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Hi ZAINAB,
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Did you have good theory to support your hypotheses in the first place, or you created them yourself thinking they must be supported? if there are no theories, then they are probably not good arguments.
Otherwise, use the T-statistics (two tailed-test) and look for good literature to argue why they are not supported.
Not that, Hypothesis IS NOT to be supported at all cost. In other words, if they are not supported, it does not mean your work is not good. You must defend why they are not supported.
Goodluck!
Answer my questions one by one. Did you have good theories to support your hypotheses?
That is the problem. So now, find theories to say why they are not supported.
Otherwise, if you want them to be supported, you must start and look for theories that support them and state your hypotheses accordingly. After your test if some few are not supported, you can say your result is showing the opposite. Which is also accepted.
WarpPLS provides P values for each and every path, in addition to standard errors and effect sizes. The available methods for obtaining standard errors and P values are the following: Stable1, Stable2, and Stable3, Bootstrapping, Jackknifing, Blindfolding, and Parametric. I hope that the materials linked below can be of use in connection with this:
User Manual (link to specific page):
http://www.scriptwarp.com/warppls/UserManual_v_5_0.pdf#page=21
Kock, N. (2015). Hypothesis testing with confidence intervals and P values. Laredo, TX: ScriptWarp Systems.
Kock, N. (2014). Stable P value calculation methods in PLS-SEM. Laredo, TX: ScriptWarp Systems.
http://www.scriptwarp.com/warppls/pubs/Kock_2014_StableAlgorithPvalues_SWSReport.pdf
Kock, N. (2015). One-tailed or two-tailed P values in PLS-SEM? International Journal of e-Collaboration, 11(2), 1-7.
http://cits.tamiu.edu/kock/pubs/journals/2015JournalIJeC2/Kock_2015_IJeC_OneTwoTailedPLSSEM.pdf
The links above, as well as other links that may be relevant in this context, are available from:
Dear,[...] but how can i get the P value from the PLS algorithm?
[...]
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Write two papers for publication. One supported and the other not supported. You will be a professor soon.
Good luck.
Discriminant validity of variable constructs
|
|
1 |
2 |
3 |
4 |
5 |
6 |
7 |
8 |
|
1 |
(0.804) |
|
|
|
|
|
|
|
|
2 |
0.789 |
(0.891) |
|
|
|
|
|
|
|
3 |
0.854 |
0.847 |
(0.870) |
|
|
|
|
|
|
4 |
0.741 |
0.840 |
0.886 |
(0.907) |
|
|
|
|
|
5 |
0.696 |
0.840 |
0.857 |
0.764 |
(0.896) |
|
|
|
|
6 |
0.803 |
0.798 |
0.948 |
0.815 |
0.831 |
(0.983) |
|
|
|
7 |
0.731 |
0.746 |
0.916 |
0.861 |
0.827 |
0.907 |
(0.930) |
|
|
8 |
0.699 |
0.619 |
0.790 |
0.664 |
0.748 |
0.815 |
0.813 |
(0.853) |
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