The year 2022 is the 20th anniversary of Joseph Schafer and John Graham's paper titled "Missing data: Our view of the state of the art," currently the most highly cited paper in the history of "Psychological Methods." Much has changed since 2002, as missing data methodologies have continually evolved and improved; the range of…

We examine the intrinsic value students placed on schoolwork (i.e. academic intrinsic value) and social relationships (i.e. social intrinsic value). We then look at how these values predict middle and high school achievement. To do this, we came up with four profiles based on cluster analyses of 6,562 South Korean middle school students. The four…

The stability of educational test results from the Programme for International Student Assessment (PISA) over 15 years was examined, and the influence of demographics and social capital was assessed, as was the impact of educational reforms. The test results were remarkably stable, with correlations up to 0.99 for country-level results over 2…

Multilevel modeling (MLM) is frequently used to detect cluster-level group differences in cluster randomized trial and observational studies. Group differences on the outcomes (posttest scores) are detected by controlling for the covariate (pretest scores) as a proxy variable for unobserved factors that predict future attributes. The pretest and…

Little is known empirically about intraclass correlations (ICCs) for multisite cluster randomized trial (MSCRT) designs, particularly in science education. In this study, ICCs suitable for science achievement studies using a three-level (students in schools in districts) MSCRT design that block on district are estimated and examined. Estimates of…

Ratio and proportional relationships are of primary importance during the upper elementary and middle school grades (Kilpatrick, Swafford, & Findell, 2001; National Council of Teachers of Mathematics, 1989, 2000; National Mathematics Advisory Panel [NMAP], 2008). These relationships, along with the interrelated topics of fractions, decimals,…

Using state achievement data that are openly accessible, this paper demonstrates the application of hierarchical linear modeling within the context of career technical education research. Three prominent approaches to analyzing clustered data (i.e., modeling aggregated data, modeling disaggregated data, modeling hierarchical data) are discussed…

Use of multivariate analysis (e.g., multivariate analysis of variance) is common when normally distributed outcomes are collected in intervention research. However, when mixed responses--a set of normal and binary outcomes--are collected, standard multivariate analyses are no longer suitable. While mixed responses are often obtained in…

This is an application of contemporary multilevel regression modeling to the prediction of academic performances of 1st-year college students. At a first level of analysis, the data come from N greater than 16,000 students who were college freshman in 1994-1995 and who were also participants in high-level college athletics. At a second level of…

This study examines math and English standardized test score progress of students who participated in the 21st century program across 2 years of involvement with a focus on the learning trajectories of limited English proficiency (LEP) students. We find that math and English scores are highly associated with the school and program type--even…

Relatively little research has explored whether schools differ in their effectiveness for different group of pupils (e.g. by ethnicity, poverty or gender), for different curriculum subjects (e.g. English, mathematics or science) or over time (different cohorts). This paper uses multilevel modelling to analyse the national test results at age 7 and…