Loading wiki pages...

Wiki Version:
<p>These files accompany a short manuscript that can be found here: <a href="http://papers.ssrn.com/sol3/papers.cfm?abstract_id=2381936" rel="nofollow">http://papers.ssrn.com/sol3/papers.cfm?abstract_id=2381936</a></p> <p>The two p-curve analyses presented here showcase the benefits of p-curve analyses to improve our understanding of what is likely to be true. Stroebe and Strack (2014) recently discussed the importance of conceptual replications and questioned the usefulness of direct replications when examining the effects of elderly primes and professor primes on human behavior. I believe that both direct and conceptual replications have their place in the empirical cycle, but that it is especially important to evaluate the outcome of replication studies in their meta-analytic context. Sometimes, a failed direct replication is expected because the available empirical research indicates the original effect is likely to be a Type 1 error. Other times, a failed replication should instigate a discussion about potential moderators, because based on the available empirical research, the effect is most likely true. Which interpretation is more rational can only be determined by weighing the informational value of the research line. P-curve analyses are one way to achieve this.</p>
OSF does not support the use of Internet Explorer. For optimal performance, please switch to another browser.
This website relies on cookies to help provide a better user experience. By clicking Accept or continuing to use the site, you agree. For more information, see our Privacy Policy and information on cookie use.

Start managing your projects on the OSF today.

Free and easy to use, the Open Science Framework supports the entire research lifecycle: planning, execution, reporting, archiving, and discovery.