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We performed our primary analyses using tagging SNPs from the downstream block and plasma TG level, the trait most strongly associated with CNR1 in our prior work [4].
48 49 We undertook our primary analyses using "shift analysis," an analytical approach accepted by the European Drug Licensing agency.
All primary analyses using regression models were performed using diagnostic sub-type as the only predictor variable.
As a result of a large missing data fraction, we also reran the primary analyses using multiple imputation with SAS 18.0 to handle missing data.
Figure 1 shows the results from the primary analyses using a multivariable proportional odds logistic regression model of the VES-13 score.
We undertook sensitivity analyses around our primary analyses, using a 'one-study removed' analysis, whereby the meta-analysis is run multiple times each with a different and single study removed, was undertaken.
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First, primary analyses used all available results but without imputation of missing data.
Primary analyses used the GENMOD procedure in SAS to develop generalized estimating equation (GEE) models [35] using an exchangeable correlation structure which examined the relationship between the repeated outcome measure of failure to remit at each assessment point and the independent variables.
The primary analyses used generalized estimating equations.
All primary analyses used the relative telomere length measure.
Our primary analyses used the latter approach, and we incorporated the sample weights in sensitivity analyses.
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