A SOLUTION TO THE EFFECT OF SAMPLE-SIZE ON OUTLIER ELIMINATION
A SOLUTION TO THE EFFECT OF SAMPLE-SIZE ON OUTLIER ELIMINATION
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DOI：
10.1080/14640749408401131
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发表时间：
1994-08-01
期刊：
影响因子：
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通讯作者：
JOLICOEUR, P
中科院分区：
文献类型：
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作者：
VANSELST, M;JOLICOEUR, P
从蒙特卡罗研究的结果表明，如何非递归，简单的递归，修改后的递归，和混合离群值消除过程的影响，人口偏斜和样本量。所有程序都基于计算样本的平均值和标准差，以确定观测值是否为离群值。米勒（1991）指出，由简单的非递归过程产生的估计平均值可能受到样本大小的影响，这种影响可能在某些类型的实验中产生偏倚。我们将这一结果推广到其他三个程序。我们还创建了两个新的程序，其中用于识别离群值的标准作为样本量的函数进行调整，以产生不受样本量影响的结果。
Results from a Monte Carlo study demonstrate how a non-recursive, a simple recursive, a modified recursive, and a hybrid outlier elimination procedure are influenced by population skew and sample size. All the procedures are based on computing a mean and a standard deviation from a sample in order to determine whether an observation is an outlier. Miller (1991) showed that the estimated mean produced by the simple non-recursive procedure can be affected by sample size and that this effect can produce a bias in certain kinds of experiments. We extended this result to the other three procedures. We also create two new procedures in which the criterion used to identify outliers is adjusted as a function of sample size so as to produce results that are unaffected by sample size.