The omega (?) statistic is reputed to be one of the best indices for detecting answer copying on multiple choice tests, but its performance relies on the accurate estimation of copier ability, which is challenging because responses from the copiers may have been contaminated. We propose an algorithm that aims to identify and delete the suspected…

The research reported here uses a pre/post-test model and stimulated recall interviews to assess teachers' statistical reasoning about comparing distributions, when enrolled in a graduate-level statistics education course. We discuss key aspects of the course design aimed at improving teachers' learning and teaching of statistics, and the…

There is a long-standing debate as to whether nonexperimental estimators of causal effects of social programs can overcome selection bias. Most existing reviews either are inconclusive or point to significant selection biases in nonexperimental studies. However, many of the reviews, the so-called "between-studies," do not make direct…

Propensity score estimation plays a fundamental role in propensity score matching for reducing group selection bias in observational data. To increase the accuracy of propensity score estimation, the author developed a bootstrap propensity score. The commonly used propensity score matching methods: nearest neighbor matching, caliper matching, and…

Often researchers face situations where comparative studies between two or more programs are necessary to make causal inferences for informed policy decision-making. Experimental designs employing randomization provide the strongest evidence for causal inferences. However, many pragmatic and ethical challenges may preclude the use of randomized…

Investigation of peer effects on achievement with sample survey data on schools may mean that only a random sample of the population of peers is observed for each individual. This generates measurement error in peer variables similar in form to the textbook case of errors-in-variables, resulting in the estimated peer group effects in an OLS…

This article presents a method for addressing the self-selection bias of students who participate in learning communities (LCs). More specifically, this research utilizes equivalent comparison groups based on selected incoming characteristics of students, known as bootstraps, to account for self-selection bias. To address the differences in…

Adjustment methods such as propensity scores and analysis of covariance are often used for estimating treatment effects in nonexperimental data. Shadish, Clark, and Steiner used a within-study comparison to test how well these adjustments work in practice. They randomly assigned participating students to a randomized or nonrandomized experiment.…

The biases and mean squared errors of the sample squared multiple correlation coefficient and five adjusted estimators of the population squared multiple correlation are examined. A quadratic estimator and the minimum variance unbiased estimator are also examined. These estimators are compared in terms of absolute bias and mean squared error.…

Use of Tukey's Jackknife in establishing a confidence interval around the population coefficient alpha is explored and the robustness of Feldt's procedure along with ten variants of the Jackknife when the data do not conform to the necessary normality requirements are evaluated. Only two of the variants compared to Feldt's approach. (RC)

Concludes little relationship exists between the three substances marihuana, alcohol and tobacco. Youthful subjects tend to overestimate the relationships between the three substances and cannot be generalized to other populations. Suggests an explanation of this youthful association focuses on simultaneous experimentation rather than causal…

Evaluations involving nonrandom assignment to treatment or control groups are vulnerable to an accidental or intentional confounding of a selection effect with the treatment effect. Two techniques, discriminant analysis and base expectancy analysis, permit separate estimation of the selection and treatment effects in the final results. (Author/CTM)

This monograph critiques the many nonexperimental impact estimation approaches that have been based on external comparison groups. It proposes an approach to evaluating employment and training (E&T) programs that calls for using the group of individuals who apply to a program but then choose not to participate in that program as an…

Abuses and misuses of statistics are frequent. This digest attempts to warn against these in three broad classes of pitfalls: sources of bias, errors of methodology, and misinterpretation of results. Sources of bias are conditions or circumstances that affect the external validity of statistical results. In order for a researcher to make…