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Differences between groups at baseline will be tested using linear regression techniques or Chi-square statistics.
Following this assessment of the measurement model, descriptive statistics will be computed and the associations presented in Figure 1 will be tested using linear stepwise regression analyses.
Many associations can be tested using linear models and practicable alternative methods for handling non-linear relationships have been broadly developed and validated in recent years.
The analysis for all of the secondary mortality outcomes will also be tested using linear mixed models, with a structure comparable to that used for the primary analysis that incorporates both random cluster effect and fixed effects for time (pre versus post HBB/ENC training and equipment).
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Neat, polymer modified and nanoclay modified bitumens were tested using linear amplitude sweep test.
First, the correlations between the MIDAS scores and the PTSD scores and the MIDAS scores and the alexithymia scores were tested using linear regression analysis.
The hypotheses were tested using linear mixed effects models on species richness, biomass and phylogenetic community structure with treatments and interactions among treatments as explanatory variables and site as a random effect.
SBP and DBP were tested using linear regression with and without covariates (age, sex).
Differences in colony forming units (CFU) across genotypes and time were tested using linear regression.
The differences in SNP and haplotype frequencies between young, middle-aged and older study participants were tested using linear regression.
First, the association between each SNP and BMI at baseline was tested using linear regression, assuming an additive effect of the minor allele.
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