What is the difference between validity testing and actual results? Researches usually present the results of validity tests conducted before the actual results - these include descriptive statistics with Mean and SD and also inter-construct correlations.
Then there is the actual testing of the logic model e.g. based on Partial Least Square (PLS) method where standardised beta coefficients are presented.
What is the difference between the two? Can they be used interchangeably i.e. in a meta-analysis, can I use the results from the inter-construct correlations (r) as effect size?

One person's manipulation check is another person's model check.
You want to know if giving people candy makes them happy, so you give them candy and see if they smile more.
I want to know if people try harder at tasks when they're happy, so I give them candy and then see if they persevere more than non-candy controls.
BUT I want to know if giving them candy actually made them happy - a manipulation or validity check, so I count how much they smile.
(Example sort of based on: https://psycnet.apa.org/doiLanding?doi=10.1037%2Fbul0000224 ).
