I am a newby to that forum, so I hope my question is not redundant. I am currently sitting on my master thesis where I investigate which effect diversity in teams has on publications.

Herefore, I have a dependent variable 'publications' which is a count variable. I have two control variables 'Team_Size' and 'Start_Year'. For my independent variable I have generated four diversity indices (I don't want to get too much in detail) as well as the average experience per team member (therefore five independent variables.)

As I assume a curvilinear relationship between diversity in teams and the publication rate, I would like to test whether an inversed U-shaped relationship is given between the dependent and independent variable. Hence, I have generated the squares of my independent variable in STATA.

I have used the nbreg (negative binomial regression) command as my dependent variable 'Pub' is a count variable with many zeros (--> overdispersion).

In my first model, I have only included my controll variables, then I have stepwise included my independent variables and squares.

Now, I am not sure how to interpret my results. Could somebody help me? Below attached you can see a photo of my output (It is still not beautiful but just exported to excel)

As far as I see it, I would say the following:

1) There is a significant relationship between Team_Size and Publications, such that bigger teams produce less.

2) Also, the control variable 'Start_Year" has a significant association with the publication rate, as the publication rate seems to decrease with time.

3) Diversity Index number 2 has a significant association with the publication rate. It is not a curvilinear relationship as the square of Diversity Index number 2 is not significant but is instead a linear negative relationship.

4) Diversity Index number 4 and number 5 are insignificant.

5) Average_Experience is significant. There is a U-shaped relationship between the independent and the dependent variable.

Is that all correct?

How come, that my control variable 'Team_Size' is in some models significant and in others it is not? Can I still say, that Team_Size is significant?

Diversity_Index_2 is only significant in model 2. Can I say that it is still overall significant?

Thank you very much for your help!!

Best wishes

Sophie