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Thus, the occurrence of type I error in the present material is unlikely.
The Type I error in case of Altman original model on holdout sample is very high and close to 75%%.
This effect leads to a change in the probability of the type I error in ns trials.
The inclusion of the studied item facilitates controlling for type I error in the DIF detection for these procedures (Jiang and Stout 1998).
The Type I error in case of new model is found to be 18%% and Type II error close to 8%%.
Regarding the type I error, in some of the analyses the α-levels were Bonferroni corrected, since the items supposedly measured the same construct.
They can err by permitting something bad to happen (approving a harmful product, a Type I error in risk-analysis parlance) or by preventing something good from becoming available (not approving a beneficial product, a Type II error).
Therefore, we used the Bonferroni correction, respectively its exact version (the Sidak correction), both adjusting for the fact that the probability of a type I error in a multiple test differs from the error probability in a single test.
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The randomization approach is therefore a conservative approach and properly controls type-I error in the presence of chip-to-chip variation of β-values.
Only one previous study has identified gender differences in HA [ 17]; however, the sample for this study was small, such that the results may be due to a type-I error in the statistical analyses.
However, under certain conditions, the CD method may result in upwardly or downwardly biased estimates for the Type-I error in specific regions of the genome a property we refer to as location bias.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com