Dear all,
I have an age moderator in SmartPLS but I struggle to interpret the results and simple slope analysis to confirm my hypotheses correctly.
I will be so thankful if you could interpret at least one of my results so I can continue from there and use it as a template for other moderate variables (gender and education level) in my research. I have attached the result below.
H5a: Age will moderate the relationship between (PEU) and behavioral intention (BI) to use e-government services.
H5b: Age will moderate the relationship between (SN) and behavioral intention (BI) to use e-government services.
H5c: Age will moderate the relationship between (TOI) and behavioral intention (BI) to use e-government services.
H5d: Age will moderate the relationship between (TOG) and behavioral intention (BI) to use e-government services.
Thanks
Best Regards
Interpret Moderation Analysis
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- PLS Junior User
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- Real name and title: ahmed totonchi
Interpret Moderation Analysis
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- RESULT.png (102.68 KiB) Viewed 2908 times
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- MODEL.png (167.17 KiB) Viewed 2908 times
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- AGE_TOI.png (149.91 KiB) Viewed 2908 times
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- SmartPLS Developer
- Posts: 1287
- Joined: Tue Mar 28, 2006 11:09 am
- Real name and title: Dr. Jan-Michael Becker
Re: Interpret Moderation Analysis
The p-values for the interaction terms (Age x ... --> BI) are all above 0.05. Most researchers would conclude from that there is no significant interaction (i.e., no moderation); i.e. rejecting your hypothesis.
The more substantive interpretation of the simple slopes graph would be that the TOI effect (which is not significant for age at the mean; i.e., -0.021; p=0.787) becomes positive for people high in age (green line; age + 1SD) and (more) negative for people low in age (red line; age -1SD).
However, the changes in the slope are relatively week (Age x TOI is 0.041; and not significant based on the p=0.608). Thus, you do not have enough evidence to conclude moderation.
Some interaction coefficients are quite substantive, but with four interactions you may not have enough power (sample size) to detect these effects reliably.
The more substantive interpretation of the simple slopes graph would be that the TOI effect (which is not significant for age at the mean; i.e., -0.021; p=0.787) becomes positive for people high in age (green line; age + 1SD) and (more) negative for people low in age (red line; age -1SD).
However, the changes in the slope are relatively week (Age x TOI is 0.041; and not significant based on the p=0.608). Thus, you do not have enough evidence to conclude moderation.
Some interaction coefficients are quite substantive, but with four interactions you may not have enough power (sample size) to detect these effects reliably.
Dr. Jan-Michael Becker, BI Norwegian Business School, SmartPLS Developer
Researchgate: https://www.researchgate.net/profile/Jan_Michael_Becker
GoogleScholar: http://scholar.google.de/citations?user ... AAAJ&hl=de
Researchgate: https://www.researchgate.net/profile/Jan_Michael_Becker
GoogleScholar: http://scholar.google.de/citations?user ... AAAJ&hl=de