Statistician for dental researchers: inter-rater agreement (kappa and ICC), logistic regression, survival analysis and reviewer responses. PhD theses and Q1/Q2.
Before discarding the study: we check whether the kappa model is correct (sometimes simple kappa is used when weighted kappa or ICC is needed), whether the scale can be collapsed into broader categories, and whether one extra calibration session changes things. I've seen 0.55 → 0.82 just by adjusting the model and one extra session.
If your clinical unit is the tooth (caries, restoration, acid attack), analysing each tooth as independent overestimates power and the reviewer will flag it. The right solution is mixed models with patient as random effect. I deliver both analyses so you see the difference and justify it.
Depends on variable type and assumptions. Continuous with normality and homoscedasticity: ANOVA + Tukey. Without normality: Kruskal-Wallis + Dunn. N=10 per group is tight but defensible if the report includes effect size and explicit assumptions.
Yes, it's one of the most requested services. I review the reviewer letter, run the additional analyses and help you draft the point-by-point response. Turnaround: 48-72h.