What you're asking is basically the concept of statistical power. Assume the original study found an effect size E, and we take that as the truth. How likely is the replication attempt to find a statistically significant effect?
The Reproducibility Project calculated the sample sizes necessary in advance, so if the effects are the size the original researchers claim, they'd have good power to detect them.
Their power could be worse than they expect, though; pioneering studies tend to overestimate effect sizes, because their sample sizes are too small and they filter for statistical significance. I call the problem truth inflation: http://www.statisticsdonewrong.com/regression.html#truth-inf...
Anyway: understanding the random nature of results is exactly the job of statistics, and the Reproducibility Project researchers are being very careful with their statistics.
Comments
What you're asking is basically the concept of statistical power. Assume the original study found an effect size E, and we take that as the truth. How likely is the replication attempt to find a statistically significant effect?
The Reproducibility Project calculated the sample sizes necessary in advance, so if the effects are the size the original researchers claim, they'd have good power to detect them.
Their power could be worse than they expect, though; pioneering studies tend to overestimate effect sizes, because their sample sizes are too small and they filter for statistical significance. I call the problem truth inflation: http://www.statisticsdonewrong.com/regression.html#truth-inf...
Anyway: understanding the random nature of results is exactly the job of statistics, and the Reproducibility Project researchers are being very careful with their statistics.