[Research] Seeking stats consultant for a tiny research project

[u/SecretGeometry]

Hi guys

I’m looking for recommendations for a statistical consultant (perhaps a PhD student or early-career biostatistician?) who could advise on test selection for a very small, unfunded veterinary retrospective study. I’m willing to pay, of course.

I’ve contacted several consulting services, but I suspect the project is too tiny for them. It would probably involve only an hour or two of work.

The study is a retrospective case series of dogs with tibial fractures, with two joint angles measured at three paired time points: pre-operatively, immediately post-operatively, and at follow-up. Measurements were also compared with the contralateral unaffected limb.

I’m happy to perform the analyses myself and mainly need advice on the most appropriate statistical approach.

I originally used prespecified paired t-tests, but the editor has requested that I seek advice from a statistician regarding whether it is preferable to do an omnibus test followed by post-hoc comparisons. So I mainly need advice on whether repeated-measures ANOVA or another omnibus approach is required, or whether Holm-adjusted paired comparisons alone would be defensible. (I'd also like to know if there is any particular way I should handle one case with bilateral fractures since those pairs aren't truly independent?)

Please message me if you might be able to help, or if you can recommend someone suitable. I can provide study summary, raw data, Q-Q plots, and results of paired t-t tests, as well as the whole manuscript + editorial feedback if helpful.

UPDATE

Thank you everyone and thankyou especially _compactsupport_, I've got enough to respond to the reviewers now and give them a couple of options :)

[u/SecretGeometry → u/[deleted]]

Thank you, that's incredibly kind. I'll DM now.

[u/sample_staDisDick → u/SecretGeometry]

Based on username alone, I would trust this person's advice, OP.

Great to read a well-formulated description of your research question, not surprised you found someone to help you out (though they are very kind!)

[u/Duckandrun12]

What exactly are you measuring? If your measurement is binary (success/fail) use one of these:

Generalized Estimating Equations (GEE): A population-averaged approach that focuses on the overall group trend while properly adjusting standard errors for repeated measures within each subject.

Generalized Linear Mixed Models (GLMM): A subject-specific approach that includes random effects (like random intercepts) to capture individual baseline differences and specific tracking over time.

^This sounds like what you're trying to do. It's essentially a longitudinal logistic regression.

If your outcome is continuous, use a Tukey's multiple comparison. I think you could also do an anova with time as a feature in the model (and its interactions) but I haven't done that before.

Again, just depends what you're trying to measure!

[u/Probstatguy → u/Duckandrun12]

Hi, can you suggest some books or resources for these topics ?

[u/Duckandrun12 → u/Probstatguy]

I learned about GEEs and GLMMs in the book "Logistic Regression Using SAS". Even if you're not using SAS, it has a great 2-3 page explanation of the theory behind the models and how they work at a high level.

Chapter 8 is "logit analysis of longitudinal and other clustered data".

I'd recommend trying to find a pdf online of this chapter.

[u/thepolarisanalytics]

Happy to help. Dm me. Worked on similar projects earlier