A Mixture Regression Approach for Modelling Early Post Operative Hypocalcemia

Regression Approach for Modelling Early Post Operative Hypocalcemia

Authors

  • Sreelaya K Kannur University, India
  • Yadev I Government Medical College, Pariapally, Kollam, India
  • Sebastian George Kannur University, India

semicolon

EM algorithm, Gaussian mixture models, Laplace mixture models, Laplace mixture regression models, Post operative hypocalcemia, Thyroidectomy

Abstract

In this paper, we show that a two component Laplace mixture model is an appropriate distribution to model postoperative calcium levels of patients undergoing thyroidectomy or surgery for thyroid diseases. A mixture regression model is constructed to predict postoperative calcium levels based on a pre-determined set of potential predictors. The parameters of the model are estimated using EM algorithm. Our study based on a real data set shows that two component Laplace mixture regression model is suitable for prediction and interpretation compared to the usual Gaussian mixture regression model.

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Published

2023-12-01

Issue

Vol. 34 No. 1 (2023)

Section

Articles

How to Cite

1.
A Mixture Regression Approach for Modelling Early Post Operative Hypocalcemia: Regression Approach for Modelling Early Post Operative Hypocalcemia. JKSA [Internet]. 2023 Dec. 1 [cited 2026 Feb. 27];34(1):39-51. Available from: https://ojs.ksa.org.in/index.php/JKSA/article/view/49