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Two approaches were used to calculate the GRS: a simple risk alleles count method (count GRS, cGRS) and a weighted method (weighted GRS, wGRS).The wGRS weights each risk allele by the logarithm odds ratio (Log(OR)) for that allele in our dataset.
Logistic regression analysis and analysis of covariance was conducted after adjusting for age, education, income, residential area, height, weight, and self-perceived health using a weighted method.
We used in our developments a weighted method to assess the group effect: this method gives equal weight to each subject, whatever the size of his/her center is.
Based on the traditional eigenvector method, a weighted method is proposed.
A weighted method was used to quantify the index and produced both a qualitative class and a score.
In this paper, we present a weighted method based upon the node betweenness, and discover that synchronizability of the complex networks can be enhanced by the weighted method.
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We also use an evolvable weighted method to change our classifier with time.
The material velocity vector at any node can be obtained by the potential of adjacent nodes with an appropriate weighted method.
Two methods have been proposed for the estimation of a causal effect from these summarized estimates: an inverse-variance weighted method [ 19], and a likelihood-based method [ 20].
A "non-parametric weighted" method used for the PRRSV analysis was previously used [ 12].
The obesity and diabetes genotype scores were calculated, respectively, on the basis of the 32 and 35 SNPs by using a previously described weighted method (19).
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