Hi - I would be grateful for some advice....I have conduced a regression analysis using HP and OP as predictor variables of overall affect.
A non-significant model was noted F(2, 109) = 2.13, p = .124. The model explains 2.0% of variance in post-playing/singing overall affect (adjusted R2 = .020).
However, in looking at the regression co-efficients I have the results illustrated in the attached.
I'm confused as to how I can have a non-significant model when one of the predictor variables is significant?
Many thanks
Karan
Since your F statistic is not significant, it basically tells you that your model does not work. In other words, it indicates that your set of independent variables (IVs) does not significantly predict your dependent variable (DV). Therefore, you should delete or add some IVs and then examine the F statistic if your goal is finding the best model. As regards the coefficients, they allow you to compare the amount each IV contributes to predicting your DV when considering all IVs. Even though one IV is significant and the other is not, this tells you that when they interact, their combination yields an insignificant prediction of your DV. For more insights, you could go through the piece by Frost (2021) and the RG thread initiated by Sternberg (2015). Both are referenced below.
Frost, J. (2021, June 8). How to interpret P-values and coefficients in regression analysis. Statistics By Jim. https://statisticsbyjim.com/regression/interpret-coefficients-p-values-regression/
Sternberg, N. (2015, September 6). Can I interpret a regression when the regression model is non-significant, but it still results in a significant interaction effect? ResearchGate. https://www.researchgate.net/post/Can_I_interpret_a_regression_when_the_regression_model_is_non-significant_but_it_still_results_in_a_significant_interaction_effect
Good luck,
Dear Karan, As inferential statistics we use regression model. If we do not get F is significant then we can't say the predictors explain the dependent variables. Beta indicates regression co-efficient.
Thanks for
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