Matthew J. Smith

Postdoctoral Research Fellow in Statistics | PhD | MRC-NIHR awardee in Causal Inference methods @LSHTM (@icon_lshtm)

[Matthew J. Smith @MJTSmith]

🚨New paper🚨 Tutorial on causal inference in Stata, R, and Python https://t.co/ru6n78CMnF

Code on GitHub! https://t.co/d6kr6B8SFz

with @Mohamma70696197 @WATZILEI @camaringe @PausalZ @nondogmatist @LeyClem @aurelien_belot @icon_lshtm

@epi_twit @statstwitbot @CausalInferBot

[Matthew J. Smith @MJTSmith]

📢 New paper in Statistics in Medicine!
We compare TMLE vs CV-TMLE across tough simulation settings:
✔️ Misspecification
✔️ Limited overlap
✔️ High-dimensional data
✔️ Super Learner + cross-fitting

Read it here: https://t.co/J1Fjx61eGM

@epi_twit @statstwitbot

[Matthew J. Smith @MJTSmith]

🚨 New #SystematicReview in @AnnalsOfEpi with @rachaelvp, @watzilei, @camaringe 🎉

How has Targeted Maximum Likelihood Estimation (#TMLE) been applied in public health and epidemiological studies?👉 https://t.co/VXmaka4J61

TL;DR #Thread 🧵

(@UKRI_News @The_MRC @NIHRresearch)

[Matthew J. Smith @MJTSmith]

We argue that dissemination of #TMLE relies on 5 key factors:

1. Software availability (https://t.co/Rfnk4B2LqX) 🧑‍💻
2. Accessibility of available material 📄🔓
3. Number of experts in #TMLE 🤓🤓🤓
4. Teaching 🏫🧑‍🎓
5. Collaborations 🧑‍🎓🤝🧑‍💼🤝🧑‍💻🤝🧑‍🔬🤝🧑‍⚕️ ...... 💡...... 🤯🤯🤯

[Matthew J. Smith @MJTSmith]

🚨 New #SystematicReview in @AnnalsOfEpi with @rachaelvp, @watzilei, @camaringe 🎉

How has Targeted Maximum Likelihood Estimation (#TMLE) been applied in public health and epidemiological studies?👉 https://t.co/VXmaka4J61

TL;DR #Thread 🧵

(@UKRI_News @The_MRC @NIHRresearch)

[Matthew J. Smith @MJTSmith]

#TMLE has been methodologically adapted to multiple data settings:

1. Small sample size
2. (Nested) Case-control studies
3. Collaborative TMLE
4. Longitudinal data
5. Sequential randomised trials
6. Mediation analysis
7. Meta-analysis
8. Cross-validated TMLE
9. One-step TMLE
etc

[Inequalities in Cancer Outcomes Network @icon_lshtm]

New #SystematicReview available in @AnnalsOfEpi - by @MJTSmith, @rachaelvp, @WATZILEI & @camaringe 👏

The team investigated the application of #TMLE in public health and epidemiological studies👇
https://t.co/qVwQZewtQR

[Matthew J. Smith @MJTSmith]

@rabois @MaartenvSmeden For a confounder with low prevalence (e.g., 1%), if you only sample the other 99% of the population, then you should get an unbiased estimate?

So as you increase n from 50% to 99%, you decrease the bias of the confounder that you never captured in the first place…?

Hmmmm….

[Matthew J. Smith @MJTSmith]

@kenkoonwong @epi_twit @statstwitbot @CausalInferBot @WATZILEI @camaringe Of course 🙂

[Matthew J. Smith @MJTSmith]

If you’ve considered using Targeted Maximum Likelihood Estimation in the past for an observational study and decided not to use it, what was the main reason for not using it?
@epi_twit @statstwitbot @CausalInferBot #epitwitter #statstwitter #causalinference #TMLE

[Matthew J. Smith @MJTSmith]

@kenkoonwong @epi_twit @statstwitbot @CausalInferBot Certainly! Below are two tutorials. The first offers a comparison of the common estimators (including TMLE). The second is a tutorial of TMLE for a binary treatment.

https://t.co/8R0lcRHjhD

and

https://t.co/iJVbJqhiSM

@WATZILEI @camaringe

[Jonathan Bartlett @TheStatsGeek]

G-formula for causal inference via multiple imputation https://t.co/wHe2UUMO2e

[Inequalities in Cancer Outcomes Network @icon_lshtm]

📢 New publication by @icon_lshtm researchers highlights importance of diagnostic route in survival of people with #lymphoma and comorbidities.
➡️https://t.co/DkPwjxBSIn

Further research is vital to ensure timely diagnoses to reduce the #inequalities in #cancer survival.

[EuroCIM @TheEuroCIM]

Save the dates! EuroCIM 2023 will take place in Oslo, April 19-21 (with short courses April 18). Keep an eye on https://t.co/FDUHFQEB19 for more information.

[Matthew J. Smith @MJTSmith]

@stats_q

[Matteo Quartagno @stats_q]

Coming soon...

[Matthew J. Smith @MJTSmith]

@TheStatsGeek @LSHTM Welcome back!

[Matthew J. Smith @MJTSmith]

@PausalZ Or Pauled logistic regression

[Matthew J. Smith @MJTSmith]

@tmorris_mrc @kerryhood Do you mean a Mars bar flavoured ice cream? Or an ice cream flavoured Mars bar?