Sentence examples for multinomial logit regression from inspiring English sources

For a sample of 1397 trips, we fitted a multinomial logit regression model.

Survey data from exurban landowners in rural Wyoming are analyzed using multinomial logit regression.

Finally, a model-based behavioral analysis based on Multinomial Logit regression was conducted to systematically identify the statistically significant variables in explaining rear-end risk potential.

We estimate physician altruism, the weight individuals attach to patients' health benefit, by fitting mixed logit and multinomial logit regression models to the experimental data.

The data for the analysis are drawn from the survey Encuesta de Mayores 2010 (IMSERSO) by means of different specifications of Logit techniques, namely a Logit Regression Model and a Multinomial Logit Regression Model.

Here we describe a method to monitor changes in habitat types by producing sequential maps based on point information followed by mapping using a multinomial logit regression model with abiotic variables of which maps are available as predictors.

22Similar multinomial logit regressions for the sample of ineligibles produced PBD coefficients that were highly insignificant in all cases.

Furthermore, as a robustness test, we estimate multinomial logit regressions of the log odds of being married or cohabiting relative to being single.

To make this correlation apparent, simple multinomial Logit regressions are run using self-reported decision information (that is "distribution of income" and "final say on financial decision") as dependent variables and age and education as regressors (Table 7).

In order to measure the impact of age at arrival on educational attainment of children immigrants, we run multinomial logit regressions for the three education outcomes: 0-11 (HSD), 12 (HSG) and 13+ (ACD) years of schooling with age at arrival categorical dummies as well as with continuous age at arrival high-order polynomial.

Attribute 2 was the only explanatory variable to show significant population heterogeneity in our mixed multinomial logit regressions.