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Use of linear multiple regression analysis on dental survey data
1Department of Dental Health Policy, Eastman Dental Institute, London, UK.
Community Dental Health
|December 1, 1994
Summary
Multiple regression analysis in dental research is complex, especially with categorical variables. This study highlights challenges in applying linear multiple regression to caries data, requiring extensive data transformation for valid results.
Area of Science:
- Dental Research
- Biostatistics
- Public Health
Background:
- Multiple regression analysis is increasingly used in dental research.
- Insufficient methodological details often hinder result validity.
- This technique is suitable for analyzing multiple variables when assumptions are met.
Purpose of the Study:
- To apply linear multiple regression to caries data from Spanish schoolchildren.
- To assess the feasibility and challenges of using this statistical method on survey data.
- To identify helpful statistics and significant influences on caries experience.
Main Methods:
- Linear multiple regression analysis was employed.
- Caries experience (dmft/DMFT) served as the quantitative dependent variable.
- Independent variables included gender, area type, social class, and province.
Main Results:
- Complex data transformations were necessary to meet regression assumptions.
- Significant influences on caries experience were detected.
- The order of importance of independent variables was established.
Conclusions:
- Applying linear multiple regression to survey data with categorical variables can be challenging.
- Extensive data transformation may be required to ensure valid results.
- The technique can identify significant factors affecting caries but demands rigorous methodological adherence.