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Comparison of Simulated Power Among Multiple Comparison Tests

2019
In this chapter, we perform a Monte Carlo simulation to investigate the performance of several procedures discussed in Chaps. 1– 4. Proposed procedures [1.5] and [3.4] demonstrate the best performance in each situation.
Taka-aki Shiraishi   +2 more
openaire   +1 more source

LOPSIDED REASONING ON LOPSIDED TESTS AND MULTIPLE COMPARISONS

Australian & New Zealand Journal of Statistics, 2012
SummaryFor those who have not recognized the disparate natures of tests of statistical hypotheses and tests of scientific hypotheses, one‐tailed statistical tests of null hypotheses such as ∂≤ 0 or ∂≥ 0 have often seemed a reasonable procedure. We earlier reviewed the many grounds for not regarding them as such.
Hurlbert, Stuart H., Lombardi, Celia M.
openaire   +2 more sources

Multiple Comparisons and Multiple Tests

Technometrics, 2000
Eric R. Ziegel   +5 more
openaire   +2 more sources

Test for Inference: Multiple Sample Comparisons

2019
Background Concept of sum of squares ANOVA one way ANOVA two way Duncan’s multiple range method Fisher’s least significance difference ...
Shakti Kumar Yadav   +2 more
openaire   +1 more source

Algorithm for Shaffer'S Multiple Comparison Tests

Educational and Psychological Measurement, 1993
Shaffer has presented two tests to improve the power of multiple comparison procedures. The present article describes an algorithm to carry out the tests. The logic of the algorithm and an application to a data set are given.
openaire   +1 more source

Multiple Comparison Tests for Path Analysis and Multiple Regression

The Journal of Experimental Education, 1981
A joint probability, multiple comparisons significance test is developed for path analysis, multiple regression, and a correlation matrix. Tests are developed for determining the: obtained α level for an entire family of tests, probability of a specified number of tests being statistically significant by chance, obtained α level for indirect paths, and
openaire   +1 more source

Designs for Multiple Pair-Comparison Sensory Tests

Canadian Institute of Food Technology Journal, 1970
Abstract A complete schedule of paired comparisons among n items for (say) flavor appraisal involves n(n — 1)/2 pairs. Schemes for allocating the pairs equitably among a panel of n — 1 subjects (if n is even) or n subjects (if n is odd) are given.
openaire   +1 more source

Multiple comparison tests

2003
Stephen Ashcroft, Chris Pereira
openaire   +1 more source

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