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Welcome to the Wiki Resource for TrialTree

What Is TrialTree?

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TrialTree is an innovative online platform designed to simplify the process of designing, learning about, and managing clinical trials. It combines interactive tools, educational resources, and collaborative features to make trial design more accessible for everyone—from students and early-career researchers to experienced clinicians and investigators.It offers a user-friendly, visual approach to trial design, making it accessible to researchers, clinicians, and students, even those with limited experience in clinical trial methodology. TrialTree helps users build scientifically rigorous and ethically sound clinical trials through step-by-step guidance, real-world examples, and collaborative tools.

TrialTree is a resource for anyone interested in improving the quality, ethics, and accessibility of clinical trials. Whether you're learning, designing, or teaching—TrialTree supports you every step of the way.

Table of Contents

TrialTree Wiki Table of Contents
Trial Foundations Research question Hypothesis Equipoise Systematic review Types of trials SPIRIT
Trial Design Types Cluster randomized trials Cross-over trials Stepped wedge trials Factorial trials Pragmatic trials Pilot and feasibility trials Vanguard trials Multi-arm trials Multi-arm multi-stage trials Platform trials Non-inferiority trials N-of-1 trials Expertise-based trials Phases of trials Group sequential trials Implementation trials Hybrid trials Registry-based trials
Oversight & Participants Data Safety and Monitoring Board Trial participants Trial interventions Trial controls Trial outcomes TIDieR Patient and public involvement Equity-relevant trials Quality of life measures Patient-reported outcomes Ethics Informed consent
Randomization Randomization Implementing randomization Allocation concealment Implementing allocation concealment Minimization Stratification
Blinding & Bias Blinding Implementing blinding Preventing attrition Internal and external validity
Analysis & Interpretation Statistical Analysis Plan (SAP) Sample size Analysis Intention-to-treat analysis Per-protocol analysis Subgroup analysis Sensitivity analysis Multiple testing Clinical versus statistical significance Frequentist and Bayesian approaches
Cost & Scalability Cost effectiveness Scaling up Budgeting
Data & Documentation Database creation Data management plan (DMP) Missing data Digital tools
Reporting Guidelines CONSORT SPIRIT