Cohen's kappa coefficient is commonly used for assessing agreement between classifications of two raters on a nominal scale. Three variants of Cohen's kappa that can handle missing data are presented. Data are considered missing if one or both ratings of a unit are missing. We study how well the variants estimate the kappa value for complete data…

Simulation studies are extremely common in the item response theory (IRT) research literature. This article presents a didactic discussion of "truth" and "error" in IRT-based simulation studies. We ultimately recommend that future research focus less on the simple recovery of parameters from a convenient generating IRT model,…

We present a method for data-based decision making at the school level using student achievement data. We demonstrate the potential of a national assessment database [i.e., the University of Oregon DIBELS Data System (DDS)] to provide comparative levels of school-level data on average student achievement gains. Through the DDS as a data source,…

It is often difficult and costly to obtain individual-level student achievement data, yet, researchers are frequently reluctant to use school-level achievement data that are widely available from state websites. We argue that public-use aggregate school-level achievement data are, in fact, sufficient to address a wide range of evaluation questions…

Single case designs (SCDs) generally consist of a small number of short time series in two or more phases. The analysis of SCDs statistically fits in the framework of a multilevel model, or hierarchical model. The usual analysis does not take into account the uncertainty in the estimation of the random effects. This not only has an effect on the…

The present study sought to investigate the family, individual, and dyad-specific contributions to observed cognitive sensitivity during family interactions. Moreover, the influence of cumulative risk on sensitivity at the aforementioned levels of the family was examined. Mothers and 2 children per family were observed interacting in a round robin…

Missing data are a common occurrence in survey-based research studies in education, and the way missing values are handled can significantly affect the results of analyses based on such data. Despite known problems with performance of some missing data handling methods, such as mean imputation, many researchers in education continue to use those…

The objective of this research was to determine the robustness and statistical power of three different methods for testing the hypothesis that ordinal samples of five and seven Likert categories come from equal populations. The three methods are the two sample t-test with equal variances, the Mann-Whitney test, and the Kolmogorov-Smirnov test. In…

This "What Works Clearinghouse Procedures and Standards Handbook (Version 3.0)" provides a detailed description of the standards and procedures of the What Works Clearinghouse (WWC). The remaining chapters of this Handbook are organized to take the reader through the basic steps that the WWC uses to develop a review protocol, identify…

The comparative format used in ranking and paired comparisons tasks can significantly reduce the impact of uniform response biases typically associated with rating scales. Thurstone's (1927, 1931) model provides a powerful framework for modeling comparative data such as paired comparisons and rankings. Although Thurstonian models are generally…

In this paper, we use two complementary Italian data sources (the 1995 ISTAT and Bank of Italy household surveys) to generate household-specific nondurable expenditure in the Bank of Italy sample that contains relatively high-quality income data. We show that food expenditure data are of comparable quality and informational content across the two…

Many times in both educational and social science research it is impossible to collect data that is complete. When administering a survey, for example, people may answer some questions and not others. This missing data causes a problem for researchers using structural equation modeling (SEM) techniques for data analyses. Because SEM and…