Evaluating the effectiveness of interventions: exploration of two statistical methods.

Fox MT; Brathwaite AC; Sidani S

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Evaluating the effectiveness of interventions: exploration of two statistical methods.

机译：评估干预措施的有效性：探索两种统计方法。

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Repeated measures designs are often used to evaluate the effectiveness of interventions. In these designs, the outcomes are measured on several occasions before and after implementation of the intervention. Two statistical methods, the repeated measures analysis of variance (RM-ANOVA) and hierarchical linear models (HLM), can be used to analyze the data. The authors provide an overview of the statistical models underlying RM-ANOVA and HLM and discuss the strengths and limitations of each. They propose that the 2 methods are complementary in determining the effectiveness of interventions.

机译：重复措施设计通常用于评估干预措施的有效性。在这些设计中，在干预措施实施之前和之后的几次情况下都会评估结果。可以使用两种统计方法，即重复测量方差分析（RM-ANOVA）和层次线性模型（HLM），来分析数据。作者概述了基于RM-ANOVA和HLM的统计模型，并讨论了每种模型的优缺点。他们提出，这两种方法在确定干预措施的有效性方面是互补的。

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《The Canadian journal of nursing research》 |2004年第3期|共11页
作者
Fox MT; Brathwaite AC; Sidani S;
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正文语种 eng
中图分类护理学;
关键词
statistical; Analysis of Variance; hierarchical linear modeling; overview; 方差分析;

机译：statistical;Analysis of Variance;hierarchical linear modeling;overview;方差分析;

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1. Evaluating the effectiveness of interventions: exploration of two statistical methods. [J] . Fox MT, Brathwaite AC, Sidani S The Canadian journal of nursing research . 2004,第3期

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Evaluating the effectiveness of interventions: exploration of two statistical methods.

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