BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

1081 related articles for article (PubMed ID: 26174714)

  • 1. Confirmatory factor analysis with ordinal data: Comparing robust maximum likelihood and diagonally weighted least squares.
    Li CH
    Behav Res Methods; 2016 Sep; 48(3):936-49. PubMed ID: 26174714
    [TBL] [Abstract][Full Text] [Related]  

  • 2. The performance of ML, DWLS, and ULS estimation with robust corrections in structural equation models with ordinal variables.
    Li CH
    Psychol Methods; 2016 Sep; 21(3):369-87. PubMed ID: 27571021
    [TBL] [Abstract][Full Text] [Related]  

  • 3. Statistical estimation of structural equation models with a mixture of continuous and categorical observed variables.
    Li CH
    Behav Res Methods; 2021 Oct; 53(5):2191-2213. PubMed ID: 33791955
    [TBL] [Abstract][Full Text] [Related]  

  • 4. A Monte Carlo study comparing PIV, ULS and DWLS in the estimation of dichotomous confirmatory factor analysis.
    Nestler S
    Br J Math Stat Psychol; 2013 Feb; 66(1):127-43. PubMed ID: 22524532
    [TBL] [Abstract][Full Text] [Related]  

  • 5. When can categorical variables be treated as continuous? A comparison of robust continuous and categorical SEM estimation methods under suboptimal conditions.
    Rhemtulla M; Brosseau-Liard PÉ; Savalei V
    Psychol Methods; 2012 Sep; 17(3):354-73. PubMed ID: 22799625
    [TBL] [Abstract][Full Text] [Related]  

  • 6. Robustness of Parameter Estimation to Assumptions of Normality in the Multidimensional Graded Response Model.
    Wang C; Su S; Weiss DJ
    Multivariate Behav Res; 2018; 53(3):403-418. PubMed ID: 29624093
    [TBL] [Abstract][Full Text] [Related]  

  • 7. Evaluating FIML and multiple imputation in joint ordinal-continuous measurements models with missing data.
    Lim AJ; Cheung MW
    Behav Res Methods; 2022 Jun; 54(3):1063-1077. PubMed ID: 34545537
    [TBL] [Abstract][Full Text] [Related]  

  • 8. A Comparative Study on the Performance of GSCA and CSA in Parameter Recovery for Structural Equation Models With Ordinal Observed Variables.
    Jung K; Panko P; Lee J; Hwang H
    Front Psychol; 2018; 9():2461. PubMed ID: 30568625
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Analysing multitrait-multimethod data with structural equation models for ordinal variables applying the WLSMV estimator: what sample size is needed for valid results?
    Nussbeck FW; Eid M; Lischetzke T
    Br J Math Stat Psychol; 2006 May; 59(Pt 1):195-213. PubMed ID: 16709286
    [TBL] [Abstract][Full Text] [Related]  

  • 10. More efficient parameter estimates for factor analysis of ordinal variables by ridge generalized least squares.
    Yuan KH; Jiang G; Cheng Y
    Br J Math Stat Psychol; 2017 Nov; 70(3):525-564. PubMed ID: 28547838
    [TBL] [Abstract][Full Text] [Related]  

  • 11. An empirical evaluation of alternative methods of estimation for confirmatory factor analysis with ordinal data.
    Flora DB; Curran PJ
    Psychol Methods; 2004 Dec; 9(4):466-91. PubMed ID: 15598100
    [TBL] [Abstract][Full Text] [Related]  

  • 12. The performance of robust test statistics with categorical data.
    Savalei V; Rhemtulla M
    Br J Math Stat Psychol; 2013 May; 66(2):201-23. PubMed ID: 22568535
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Comparison of alternative estimation methods in confirmatory factor analyses of the General Health Questionnaire.
    Wang WC; Cunningham EG
    Psychol Rep; 2005 Aug; 97(1):3-10. PubMed ID: 16279297
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Fitting Large Factor Analysis Models With Ordinal Data.
    DiStefano C; McDaniel HL; Zhang L; Shi D; Jiang Z
    Educ Psychol Meas; 2019 Jun; 79(3):417-436. PubMed ID: 31105317
    [TBL] [Abstract][Full Text] [Related]  

  • 15. The Impact of Model Parameterization and Estimation Methods on Tests of Measurement Invariance With Ordered Polytomous Data.
    Koziol NA; Bovaird JA
    Educ Psychol Meas; 2018 Apr; 78(2):272-296. PubMed ID: 29795956
    [TBL] [Abstract][Full Text] [Related]  

  • 16. A Comparison of ML, WLSMV, and Bayesian Methods for Multilevel Structural Equation Models in Small Samples: A Simulation Study.
    Holtmann J; Koch T; Lochner K; Eid M
    Multivariate Behav Res; 2016; 51(5):661-680. PubMed ID: 27594086
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Pairwise Likelihood Ratio Tests and Model Selection Criteria for Structural Equation Models with Ordinal Variables.
    Katsikatsou M; Moustaki I
    Psychometrika; 2016 Dec; 81(4):1046-1068. PubMed ID: 27734296
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Scaled test statistics and robust standard errors for non-normal data in covariance structure analysis: a Monte Carlo study.
    Chou CP; Bentler PM; Satorra A
    Br J Math Stat Psychol; 1991 Nov; 44 ( Pt 2)():347-57. PubMed ID: 1772802
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Comparing interval estimates for small sample ordinal CFA models.
    Natesan P
    Front Psychol; 2015; 6():1599. PubMed ID: 26579002
    [TBL] [Abstract][Full Text] [Related]  

  • 20. Expected versus observed information in SEM with incomplete normal and nonnormal data.
    Savalei V
    Psychol Methods; 2010 Dec; 15(4):352-67. PubMed ID: 20853954
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 55.