RESEARCH DISCIPLINE
Statistical Consulting for
Medical, Health & Clinical Research
Statistical consulting for clinical research serves physicians, nurses, allied health and public health researchers in trials, cohorts, diagnostic studies and economic evaluations, with the analysis shaped by how outcomes are defined, how complete follow-up is and which reporting guideline applies.
Statistical consulting for clinical research is specialist statistical support for studies that measure outcomes in patients, participants or populations, from randomized trials and cohort studies to diagnostic accuracy studies and economic evaluations, with the design, analysis and reporting shaped by how each outcome is defined, how observations cluster or repeat and how complete follow-up is. Within Research Disciplines, these requirements also vary inside the family: a dental study clusters teeth within mouths, a trial answers to a prespecified estimand and an economic evaluation models costs that are skewed with many zeros. OnlineSPSS is a specialist statistical consultancy for academic, clinical and professional research, and the analysis is carried out in-house by PhD-level statisticians.
RESEARCH FIELDS
Areas We Support Within Medical, Health & Clinical Research
Ten fields share the study designs of clinical research but differ in the data they produce, from care records and ward-level samples to costs, medication exposure and teeth clustered within mouths.
01
Medicine
Clinician-led studies from routine care records, where encounters repeat per patient and missing values follow clinical decisions rather than a protocol.
Chart review
Hospital cohorts
02
Nursing
Practice-based research on care delivery, with Likert and patient-reported scales, small ward samples and pre-post designs.
Ward samples
Scale scores
03
Public Health
Population programs and policy outcomes, analyzed with complex survey weights, area-level data and program evaluation designs.
Survey weights
Area-level data
04
Epidemiology
Disease occurrence and risk in populations, where the choice of rate, risk or odds and the causal case for each adjustment drive the analysis.
Rates and risks
Confounding
05
Clinical Trials
Prespecified comparisons in randomized designs, built on the estimand, the intention-to-treat principle and the flow of participants.
Estimands
Intention-to-treat
06
Biostatistics
Methodology for health studies as a discipline: sample size, statistical analysis plans and prediction models, with the plan fixed before the data are seen.
Analysis plans
Study design
07
Health Sciences
Allied health and clinical practice research that combines mixed designs, validated instruments and outcome measures in a single project.
Allied health
Validated scales
08
Health Economics
Costs and utilities in the evaluation of care, where skewed costs with many zeros, QALYs and the uncertainty around an ICER need dedicated methods.
Skewed costs
QALYs and ICERs
09
Pharmacy & Pharmacology
Medication use and outcomes in practice, with adherence measures, exposure definitions and pharmacoepidemiologic designs.
Medication exposure
Adherence
10
Dentistry
Oral health studies in which teeth, sites and quadrants are clustered within mouths, including split-mouth designs.
Clustered teeth
Split-mouth
RESEARCH CONTEXT
Study Designs and Data Structures in Medical, Health & Clinical Research
The same design recurs across several health fields with a different data structure, and in health research statistics that structure, more than the name of the field, decides which analysis can be defended.
| Study design | Data structure | Where it recurs in this family |
|---|---|---|
| Randomized trials | Allocated groups, baseline plus scheduled follow-up visits, a prespecified primary endpoint | Clinical Trials and Biostatistics, with small pragmatic trials in Nursing and Pharmacy |
| Cohorts and registries | Patients followed over time, exposures that change, censored and competing outcomes | Epidemiology and Medicine, with population cohorts in Public Health |
| Case-control studies | Cases compared with sampled controls, exposure taken from records or recall | Epidemiology and drug safety work in Pharmacy, with oral disease in Dentistry |
| Cross-sectional surveys | One time point, weighted or multistage samples, respondents nested in areas | Public Health first, then Nursing and Health Sciences |
| Diagnostic accuracy studies | Index test and reference standard on the same patients, thresholds to choose | Medicine and Dentistry, with Biostatistics for prediction models |
| Repeated measures and patient-reported outcomes | Several visits per patient, scale scores, visits missing for reasons tied to health | Nursing and Health Sciences, and as endpoints in Clinical Trials |
| Economic evaluations | Patient-level costs and utilities from trials or claims, skewed with many zeros | Health Economics, with program evaluation in Public Health |
| Qualitative and mixed designs | Interviews or open responses coded alongside a quantitative strand | Nursing and Health Sciences, with implementation studies in Public Health |
METHODOLOGICAL CONSIDERATIONS
Statistical Issues That Matter in Medical, Health & Clinical Research
These issues recur across the family, and each one bites hardest in a different field, from non-independent observations in dentistry to confounding in epidemiology.
Endpoint and Case Definitions Each field defines its outcome differently: composite endpoints in trials, case definitions in epidemiology, scored scales in nursing and costs in health economics, all fixed before analysis.
Non-Independent Observations Repeated visits, paired organs, teeth within a mouth and patients within wards are correlated, not independent rows. The unit differs by field: the mouth in dentistry, the ward in nursing, the area in public health.
Confounding Versus Estimand Observational work needs a causal case for each adjustment variable, while a trial needs a prespecified estimand that states how events after randomization are handled.
Follow-Up and Attrition Dropout in a trial, loss to follow-up in a cohort and missing records in routine data arise differently, so each needs its own assumptions about why data are missing, and sensitivity analyses.
Multiplicity Several outcomes, subgroups and time points multiply the chances of a false positive. Trials prespecify a hierarchy or an adjustment, while cohort subgroup findings are reported as hypothesis-generating.
Clinical Versus Statistical Importance The difference that matters changes across the family: a minimal important change on a nursing scale, an absolute risk difference in a trial and a cost per QALY in health economics, each reported with its interval.
