Count and incidence rate data is a common outcome in areas such as chronic respiratory diseases and imaging studies.
Many methods exist for the analysis count and incidence rate data such as Poisson or Negative Binomial regression but sample size methods have been relatively basic up until recently.
Significant progress has been made in some areas including overdispersion, unequal follow-up, and group sequential design.
Please join us as we examine advanced sample size determination for counts and rates.
More About The Webinar
Recurring events are a common outcome in clinical trials in areas such as chronic respiratory diseases such as asthma and COPD. In addition, count data is an important endpoint in contexts such as MRI imaging.
Well developed methods are available for analysis of recurring events and counts using methods such as Poisson or Negative Binomial regression. However, many studies continue to choose to analyse such data using continuous approximations or time-to-(first) event data.
One barrier to using count models has been the relatively basic sample size determination methods available. However, recent years have seen significant progress as methods have been developed to determine the sample size in the presence of issues such as overdispersion, unequal follow-up, and using group sequential design.
In this webinar,we go over the methods available for analysing counts and rates, and provide an in-depth overview of the sample size determination methods available, including recent, more advanced methods, proposed in the literature.