The variable 'religionimportance' is coded inversly: 1:Very important 2: Important 3: Not important 4: Not important at all
So the interaction terms are also generated using the inversly coded variable 'religionimportance'
Using it this way, I get these results:
Robust | ||||||
alc | Coef. | Std. Err. | z | P>z | [95% Conf. | Interval] |
shorttermcon | .1118843 | .201347 | 0.56 | 0.578 | -.2827486 | .5065173 |
longtermcon | .5218077 | .2038899 | 2.56 | 0.010 | .1221908 | .9214246 |
religionimportancexshort | .0156052 | .07104 | 0.22 | 0.826 | -.1236306 | .1548411 |
religionimportancexlong | -.122903 | .0712793 | -1.72 | 0.085 | -.2626078 | .0168018 |
religionimportance | .2761201 | .0229579 | 12.03 | 0.000 | .2311235 | .3211167 |
_cons | .1510165 | .0642998 | 2.35 | 0.019 | .0249911 | .2770419 |
longtermcon: long term consequences
religionimportancexshort: (shorttermcon * religionimportance)
religionimportancexlong: (longtermcon * religionimportance)
Furthermore, when I use 'religionimportance' the other way round, I generate a new variable 'religionimp', that is: 1:Not important at all 2: Not important 3: Important 4: Very important
with the interaction terms generated using the new 'religionimp' variable.
Then the results are changing for the shorttermcon & longtermcon, also the p-values. (I was expecting that only the sign of the coefficient would change)
Here are the results when I use the new variable 'religionimp' instead of inversly coded 'religionimportance' variable:
Robust | ||||||
alc | Coef. | Std. Err. | z | P>z | [95% Conf. | Interval] |
shorttermcon | .1899104 | .1762609 | 1.08 | 0.281 | -.1555546 | .5353754 |
longtermcon | -.0927071 | .1743547 | -0.53 | 0.595 | -.434436 | .2490218 |
religionimpxshort | -.0156052 | .07104 | -0.22 | 0.826 | -.1548411 | .1236306 |
religionimpxlong | .122903 | .0712793 | 1.72 | 0.085 | -.0168018 | .2626078 |
religionimp | -.2761201 | .0229579 | -12.03 | 0.000 | -.3211167 | -.2311235 |
_cons | 1.531617 | .0580889 | 26.37 | 0.000 | 1.417765 | 1.645469 |
As expected, the coefficients of the variables 'religionimp', 'religionimpxshort' and 'religionimpxlong' only change their signs. Also, the p-values and z statistics remain the same. However, the main variables 'shorttermcon' and 'longtermcon' have totally new coefficients and are now not significant at all.
Could you please show me the way to solve this problem? Or could you please explain why this problem arises? What should I do in this case? Which regression should I proceed with?
Thank you very much in advance!
Best regards,
Mehrzad Baktash
0 Response to Why using an interaction term inversly changes the results (p-value) for the interacted variable?
Post a Comment