Clinical and Medical Research Statistics, Handled End to End
Medical data punishes generic statistics. Survival times are censored, clustered patients break independence assumptions, diagnostic studies need sensitivity and specificity rather than a plain mean, and journal reviewers scrutinise every model choice. That is why clinical biostatistics is its own discipline, and why the person running your analysis should be a biostatistician who reads medical literature every day, not a generalist adapting a textbook example.
Research Gold delivers biostatistics consulting services led by Prof. David Okonkwo (PhD, Biostatistics) alongside PhD-level statisticians with direct experience in clinical trials, observational studies, meta-analyses, and health services research. Research Gold matches you with a PhD biostatistician who has published in your field, drawing on nine PhD methodologists across biostatistics and epidemiology, so the person analyzing your data understands the conventions of health sciences, nursing, psychology, education, social sciences, and beyond. We run regression (linear, logistic, Cox), mixed-effects and multilevel models, survival analysis, ANOVA and ANCOVA, and factor analysis in R, Stata, SPSS, or SAS depending on your design, with reproducible code delivered on every engagement. Our biostatistics services span the full research lifecycle, from clinical biostatistics for trials and observational studies to analysis for dissertations, grants, and health services research.
Why Hire an Online Biostatistics Consultant
Biostatistics is remote by nature. The work is data, code, and written interpretation, none of which requires anyone in the room, so there is no reason to limit yourself to a local statistician near you. When you hire a biostatistician online you can match with a PhD specialist in your exact methodology, whether that is survival analysis, mixed-effects modeling, or a network meta-analysis, rather than whoever happens to be down the hall.
Researchers come to us instead of a solo freelance biostatistician for the same reason teams use any vetted firm: continuity, a documented analysis plan, reproducible code, and a second statistician who reviews the work before it reaches you. You get the responsiveness of an individual consultant with the accountability of a biostatistical consulting team. Whether you need to hire a statistician for a single analysis or a biostatistician for hire to support an entire trial, you work with a named PhD specialist whose work is independently reviewed.
Statistical Services We Provide
Study Design Consulting
We help you choose the right study design and analytical approach before data collection begins, including randomized trial design, cohort and case-control planning, cross-sectional survey design, and quasi-experimental methods. We align the design and its eventual reporting with the standard that fits your study, CONSORT for randomized trials (Schulz et al., BMJ, 2010) or STROBE for observational studies (von Elm et al., 2007), depending on your design.
Sample Size Calculation and Power Analysis
We calculate the minimum sample size needed to detect a clinically meaningful effect with adequate statistical power, with detailed justification for grant proposals and ethics applications: effect size assumptions, alpha level, power (typically 80% or 90%), and expected dropout. Try our free power analysis calculator for initial estimates.
Data Analysis for Medical Research
Our data analysis for medical research covers the full spectrum of quantitative methods, each delivered with reproducible code so a reviewer or co-author can rerun every result:
- Regression analysis: linear, logistic, ordinal, multinomial, Poisson, negative binomial
- Survival analysis: Kaplan-Meier curves, Cox proportional hazards, competing risks models
- Mixed-effects models: linear and generalized linear mixed models for clustered or repeated-measures data
- Propensity score methods: matching, inverse probability weighting, stratification
- Bayesian methods: Bayesian regression, hierarchical models
- Diagnostic test accuracy: sensitivity, specificity, ROC curves, likelihood ratios
- Time series and longitudinal analysis: growth curve models, generalized estimating equations
Meta-Analysis Statistics
If you have already conducted a systematic review and need the quantitative synthesis, we provide standalone meta-analysis support including effect size calculation, heterogeneity assessment, forest plots, funnel plots, and GRADE tables. See our meta-analysis service page for full details.
Explore our free statistical tools: effect size calculator, sample size calculator, chi-square calculator, and ICC calculator.
Statistical Interpretation Service
Already have your results but unsure what they mean? Our statistical interpretation service translates your outputs into clear, publication-ready language. We explain effect sizes in clinical context, assess whether assumptions were met, and help you present results accurately in your methods and results sections, reported in line with the SAMPL guidelines for statistical reporting (Lang and Altman, 2015) and, where your journal requires it, the APA Publication Manual, 7th edition (American Psychological Association, 2020). We report point estimates and confidence intervals only where model assumptions hold.
