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[Data exploration using post-factorial analysis: use of structured data interrogation software]

B Faye1, J M Bernard

  • 1INRA de Theix, laboratoire d'écopathologie, Saint-Genès-Champanelle, France.

Veterinary Research
|January 1, 1994
PubMed
Summary
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This study introduces a language for interrogating data (LID) to explore factorial analysis results. LID aids in epidemiological analysis, measuring departmental and yearly effects, and assessing risk factors in milk quality surveys.

Area of Science:

  • Epidemiology
  • Data Analysis
  • Statistical Modeling

Context:

  • Factorial analysis generates complex data clouds.
  • Epidemiological studies require robust data exploration methods.
  • Milk quality surveys involve multiple risk factors.

Purpose:

  • To introduce a Language for Interrogating Data (LID) for exploring factorial analysis outputs.
  • To demonstrate the utility of post-factorial analysis in epidemiology.
  • To quantify departmental and yearly effects and assess factor adjustments.

Summary:

  • The Language for Interrogating Data (LID) facilitates graphical and numerical exploration of factorial analysis data.
  • Post-factorial analysis is applied to measure departmental and yearly effects.

Related Experiment Videos

  • The study assesses factor adjustment within a milk quality risk factor survey.

    • Impact:

    • Provides a novel method for data interrogation in complex analyses.
    • Enhances epidemiological research by enabling precise effect measurement.
    • Improves understanding of risk factors influencing milk quality.