Article Level Metrics Do Not Predict Many Labs Replication Outcomes

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**Abstract:** Across the effects in Many Labs 1 and 3, I find that p-curve, replication index, test of insufficient variance and average sample size do not predict replication outcomes. These results suggest caution in using paper-level metrics to infer the evidential value of individual effects. **Note:** [Please read this important blog post for additional detail on methods, data, and analyses that qualifies the conclusions of the poster.](http://www.ibm.com/ibm/responsibility/initiatives/IBMSocialGoodFellowship.html) **Poster Session E:** Friday at 12:00p-1:30p, Poster 258. [Data, analysis code, and a pre-registration are available from GitHub.](https://github.com/ecsalomon/TSR---Test-Stats-Replication)

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