Suppose you have a linear model where the model is significant but some coefficients are not. How does one interpret the model when some coefficients are not significant?
Asked
Active
Viewed 2,528 times
3
-
You might have to explain a bit more about your model. Also, do you mean that some coefficients are significant whilst others not? – Sootica Apr 08 '13 at 09:45
-
3This is normal situation. Similar question (you may ignore that the talk there is about stepwise selection) – ttnphns Apr 08 '13 at 12:58
-
Its a basic linear model with some coefficients significant at alpha = 0.05 and other coefficients not. – phil12 Apr 08 '13 at 15:32
-
You may find the following related thread helpful as well: how can a regression be significant yet all predictors be non-significant?. – gung - Reinstate Monica Apr 09 '13 at 21:30
2 Answers
4
If collinearity is not a major problem, you interpret "non-significant" coefficients exactly the same as you interpret "significant" ones, with confidence intervals.
Frank Harrell
- 91,879
- 6
- 178
- 397
1
This may be a sign of high collinearity among your predictors/covariates---if the overall or omnibus test is statistically significant but none of the individual covariates are significant. Check the condition indexes and their associated variance decomposition proportions.
Scott Millis
- 61