Analysis of covariance (ANCOVA)

D. Clark-Carter
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Abstract

Introduction A common task in research is to compare the averages of two or more populations (groups). We might want to compare the income level of two regions, the nitrogen content of three lakes, or the effectiveness of four drugs. The one-way analysis of variance compares the means of two or more groups to determine if at least one mean is different from the others. The F test is used to determine statistical significance. Analysis of Covariance (ANCOVA) is an extension of the one-way analysis of variance model that adds quantitative variables (covariates). When used, it is assumed that their inclusion will reduce the size of the error variance and thus increase the power of the design.
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协方差分析(ANCOVA)
研究中的一个常见任务是比较两个或两个以上种群(群体)的平均值。我们可能想比较两个地区的收入水平,三个湖泊的氮含量,或者四种药物的有效性。单向方差分析比较两个或多个组的均值,以确定是否至少有一个均值与其他组不同。使用F检验来确定统计显著性。协方差分析(ANCOVA)是对单向方差分析模型的扩展,增加了定量变量(协变量)。当使用时,假设它们的包含将减小误差方差的大小,从而增加设计的能力。
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Going beyond description Research designs and their internal validity Bayesian statistics Reporting research Analysis of differences between two levels of an independent variable
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