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The framework is composed of three submodels considering (1) the social and economic structures based upon a social accounting matrix, (2) land use change and urban sprawl based upon a binary logit regression, and (3) stream ecosystem condition in the catchment area based upon the NAWQA National Water Quality Assessmentt) dataset.
Table 5 shows the results of the binary logit regression model.
Binary logit regression model was used to analyze factors affecting local people's knowledge on the adverse impacts of Eucalyptus woodlot.
These include a binary logit regression to identify zero outcomes associated with count data and NBR to model the count process.
Overall, the binary logit regression model explained about 70.6% of the variance of local people's knowledge on the adverse impacts of Eucalyptus woodlot (Table 5).
On the other hand, the binary logit regression model explained about 70.6% of the variance of local people's knowledge on the adverse impacts of Eucalyptus woodlot.
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Because era, age, tumor size, surgery, and radiotherapy all showed PHs assumption violations with P < 0.0001 by Therneau Grambsch tests, binary logit regressions were applied to calculate odds ratios (OR) at 6 and 12 months after diagnosis.
Table 5 presents the result of the binary logit model regression on factors influencing the operational habits exhibited by cocoa farmers during pesticides application.
Binary logit and linear regression models, using objective measures, perceived measures, and both sets of measures, were estimated to predict propensity of bicycling and frequency of bicycling separately.
Analyses will use binary and multinomial logit regression models, as well as generalized linear latent growth models.
Binary and multinomial logit regression models were constructed to estimate the effects of nurse staffing ratios on a child's likelihood of readmission at multiple time points with and without controlling for relevant patient and hospital characteristics.
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