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Resampling as a revolutionary methodology to deal with small-sample problems has been developed rapidly with the growth of modern computer techniques. This book introduces a new resampling method, the sample smoothing amplification resampling technique (S-SMART) which can produce amplified samples with adequate statistical power, conditional independence of observations, robustness to outliers, stable statistical behaviors, and an identical distribution with its small random proto-sample from any distributions. An empirical example is also provided as guidance for readers to apply S-SMART to their own research using small samples. This book also includes a systematic overview and comparison of other major resampling methods, including the Bootstrap; therefore, applied statisticians and quantitative researchers not only can use the book as an introduction to S-SMART, but also can consult it for information about other resampling methods.
About the author
Haiyan Bai, Ph.D., is an Assistant Professor of Quantitative Research Methodology at the University of Central Florida. Her research focus is in the area of resampling techniques and other statistical methods.
