For this example, we will use Approach A to conduct an interaction analysis based on logistic regression. We want to see if sex (z) moderates the association between out-patient care due to cardiovascular disease (x) and early retirement (y).
| Dataset |
| StataData1.dta |
| Variable name | earlyret |
| Variable label | Early retirement (Age 50, Year 2020) |
| Value labels | 0=No 1=Yes |
| Variable name | cvd |
| Variable label | Out-patient care due to CVD (Ages 41-50, Year 2011-2020) |
| Value labels | 0=No 1=Yes |
| Variable name | sex |
| Variable label | Sex |
| Value labels | 0=Man 1=Woman |
Define the analytical sample
We start by defining the analytical sample:
gen pop_interact2=1 if earlyret!=. & cvd!=. & sex!=. |
Let us have a quick look at the variables:
sum earlyret cvd sex if pop_interact2==1 |
Simple regression models
First, we will run the simple models, one for cvd and earlyret, and one for sex and earlyret.
logistic earlyret cvd if pop_interact2==1 |
logistic earlyret sex if pop_interact2==1 |
There are statistically significant associations in both simple models. More specifically, the OR for cvd is 5.59 (95% CI: 4.54-6.89) and the OR for sex is 1.51 (95% CI: 1.34-1.71).
Multiple regression model
Next, we run a model with both independent variables included:
logistic earlyret cvd sex if pop_interact2==1 |
Actually, both ORs increase a bit in this model.
Multiple regression model with interaction effect
In this step, we will include the interaction term using Approach 2 (two hashtags mean that we specify the main effects and the interaction effect at the same time):
logistic earlyret i.cvd##i.sex if pop_interact2==1 |
In the table above, we can see that the estimate for the interaction term has a p-value above 0.05 (0.704). This suggests that there is no statistically significant interaction effect between out-patient care due to CVD and sex on early retirement.
| Note The reference category for the interaction term is by default combination with the smallest value, in this case No#Man. The reason that some combinations are omitted is because they correlate perfectly with the main effect terms. |
| Summary Sex does not seem to moderate the association between out-patient care due to CVD and early retirement. |