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Linear Regression for Assessing Precision, Confounding, Interaction, Basic Approach

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Abstract

When the size of the study permits, important demographic or baseline value-defined subgroups of patients can be studied for unusually large or small efficacy responses; e.g. comparison of effects by age, sex; by severity or prognostic groups. Naturally, such analyses are not intended to “salvage” an otherwise negative study, but may be helpful in refining patient or dose selection for subsequent studies (Department of Health and Human Services, Food and Drug Administration 1998).

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References

  • Cox B (1999) Statistical software. University Leyden, Leyden

    Google Scholar 

  • Department of Health and Human Services, Food and Drug Administration (1998) International conference on harmonisation; guidance on statistical principles for clinical trials availability. Fed Regist 63(179):49583–49598

    Google Scholar 

  • Hosmer DW, Lemeshow S (1989) Applied logistic regression. Wiley, New York

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  • Jukema AJ, Zwinderman AH, et al for the REGRESS study group (1995) Effects of lipid lowering by pravastatin on progression and regression of coronary artery disease in symptomatic men with normal to moderately elevated serum cholesterol levels. The Regression Growth Evaluation Statin Study (REGRESS). Circulation 91:2528-2540

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  • Rao CR (1973) Linear statistical inference and its applications. Wiley, New York

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© 2012 Springer Science+Business Media B.V.

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Cleophas, T.J., Zwinderman, A.H. (2012). Linear Regression for Assessing Precision, Confounding, Interaction, Basic Approach. In: Statistics Applied to Clinical Studies. Springer, Dordrecht. https://doi.org/10.1007/978-94-007-2863-9_15

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