One Factor SEM and Multilevel SEM Model for Patient Satisfaction Data

Rehan Ahmad Khan Sherwani

College of Statistics and Actuarial Sciences, University of the Punjab Lahore, Pakistan.

Sajjad Ali Gill *

Department of sports sciences & Physical Education, University of the Punjab Lahore, Pakistan.

Shaukat Ali Raza

Department of Business Education Institute of Education and Research, University of the Punjab, Lahore, Pakistan.

Shumaila Abbas

College of Statistics and Actuarial Sciences, University of the Punjab Lahore, Pakistan.

Muhammad Farooq

Department of Statistics, Govt. College University Lahore, Pakistan.

Sana Saeed

College of Statistics and Actuarial Sciences, University of the Punjab Lahore, Pakistan.

Hira Shahid

Department of Physical Education and Sports Sciences, The University of Lahore, Pakistan.

*Author to whom correspondence should be addressed.


Abstract

Structural equation models are very common in medical, social, management and behavioral sciences where researchers established some causal relations between observed variables and latent variable. In structured populations the assumption of independence of observations is often violated and had been ignored by the researchers. As a result with the correlated structure of the error terms, biased estimates of the parameters have been produced that leads towards incorrect statistical inference. Multilevel structural equation model under one factor model has been proposed, estimated and compared with the traditional structural equation model on patient satisfaction data. Multilevel structural equation model produced better estimates than the structural equation models.

Keywords: Causal relation, path diagram, SEM, multilevel SEM


How to Cite

Sherwani, Rehan Ahmad Khan, Sajjad Ali Gill, Shaukat Ali Raza, Shumaila Abbas, Muhammad Farooq, Sana Saeed, and Hira Shahid. 2021. “One Factor SEM and Multilevel SEM Model for Patient Satisfaction Data”. Journal of Pharmaceutical Research International 33 (17):39-49. https://doi.org/10.9734/jpri/2021/v33i1731306.

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