Comparison of strategies for validating binary logistic regression models

Posted by / 27-Jul-2017 22:51

Comparison of strategies for validating binary logistic regression models

We evaluated several variants of split-sample, cross-validation and bootstrapping methods with a logistic regression model that included eight predictors for 30-day mortality after an acute myocardial infarction.

Random samples with a size between = 40,830; 2851 deaths) to reflect modeling in data sets with between 5 and 80 events per variable.

The regions with monoclinic geological structure are large portions of earth surface where the repetition of similar landform patterns is very distinguished, the scarps of cuestas being characterized by similar values of morphometrical variables.

Landslides are associated with these scarps of cuestas and consequently, a very high value of landslide susceptibility can be reported on its surface.

Often one wishes to study how a set of predictor variables = 1 denoting the occurrence of the event of interest.

Often a dichotomous outcome can be studied by calculating certain proportions, for example, the proportion of deaths among females and the proportion among males.

Performance measures included discriminative ability, calibration and overall accuracy.However, in many situations, there are multiple descriptors, or one or more of the descriptors are continuous.Without a statistical model, studying patterns such as the relationship between age and occurrence of a disease, for example, would require the creation of arbitrary age groups to allow estimation of disease prevalence as a function of age.The geomorphometric variables were computed from a Digital Elevation Model (DEM) obtained by interpolation from 00 contour data (2.5 m equidistance), at 10x10 m resolution.Distance from river network, distance from roads and land use were extracted from topographic maps and aerial images.

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For the same sample, the Analytic Hierarchy Process (AHP) approach was applied for landslide susceptibility assessment, using 7 predictors (slope angle, slope aspect, plan and profile curvature, distance to river network, distance to roads, and land use).