Zero-Inflated Count Regression Models in Solving Challenges Posed by Outlier-Prone Data; an Application to Length of Hospital Stay

Zero-Inflated Count Regression Models in Solving Challenges Posed by Outlier-Prone Data; an Application to Length of Hospital Stay

Introduction: Ignoring outliers in data may lead to misleading results. Length of stay (LOS) is often considered a count variable with a high frequency of outliers. This study exemplifies the potential of robust methodologies in enhancing the accuracy and reliability of analyses conducted on skewed...

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Bibliographic Details
Main Authors: Saeed Shahsavari, Abbas Moghimbeigi, Rohollah Kalhor, Ali Moghadas Jafari, Mehrdad Bagherpour-kalo, Mehdi Yaseri, Mostafa Hosseini
Format: Article
Language:English
Published: Shahid Beheshti University of Medical Sciences 2023-11-01
Series:Archives of Academic Emergency Medicine
Subjects:
Length of stay
intensive care units
outliers
robust
excess zeros
Online Access:https://journals.sbmu.ac.ir/aaem/index.php/AAEM/article/view/2074

Internet

https://journals.sbmu.ac.ir/aaem/index.php/AAEM/article/view/2074

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