Planning, designing, performing and publishing animal experiments

• improve the quality of my scientific work • get published in better journals • save time and money • use fewer animals

• group size • relevant effect of treatment (signal) • standard deviation (noise) • desired power • level of significance • alternative hypothesis

• pilot study • exploratory experiments • confirmatory experiments • experiments to explore relationships between variables

• logistics - setup of experimental protocol • to analyse effect of treatment • to analyse variation (noise) • determine size of experiment • staff training

• develop hypotheses for further testing • measure many outcomes • data snoopign –> hypothesis testing • should be confirmed in a controlled expeirment • analysed in a ANOVA

• is a comparison • tests a null hypothesis • subjects are randomised • should, if possible, be blind • need to be powerful - have high probability of detecting an effect

• tests whether two variables are associated • if so, the nature of that relationship

• completely randomised design (computer) • randomised block design • latin square design

• deals with known (suspected) heterogeneity • breaks up an experiment into mini experiments • subsets of experimental units (animals) e.g. males and females, large and small etc. (so that you don’t end up having all large or femal animals in one group)

• have a clear specification of the aims of the experiment • is unbiased • is powerful • has a wide range of applicability • should be simple • should be possible to statistically analyse