To test this hypothesis, we used multiple linear regression analysis by taking gefitinib profiles as response variables and U0126 and wortmannin profiles as explanatory variables, where only promoters significantly affected by gefitinib are considered.
For further investigation of the clinical applicability of PFAA profiles, the combinatorial use of both the discriminating function from PFAA profiles as explanatory variables and existing tumor markers generally used for lung cancer detection and monitoring (CEA, CYFRA, ProGRP, SCC, and NSE) was assessed [ 39, 41].
Hereby we obtained rate ratios and 95% confidence intervals for comparisons between groups of appendicectomy cohort members with different profiles of explanatory variables and confounders.
Although there are still some unexplained effects when using those two profiles as explanatory variables, our regression model successfully explained the changes in majority promoters significantly altered by gefitinib, and its statistical significance was confirmed by permutation test (see Supplementary Figure S6 online).
That is why we incorporated the healthcare professional's ICT user profile as an explanatory factor of his or her intention to use Information and Communication Technologies at an advanced level in his or her usual practice.
Multiple regression analyses were conducted, using the profile variables as explanatory (predictor) variables, on Overall performance and on each of the Section scores using an alpha level of 5% where relevant.
The objective of this paper is to try to provide a unified framework for Phase II monitoring of generalized linear profiles of which the explanatory variables can be fixed design or random arbitrary design.
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Using logistic regression analysis, the intensity of the recognition of rMSP5 and rEBA175 (higher RI values against these antigens produced by plasmas from asymptomatic individuals grouped in the 3rd tercile) was independently associated with the explanatory variable "clinical profile-symptomatic or asymptomatic".
