Sentence examples for modelling by logistic from inspiring English sources

In multivariate modelling by logistic regression, all predictor variables having an association with an outcome variable with p < 0.1 were entered into an initial model which was then reduced by successive elimination of variables with p > 0.05.

In the absence of external, independent validation, studies which rely on statistical modelling by logistic regression may lead to over-optimistic assessment of predictive utilities due to the phenomenon of "over-fitting" [ 23].

The spatial incidence of landslides, triggered by an extreme rainfall in a study area, was modeled by logistic regression.

Statistical relationships between the distance from the nearest WUI area, and large forest fire incidents from satellite remote sensing were subsequently modelled by logistic regression analysis.

MoCA scores were modelled by logistic regression, as implemented in SPSS 22 for Windows (IBM Corporation, Armonk, New York, USA).

Inherent mathematical properties in a model used may bias an effect measure such as an odds ratio modelled by logistic regression.

Data were modelled by logistic regression, with adjustment forotal energy intake and established breast cancer risk factors, as well as mutual adjustment among the micronutrients.

For each medical condition, the outcome, that is, patient status of dead/alive, was modelled by logistic regression of hospitals and case-mix variables.

The outcomes were modeled by logistic regression (responder outcome) and linear regression (future pain intensity outcome) using generalized estimating equations (with the AR1 correlation structure) to account for the repeated measures for the same subject [ 52– 52].

Briefly, an occurrence variable (O) that was modeled by logistic regression specifies whether or not people spent time at a location or in an activity; and for the non-zero values, a duration variable (D) that was modeled by normal or lognormal regression specifies how long people spent at a location or on an activity.

Once an adaptive mutation becomes established in the population by reaching a population frequency x ≈ (2 Ns)−1 that ensures its escape from future stochastic loss (Maynard Smith 1971), its frequency trajectory can be modeled by logistic growth (1) x (t ) = e s t e s t + 2 N s.