Design and Analysis of Pragmatic Trials

This book begins with an introduction of  pragmatic cluster randomized trials (PCTs) and reviews various  pragmatic issues that need to be addressed by statisticians at the  design stage. It discusses the advantages and disadvantages of each type  of PCT, and provides sample size formulas, sensitivity analyses, and  examples for sample size calculation. The generalized estimating  equation (GEE) method will be employed to derive sample size formulas  for various types of outcomes from the exponential family, including  continuous, binary, and count variables. Experimental designs that have  been frequently employed in PCTs will be discussed, including cluster  randomized designs, matched-pair cluster randomized design, stratified  cluster randomized design, stepped-wedge cluster randomized design,  longitudinal cluster randomized design, and crossover cluster randomized  design. It demonstrates that the GEE approach is flexible to  accommodate pragmatic issues such as hierarchical correlation  structures, different missing data patterns, randomly varying cluster  sizes, etc. It has been reported that the GEE approach leads to  under-estimated variance with limited numbers of clusters. The remedy  for this limitation is investigated for the design of PCTs. This book  can assist practitioners in the design of PCTs by providing a  description of the advantages and disadvantages of various PCTs and  sample size formulas that address various pragmatic issues, facilitating  the proper implementation of PCTs to improve health care. It can also  serve as a textbook for biostatistics students at the graduate level to  enhance their knowledge or skill in clinical trial design.

Key Features:

• Discuss  the advantages and disadvantages of each type of PCTs, and provide  sample size formulas, sensitivity analyses, and examples.
• Address an unmet need for guidance books on sample size calculations for PCTs;
• A wide variety of experimental designs adopted by PCTs are covered;
• The  sample size solutions can be readily implemented due to the  accommodation of common pragmatic issues encountered in real-world  practice;
• Useful to both academic and industrial biostatisticians involved in clinical trial design;
• Can be used as a textbook for graduate students majoring in statistics and biostatistics.