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Related Experiment Videos

A program for point and interval calculation of odds ratios and attributable risks from unmatched case-control data.

R A Dewar, J Siemiatycki

    International Journal of Bio-Medical Computing
    |May 1, 1985
    PubMed
    Summary

    A new FORTRAN program calculates odds ratios and attributable risks for epidemiological studies. This tool analyzes associations between diseases and risk factors using case-control data, enhancing study documentation and usability.

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    Area of Science:

    • Epidemiology
    • Biostatistics
    • Health Informatics

    Background:

    • Epidemiological investigations analyze associations between risk factors and diseases.
    • Case-control studies are crucial for identifying these associations.
    • Efficient data analysis tools are needed for complex epidemiological data.

    Purpose of the Study:

    • To develop a flexible FORTRAN program for analyzing epidemiological data.
    • To calculate point and interval estimates of odds ratios and attributable risks.
    • To facilitate the analysis of multiple disease/risk-factor combinations from stratified, unmatched case-control data.

    Main Methods:

    • Development of a FORTRAN program for statistical analysis.
    • Utilizing stratified, unmatched case-control data.

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  • Integration with the SPSS package for data management and flexibility.
  • Estimation of odds ratios by exposure level and latency.

    • Main Results:

    • The program calculates odds ratios and attributable risks.
    • It handles multiple disease/risk-factor combinations efficiently.
    • Output includes time- and date-stamping with clear labels for documentation.
    • The program is user-friendly and has been implemented on mainframes.

    Conclusions:

    • The developed FORTRAN program offers a flexible and user-friendly solution for epidemiological data analysis.
    • It enhances the ability to investigate associations between various risk factors and disease groups.
    • The program provides robust documentation and facilitates complex statistical estimations.