Linear regression analysis: part 14 of a series on evaluation of scientific publications.

@article{Schneider2010LinearRA,
  title={Linear regression analysis: part 14 of a series on evaluation of scientific publications.},
  author={Astrid Schneider and Gerhard Hommel and Maria Blettner},
  journal={Deutsches Arzteblatt international},
  year={2010},
  volume={107 44},
  pages={
          776-82
        }
}
BACKGROUND Regression analysis is an important statistical method for the analysis of medical data. It enables the identification and characterization of relationships among multiple factors. It also enables the identification of prognostically relevant risk factors and the calculation of risk scores for individual prognostication. METHODS This article is based on selected textbooks of statistics, a selective review of the literature, and our own experience. RESULTS After a brief… 
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References

SHOWING 1-10 OF 14 REFERENCES

Missing data in randomised controlled trials: a practical guide

A principled approach to handling missing data in clinical trials is proposed, and how this principled approach can be practically, and directly, applied to the majority of trials with longitudinal follow-up is outlined.

The Environment and Disease: Association or Causation?

  • A. B. Hill
  • Philosophy
    Proceedings of the Royal Society of Medicine
  • 1965
This paper contrasts Bradford Hill’s approach with a currently fashionable framework for reasoning about statistical associations – the Common Task Framework – and suggests why following Bradford Hill, 50+ years on, is still extraordinarily reasonable.

Regression - Modelle, Methoden und Anwendungen

Statistik für Human- und Sozialwissenschaftler

話題 3 : Points to Consider on Multiplicity Issues in Clinical Trialsに関する編集者のまとめ

Multiple Tests und Auswahlverfahren.

Was ist ein Konfidenzintervall

The environment and disease.

  • A. Wolman
  • Medicine
    Bulletin of the Pan American Health Organization
  • 1976

Statistik für Human-und Sozialwissenschaftler. 6th edition

  • Statistik für Human-und Sozialwissenschaftler. 6th edition

Multiple Tests und Auswahlverfahren Stuttgart: Gustav Fischer Verlag 1995. Corresponding author Prof. Dr. rer. nat

  • Multiple Tests und Auswahlverfahren Stuttgart: Gustav Fischer Verlag 1995. Corresponding author Prof. Dr. rer. nat