ESRC Postdoctoral Fellowship

I was fortunate enough to be awarded a one-year ESRC Postdoctoral Fellowship with the ‘industrial strategy steer’ award at the London School of Economics for my project titled ‘Using advanced data analytics to assess the spatial causal effects of policing policies and practices’ (I will start in this position on the 1st of October). My principal aim with this fellowship is to test and advance theoretical understanding of some core causal claims of the policing literature. Specifically, I will scrutinise neighbourhood-level and location-based police effects.

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Presentation at Waseda University

I was honoured to be invited by Kohei Watanabe and Atsushi Tago to give a talk this Wednesday at Waseda University in Tokyo. Upon their request, I was discussing my paper, which is currently under the second round of peer review at the Journal of Quantitative Criminology, from a methodological perspective. Readers of this blog should be familiar with these techniques (for details see the following thread of posts), for which I have already made available the code and the data to encourage future replications. You can find my presentation below, after the page break.

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Testing Complex Social Theories – Replication materials

As reported on Twitter, my paper on causal mediation analysis with multiple mediators has been published online:

I have already discussed the theoretical background of multiple mediators in other posts (find them here, here, here, and here). Hence, and as promised, I will instead focus on the code that you need to replicate the results of the paper.

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Causal mediation analysis with multiple mediators 4. – Some closing thoughts

After finishing my latest series of posts on causal mediation analysis with multiple mediators (you can find them here, here, and here), I had a sinking feeling that I forgot to mention a couple of important points, which means this series is not quite finished yet after all… There are two more issues I want to address: the differences between the post-treatment confounder and sequentially ordered approaches, and a potential Bayesian alternative. Continue reading “Causal mediation analysis with multiple mediators 4. – Some closing thoughts”

Causal mediation analysis with multiple mediators 3. – Sequentially ordered mediators

In this third, and final post on causal mediation analysis with multiple mediators (see the first two here and here), I discuss the case of sequentially ordered mediators.  Continue reading “Causal mediation analysis with multiple mediators 3. – Sequentially ordered mediators”

Causal mediation analysis with multiple mediators 2. – Post-treatment confounding

This is the second installment in a series of posts on causal mediation analysis with multiple mediators (see the first one here), which discusses how to handle the case of post-treatment confounding. Continue reading “Causal mediation analysis with multiple mediators 2. – Post-treatment confounding”

Causal mediation analysis with multiple mediators 1. – Causal independence and joint mediation

To kick off the year with an “easy” and “light” topic, I decided to start a series of discussions on causal mediation analysis with multiple mediators. Because the remaining papers in my PhD rely on such techniques, I thought it might make sense to write a brief summary of the different approaches one can take. I am aware that in a rapidly advancing field such as causal inference this post risks becoming obsolete very quickly, at the same time, I hope that this overview can still remain relevant for some upcoming papers (and posts).  Continue reading “Causal mediation analysis with multiple mediators 1. – Causal independence and joint mediation”

ScotCET and sensitivity analysis for causal mediation analysis with a single mediator

This post should be considered as an addendum to this previous one that discussed causal mediation analysis with a single mediator. That post ended with the argument that causal evidence could be found that procedural justice indeed mediated the effect of the treatment (previous experiences with the police) towards the outcome (normative alignment with the police). This post will discuss two sensitivity analysis techniques which assess this finding’s robustness to unmeasured confounding. Continue reading “ScotCET and sensitivity analysis for causal mediation analysis with a single mediator”

ScotCET and causal mediation analysis with a single mediator 3. – A demonstration in R

This post finishes the discussion of two other ones (this and this) by providing an example how to carry out causal mediation analysis with a single mediator in R. The “mediation” package is utilised, for a full description of the package’s capabilities, you can refer to Tingley et al. (2014). For STATA users out there, there is a “paramed” package in STATA which should also produce the same results (within rounding error). A note of caution though: the “paramed” package can only be used with linear mediators and outcomes, and with binary logit models with rare outcomes (see: VanderWeele 2016). The dataset for the analysis can be downloaded from the bottom of the page. Continue reading “ScotCET and causal mediation analysis with a single mediator 3. – A demonstration in R”

ScotCET and causal mediation analysis with a single mediator 2. – Issues with the product method and the sequential ignorability assumption

As discussed in this earlier post, to make meaningful inference from the ScotCET dataset, the focus needs to be shifted to the mediated effect. In such cases, following Baron and Kenny’s (1986) influential article, social scientists usually rely on structural equation modelling and the product method to derive the direct and indirect effects. Nevertheless, this approach has serious limitations that are usually overlooked in the applied literature. Continue reading “ScotCET and causal mediation analysis with a single mediator 2. – Issues with the product method and the sequential ignorability assumption”