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Regarding recommendations to reduce risk, an awareness campaign about the risks involved would probably have an impact since the participants in the algorithm validation were surprised about its accuracy and hence unaware of what can be achieved by analysing running data.
This subtle deficit is detected ~3 months before the earliest published motor phenotype in these mice (Acevedo-Arozena et al., 2011; Gurney, 1994) and only emerged when analysing running activity at the beginning of the dark phase during the first week.
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We analysed running speed of the lizards.
We performed parsimony analyses running the command-line Unix version of PAUP*.
Analyses run on the PP population confirmed the primary efficacy results.
Table 3 shows the analyses run for categorical variables.
With this analysis, 15 analyses produced p<0.05, or 4.87% of analyses run.
Analyses ran with and without imputed data provided similar results.
Consequently, these analyses run the risk of false-positive results.
reported large differences in results from analyses run on complete cases only and analyses run on the entire dataset with imputed values.
A summary of comparative analyses run in this study can be found in Table 3.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com