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One-way analysis of variance (ANOVA) was applied to analyze differences in data of biochemical parameters among the different groups.
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Following within-array normalization, differences in data range of the replicate arrays persisted.
Possible explanations for these different results include differences in data quantitation, inclusion of SGA newborns in the former study, or perhaps true differences between the two normal populations.
These differences were observed in data of all satellites appearing as a disturbance in magnetic field measurements varying in strength, direction and characterized by a local time dependence.
Data analysed for specific purpose were not readily applicable for others, not only because of differences in data, but also as a result of the lack of continuity of efforts following data collection campaigns for specific purposes.
Brand-specific differences in data reduction impede pooling of data for consortia to create large-scale cohorts, as for genome-wide-association-studies (GWAS).
Further, issues often arise when comparing recent to older data sets, because of differences in data quality.
The 1990 census showed 44percentt of the foreign-born were from Latin America, and 23percentt were from Europe, although the numbers are not directly comparable with 2000's because of differences in data collection.
Batch to batch differences in data were removed by synchronizing medians of QC-samples per batch.
Differences in data sets were determined using analysis of variance (ANOVA) or Student's t-tests.
Differences in data collection have questioned the validity of meta-analyses (Hawkes and Macgregor, 2009).
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