**Interaction
run in the Regression**

**BANGLADESH**

First, create the interaction term between water and latrine:

1. Open

bdeshc.sav2. Click on

Transform, Computein the data editor menu.3. Type in the name

wat_lat(this will be the name of your interaction between water and latrine use) in theTarget Variablebox.4. From the variable list on the right, select

wathcatand move it to theNumeric Expression boxusing the arrow button.5. Type the symbol * next to the term wathcat, then select

latcatfrom the variable list and move it into theNumeric Expression box. TheNumeric Expressionbox should now readwathcat*latcat.6. Click on

OK.7. You should check for the new variable at the end of your variable columns, where a variable called

wat_latshould now be.

Now, an exercise to show how to get the regression results with an interaction term (Bangladesh data):

1. Open

bdeshc.sav2. Click on

Statistics, Regression,Linearand enteracprvfm(prevalence of low arm circumference males/females) in theDependent variablebox.3. Enter the

wathcat(high or low prevalence of safe water use) variable into theIndependent variablebox using the arrow key, and then enter bothlatcat(high or low prevalence of safe latrine use) andwat_lat(interaction term for water and latrine)as well.4. Click on

OK.Results of the regression:

INTERPRETATION: Here, the B coefficient for each of the variables, water source, latrine usage, and the interaction of the two is listed. In this case, the largest change in nutrition status is seen for water source , which has 6.28 points increase for each unit increase in the prevalence of low arm circumference (p=0.000). For safe latrine use, the change is not significant (p=0.939) now that the interaction variable is introduced. The interaction term for water and latrine is significant and accounts for a large coefficient (or change) associated with low AC prevalence (B=6.121 and p=0.010), so a lot of the change with water is collinear with latrine improvement. The message is that it might be more useful to consider improving only water or latrine use when developing a program in order to see the most results for the input, and it might be more effective to select water improvement over latrines. See if the graph of a two-by-two output confirms these results.

Below the graph shows the interactive effect of water and latrine with low arm circumference as the outcome. This should look familiar from the previous section.

INTERPRETATION: Again, this graph reinforces that an interactive
effect was detected in the results of the two-by-two table. Improving either water
source *or* latrine shows a significantly large effect, but the additional
improvement of improving both is negligible. It is an interaction of the two that causes
this, and should be included as a term when testing further to determine what to include
in an intervention program. We now know the slopes of these lines are significantly
different because the interaction term was significant in the regression equation we just
performed (p= 0.010).