Two-Stage Nonparametric Bootstrap Sampling with Shrinkage Correction for Clustered Data

This article describes a new Stata command, tsb, for performing a stratified two-stage nonparametric bootstrap resampling procedure for clustered data. Estimates for uncertainty around the point estimate, such as standard error and confidence intervals, are derived from the resultant bootstrap samples. A shrinkage estimator proposed for correcting possible overestimation due to second-stage sampling is implemented as default. Although this command is written with cost effectiveness analyses alongside cluster trials in mind, it is applicable to the analysis of continuous endpoints in cluster trials more generally. The use of this command is exemplified with a case study of a cost effectiveness analysis undertaken alongside a cluster randomized trial. We also report bootstrap confidence interval coverage by using data from a published simulation study. </jats:p

Do Learners Really Know Best? Urban Legends in Education

This article takes a critical look at three pervasive urban legends in education about the nature of learners, learning, and teaching and looks at what educational and psychological research has to say about them. The three legends can be seen as variations on one central theme, namely, that it is the learner who knows best and that she or he should be the controlling force in her or his learning. The first legend is one of learners as digital natives who form a generation of students knowing by nature how to learn from new media, and for whom old media and methods used in teaching/learning no longer work. The second legend is the widespread belief that learners have specific learning styles and that education should be individualized to the extent that the pedagogy of teaching/learning is matched to the preferred style of the learner. The final legend is that learners ought to be seen as self-educators who should be given maximum control over what they are learning and their learning trajectory. It concludes with a possible reason why these legends have taken hold, are so pervasive, and are so difficult to eradicate