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Host mortality trends were analyzed using the Cox proportional-hazards regression model with coefficients estimated using maximum likelihood.
The normalized data were statistically analyzed for differential gene expression using a linear model with coefficients for each experimental group [ 24].
The primary outcome variable is HbA1c, and differences in this between the two study groups at 6 months will be compared using a marginal model, with coefficients and their associated 95% CI estimated using generalised estimating equations.
Importantly, we found that the model with coefficients for both vestibular and visual signal correlations provided a significantly better fit to the data, after accounting for the difference in the number of parameters (p=0.0003, sequential F-test).
We used a marginal generalised linear model with coefficients estimated using generalised estimating equations 32 with robust standard errors and an exchangeable auto correlation matrix in Stata v8 (StataCorp, College Station, TX) to analyse the outcomes and adjust for the potential clustering of the data.
The listed variables were used to generate the risk scores evaluated in Figures 8, 9 and 10, where risk scores for test subjects represent the output of a 13-variable Cox model with coefficients corresponding to measures listed in the table below.
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Moreover, the ANOVA analysis recommends the third-order polynomial response surface model with coefficient determination (R2) of 0.9022 for particle size.
Results showed that reaction kinetics at optimum conditions conformed to the pseudo-first order model with coefficient of determination and k values of 0.9862 and 0.0277 min−1, respectively.
Regression analysis showed good fit of the experimental data to the second-order polynomial model with coefficient of determination (R2) value of 0.9114 and Fisher F-value of 10.28.
Regression analysis indicated good fit of the experimental data to the third-order polynomial model with coefficient of determination (R2) value of 0.9994 and F-value of 2570.57.
Regression analysis showed good fit of the experimental data to the second-order polynomial model with coefficient of determination (R2) value of 0.966 and Fisher F-value of 10.28.
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