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…

In undergraduate research settings, students are likely to encounter anomalous data, that is, data that do not meet their expectations. Most of the research that directly or indirectly captures the role of anomalous data in research settings uses post-hoc reflective interviews or surveys. These data collection approaches focus on recall of past…

Test-retest reliability assessments rarely investigate whether reliability itself is stable or change in reliability affects findings from substantive models. Research across the social sciences often recognizes that measurement error could influence results, yet it rarely applies established error correction methods. Focusing on gender wage…

To determine if the observed correlation between two variables can be "explained" by a third variable, a significance test on the partial correlation coefficient is often used. This can be misleading when the third variable is measured with error. This article shows how the problem can be partially overcome. (Author/BW)

The most commonly used method of collecting outcome data in health education programs is self-report, which produces a variety of measurement errors. A model is proposed to systematically identify major influences for accuracy of self-reported health behavior. Methodologic studies are described, and eight steps to increase accuracy are proposed.…

Two articles discuss the controversy about the relationship between reliability and the power of significance tests in response to the discussion of Donald W. Zimmerman, Richard H. Williams, and Bruno D. Zumbo. Lloyd G. Humphreys emphasizes the differences between what statisticians can do and constraints on researchers. Zimmerman, Williams, and…