Small sample sizes contribute to several problems in research and knowledge advancement. This conceptual replication study confirmed and extended the inflation of type II errors and confidence intervals in correlation analyses of small sample sizes common in kinesiology/exercise science. Current population data (N = 18, 230, & 464) on four…

When designing a study for causal mediation analysis, it is crucial to conduct a power analysis to determine the sample size required to detect the causal mediation effects with sufficient power. However, the development of power analysis methods for causal mediation analysis has lagged far behind. To fill the knowledge gap, I proposed a…

Cluster sampling is common in survey practice, and the corresponding inference has been predominantly design-based. We develop a Bayesian framework for cluster sampling and account for the design effect in the outcome modeling. We consider a two-stage cluster sampling design where the clusters are first selected with probability proportional to…

Single-case design is a repeated-measures research approach for the study of the effect of an intervention, and its importance is increasingly being recognized in education and psychology. We propose a Bayesian approach for estimating intervention effects in SCD. A Bayesian inference does not rely on large sample theories and thus is particularly…

The main purpose of this study is to assess the degree to which transformational leadership was practiced in the technical vocational education and training institutions (TVETIs) of Ethiopia. To this end, cross-sectional survey research design was adopted. The study was conducted in seven government TVET institutions selected through simple random…

Evaluators of education interventions are increasingly designing studies to detect impacts much smaller than the 0.20 standard deviations that Cohen (1988) characterized as "small." While the need to detect smaller impacts is based on compelling arguments that such impacts are substantively meaningful, the drive to detect smaller impacts…

A multilevel meta-analysis can combine the results of several single-subject experimental design studies. However, the estimated effects are biased if the effect sizes are standardized and the number of measurement occasions is small. In this study, the authors investigated 4 approaches to correct for this bias. First, the standardized effect…

L. Wilkinson and the Task Force on Statistical Inference (1999) recommended reporting confidence intervals for measures of effect sizes. If the sample size is too small, the confidence interval may be too wide to provide meaningful information. Recently, K. Kelley and J. R. Rausch (2006) used an iterative approach to computer-generate tables of…

Comments on an article by J. J. Arnett regarding the assertion that American psychology focuses too narrowly on Americans while neglecting the other 95% of the world's population. The authors' comments focus on why American psychologists have become overreliant on American samples, and they provide alternative suggestions for broadening the scope…

The primary purpose of this study was to examine the differences in teacher quality, student achievement, and graduation rates among select North Carolina urban high schools based on their racial segregation when measured by the entropy index. The entropy index is a measure of evenness among racial groups used to determine the level of segregation…

Written by a social worker for social work students, this is a nuts and bolts guide to statistics that presents complex calculations and concepts in clear, easy-to-understand language. It includes numerous examples, data sets, and issues that students will encounter in social work practice. The first section introduces basic concepts and terms to…

This paper provides a framework for developing sampling designs in mixed methods research. First, we present sampling schemes that have been associated with quantitative and qualitative research. Second, we discuss sample size considerations and provide sample size recommendations for each of the major research designs for quantitative and…

The use of measures of magnitude of effect has been advocated as a way to go beyond statistical tests of significance and to identify effects of a practical size. They have been used in meta-analysis to combine results of different studies. Describes problems associated with measures of magnitude of effect (particularly study size) and…

This paper evaluates the logic underlying various criticisms of statistical significance testing and makes specific recommendations for scientific and editorial practice that might better increase the knowledge base. Reliance on the traditional hypothesis testing model has led to a major bias against nonsignificant results and to misinterpretation…

Statistical significance is misused in educational and psychological research when it is applied as a method to establish the reliability of research results. Other techniques have been developed which can be correctly utilized to establish the generalizability of findings. Methods that do provide such estimates are known as invariance or…