|
Model
|
H0
|
−2LL*
|
P£
|
|---|
|
Locality + Age + Education + Int**
| |
142.76
|
---
|
|
Locality + Age + Education
|
βInt = 0
|
146.83
|
0.250
|
|
Locality + Education
|
βAge = 0
|
151.11
|
0.015
|
- *-2 log likelihood, ** All possible 2 way interactions, £ p values based chi square of −2 log likelihood difference between the reduced model and initial model. The predictors: localities, age and education level of the farmers had P values < 0.25 and were the potential predictors in univariate analysis (Figure 2). These three potential predictors were then entered in the multivariate model by following the methodology of Hosmer and Lemeshow [17]. In succeeding steps, the predictors with a P > 0.05 in the previous step were removed from the model until complete loss of fit (P < 0.05) of the model was achieved.
