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The Measurement of Association - A Permutation Statistical Approach (Hardcover, 1st ed. 2018)
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The Measurement of Association - A Permutation Statistical Approach (Hardcover, 1st ed. 2018)
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This research monograph utilizes exact and Monte Carlo permutation
statistical methods to generate probability values and measures of
effect size for a variety of measures of association. Association
is broadly defined to include measures of correlation for two
interval-level variables, measures of association for two
nominal-level variables or two ordinal-level variables, and
measures of agreement for two nominal-level or two ordinal-level
variables. Additionally, measures of association for mixtures of
the three levels of measurement are considered: nominal-ordinal,
nominal-interval, and ordinal-interval measures. Numerous
comparisons of permutation and classical statistical methods are
presented. Unlike classical statistical methods, permutation
statistical methods do not rely on theoretical distributions, avoid
the usual assumptions of normality and homogeneity of variance, and
depend only on the data at hand. This book takes a unique approach
to explaining statistics by integrating a large variety of
statistical methods, and establishing the rigor of a topic that to
many may seem to be a nascent field. This topic is relatively new
in that it took modern computing power to make permutation methods
available to those working in mainstream research. Written for a
statistically informed audience, it is particularly useful for
teachers of statistics, practicing statisticians, applied
statisticians, and quantitative graduate students in fields such as
psychology, medical research, epidemiology, public health, and
biology. It can also serve as a textbook in graduate courses in
subjects like statistics, psychology, and biology.
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