The P-P Plot as a Method for Comparing Treatment Effects
作者:
EricB. Holmgren,
期刊:
Journal of the American Statistical Association
(Taylor Available online 1995)
卷期:
Volume 90,
issue 429
页码: 360-365
ISSN:0162-1459
年代: 1995
DOI:10.1080/01621459.1995.10476520
出版商: Taylor & Francis Group
关键词: Percentile-percentile plot;Probability-probability plot;Quantile-quantile plot
数据来源: Taylor
摘要:
This article examines the use of the probability-probability plot (p-p plot) as a method for comparing treatment effects. To begin in the context of three examples the p-p plot is contrasted with the quantile-quantile plot (q-q plot), which is an alternative means of describing treatment effects. In these examples it is shown that p-p plots representing different experimental conditions or patient populations allow scale-invariant comparisons of treatment effects but q-q plots do not; that the presentation of the treatment effect by the p-p plot is not obscured by outliers, whereas it may be in the q-q plot; and that the p-p plot encompasses information in the control distributions that is important for the assessment of treatment effects but that is not incorporated in the q-q plot. Theoretical considerations are presented that show that under appropriate assumptions, the p-p plot is a maximal invariant and contains all the information necessary to make scale-invariant comparisons of treatment effects. Further, statistical methods for assessing patterns observed in the p-p plots are presented and illustrated in two examples.
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