WebPower

The importance of conducting a statistical power analysis at the beginning of a study is universally accepted (e.g., Cohen, 1988; Hedges & Rhoads, 2009). Without careful planning, a study can easily fail to detect an existing effect by chance. The increasing complexity of education research driven by education practice poses great challenges on existing methods of statistical power analysis. For example, education research often involves longitudinal and multilevel designs as well as advanced techniques such as structural equation and multilevel models. Furthermore, practical data in education are often not normally distributed and are incomplete. Regarding the nature of real data, Micceri (1989) reported that among 440 large-sample achievement and psychometric measures taken from journal articles, research projects, and tests, all were significantly non-normally distributed. In impact evaluations funded by the National Center for Educational Evaluation and Regional Assistance (NCEE), student achievement outcomes are often missing for 10-20 percent (e.g., Puma, 2009). Without careful consideration of the complexity of study designs and the impact of non-normal data and missing data, the validity of education research can be harmed.

With the support from the grant program on Statistical and Research Methodology in Education from the Institute of Education Sciences of U.S. Department of Education, WebPower is developed to conduct both simple and complex statistical power analysis online. This Android app makes the use of the online software easy to use on phone and tablets.