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How to calculate sample size in animal studies

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TLDR
Few methods of sample size calculations for animal studies are suggested on the basis of review of literature done by us and these methods may lead to unnecessary wastage of resources and ethical issues.
Abstract
Calculation of sample size is one of the important component of design of any research including animal studies. If a researcher select less number of animals it may lead to missing of any significant difference even if it exist in population and if more number of animals selected then it may lead to unnecessary wastage of resources and may lead to ethical issues. In this article, on the basis of review of literature done by us we suggested few methods of sample size calculations for animal studies.

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Journal ArticleDOI

How to calculate sample size for different study designs in medical research

TL;DR: In this review sample size calculation for most frequently used study designs are mentioned and for genetic and microbiological studies readers are requested to read other sources.
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Light Affects Mood and Learning through Distinct Retina-Brain Pathways

TL;DR: It is revealed that the direct effects of light on learning and mood utilize distinct ipRGC output streams, and the results provide new insights into the neural basis required for light to influence mood and learning.
Journal ArticleDOI

Sample Size Calculation in Animal Studies Using Resource Equation Approach.

TL;DR: The aim of this article is to guide researchers in calculating the minimum and maximum numbers of animals required in animal research by reformulating the error DF formulas.
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Sample size, power and effect size revisited: simplified and practical approaches in pre-clinical, clinical and laboratory studies.

TL;DR: In this article, the importance of sample size and its relationship to effect size (ES) and statistical significance is discussed. But, there is no straightforward way of calculating the effective sample size for reaching an accurate conclusion, and use of a statistically incorrect sample size may lead to inadequate results in both clinical and laboratory studies.
References
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Journal ArticleDOI

G*Power 3: A flexible statistical power analysis program for the social, behavioral, and biomedical sciences

TL;DR: G*Power 3 provides improved effect size calculators and graphic options, supports both distribution-based and design-based input modes, and offers all types of power analyses in which users might be interested.
Journal ArticleDOI

Improving Bioscience Research Reporting: The ARRIVE Guidelines for Reporting Animal Research

TL;DR: Most of the papers surveyed did not report using randomisation or blinding to reduce bias in animal selection and outcome assessment, consistent with reviews of many research areas, including clinical studies, published in recent years.
Journal ArticleDOI

Guidelines for the Design and Statistical Analysis of Experiments Using Laboratory Animals

TL;DR: In this article, the authors present guidelines to help biomedical research workers perform their experiments efficiently and analyze their results so that they can extract all useful information from the resulting data, including the varying purposes of experiments, the experimental unit, the necessity of recording full experimental details (e.g., species, sex, age, microbiological status, strain and source of animals, and husbandry conditions).
Journal Article

Guidelines for the design and statistical analysis of experiments using laboratory animals. [Erratum: 2005, v. 46, no. 3, p. 320.]

M.F.W. Festing, +1 more
- 01 Jan 2002 - 
TL;DR: These guidelines are provided to help biomedical research workers perform their experiments efficiently and analyze their results so that they can extract all useful information from the resulting data.
Journal ArticleDOI

An introduction to power and sample size estimation

TL;DR: The importance of power and sample size estimation for study design and analysis and the role of meta-analysis in this work is illustrated.
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