Content analysis as pursued by the MERCI project suits such nested analysis, which requires access to a quantitative data set with sufficient observations to allow statistical analysis.
Differences in cell proliferation were examined using a mixed model nested analysis of variance (ANOVA).
We conducted nested analysis of variance to identify statistical effects of treatments, biological replicates within treatments, and arrays within biological replicates.
The data are then analyzed within a nested analysis of variance framework.
In this nested analysis only patients who were tested positive for HCV antibodies or HBV antigens were included.
This is a nested analysis within a main study in the ICONA Cohort which investigated the association between biomarkers of MT and IA and HIV progression [ 7].
F-tests performed for a fully nested analysis of variance (ANOVA) showed an effect of genotype (p = 0.000), but no effect of biological replication (p = 0.334).
Similarly, nested analysis partitioned by country, within population, Uganda 83 %, Kenya 97 %, Tanzania 86 % and ILRI-FG 96 %, was also highly significant (P < 0.001).
Moreover, a nested Analysis of Molecular Variance (AMOVA, [ 96]) was implemented to test for the partition of genetic variance within locations, among locations within haplogroup and among haplogroups.
Moreover a previous professional exposure to active TB cases resulted independently associated with TST positivity, at both multivariate and nested analysis.
We used nested analysis of covariance (ANCOVA) to test for differences in the rate of response between selection directions, with 'cumulative selection differential' as the covariate and 'replicate within direction' as a random effect.
