icegov2012 proceedings

0 200 600
0 10 30 50
infd
0 200 600 0 10 30 50
pov
lbw
abhp
0 200 400 600 0 1000 2000 0 2 4 6
Figure 2. Scatter plots of five indicators of infant health
Table 2. Correlation matrix of five indicators of infant health
infd pov lbw abhp avedsf
infd 1.000 0.567 0.416 0.319 0.290
pov 0.567 1.000 0.399 0.317 0.559
lbw 0.416 0.399 1.000 0.304 -0.005
abhp 0.319 0.317 0.304 1.000 0.299
avedsf 0.290 0.559 -0.005 0.299 1.000
0 500 1000 1500 2000 2500
infd pov lbw
avedsf
Figure 3a. Parallel Boxplots of infant health data (Infant
deaths, poverty, low birth weight) in Java, 2007
0 200 400 600
0 1000 2000
0 2 4 6
230
0 10 20 30 40 50
abhp avedsf
Figure 3b. Parallel Boxplots of infant health data (births
without health personnel, average education shortfall) in Java,
2007
6.2 Ranking Process
Better results of the ORDIT method will be obtained if the
correlations between indicators are sufficiently strong. Based on
Table 2, correlations between infd, pov, and lbw are higher with
each other than the correlation between abhp and avedsf. For this
reason, ranking of districts will be carried out based on 5 (all)
indicators and 3 indicators (infd, pov, lbw). A comparison of the
results will give a broader view of the ranking. Theoretically, rank
results will be more representative, if the variables (indicators)
have stronger relationship or higher coefficient correlation where
infant health is an abstract concept and unable to be measured.
Table 3 shows the place rank of each infant health indicator for
the leading lines of the data sets by Function Facilities of R [8]
function called PlacRank in Schema 1. The first column of the
data frame to be ranked is assumed to contain case identifiers, and
this column remains unaltered.
Table 3. Head (first 6 lines) of the data frame in ranking
obtained by applying the PlacRank function to place ranks of
infant health indicators via the R commands [8]
No. district infd pov lbw abhp avedsf
1 1 85.5 77 82.0 30 28.5
2 2 53.0 71 71.0 44 22.5
3 3 75.5 72 86.5 41 54.0
4 4 62.0 67 55.0 92 65.0
5 5 72.0 66 56.5 98 57.5
6 6 12.0 40 38.0 59 61.0
Tables 4a and 4b show the head (first six lines) of the data frame
obtained by applying the ProdOrdr function to the place ranks of
infant health measurement. In the current content, the idea of
‘better’ from reference [4] is replaced by ‘more severe’. Table 4a
and 4b are the results of ProdOrdr for 5 indicators and 3 indicators
respectively. Figure 4 is a scatter plot of these two salient scaling
(rankings) based on 5 and 3 indicators. It shows that there is a
linear tendency between those two ranking results with correlation
0.82 (p-value < 2.2e-16). This means the rankings based on 5 and
5