Webinars

Sample Size for Measures of Association
Correlation, Agreement and Diagnostic Measures 

Dealing with Uncertainty in Sample Size Determination
Pilot Studies, Model Selection and Practical Equivalence

Sample Size for Categorical Endpoints
Binary, Ordered & Contingency Table Data 

Sample Size for Regression Models
Calculations for Common Regression, Mixed-Effects and Prediction Models

Clinical Trial Design Trends for 2023

Clinical Trial Design
This Year's Most Popular Topics

Guide to Sample Size Re-estimation
Approaches for blinded and unblinded
sample size re-estimation

Improving Sample Size Using Bayesian Thinking
Hybrid Bayesian/Frequentist Methods for Sample Size Determination

Sample Size for Non-inferiority Designs
Design Considerations and Dealing with Non-continuous Endpoints

Randomization in Clinical Trials
Understanding it’s Importance & A Guide to Generating Randomization Lists

Sample Size for Statistical Intervals
Calculations for Confidence, Prediction and Credible Intervals

Sample Size for Complex Endpoints
Ordinal, Composite and Complex Survival Case Studies

Advanced Sample Size Determination for Counts and Rates
Dealing with Overdispersion, Unequal Followup and Interim Analysis

Improving Your Pre-Trial Milestone Predictions
Using Interim Data to Improve Expected Study Length Prediction

Designing Sequential Clinical Trials
A practical implementation of a sequential vaccine trial

Crossover & Cluster Randomized Trials
Alternative Study Designs and Randomization Schemes

Clinical Trial Design Trends for 2022

This year's most popular topics

Overcoming Challenges in Survival Analysis

How to predict key events for survival analysis trials
Using Simulation to Project Event Targets

Predicting Key Study Milestones
Using Simulation for Enrollment and Event Predictions

Bayesian Sample Size -
Approaches to Interval Estimation & Hypothesis testing

Sample Size for Oncology Trials - Survival Analysis, Delayed Effects and Adaptive Designs

Design and Sample Size for Vaccine Trials -
Case Study of Covid-19 Vaccine Trials

Phase II Oncology Trial Designs -
Their unique issues & the adaptive solutions

Choosing the right sample size method-
Rules for what will work for your study

2021 Trends In Biostatistics - Latest developments in clinical trial design

This year's most popular
clinical trial design topics

The impact of COVID-19 in clinical trials

Non-inferiority & Equivalence study design

Extending a trial’s design
Case studies of dealing with study design issues

Adaptive designs
for phase II trials

Flexible clinical trial design
Survival, Stepped-Wedge & MAMS Designs

Designing MAMS trials
Advantages, issues and sample size

Optimizing oncology trial design

MCP-Mod
Optimizing Phase II Dose Selection for
Continuous and Non-Continuous Endpoints

Designing studies with
recurrent events

2020 trends In biostatistics

5 Reasons to upgrade to
nQuery v8.5

Optimizing trial design:
From early phase to confirmatory trials

Sample size for phase II clinical trials
Simon's design and MCP-Mod case studies

Alternatives to the p-value & power:
The effect on sample size determination

Why include Bayesian statistics
(when planning your frequentists trial)

Innovative strategies for successful trial design

How to reduce sample size
Ethically and responsibly

Sample size for survival analysis
A guide to planning successful clinical trials

Get Started With Cards

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2019 trends in biostatistics What you should know about study design

nQuery Interviews Professor Stephen Senn

Adaptive clinical trials
Why & how to use nQuery for your sample size calculations

Innovative sample size methods for adaptive clinical trials

FDA guidance on adaptive sample size re-estimation

Innovative sample size methods for clinical trials

Bayesian assurance: Formalizing sensitivity analysis for sample size

Bayesian approaches to improve sample size

Practical methods to overcome sample size challenges

The 5 essential steps for sample size determination

Power and sample size calculations for survival analysis

Response, Quality & Variation.
What drug development may be missing