Topics covered include population sampling and generalizability, power and sample size calculations, correction for multiple statistical testing, and how to identify the appropriate use of statistics.
These inconsistencies likely relate to a variety of methodological issues, including small sample sizes, variable definitions of case and control groups, failure to adjust for multiple statistical testing, and inadequate adjustments for population stratification and smoking exposure.
The lack of randomization, allocation concealment, blinding, primary outcome, and sample-size calculation, multiple statistical testing, and publication bias have been assumed to account for the poor translation of AR to human medicine [ 24– 324.
The difference in predictivity of multiple statistical methods and descriptors between pharmaceutically relevant data and literature compilations is analyzed firstly for aryl-amines and then for sets containing all substructures.
Consequently, they also clearly violate the CONSORT guidelines [67] regarding interpretation of the results under consideration of the study hypotheses, the possible causes of distortions ("bias") and the problems brought about by multiple statistical testing and multiple target criteria.
These included IGFBP2 and GATA3, which were identified by multiple statistical methods, and a number of additional proteins that were detected by multiple (Table 3, Table 4) or any method (Supplemental Table 3, Supplemental Table 4).
The lack of randomization, allocation concealment, blinding, primary outcome and sample size calculation, as well as multiple statistical testing, and publication bias have been assumed to account for the poor translation of AR to human medicine [3],[3],[3],[3]].
In fact, the lack of randomization, allocation concealment, blinding, eligibility criteria, primary outcome, and sample size calculation, as well as multiple statistical testing, and publication bias have been assumed to account for the poor translation of AR to human medicine [3],[3],[3],[3]],[3]].
The lack of randomization, allocation concealment, blinding, primary outcome and sample size calculation, as well as multiple statistical testing, and publication bias have been assumed to account for the poor translation of AR to human medicine [ 3],[ 6],[ 8],[ 27].
In fact, the lack of randomization, allocation concealment, blinding, eligibility criteria, primary outcome, and sample size calculation, as well as multiple statistical testing, and publication bias have been assumed to account for the poor translation of AR to human medicine [ 3],[ 6],[ 8],[ 27],[ 51].
