Regression Analysis for Longitudinal Aging Study in India Data

Title

Regression Analysis for Longitudinal Aging Study in India Data

Creator

Saxena, Maanya; Sharma, Ashish; Raj, S. Stephen

Description

This paper examines the Longitudinal Aging Study in India (LASI) and its role in providing valuable insights into the health, social, psychological, and economic well-being of the older Indian population. The paper examines the use of dependent independent variables in a multiple linear regression model, tests assumptions of linearity, and examines the significance of the overall model and the individual variables. There are 190 variables in the dataset being used. This paper presents the results of comparing the regression models obtained through basic, forward, and stepwise selection methods where the model obtained using the stepwise selection method, when all the linearity assumptions are satisfied, explains 86.51% of the variation in the dependent variable and the Adjusted R-squared of the model is 0.8374. The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

Source

Lecture Notes on Data Engineering and Communications Technologies;Volume;236;pp.149-161

Date

01-01-2025

Publisher

Springer Science and Business Media Deutschland GmbH

Subject

Data analytics; Healthcare; Linearity assumptions; Longitudinal aging; Regression; Selection methods; Statistics

Coverage

Saxena M., CHRIST (Deemed to be University), Ghaziabad, 201003, India; Sharma A., CHRIST (Deemed to be University), Ghaziabad, 201003, India; Raj S.S., CHRIST (Deemed to be University), Ghaziabad, 201003, India

Rights

Restricted Access; Hardcopy may be available in the library

Relation

ISSN: 23674512;

Format

online

Language

English

Type

Book chapter

Identifier

https://doi.org/10.1007/978-981-96-0451-7_10

https://www.scopus.com/pages/publications/105002446628?origin=resultslist