Journal Article10.2307/2348620
Comparing Two Independent Groups Via Multiple Quantiles
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TL;DR: In this paper, the authors compare two groups in terms of multiple quantiles and illustrate a method for accomplishing this task, which is similar to the one described in this paper.
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Abstract: Typically two independent groups are compared in terms of some measure of location, usually the mean, or a method based on ranks. A concern about both of these approaches, already raised in statistical references, is that they can miss important differences. For example, a new treatment method might be beneficial for some subjects but detrimental for others. Details are given in this paper. An approach to this problem is to compare two groups in terms of multiple quantiles. The paper describes and illustrates a method for accomplishing this
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Citations
Beyond differences in means: robust graphical methods to compare two groups in neuroscience
TL;DR: It is illustrated how detailed graphical methods, combined with robust inferential statistics, can lead to a much more detailed understanding of group differences than bar graphs and t‐tests on means.
ANOVA: A Paradigm for Low Power and Misleading Measures of Effect Size?
TL;DR: There are many robust and exploratory ways of comparing groups that can reveal important differences that are missed by conventional methods based on means, and even modern methods based solely on robust measures of location.
Beyond differences in means: robust graphical methods to compare two groups in neuroscience
TL;DR: It is illustrated how detailed graphical methods, combined with robust inferential statistics, can lead to a much more detailed understanding of group differences than bar graphs and t-tests on means.
Review of assumptions and problems in the appropriate conceptualization of effect size.
Robert J. Grissom,John Kim +1 more
TL;DR: Estimation of the effect size parameter, D, the standardized difference between population means, is sensitive to heterogeneity of variance (heteroscedasticity), which seems to abound in psychological data, and various proposed solutions are reviewed, including measures that do not make these assumptions.
102
Re-Examining Phonetic Variability in Native and Non-Native Speech.
TL;DR: Results show that non-native speakers do not always exhibit more phonetic variability than native speakers, but rather that patterns of variability are specific to individual linguistic features and their instantiations in L1 and L2.
64
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