; Kirby J; Chen F Multivariate Behav Res; 2002 Jan; 37(1):1-36. PubMed ID: 26824167 [TBL] [Abstract][Full Text] [Related]
10. Understanding the Model Size Effect on SEM Fit Indices. Shi D; Lee T; Maydeu-Olivares A Educ Psychol Meas; 2019 Apr; 79(2):310-334. PubMed ID: 30911195 [TBL] [Abstract][Full Text] [Related]
11. Evaluating the performance of existing and novel equivalence tests for fit indices in structural equation modelling. Beribisky N; Cribbie RA Br J Math Stat Psychol; 2024 Feb; 77(1):103-129. PubMed ID: 37448144 [TBL] [Abstract][Full Text] [Related]
12. A framework for power analysis using a structural equation modelling procedure. Miles J BMC Med Res Methodol; 2003 Dec; 3():27. PubMed ID: 14670092 [TBL] [Abstract][Full Text] [Related]
14. Quantified choice of root-mean-square errors of approximation for evaluation and power analysis of small differences between structural equation models. Li L; Bentler PM Psychol Methods; 2011 Jun; 16(2):116-26. PubMed ID: 21341916 [TBL] [Abstract][Full Text] [Related]
15. The Influence of Number of Categories and Threshold Values on Fit Indices in Structural Equation Modeling with Ordered Categorical Data. Xia Y; Yang Y Multivariate Behav Res; 2018; 53(5):731-755. PubMed ID: 30477318 [TBL] [Abstract][Full Text] [Related]
16. RMSEA, CFI, and TLI in structural equation modeling with ordered categorical data: The story they tell depends on the estimation methods. Xia Y; Yang Y Behav Res Methods; 2019 Feb; 51(1):409-428. PubMed ID: 29869222 [TBL] [Abstract][Full Text] [Related]
17. Decomposing model fit: measurement vs. theory in organizational research using latent variables. O'Boyle EH; Williams LJ J Appl Psychol; 2011 Jan; 96(1):1-12. PubMed ID: 20718518 [TBL] [Abstract][Full Text] [Related]