Sentence examples for models of stepwise from inspiring English sources

One finding from these final models of stepwise regression analysis was that female gender was associated with reporting higher scores on the HSCL-37A in both forced entry and stepwise models.

Variables resulting statistically significant at univariate analysis were selected by two models of stepwise logistic regression, including or excluding the Charlson index (which already takes into account diseases reported in the index admission).

Two different models of stepwise logistic regression with backward elimination were performed on the overall sample of woman to identify: (i) predictors of knowledge of cervical cancer aetiology and (ii) predictors of having a Pap-test as a consequence of the mass media campaign.

Data from the literature on activation parameters for the electrochemical reduction of O2 in various acid media (concentrated phosphoric acid, trifluoromethane sulphonic acid and perchloric acid) have been treated, using a model of stepwise change of the activation energy.

Multivariate analysis was performed using a hierarchical model of stepwise logistic regression that included possible explanatory variables, calculating the adjusted risk of PMPS from the odds ratio (OR) and the 95% CI at a significance level of 5%.

In this report, however, we present evidences to support the other model of stepwise polymerization for the amyloid fibril formation of α-synuclein.

A simulation model of stepwise tumorigenesis illustrates how powerful clonal selection can be by, in effect, raising the mutation rate through increasing population size.

Colorectal cancer has served as a model of stepwise progression from normal epithelium, through benign growth, into malignant cells that eventually become invasive and acquire metastatic properties [ 5].

We propose here a new model of stepwise, Fibonacci process-like elongation of a tRNA molecule from just two (triplet and quadruplet) motifs to a 76 nt-long cloverleaf.

Models of multiple stepwise linear and logistic regression analysis were constructed to evaluate the relationships between several explanatory variables and these functional outcomes.

Models of multiple stepwise linear and logistic regression analysis were constructed to evaluate the relationships between the explanatory variables and the outcomes with continuous and categorical distributions, respectively.