BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

317 related articles for article (PubMed ID: 30477339)

  • 1. Structural Equation Modeling of Social Networks: Specification, Estimation, and Application.
    Liu H; Jin IH; Zhang Z
    Multivariate Behav Res; 2018; 53(5):714-730. PubMed ID: 30477339
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Maximum likelihood estimation of a social relations structural equation model.
    Nestler S; Lüdtke O; Robitzsch A
    Psychometrika; 2020 Dec; 85(4):870-889. PubMed ID: 33094388
    [TBL] [Abstract][Full Text] [Related]  

  • 3. Generalized Network Psychometrics: Combining Network and Latent Variable Models.
    Epskamp S; Rhemtulla M; Borsboom D
    Psychometrika; 2017 Dec; 82(4):904-927. PubMed ID: 28290111
    [TBL] [Abstract][Full Text] [Related]  

  • 4. Social Network Mediation Analysis: A Latent Space Approach.
    Liu H; Jin IH; Zhang Z; Yuan Y
    Psychometrika; 2021 Mar; 86(1):272-298. PubMed ID: 33346886
    [TBL] [Abstract][Full Text] [Related]  

  • 5. A Quasi-Likelihood Approach to Assess Model Fit in Quadratic and Interaction SEM.
    Büchner RD; Klein AG
    Multivariate Behav Res; 2020; 55(6):855-872. PubMed ID: 31825255
    [TBL] [Abstract][Full Text] [Related]  

  • 6. Maximum Likelihood Estimation of Multilevel Structural Equation Models with Random Slopes for Latent Covariates.
    Rockwood NJ
    Psychometrika; 2020 Jun; 85(2):275-300. PubMed ID: 32303976
    [TBL] [Abstract][Full Text] [Related]  

  • 7. Two-Stage maximum likelihood estimation in the misspecified restricted latent class model.
    Wang S
    Br J Math Stat Psychol; 2018 May; 71(2):300-333. PubMed ID: 29080215
    [TBL] [Abstract][Full Text] [Related]  

  • 8. 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]  

  • 9. A penalized likelihood method for multi-group structural equation modelling.
    Huang PH
    Br J Math Stat Psychol; 2018 Nov; 71(3):499-522. PubMed ID: 29500879
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Virtual Levels and Role Models: N-Level Structural Equations Model of Reciprocal Ratings Data.
    Mehta PD
    Multivariate Behav Res; 2018; 53(3):315-334. PubMed ID: 29558166
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Modeling Interactions Between Latent Variables in Research on Type D Personality: A Monte Carlo Simulation and Clinical Study of Depression and Anxiety.
    Lodder P; Denollet J; Emons WHM; Nefs G; Pouwer F; Speight J; Wicherts JM
    Multivariate Behav Res; 2019; 54(5):637-665. PubMed ID: 30977400
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Using structural equation modeling for network meta-analysis.
    Tu YK; Wu YC
    BMC Med Res Methodol; 2017 Jul; 17(1):104. PubMed ID: 28709406
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Accounting for Latent Covariates in Average Effects from Count Regressions.
    Kiefer C; Mayer A
    Multivariate Behav Res; 2021; 56(4):579-594. PubMed ID: 32329366
    [TBL] [Abstract][Full Text] [Related]  

  • 14. EM algorithm estimation of a structural equation model for the longitudinal study of the quality of life.
    Barbieri A; Tami M; Bry X; Azria D; Gourgou S; Bascoul-Mollevi C; Lavergne C
    Stat Med; 2018 Mar; 37(6):1031-1046. PubMed ID: 29250835
    [TBL] [Abstract][Full Text] [Related]  

  • 15. A Comparison of Regularized Maximum-Likelihood, Regularized 2-Stage Least Squares, and Maximum-Likelihood Estimation with Misspecified Models, Small Samples, and Weak Factor Structure.
    Finch WH; Miller JE
    Multivariate Behav Res; 2021; 56(4):608-626. PubMed ID: 32324059
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Out-of-bag Prediction Error: A Cross Validation Index for Generalized Structured Component Analysis.
    Cho G; Jung K; Hwang H
    Multivariate Behav Res; 2019; 54(4):505-513. PubMed ID: 30977677
    [TBL] [Abstract][Full Text] [Related]  

  • 17. A Latent Auto-Regressive Approach for Bayesian Structural Equation Modeling of Spatially or Socially Dependent Data.
    Roman ZJ; Brandt H
    Multivariate Behav Res; 2023; 58(1):90-114. PubMed ID: 34379011
    [TBL] [Abstract][Full Text] [Related]  

  • 18. R-squared change in structural equation models with latent variables and missing data.
    Hayes T
    Behav Res Methods; 2021 Oct; 53(5):2127-2157. PubMed ID: 33782902
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Using empirical Bayes predictors from generalized linear mixed models to test and visualize associations among longitudinal outcomes.
    Mikulich-Gilbertson SK; Wagner BD; Grunwald GK; Riggs PD; Zerbe GO
    Stat Methods Med Res; 2019 May; 28(5):1399-1411. PubMed ID: 29488446
    [TBL] [Abstract][Full Text] [Related]  

  • 20. Bayesian structural equation modeling: a more flexible representation of substantive theory.
    Muthén B; Asparouhov T
    Psychol Methods; 2012 Sep; 17(3):313-35. PubMed ID: 22962886
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 16.