“Application of Lavaan for Structural Equation and Path Model on Unmet Healthcare Needs Latent from Demographic and Health Survey Data of Maharashtra State, India”


  • Kishor N Raut, Ashok Y Tayade


lavaan, Path Analysis, Structural Equation Model (SEM), Latent Variable Analysis, semPath, unmet need, Heywood case.


Structural Equation Modeling (SEM) is useful in many areas of research including Medical Research. In R Project, the package lavaan have commercial-quality with fully free open-source to use for latent variable analysis. This study aimed to analyze the strength of association latent variable (V623 (Exposure), V624 (Unmet need) and S253 (Had your uterus removed) with other endogenous latent variable of Demographic and Health Survey Program 2019-21 Phase VII, data of Maharashtra State, India. The women age ranged from 16 to 49 years.

Path model of endogenous latent variable f7 (V623 (Exposure), V624 (Unmet need) and S253 (Had your uterus removed)) measured the effect of f1, f2, f3, f4, f5 and f6 latent variable in addition to V613 and V625A exogenous variable, The study revealed that for latent model f7 needs each latent was built-up on sufficient (3 or more) variables in each latent to avoid the Heywood case, even after study data having sufficiently enough large of observation data.


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How to Cite

Kishor N Raut. (2024). “Application of Lavaan for Structural Equation and Path Model on Unmet Healthcare Needs Latent from Demographic and Health Survey Data of Maharashtra State, India”. International Journal of Intelligent Systems and Applications in Engineering, 12(21s), 2012–2022. Retrieved from https://ijisae.org/index.php/IJISAE/article/view/5771



Research Article