The impact of patient characteristics, including gender, age categories, number of concomitant drugs taken, diabetes treatment, and hyperlipidemia treatment, was adjusted using a multivariable regression method.
Then expressions to calculate the combustion parameters have been obtained by using a multivariable regression fitting method.
At Eurocrypt 2012, Faugère, Perret, Petit and Renault proposed a new method (FPPR method) using a multivariable polynomial system to solve ECDLP over finite fields of characteristic 2. At Asiacrypt 2012, Petit and Quisquater showed that this method may beat generic algorithms for extension degrees larger than about 2000.
To further assess the underlying differences among our CRC models, we identified gene signatures (lists of differentially expressed genes) characteristic of each mutant allele (Apc, Tp53, Kras, Braf) within the GEMM collection using a multivariable analysis (see Materials and Methods).
Data were analyzed using a multivariable linear mixed regression model.
Determinants of hospital mortality were identified using a multivariable logistic regression model.
This was tested using a multivariable, general linear model (multivariable GLM).
Significant variables from univariable regression, or those factors that were plausible confounders were included in a multivariable logistic regression model using a stepwise method.
This was initially done as a univariate analysis, then as a multivariable analysis using a forward stepwise method.
Using a backward elimination method multivariable logistic regression were developed (Table 3).
