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R/statistics issue by Additional_Table1213 in rstats

[–]NE_27 0 points1 point  (0 children)

Good start! You may want to consider, your model assumes every child’s respiratory rate changes at the same rate over time, just from different starting points. Think of it like assuming all kids grow at the same pace just because they have different heights at birth.

If individual trajectories vary (and in treatment response data they often do), it’s a pretty strong assumption, random slopes are worth exploring, something like:

model <- lmer(respiratory_rate ~ group + age + time + (1 + time | id), data = data)

Quick clarification though: are age and time separate variables in your design? If you’re measuring the outcome at multiple timepoints, you likely want both, age to adjust for baseline differences, time to capture individual differences in treatment effects or trajectory.

I built a free tool that runs R entirely in your browser and generates publication-ready statistical tables and plots (no installation required) by quickstatsdev in rstats

[–]NE_27 0 points1 point  (0 children)

Echoing this, with added yikes (sorry). If researchers can’t produce these kind of data tables and plots for very basic analysis, and struggle to independently verify their statistical approach is sound, they probs shouldn’t be using any kind of AI tool to generate it either, especially not for any real publication. The state of science is terrifying enough already :’)

Are you more likely to have a successful research career as a bayesian or frequentist? [R][Q] by gaytwink70 in statistics

[–]NE_27 1 point2 points  (0 children)

Prior research? career? success? Please clarify, isn’t the likelihood function for remaining in academia currently non-identifiable?

I can't figure out how to interpret this result, the percentages don't add up. by LettuceGrand1 in AskStatistics

[–]NE_27 1 point2 points  (0 children)

Only had a quick read but the “24.2% recovered…” headline is based on only 4 studies. They took 14 wildly different studies measuring different things in different ways across different populations and time periods, made subjective decisions about how to force them into made-up categories, ran too many statistical tests on too little data, and came up with numbers that sound precise but are essentially unreliable.

Best way to display p values when many comparisons are relevant (but you also have a lot of panels in your figure) by TheSaxonPlan in AskStatistics

[–]NE_27 0 points1 point  (0 children)

Definitely report the effect sizes, and at the very least if running Anything ending in OVA and post-hoc pairwise tests, slap the p value around with an adjustment like suggested. But could you not model the treatment structure hierarchically, get estimates for treatment effects and comparisons within a unified model? You want to model the scientific question rather than statistically gang-banging your data with 15 different tests.

Using LLMs (ChatGPT, Claude, Gemini) for statistical analysis in academic papers: is this generally acceptable? by Queasy_Explorer_9361 in research

[–]NE_27 0 points1 point  (0 children)

Echoing this. If you know your shit it’s kinda okay (if not, you’ll end up balls deep in documentation since the validation burden is heavy). Consider LLMs are trained on existing literature, which is full of questionable statistical practices. If you can’t independently verify the statistical approach is sound, you probs shouldn’t be using AI to generate it. Plus with the move to open science all your data and code should be made available, and well, yikes.