Chris Greenwood retweeted
And that's a wrap! Congratulations to our winners Jillian Hidrerh, @SavinStacey, Dr. Christopher Greenwood and @ArachidonicAlex
And a big thankyou to all our speakers for attending, the LOC and the @ANZDOHaD committee! 👏👏
#DOHaDANZ_2022 #DOHaD @DOHaDANZ_2022
Chris Greenwood retweeted
Replying to @LukasSchlogl
Chris Greenwood retweeted
The gfoRmula package is available on CRAN.
cran.r-project.org/web/packa…
All #Rstats users can now implement the parametric #gformula for #causalinference with time-varying treatments and confounders.
For a detailed software guide, see arxiv.org/abs/1908.07072
Have fun, everybody!
Our new(ish) @DrugAlcoholDep paper is up! We compare common longitudinal modelling approaches to tracking the trajectory of substance use across adolescence and young adulthood:
doi.org/10.1016/j.drugalcdep…
Chris Greenwood retweeted
We are currently conducting a study investigating exploratory behaviours, risk taking behaviours and development in emerging adulthood (18-30 years). Please find the link to our survey on our Facebook page: facebook.com/Exploration-and…
😀
I'm looking for a key resource on latent growth modelling specifically.
Hopefully something covering latent curve models, growth mixture models, and latent class growth analysis - discussing assumptions, etc.
Any leads? HELP
@gjyacademic
Chris Greenwood retweeted
Our review of #MachineLearning in #mentalhealth is finally out - woohoo! Synthesising 300 papers was no easy task; hopefully it's useful for those looking for some ideas in this space.
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Chris Greenwood retweeted
Interested in working with a 25-year longitudinal study for our 11th wave of participant follow-up? @2000stories are looking for a data collection coordinator (bit.ly/2RGfD2r), and participant tracing/engagement specialist (bit.ly/2RFJdVS). Please share!
DAGs applied to substance use research
academicworks.cuny.edu/cgi/v…
Here is the pre-print of my first paper!
psyarxiv.com/ktvzw/
Can someone point me towards some machine learning methods/packages for variable/feature selection that can handle missing data (e.g. using multiple imputation)?
Found this so far:
ncbi.nlm.nih.gov/pubmed/2352…
#rstats
Too true! teapaw.org/liz_spry/status/993812…
Chris Greenwood retweeted
The five-item Brief Problem Gambling Screen (BPGS) will be useful for mental health services wanting to screen for any level of gambling problem onlinelibrary.wiley.com/doi/…
Some interesting (and simple to implement) things to consider in relation to producing clear and replicable science.
frontiersin.org/articles/10.…
Great read to get you thinking about causal inference in observational studies teapaw.org/_MiguelHernan/status/9…
The C-word: "We need to stop treating #causal as a dirty word that respectable investigators do not say in public or put in print."
Not saying "causal" harms science. Saying "observational studies cannot prove causation" misses the point.
I explain here ncbi.nlm.nih.gov/pubmed/2956…



















