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The problem with the ANOVA analysis is that it has reduced power to detect linear relationships (and hence larger p-values), which can lead to increased Type II errors.
Because obesity is an established risk factor for type 2 diabetes, it is important to determine whether the increased genetic predisposition to obesity translates to increased type 2 diabetes risk, which we were able to confirm for several variants.
However, mixed model test statistics are prone to increased type I error rates, particularly if utilized with large amounts of missing data.
This, in turn, can lead to increased Type I errors, causing analysts to incorrectly reject null hypotheses.
Using the Poisson model for statistical tests would lead to increased Type 1 errors (rejecting the null hypothesis when it is true).
However, correlated genes lead to increased type I error for the gene randomization (Q1) and parametric methods (PAGE and PAR Wilcoxon).
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Next, we examined whether the increased CTX-II levels relate to an increased type II collagen synthesis in the rats and therefore measured the synthesis marker PIIANP.
To account for increased Type 1 error the critical alpha was adjusted using Bonferroni's inequality, giving a p value of less than 0.016 as denoting statistical significance [ 12].
Thus we might anticipate a smaller value for the t-statistic, leading to increased type-II errors.
This may be due to increased type-I collagen expression resulting in increased the matrix density, and altered cell behavior resulting in a more organized collagen matrix.
It seems that as we moved from phones with buttons – BlackBerrys and even feature phones – the parts of our brain associated with the thumbs are changing thanks to increased screen typing activity.
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Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.

Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com