Dataset Information

Model Implied Instrumental Variables (MIIVs): An Alternative Orientation to Structural Equation Modeling.

ABSTRACT: Few dispute that our models are approximations to reality. Yet when it comes to structural equation models (SEMs), we use estimators that assume true models (e.g. maximum likelihood) and that can create biased estimates when the model is inexact. This article presents an overview of the Model Implied Instrumental Variable (MIIV) approach to SEMs from Bollen (1996). The MIIV estimator using Two Stage Least Squares (2SLS), MIIV-2SLS, has greater robustness to structural misspecifications than system wide estimators. In addition, the MIIV-2SLS estimator is asymptotically distribution free. Furthermore, MIIV-2SLS has equation-based overidentification tests that can help pinpoint misspecifications. Beyond these features, the MIIV approach has other desirable qualities. MIIV methods apply to higher order factor analyses, categorical measures, growth curve models, dynamic factor analysis, and nonlinear latent variables. Finally, MIIV-2SLS permits researchers to estimate and test only the latent variable model or any other subset of equations. In addition, other MIIV estimators beyond 2SLS are available. Despite these promising features, research is needed to better understand its performance under a variety of conditions that represent empirical applications. Empirical and simulation examples in the article illustrate the MIIV orientation to SEMs and highlight an R package MIIVsem that implements MIIV-2SLS.

SUBMITTER: Bollen KA

PROVIDER: S-EPMC6693517 | biostudies-literature | 2019 Jan-Feb

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Model Implied Instrumental Variables (MIIVs): An Alternative Orientation to Structural Equation Modeling.

Bollen Kenneth A KA

Multivariate behavioral research 20180917 1

Few dispute that our models are approximations to reality. Yet when it comes to structural equation models (SEMs), we use estimators that assume true models (e.g. maximum likelihood) and that can create biased estimates when the model is inexact. This article presents an overview of the Model Implied Instrumental Variable (MIIV) approach to SEMs from Bollen (1996). The MIIV estimator using Two Stage Least Squares (2SLS), MIIV-2SLS, has greater robustness to structural misspecifications than syst ...[more]

PMID: 30222004

Similar Datasets

Project description:INTRODUCTION:Patients' sexual concerns are private, sensitive issues, and providing sexual health care (SHC) is a legitimate area of concern for the nursing practice. AIMS:This study tests a structural equation model for factors that affect SHC among Taiwanese nurses. METHODS:A cross-sectional study was performed between August 2014 and July 2015. A total of 471 registered nurses from a medical center in Taiwan were enrolled in this study. All nurses participated anonymously and completed 3 questionnaires: Nursing Attitude in Sexual Health Care scale, Nursing Intervention in Sexual Health scale, and Gender Role Orientation scale. The Permission-Limited Information-Specific Suggestions-Intensive Therapy model based on scale was application, and theory of planned behavior was used to examine the relationship of these 3 scales in nurses. MAIN OUTCOME MEASURES:SHC surveys were developed for nurses. These valid and reliable instruments included Nursing Attitude in Sexual Health Care, Nursing Intervention in Sexual Health, and Gender Role Orientation. RESULTS:The fitted structural equation model was valid. The construct reliability of latent variables ranged from 0.730 to 0.942, which met the requirement of 0.70. The attitude about SHC (β = 0.182, P < .001), subjective norms on SHC (β = 0.146, P < .001), and confidence about SHC (β = 0.583, P < .001) had significant effects on the behavioral intention to provide SHC. Subsequently, the behavioral intention to provide SHC had a significant, direct effect on the behavioral frequency of providing SHC (β = 0.356, P < .001). However, gender role orientation was not significantly associated with behavioral intention and behavioral frequency to provide SHC. CONCLUSIONS:The good fit for the structural equation model suggests that the predictors of behavioral intention and behaviors of providing SHC include attitude, subjective norms, and perceived control. The stronger behavioral intention of providing SHC resulted in a higher frequency of providing SHC. However, the relationship between gender role orientation and SHC had no significant effect. Huang C-Y, Liou C-F, Lee S-H, et al. The Relationship Between Gender Role Orientation and Sexual Health Care in Taiwanese Nurses: A Structural Equation Model. Sex Med 2020;8:565-573.

Dataset Information

Model Implied Instrumental Variables (MIIVs): An Alternative Orientation to Structural Equation Modeling.

Publications

Model Implied Instrumental Variables (MIIVs): An Alternative Orientation to Structural Equation Modeling.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets