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Data were filtered according to different criteria as prediction significance, type and number of alleles, and absence of repetitive sequences.
Arrays were quantified on the basis of spot intensity relative to background, adjusted for experimental variation between arrays using average intensity over multiple channels, and fitted to a previously described error model [29] to determine significance (type I error).
We accounted for the potential for this pseudo-replication to generate false significance (type I error) in two ways.
For sample size calculations, power (type II error, or β) was set to 80%% and statistical significance (type I error, or α) was set to 0.05.
Given the small number of women with long-term metformin exposure (N = 150) and the shorter follow-up for breast cancer–specific mortality of 3.7 years, lack of power cannot be excluded as a reason for our failure to detect statistical significance (type II error).
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The paper first elaborates on the significance, types and the methods of academic assessments.
The types of data being collected, level of significance, types I and II errors, and power are also addressed.
Molecular profiling studies have classified breast cancers to five types with distinct prognostic significance: luminal type A, luminal type B, ErbB2-positive, normal-like, and basal type [ 28, 29].
Gu [ 29- 31] has developed a statistical method to test the significance of Type I and Type II functional divergence between duplicate genes.
Calculation requires that significance level (Type I error) and study power (1 – Type II error) are known.
Therefore, it is plausible that Mg deficiency has specific pathogenic significance in type 2 diabetic nephropathy; however, the exact role of Mg deficiency in type 2 diabetic nephropathy warrants further investigation.
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