Alex Crenshaw

@crenshaw.bsky.social

Assistant Professor of Psychology. Couples, clinical trials, stats & methods. Views my own.

I feel ambivalent whether preregistration should be standard for any experiment. But when interpreting clinical trial results, knowing a bit about the history, I treat studies pub’d before the era of mandatory trial registration with extreme skepticism. Hard to defend the 1st thought given the 2nd

The editorial process for this paper was the best I've ever exp'd. Sharp feedback that hugely improved the argument & led to the 8 properties. Raising ~12 new refs to consider, leading to a rabbit hole of me reading ~30 more papers. & those papers inspired an idea for the next paper I want to write

Alex Crenshaw@crenshaw.bsky.social · 4w ago

New commentary out in JCCP! In which I try to solve the problem of incomparable effect size estimates in clinical trials by recommending a standard, one-size-fits-most way to compute the standardized mean difference (SMD; e.g., Cohen’s d) in psychology trials. doi.org/10.1037/ccp0...

Abstract: The standardized mean difference (SMD) is widely used in psychology clinical trials to convert intervention effect estimates from raw units to a common scale, enabling comparison across settings. However, multiple operationalizations of the SMD are possible for clinical trial data, with large potential impacts on estimate magnitudes. In this commentary, I review practices for operationalizing the SMD in the Journal of Consulting and Clinical Psychology and other journals that publish results of clinical trials. I find that only one third of studies report sufficient information to determine the operationalization. Among those, the operationalization varies widely, threatening the SMD’s utility in providing a common scale. Given the common goals and design elements across many trials, it is feasible to establish a default operationalization for the SMD’s standardizer. I outline eight desirable SMD properties and evaluate each option against these properties. The pooled baseline standard deviation meets seven of eight, far more than any alternative, with its main limitation being susceptibility to inflation from restrictive inclusion criteria. I conclude that raw effect estimates should be divided by the pooled baseline standard deviation as a default, one-size-fits-most choice. Adopting this standard will help the SMD meet its promise as a standardized metric, improving comparability of results across different measures, outcomes, studies, and populations. I also provide reporting recommendations to improve transparency and enable recomputation using alternative standardizers when needed.

At the end of the term I asked my college creative wriing students to submit anonymous thoughts on AI. No real surprises: Mood ranges from resignation to despair, capitulation from embittered erosion of standards to total, feelings of betrayal from deep to furious. 1/

AI seems to be the topic of the year — nearly every conversation I have in my role as academic lead for good research practice touches on it in some way. I’d like to lay out my developing thoughts for conversation and critique. (1/7)

When drawing links between health and the gut microbiome, the obvious explanation that should be ruled out first is always disease—>diet—>microbiome (or M—>diet and disease—>microbiome). Microbiome—>disease is the least likely explanation by a light year www.sciencealert.com/parkinsons-l...

Parkinson's Link to Gut Bacteria Hints at Unexpectedly Simple Treatment

Scientists have suspected for some time that the link between our gut and brain plays a role in the onset of Parkinson's disease.

sciencealert.com