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The magnitudes of these distances are then compared between groups using ordinary ANOVA.
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Comparison between groups used two-tailed Student's t-test.
These contrast images were then input into a random-effects model for group analysis, using ordinary least squares (OLS) estimation.
Results were adjusted for differences in baseline clinical, demographic, and hospital characteristics between the bleeding-related complication and/or blood product transfusion and no bleeding-related complication and/or blood product transfusion study groups using multivariate ordinary least squares regression modelling techniques.
Second, for all k, we calculate P-values of the covariates in Q k based on the second group of data, Ψ2, using ordinary least-squares estimates.
Relationships between the instruments were estimated using ordinary least squares (OLS), generalized linear models (GLM), and censored least absolute deviations (CLAD) regression approaches.
Group number 1 is the control group in which the beams were cast using ordinary formwork.
Participants classified as lost to follow-up (n=34) were compared with the study group (n=235) for baseline demographic data using ordinary t test and 2 χ2 test for homogeneity.
The multiple comparisons between E. coli genotypes were processed using ordinary one-way analysis of variance (ANOVA).
Bivariate associations between all 44 correlates were estimated using ordinary least squares (OLS) regression.
The statistical differences between groups were determined according to SPSS version 16.0 and Graph Pad prism 6 using ordinary one-way ANOVA followed by Dunnetts multiple comparison tests.
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