ANALYTICAL NEEDS
Common Statistical Questions in Medical, Health & Clinical Research
Each recurring research need maps to a family of methods, and the choice within it follows the design, the outcome type and the way follow-up was completed.
Time-to-Event Outcomes
Time until recurrence, death or discharge, with some participants still event-free at last contact, calls for survival methods that handle censoring and competing events.
Repeated Measurements
Several observations from the same participant call for longitudinal or mixed-effects models that represent the correlation, not a test treating every visit as a new case.
Adjusted Associations
An association between an exposure and an outcome, adjusted for covariates, calls for a regression model chosen for the outcome type, whether binary, count or continuous.
Patient-Reported Scales
Questionnaires and symptom scores need checks of dimensionality and reliability before total or subscale scores are analyzed as outcomes.
Incomplete Follow-Up
Missing outcomes and covariates can be handled by multiple imputation or related computational approaches, once the assumptions about the missingness are stated.
Pooled Evidence
Combining results across studies calls for a systematic search and a pooling model that reflects heterogeneity, and sometimes for a decision not to pool at all.
REPORTING & RESEARCH STANDARDS
Reporting Standards in Medical, Health & Clinical Research
Reporting expectations differ by study design more than by specialty, and they shape how estimates, tables and the flow of participants are prepared.
Randomized trials report to CONSORT 2025 and their protocols to SPIRIT 2025. Observational designs follow STROBE, and RECORD extends it to studies built on routinely collected health data. Diagnostic accuracy studies report to STARD 2015, prediction models to TRIPOD+AI, systematic reviews to PRISMA 2020, economic evaluations to CHEERS 2022 and interview-based qualitative strands to COREQ. Each journal then adds its own conventions: the AMA Manual of Style in many medical journals, APA 7 where a journal or institution requires it, and the ICMJE recommendations on authorship, trial registration and data sharing. Effect estimates are reported with confidence intervals and with absolute measures a clinician can interpret, and tables, flow diagrams and methods text are prepared to the guideline and the target journal.
ANALYTICAL SUPPORT
Statistical Support for Clinical and Health Studies
Statistical analysis for health research runs from the planning of a trial, cohort or diagnostic study to the reporting of its results, within the scope agreed before work begins.
Research Planning & Study Design
Design, sample size and analysis plans for clinical studies
Quantitative Data Analysis
Analysis of clinical trial, cohort and diagnostic data
Results Reporting & Interpretation
Reporting of effects and uncertainty for clinical audiences
Independent Statistical Review
Independent review of analyses before submission or reply
OnlineSPSS provides the agreed methodological, analytical, and statistical reporting support. The researcher or research team retains the scientific question, substantive interpretation, conclusions, and overall responsibility for the research.
SOFTWARE
Statistical Software Used in Medical, Health & Clinical Research
Clinical research data analysis is run in the software that fits the data and the study design, with syntax or scripts provided where applicable, including coding tools for qualitative strands.
RESEARCHER VOICE
What Researchers Say
Feedback from two researchers, on clinical study design, follow-up and reporting standards, and on clustered data that cannot be treated as independent rows.
“The main value was having statisticians who understood clinical study design, patient-level data, repeated measures, missing follow-up, and reporting standards. We did not have to explain why those details mattered, and the analysis was structured around the clinical question rather than around the software.”
“Our project had a very field-specific problem around the clustered structure of the data rather than treating every row as independent. The team understood why it mattered in Dentistry and chose the analysis accordingly. The final tables and interpretation felt written for our research context rather than copied from a generic statistics template.”
FREQUENTLY ASKED QUESTIONS
Questions About Statistical Consulting for Medical, Health & Clinical Research
Short answers to what researchers ask before sharing a clinical or health project, from reporting guidelines and clustered data to planning, confidentiality and the assessment process.
Which reporting guideline applies to my study?
The guideline follows the study design, not the specialty, so a nursing survey and a medical cohort can both report to STROBE, while a pharmacy trial reports to CONSORT 2025. Studies that combine designs or units report to each part: a trial with an economic evaluation adds CHEERS 2022, and a trial that randomizes wards or practices adds the CONSORT extension for cluster randomized trials. The target journal’s own requirements apply on top.
Can both eyes, several teeth or repeat visits count as separate observations?
They count as observations, but not as independent ones. Measurements from both eyes, several teeth or repeated visits of one patient are correlated, so treating each as an independent case usually understates standard errors and overstates precision. The analysis represents the correlation where it arises, with mixed models or generalized estimating equations for repeated visits and cluster-aware models for teeth within a mouth or patients within a ward.
Can you advise on the protocol or sample size before data collection?
Yes. Before data collection we can review the primary outcome, the comparison, the planned analysis and the sample size, and set them out in a statistical analysis plan that is fixed before the data are seen. The clinical aims and decisions stay with the research team, and the plan documents the statistical choices that follow from them.
How do you protect my research data and confidentiality?
Study datasets, protocols and analysis files are handled confidentially, and project information is not published. An NDA is available where required and can be arranged before sensitive materials are shared. Read more about confidentiality and data security.
What happens when I request an assessment, and how long does it take?
You share your research question, design and relevant materials, and a statistically trained Research Coordinator reviews the request and responds the same day. The analysis, deliverables, timeline and one fixed project fee are then confirmed before any work begins, so the timeline follows from the agreed scope.
Still have a question? Find more answers in our full FAQ.
NEXT STEP
Discuss Your
Clinical or Health Research With Us
Share your research question, study design, available data and analytical requirements. We review them against the reporting guideline your study answers to and confirm the approach before any work begins.
No Commitment Required
Strictly Confidential
Fixed Project Fee
In-House PhD-Level Statisticians
Same-Day Response
Serving Researchers Since 2014