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We found no evidence for population stratification between the cohorts using 40 unlinked SNPs from unrelated genes (mean χ2 = 3.3, P = 0.58) [40.58
We identified 3 variants displaying effect differences between the cohorts using genotype-cohort interaction analysis (interaction p-value <0.05), and they were removed.
Study outcomes were compared between the cohorts using standard bivariate and multivariable methods.
Data for counts of injuries, illness, restricted work days, sick days and hospital visits were compared between the cohorts using negative binomial regression.
These characteristics were compared between the cohorts using two-sample t-tests for continuous variables and chi-squared tests for categorical variables.
Similar(55)
For the serial in vivo MR spectroscopy data and viral loads, repeated measures analysis of variance RM-ANOVAA) in combination with Holm's t-tests was employed to isolate differences between time-points within the cohorts using JMP 7.0 (SAS, Cary, NC).
Comparisons were made between the two cohorts using the nonparametric Mann-Whitney U test if the data were not normally distributed and Student t test if data were normally distributed.
To more objectively illustrate this, we evaluated the Spearman's rank correlation of the delta-Rg between the two cohorts using all SNP-transcript pairs (Cor = 0.25, p < 2x10-16).
We calculated and compared the cumulative incidence of CKD in data with competing risk by the modified Kaplan-Meier method and Gray's method [ 31], and tested differences in the full time-to-event distributions between the study cohorts using modified log-rank test.
Comparison was made between the two cohorts using standard descriptive statistics.
Altogether these results show strong similarities between the two cohorts using virological markers aimed at further assessing viral reservoirs and residual replication in peripheral blood in these aviremic subjects.
Related(20)
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