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The distribution of the data was explored by Sharpiro-Wilk's test for normality.
Sensitivity of the results to imputation of missing data was explored by running the models with and without imputation.
The relation between the size of the trial and the difference between the assumptions and observed data was explored by use of Spearman's correlation coefficient, and its 95% confidence interval was estimated by bootstrap.
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Themes emerging from these data were explored by in-depth interviews with a sample of 18 childcare providers and 7 Local Authority Early Years Service staff.
FRAP data were explored by mathematical modeling to estimate steady-state reaction parameters.
Categorical and continuous data were explored by means of frequency and mean ± standard deviation.
Structures within the data were explored by means of exploratory factor analysis using principal axis factoring with oblique rotation.
The GSF data were explored by looking at a range of factors which might contribute to likelihood of such physical and psychological burden for the GSF group.
The efficacy data were explored by stratifying into quartiles of body weight (≤72.6 kg, >72.6 to ≤90 kg, >90 to ≤101 kg, and >101 kg).
The statistical heterogeneity of the data was explored and quantified by the Mantel-Haenszel chi-square test and the I test.
Subsequently, the clr-transformed data set was explored by biplots, a graphical representation of variables and cases projected on to principal component planes.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com