Correlation Matrix revisited

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This time, as we did previously for a larger matrix, we will use the routine in SPSS to run Pearson's correlation for water, sanitation, education and the outcome variable waz score. Try this exercise:

1.  Open keast4j.sav

2.  Click on Statistics, Correlate, Bivariate.

3.  Enter the list of variables (waz, dlowedn, notoilet, dpiped, dwell) one-by-one into the variables box using the arrow key.

4.  Click on the box to highlight Pearson's Correlation Coefficient and the box for Two-tailed.

5.  Click on OK.


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Among the independent variables in the model, it is evident that there is some collinearity.  For example, the Low Education variable has a significant correlation coefficient with toilet access (r = 0.169, p= .000) and piped water (r = -0.152, p= 0.000). Toilet access has a significant correlation with both piped water (r = -0.153, p=0.000) and well water (r = -0.158, p= 0.000). The collinearity which has been detected here will need to be addressed when a model is developed to show the association between water and sanitation with nutrition status.  Return to the main text for some ideas on how to confront this issue.

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