Page 42 - Contributed Paper Session (CPS) - Volume 2

CPS1414 Bashiru. I.I S. at el.
Table 3: Summaries of local parameters in the geographically weighted
linear model
Variable Minimum Lower Quintile Median Upper Quintile Maximum
Intercept -0.5130 -0.0547 0.0025 0.1225 0.2569
Schild*
-0.0025 -0.0013 -0.0005 0.0014 0.0020
Aged* 0.0004 0.0011 0.0024 0.0042 0.0056
log(Const)* -0.0427 -0.0354 -0.0188 -0.0108 0.0160
log(Agric)* 0.0153 -0.0354 0.0316 0.0438 0.0697
HSabove -0.0022 -0.0001 0.0007 0.0013 0.0016
Unemployed -0.0040 -0.0015 -0.0006 0.0004 0.0016
Poor -0.0011 -0.0004 -0.0001 0.0004 0.0010
log(Bschool) -0.0659 -0.0297 -0.0142 0.0174 0.0468
Mining 0.0000 0.0000 0.0000 0.0000 0.0000
R 0.43
2
Adj. R 0.30
2
AICc -329.58
*
* *
`  . 0 01 , p  . 0 001 , p  . 0 0001 , * * * p  . 0 0001 , ≤ 0.05
.
p

Figure 2: Map Showing fitted Values of GLM and GWLM by District

4. Conclusion and Recommendation
The findings of this study can help to target areas where child labour
practices are very high. The improvement of the GWLM model approach
is more robust and useful for identify and interpreting the outcomes of
high child labour proportion areas. This helps to clarify issues such as
the spatial aspects of both the response and explanatory variables at
the specific location with significant determination. The results of this

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