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Cluster analysis was applied on the total dataset from the two seasons.
The population analysis was carried out using a combined dataset from the two separate studies, as detailed below.
The pooled dataset from the two studies consisted of 1,426 patients (intention-to-treat population) of which 712 were treated with olmesartan at an average dose of 27.2±12.6 mg (47.1% of patients taking the full drug dosage) and 714 treated with ramipril at an average dose of 7.3±3.1 mg (55.3% of patients taking the full drug dosage, P=0.008 vs olmesartan).
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The proposed genetic unit averages of pseudo-model (Eq. 4) was validated using dataset from the four (4) fields within various depositional environment of the Niger Delta.
The proposed model validation indicates an excellent adjusted correlation coefficient and lower errors based on analysis of variance (ANOVA) using approximately 1000 routine core and well log dataset from the four distinct environments of deposition.
We performed further analyses with a combined dataset from the three populations to distinguish the relationship between GC-effect and size-effect.
Datasets from the two different temperatures were handled separately.
We pooled the datasets from the two National Health Interview Surveys.
The distribution of correlation coefficients of different datasets varies greatly, as is demonstrated in Figure 1, which plots actual expression datasets from the two species.
To assess the reliability of using mouse and human gene expression data we have compared the datasets from the two species separately.
Next, the datasets from the two assessors were compared and any disagreements were solved by an obstetrician (CR) who was blind to the assessor.
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