Assessing student achievement over multiple years is complicated by students' memberships in shifting upper-level nesting structures. These structures are manifested in (1) annual matriculation to different classrooms and (2) mobility between schools. Failure to model these shifting upper-level nesting structures may bias the inferences…

Federal law requires that state accountability systems include "another academic indicator" for elementary and middle schools in addition to academic achievement. Nearly all states use a measure of student longitudinal growth as their other academic indicator. But how should states decide which growth model to use? The Center for…

The number of low-performing schools has drastically increased since COVID-19. During the 2018-2019 school year, there were 488 low-performing schools (North Carolina Department of Public Instruction, 2024). The number increased to 736 schools during the 2023- 2024 school year, a 50.8% increase (North Carolina Department of Public Instruction,…

Vertical scales are frequently developed using common item nonequivalent group linking. In this design, one can use upper-grade, lower-grade, or mixed-grade common items to estimate the linking constants that underlie the absolute measurement of growth. Using the Rasch model and a dataset from Curriculum Associates' i-Ready Diagnostic in math in…

Coping Power (CP) is a preventive intervention that focuses on reducing child externalizing problems. Although it is typically delivered in a group format (GCP), individually-delivered CP (ICP) has produced greater mean reductions in externalizing problems. However, standard analysis of randomized trials loses individual-level information…

While working memory (WM) is a powerful predictor for children's school outcomes, autistic children are more likely to experience delays. This study compared autistic children and their neurotypical peers' WM development over their elementary school years, including relative growth and period of plasticity. Using a nationally-representative…

Michigan's Great Start Readiness Program (GSRP) is a state-funded pre-K program that serves at risk four-year-old children across the state. Utilizing longitudinal data from 1,394 children in a mid-sized urban school district, we conducted regression analyses and piecewise linear growth models to examine the growth trajectory of GSRP children and…

We used the Stanford education data archive (SEDA) data to examine the heterogeneity among urban school districts in the United States. The SEDA 2.1 includes data sets on students' mathematics (Math) and English language arts (ELA) achievement from 2008 to 2014 at the district level. Growth mixture modeling was used to uncover the underlying…

This study evaluated the forecasting accuracy of trend estimation methods applied to time-series data from computer adaptive tests (CATs). Data were collected roughly once a month over the course of a school year. We evaluated the forecasting accuracy of two regression-based growth estimation methods (ordinary least squares and Theil-Sen). The…