nstantaneous and historical temperature effects on a-pinene
Statistical tools for analysing the data obtained from repeated dose toxicity
studies with rodents: A comparison of
the statistical tools used
in Japan with that of used in other
countries
Author Details
KatsumiKobayashi(Corresponding
author)
National Institute of Technology and Evaluation (NITE), 2-49-10
Nishihara, Shibuya-ku,
Tokyo
- 151 0066, Japan
e-mail: kobayashi@beige.plala.or.jp
K. SadasivanPillai???
Frontier
Lifeline, International Centre for Cardio-Thoracic and Vascular Diseases,
Chennai
- 600 101, India
Soma
Guhatakurta
Frontier
Lifeline, International Centre for Cardio-Thoracic and Vascular Diseases,
Chennai
- 600 101, India
K.M.
Cherian
Frontier
Lifeline, International Centre for Cardio-Thoracic and Vascular Diseases,
Chennai
- 600 101, India
MarikoOhnishi
National
Institute of Technology and Evaluation (NITE), 2-49-10 Nishihara, Shibuya-ku,
Tokyo
151-0066, Japan
Publication Data
Paper received:
01
December 2009
Revised
received:
April 24 2010
Accepted:
11 May 2010
Abstract
In the present study, an attempt was made to compare the
statistical tools used for analysing the data of repeated
dose toxicity studies with rodents conducted in 45 countries, with that of Japan. The
study revealed that there was no congruence among the countries in the use of
statistical tools for analysing the data obtained
from the above studies. For example, to analyse the
data obtained from repeated dose toxicity studies with rodents, Scheff?s multiple range and Dunnett
type (joint type Dunnett) tests are commonly used
in Japan,
but in other countries use of these statistical tools is not so common. However,
statistical techniques used for testing the above data for homogeneity of
variance and inter-group comparisons do not differ much between Japan and
other countries. In Japan,
the data are generally not tested for normality and the same is true with the
most of the countries investigated. In the present investigation, out of 127
studies examined, data of only 6 studies were analysed
for both homogeneity of variance and normal distribution. For examining
homogeneity of variance, we propose Levene?s test,
since the commonly used Bartlett?s test may show
heterogeneity in variance in all the groups, if a slight heterogeneity in
variance is seen any one of the groups. We suggest the data may be examined
for both homogeneity of variance and normal distribution. For the data of the
groups that do not show heterogeneity of variance, to find the significant
difference among the groups, we recommend Dunnett?s
test, and for those show heterogeneity of variance, we recommend Steel?s
test.
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