Both Frequentist & Bayesian analysis to optimize sample size and trial design
With increasing costs and historically low rates of success it has never been more difficult to conduct a clinical trial. At nQuery we recognize that part of the solution is to ensure that researchers have access to the latest innovations in study planning, design and monitoring. Reduce the risk and cost of your clinical trial by using nQuery as your sample size software.
Whether unlocking the power of previous data using Bayesian methodologies, understanding the true probability of success for your trial or giving researchers the ability to make decisions about their trial while it is still ongoing. At nQuery we want to make sure that you have access to the latest tools such as the Bayesian analysis module in our sample size calculator to maximize the chance of success in your trial.
Bayesian statistical methods continue to gain in popularity thanks to their ability to integrate prior information into their estimates. Despite this, there is still a lack of tools available for when planning or doing a sample size estimation estimation with Bayesian analysis in mind.
With the nQuery sample size calculator you gain access to sample size methods for Bayesian analysis such as posterior credible intervals and thus can be confident that whether you're using a Bayesian or Frequentist analysis you'll be able to find the appropriate sample size for your study.
Using assurance also known as Bayesian power you can integrate prior uncertainty about the effect size or other parameters to gain a more complete understanding of your sample size estimate. Whether using previous data or eliciting expert opinion using frameworks such a SHELF to construct a prior, with assurance you will gain insights into the effect of uncertainty on the true probability of success for your trial.
Adaptive trials empower researchers to make decisions about their trial while it is still ongoing. By monitoring information as it becomes available they can maximize the value probability of success for their trial.
For example in a group sequential design a researcher could choose to end the trial early if the evidence suggests that there is a very high probability that a trial would end in success or failure. By stopping the trial early they can minimize the cost of the trial and reduce patient risk.
At nQuery we continue to add adaptive designs such as Group Sequential Trials and ensure you have access to the latest innovations in adaptive design. This will ensure that you will have access to the flexibility you need to make sure that your trial is a success at each stage of the process.
Reduce the risk and cost of your clinical trial by using nQuery as your sample size software. nQuery helps biostatisticians calculate the appropriate sample size by implementing both Frequentist & Bayesian Statistics to optimize their trial design. nQuery - 20+ Years helping statisticians with 50K+ users.