Sentence examples for by multiple statistical from inspiring English sources
This counterintuitive finding is reinforced by multiple statistical methods and suggests that contact by a political campaign may engender a backlash.
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.
For example, Mario's strength is determined by multiple statistical fields and status-boosting items that can be used in and outside of combat.
To account for the problem caused by multiple statistical tests we used the Bonferroni adjustment to modify the significance criterion (α/k where k = the number of statistical tests) [40].
The paper would have been strengthened by multiple statistical testing of the hypotheses (see comments below).
Hypothesis generation is performed automatically by a computer program that utilizes the KAM to identify hypotheses that explain the input RNA State Changes, prioritized by multiple statistical criteria.
Our effort builds on earlier analyses [ 30, 31] by focusing on a distinct cohort of patients and by using multiple statistical methods to cross-validate the algorithms.
This work demonstrates the biomimetic nature of the plasma treated polymer membranes by evaluating multiple statistical relationships, including Bland-Altman analysis and correlation coefficients (Puppolo et al. 2017).
A more recent approach, namely meta-analysis, looks for common signatures across multiple independent datasets by combining multiple statistical methods including simple t-test, FDR, and cross-validation into a single result [18].
Our study contributes to this literature by employing multiple statistical methods to examine the community context of human actions in response to forest disturbance by beetles in north central Colorado.
By means of multiple statistical tests, including geographically weighted regression, we analysed the effects of eight variables on the regional spatial variation of aboveground biomass.
