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Open Access Highly Accessed Research article

Improving basic and translational science by accounting for litter-to-litter variation in animal models

Stanley E Lazic1* and Laurent Essioux2

Author Affiliations

1 In Silico Lead Discovery, Novartis Institutes for Biomedical Research, Switzerland

2 , Bioinformatics and Exploratory Data Analysis, F. Hoffmann-La Roche, Basel, Switzerland

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BMC Neuroscience 2013, 14:37  doi:10.1186/1471-2202-14-37

Published: 22 March 2013

Additional files

Additional file 1:

R code for the analyses and power calculations. Code for the analyses and power calculations are given as a plain text file.

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Additional file 2:

Raw data. Raw data from Mehta et al. [41], including body weight, locomotor activity and anxiety measures from the open field test, grooming behaviour, and number of marbles buried in the marble-burying test. Details can be found in the original publication.

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Additional file 3:

List of VPA studies. List of the thirty-four studies using the VPA rodent model of autism.

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Additional file 4:

Power analysis for the mixed-effects model and the incorrect analysis. The interpretation of the graphs is the same as Figure 4 (main text). Panels A and B are for the mixed-effects model and are nearly identical to the results for averaging the values within each litter and then using a t-test (Figure 4 main text). Panels C and D ignore litter and compare all of the data with a t-test, which results in an artificially inflated sample size and inappropriately high power.

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