Journal Article10.1080/14640749408401131
A Solution to the Effect of Sample Size on Outlier Elimination
Mark Van Selst,Pierre Jolicoeur +1 more
878
TL;DR: In this article, the authors 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.
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Abstract: 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.
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References
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John Jonides,Steven Yantis +1 more
TL;DR: Experiments are reported investigating whether abrupt onset is simply one member of a large class of stimulus characteristics, all of which are capable of capturing attention, and whether these also could elicit shifts of attention.
Chronometric evidence for central postponement in temporally overlapping tasks
Harold Pashler,James C. Johnston +1 more
TL;DR: In this paper, two general types of models have been proposed to account for response delays: capacity sharing and postponement models, which assume that processing stages in the second task are delayed due to a single-channel bottleneck.
Analysis of Response Time Distributions: An Example Using the Stroop Task
TL;DR: In this paper, the shape of a response time (RT) distribution can be described by a 3-parameter model consisting of the convolution of the normal and exponential distributions, the ex-Gaussian.
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Reaction time analysis with outlier exclusion: bias varies with sample size.
TL;DR: Simulations show that there is substantial differential bias when comparing conditions with fewer than 10 observations against conditions with more than 20, and strongly skewed distributions and a cutoff of 3.0 standard deviations can influence comparisons of conditions with even more observations.
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