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      Statistical analysis for toxicity studies

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          Abstract

          Generally, multiple statistical analysis methods can be applied for certain kind of data, and conclusion could differ, depending on the selected statistical method. Therefore, it is necessary to fully understand the performance of each statistical method and to examine which method is appropriate to use and to standardize statistical methods for toxicity studies to be carried out routinely. Several viewpoints for selecting appropriate statistical methods are discussed in this review paper. According to the distribution form, i.e., whether a distribution has a bell shape without outliers or not, either a parametric or a nonparametric approach should be selected. The nonparametric approach is also available for categorical data. Depending on the design and purpose of a study, several forms of statistical analysis are available. Assuming dose dependency, comparisons with a control are conducted by Williams test (nonparametric: Shirley-Williams test). When a dose dependent relationship is not expected, comparisons with the control are conducted by Dunnett test (nonparametric: Steel test). All possible pairwise comparisons among groups are conducted by Tukey test (nonparametric: Steel-Dwass test). If we are interested in several specific comparisons among groups, the Bonferroni-adjusted Student’s t-test (nonparametric: the Bonferroni-adjusted Wilcoxon test) can be used.

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          t Tests and Intervals for Comparisons Suggested by the Data

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            Pairwise Multiple Comparisons in the Homogeneous Variance, Unequal Sample Size Case

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              • Article: not found

              Tree-type algorithm for statistical analysis in chronic toxicity studies.

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                Author and article information

                Journal
                J Toxicol Pathol
                J Toxicol Pathol
                TOX
                Journal of Toxicologic Pathology
                Japanese Society of Toxicologic Pathology
                0914-9198
                1881-915X
                15 September 2017
                January 2018
                : 31
                : 1
                : 15-22
                Affiliations
                [1 ]Department of Information and Computer Technology, Faculty of Engineering, Tokyo University of Science, 6–3-1 Niijuku, Katsushika-ku, Tokyo 125–8585, Japan
                Author notes
                *Corresponding author: C Hamada (e -mail: hamada@ 123456rs.kagu.tus.ac.jp )
                Article
                2017-0050
                10.1293/tox.2017-0050
                5820099
                29479136
                063b163f-51a3-4ebb-9b67-e053c84dc92f
                ©2018 The Japanese Society of Toxicologic Pathology

                This is an open-access article distributed under the terms of the Creative Commons Attribution Non-Commercial No Derivatives (by-nc-nd) License. (CC-BY-NC-ND 4.0: https://creativecommons.org/licenses/by-nc-nd/4.0/ ).

                History
                : 22 August 2017
                : 23 August 2017
                Categories
                Review

                Pathology
                decision tree,parametric method,nonparametric method and multiple comparison
                Pathology
                decision tree, parametric method, nonparametric method and multiple comparison

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