- Thread starter noetsi
- Start date

How big of an effect do you want and expect, 0.2 seems high to me!

I thought values below .2 were really small. Shows my inexperience. All the variables I care about are categorical. So they have a linear relationship with the DV. Not sure if that alleviates the problem. I historically I ran logitistic regression, but the federal government decided on LPM.

If I understand hlsmith I do have to remove one, but it really does not matter much which one. I was trying to figure out a way I could create an artificial unit that was the average of the others to compare to, but given that there are actual cases associated with these I do not know how. Or if that would even be valid. I have never seen someone average that way to create an artificial level for comparison of a categorical variable.

I have no real theory to choose here (this is literally never been done that I can find in the literature). Should I avoid a unit that has only a very few cases? I chose one at random, but it turned out to have only 8 cases compared to hundreds for other units.

When you put an indicator variable in a regression model, there are two things you must always keep in mind about interpreting the coefficients associated with the indicator variable:

- The coefficient on an indicator variable is an estimate of the average
**DIFFERENCE**in the dependent variable for the group identified by the indicator variable (after taking into account other variables in the regression) and - the
**REFERENCE GROUP**, which is the set of observations for which the indicator variable is always zero.

lol