Many generalization studies in education are typically based on a sample of 30-70 schools while the inference population is at least twenty times larger. This small sample to population size ratio limits the precision of design-based estimators of the population average treatment effect. Prior work has shown the potential of small area estimation…

Causal inference involves determining whether a treatment (e.g., an education program) causes a change in outcomes (e.g., academic achievement). It is well-known that causal effects are more challenging to estimate than associations. Over the past 50 years, the potential outcomes framework has become one of the most widely used approaches for…

Within multitiered systems of support, assessment practices that limit the amount of time students miss instruction should be prioritized. At the same time, decisions about student response to intervention need to be based upon technically adequate data. We evaluated the impact of data collection frequency and trend estimation method on the…

Many students' knowledge of fractions is adversely affected by whole number bias, the tendency to focus on the separate whole number components (numerator and denominator) of a fraction rather than on the fraction's integrated magnitude (ratio of numerator to denominator). Although whole number bias appears early in the fraction learning process…

This article proposes a latent variable regression four-level hierarchical model (LVR-HM4) that uses a fully Bayesian approach. Using multisite multiple-cohort longitudinal data, for example, annual assessment scores over grades for students who are nested within cohorts within schools, the LVR-HM4 attempts to simultaneously model two types of…

Two objectives guided this research. First, this study examined how well teachers' tracking decisions contribute to the homogenization of their students' achievements. Second, the study explored whether teachers' tracking decisions would be outperformed in homogenizing the students' achievements by statistical models of tracking decisions. These…

Schools need evidence-based guidance on which measures in mathematics, administered under what particular set of conditions (e.g., time of year), provide the most useful prediction. The purpose of this study was to examine decision accuracy among commonly used screening measures with a priority toward identifying the least costly screening…

Large-scale assessment programs such as the National Assessment of Educational Progress (NAEP), Trends in International Mathematics and Science Study (TIMSS), and Programme for International Student Assessment (PISA) use a sophisticated assessment administration design called matrix sampling that minimizes the testing burden on individual…

Regression, weighting and related approaches to estimating a population mean from a sample with nonrandom missing data often rely on the assumption that conditional on covariates, observed samples can be treated as random. Standard methods using this assumption generally will fail to yield consistent estimators when covariates are measured with…

A common strategy for estimating treatment effects in observational studies using individual student-level data is analysis of covariance (ANCOVA) or hierarchical variants of it, in which outcomes (often standardized test scores) are regressed on pretreatment test scores, other student characteristics, and treatment group indicators. Measurement…

In large-scale educational surveys, a latent regression model is used to compensate for the shortage of cognitive information. Conventionally, the covariates in the latent regression model are principal components extracted from background data. This operational method has several important disadvantages, such as the handling of missing data and…

School suspension rates have been rising since the early 1970s, especially for children of color. One body of research has demonstrated that suspension from school is harmful to students, as it increases the risk of retention and school dropout. Another has demonstrated that school dropouts impose huge social costs on their states and localities,…

The purpose of the current study was to evaluate the importance of growth in math fact skills within the context of overall math proficiency. Data for 1,493 elementary and middle school students were included for analysis. Regression models were fit to examine the relative value of math fact fluency growth, prior state test performance, and a fall…

In an effort to promote best practices regarding mathematics teaching and learning at the preschool level, national advisory panels and organizations have emphasized the importance of children's emergent counting and related competencies, such as the ability to verbally count, maintain one-to-one correspondence, count with cardinality, subitize,…

Numerical understanding and arithmetic skills are easier to acquire for whole numbers than fractions. The "integrated theory of numerical development" posits that, in addition to these differences, whole numbers and fractions also have important commonalities. In both, students need to learn how to interpret number symbols in terms of…