Over the past ten years, propensity score methods have made an important contribution to improving generalizations from studies that do not select samples randomly from a population of inference. However, these methods require assumptions and recent work has considered the role of bounding approaches that provide a range of treatment impact…

Optimal design of multisite randomized trials leverages sampling costs to optimize sampling ratios and ultimately identify more efficient and powerful designs. Past implementations of the optimal design framework have assumed that costs of sampling units are equal across treatment conditions. In this study, we developed a more flexible optimal…

The debate on determining sample size in qualitative research is confounded by four fundamental methodological issues: the exclusive focus on theme analysis; the diverse and imprecise use of 'qualitative'; a reliance on only two logics of inquiry, "induction" and "deduction," and the occasional confusion of…

There has been considerable recent interest in methods of determining sample size for qualitative research a priori, rather than through an adaptive approach such as saturation. Extending previous literature in this area, we identify four distinct approaches to determining sample size in this way: rules of thumb, conceptual models, numerical…

In his detailed response to our paper on sample size in qualitative research, Norman Blaikie raises important issues concerning conceptual definitions and taxonomy. In particular, he points out the problems associated with a loose, generic application of adjectives such as 'qualitative' or 'inductive'. We endorse this concern, though we suggest…

This article discusses the sample size requirements for the interaction, row, and column effects, respectively, by forming a linear contrast for a 2×2 factorial design for fixed-effects heterogeneous analysis of variance. The proposed method uses the Welch t test and its corresponding degrees of freedom to calculate the final sample size in a…

Recently Watkins, Bargagliotti, and Franklin (2014) discovered that simulations of the sampling distribution of the mean can mislead students into concluding that the mean of the sampling distribution of the mean depends on sample size. This potential error arises from the fact that the mean of a simulated sampling distribution will tend to be…

Randomization tests are often recommended when parametric assumptions may be violated because they require no distributional or random sampling assumptions in order to be valid. In addition to being exact, a randomization test may also be more powerful than its parametric counterpart. This was demonstrated in a simulation study which examined the…

Due to statistical analysis, the issue of random sampling is pertinent to any quantitative study. Unlike quantitative study, the elimination of inferential statistical analysis, allows qualitative researchers to be more creative in dealing with sampling issue. Since results from qualitative study cannot be generalized to the bigger population,…

Individually administered tests are often normed on small samples, a process that may result in irregularities within and across various age or grade distributions. Test users often smooth distributions guided by Thurstone assumptions (normality and linearity) to result in norms that adhere to assumptions made about how the data should look. Test…

Large surveys often use probability sampling in order to obtain representative samples, and these data sets are valuable tools for researchers in all areas of science. Yet many researchers are not formally prepared to appropriately utilize these resources. Indeed, users of one popular dataset were generally found "not" to have modeled…

The purpose of this review was to examine the methods used to conduct meta-analyses of single-subject research involving students with and at-risk for disabilities. Specifically, the procedures used for preparing, aggregating, analyzing, and evaluating single-subject data across 68 primary syntheses were examined. In addition to these…

A concern for generalization dominates quantitative research. For generalizability and repeatability, identification of sample size is essential. The present study investigates 90 qualitative master's theses submitted for the Primary and Secondary School Science and Mathematics Education Departments, Mathematic Education Discipline in 10…

The use of random numbers is pervasive in today's world. Random numbers have practical applications in such far-flung arenas as computer simulations, cryptography, gambling, the legal system, statistical sampling, and even the war on terrorism. Evaluating the randomness of extremely large samples is a complex, intricate process. However, the…

On the 2009 AP[c] Statistics Exam, students were asked to create a statistic to measure skewness in a distribution. This paper explores several of the most popular student responses and evaluates which statistic performs best when sampling from various skewed populations. (Contains 8 figures, 3 tables, and 4 footnotes.)