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Inverse distance weighting (IDW) method was used due to lack of normality of distribution of annualized average incidence and difficulty of transformation (into to normal distribution).
The generalized least squares extraction method was used in favor of maximum likelihood because of the lack of normality of the data.
The Mann–Whitney test was used to compare RPKM between groups of genes due to lack of normality of the RPKM distribution.
28 Standard errors and 95% confidence intervals for parameters were calculated using robust (sandwich) estimators, allowing for the effects of the inverse probability weights and possible skewness (lack of normality) of the outcome data.
This association remained significant when a binary definition of severity was used indicating that the lack of normality of the distribution of K/L grades was not a statistical artefact.
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This lack of normality may be attributed to the existence of two scoring subgroups (normal subjects and GAD subjects), assumed to originate from different reference populations.
Lack of normality in the distribution of detection scores, and the inability to adequately normalize these values led us to employ the Spearman Rank Correlation to determine the correlation between detection and our metrics of interest, as well as to examine the correlation between detection and key constraints (e.g. heritability).
Thus, there is no longer any evidence of lack of normality.
I present for all correlational analyses parametric and non-parametric correlation coefficients, to deal with the potential problem of lack of normality in the distribution of the variables.
A value of v1/v0>0.4 (a decrease of β-CTX in v1 of <40%) and/or lack of normality in levels of β-CTX, indicates a six-fold increase in risk of mortality along the study.
A decrease of β-CTX in v1 of <40% and/or lack of normality in levels of β-CTX, indicates a six-fold increase in the risk of mortality along the study.
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