My MSc thesis: A meta-analysis of relative clause processing in Mandarin Chinese using bias modelling

Here is my MSc thesis, which was submitted to the University of Sheffield in September 2015. 

The pdf is here.

Title: A Meta-analysis of Relative Clause Processing in Mandarin Chinese using Bias Modelling

Abstract
The reading difficulty associated with Chinese relative clauses presents an important empirical problem for psycholinguistic research on sentence comprehension processes. Some studies show that object relatives are easier to process than subject relatives, while others show the opposite pattern. If Chinese has an object relative advantage, this has important implications for theories of reading comprehension.  In order to clarify the facts about Chinese, we carried out a Bayesian random-effects meta-analysis using 15 published studies; this analysis showed that the posterior probability of a subject relative advantage is approximately $0.77$ (mean $16$, 95% credible intervals $-29$ and $61$ ms). Because the studies had significant biases, it is possible that they may have confounded the results. Bias modelling is a potentially important tool in such situations because it uses expert opinion to incorporate the biases in the model. As a proof of concept, we first identified biases in five of the fifteen studies, and elicited priors on these using the SHELF framework. Then we fitted a random-effects meta-analysis, including priors on biases. This analysis showed a stronger posterior probability ($0.96$) of a subject relative advantage compared to the standard random-effects meta-analysis (mean $33$, credible intervals $-4$ and $71$).

Best statistics-related comment ever from a reviewer

This is the most interesting comment I have ever received from CUNY conference reviewing. It nicely illustrates the state of our understanding of statistical theory in psycholinguistics:

"I had no idea how many subjects each study used. Were just one or two people
used? ... Generally, I wasn't given enough data to determine my confidence in the provided t-values (which depends on the degrees of freedom involved)."
 

Five thirty-eight provides a brand new definition of the p-value

The Five-Thirty Eight blog provides a brand new definition of the p-value: 
http://fivethirtyeight.com/datalab/psychology-is-starting-to-deal-with-its-replication-problem/?ex_cid=538twitter

"A p-value is simply the probability of getting a result at least as extreme as the one you saw if your hypothesis is false."

I thought this blog was run by Nate Silver, a statistician?