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The regression results of the binary logit model presented in the second column of Table 6 confirm these observations.
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Probabilistic models of the binary logit model for both middle/small and large-scale levees are presented for the evaluation of the stability of river levees.
Table 5 presents the result of the binary logit model regression on factors influencing the operational habits exhibited by cocoa farmers during pesticides application.
Thus, we took the results of the binary logit model.
Table 2 provides model estimation results for the cross-sectional binary logit model and the mixed logit model.
The VOSL model is established based on the binary Logit model.
For multilevel data, the resulting model is called the multilevel sequential binary logit model (MBL).
Thus, the binary logit model [33] is an appropriate modeling method for behavior analysis.
This equation corresponds to a binary logit model across time periods of new employment.
All the variables remaining in the final cross-sectional binary logit model take statistically significant coefficients.
For estimation, we used a binary logit model because of the binary nature of the explained variable.
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