# Linear Regression: Ordinal or dummy independent variables?

I am a beginner who needs some help reading some results from linear regressions.

I am looking for factors that influence the location of civil conflict events. My dependent variable is the distance from the capital (km), a continuous variable.

I have 4 control variables which are all continuous too.

The variable (fightcap) I want to test is the fight capability of the rebels. This ordinal variable has three levels:
1 = low
2 = moderate
3 = high

However, I read in a couple of textbooks that to deal with ordinal predictors it is better to convert them to dummy variables. I thus created two dummies:
fightCap(low): 1 if fightcap = 1, 0 otherwise
fightCap(moderate): 1 if fightCap = 2, 0 otherwise

Using JMP (the software I know best), I ran the two models in parallel: one (left) with the fightcap ordinal variable, the second (right) with both fightCap(Low) and fightcap(moderate) dummy variables.

I notice that the output is identical for both models, excepts regarding the estimates of the ordinal/dummy variables.

My questions are thus the following:

1. How do I interpret the terms "fightcap[2-1]", "fightcap[3-2]" and their estimates? Do I read that a change of "fightcap" from 1 to 2 results in a 59.42 change in the dependent variable?

2. How do I interpret the fact that "fightcap[2-1]" has a significant estimate, but not "fightcap[3-2]"? Does it mean that only the variation from 1 to 2 explains the variation, but not the variation from 2 to 3?

3. How can I understand that "half" of my variable works if using the ordinal setup, but none of the dummies has a significant estimate?

Damien

• worth noting (1) that on the right pane you have (low)(moderate) dummy variable and not (low)(high) dummy variables. (2) My understanding is that JMP uses fairly odd coding strategy for dummy variables. Looks like it has done "reverse helmert" coding? Feb 12, 2014 at 15:02
• My bad, I mixed the variable names. Now it's fixed. Feb 12, 2014 at 15:05
• Possibly helpful notes from the JMP docs: Coding Nominal Effects and Ordinal Factors
– xan
Feb 12, 2014 at 16:23