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”

A 32-year old White Alabamian man* and the luxury of quantitative criminology

I have been conducting online experiments with MTurk and other similar online platforms for almost four years now. I usually leave a little feedback box at the end of each experiment, where participants can share their thoughts, make some comments, and potential complaints about the study. I have found this a very useful tool, especially during the piloting of the experiments, where many attentive respondents have pointed out several typos and other mistakes over the years. Continue reading “A 32-year old White Alabamian man* and the luxury of quantitative criminology”

OSF account

This is another post with a news item: I have recently registered to the Open Science Foundation’s website where I have already uploaded two papers of mine (more to come in due time). My supervisor, Jon Jackson has encouraged me to do this, which I am really grateful for. It is great to have your articles accessible somewhere whilst you are waiting for the painstakingly slow review process to hopefully bear some fruit…

You can find my public profile here.

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”