Cooperative Extension professionals utilize proven qualitative techniques to collect and analyze information to make data-driven decisions that guide program direction and determine impact. While the process may not always look the same, it is indeed essential to ensure findings are credible and reflective of the data. A codebook is a valuable…

Textbook data is essential for teaching statistics and data science methods because it is clean, allowing the instructor to focus on methodology. Ideally textbook datasets are refreshed regularly, especially when they are subsets taken from an ongoing data collection. It is also important to use contemporary data for teaching, to imbue the sense…

Longitudinal panel studies are widely used in developmental science to address important research questions on human development across the lifespan. These studies, however, are often challenging to implement. They can be costly, time-consuming, and vulnerable to test--retest effects or high attrition over time. Planned missingness designs (PMDs),…

For states to build statewide longitudinal data systems that empower people with access to information about education and workforce pathways, state leaders must consider the human capacity they already have, and must develop, to support this work. Building the human capacity required to manage, analyze, and protect data means investing in and…

Currently, dynamic structural equation modeling (DSEM) and residual DSEM (RDSEM) are commonly used in testing intensive longitudinal data (ILD). Researchers are interested in ILD mediation models, but their analyses are challenging. The present paper mathematically derived, empirically compared, and step-by-step demonstrated three types (i.e.,…

With Governor Newsom's signature on the state budget in June 2019, California is finally on the path to joining the majority of other states in the country who have robust data systems. Having this administration provide funding to begin to build and maintain a statewide longitudinal data system (SLDS) is an important win. Advocates have been…

Secondary data analyses occur when new analyses are proposed for existing data. Although they are prevalent in special education research, there is little guidance on how to prepare secondary data analyses studies. Preregistration of secondary data analyses studies provides a nice opportunity and structure for fellow researchers to share…

Participatory modeling (PM) is an engaged research methodology for creating analog or computer-based models of complex systems, such as socio-environmental systems. Used across a range of fields, PM centers stakeholder knowledge and participation to create more internally valid models that can inform policy and increase engagement and trust…

The 2020 election brought about legislative change across the country. New and veteran policymakers need information about the schools in their state. What programs are the most cost effective and work best for students? How can states attract and retain great teachers? What information do parents need to ensure that their kids are on track to…

We contextualize the magnitude of teacher attrition during the pandemic, including from the 2020-2021 school year to the 2021-2022 school year, using longitudinal data on teachers in Washington since the 1984-1985 school year. The teacher attrition rate after the 2020-2021 school year (7.3%) increased by almost one percentage point from the…

SEERNet digital learning platforms (DLPs) are developing new infrastructure to support research in authentic contexts where student learning is happening. In order to contextualize this work within the larger field, we trace historical precedents along four main categories: data repositories, data collection services, research design interfaces,…

The analysis of cross-lagged relationships is a popular approach in prevention research to explore the dynamics between constructs over time. However, a limitation of commonly used cross-lagged models is the requirement of equally spaced measurement occasions that prevents the usage of flexible longitudinal designs and complicates cross-study…

When using multiple imputation, users often want to know how many imputations they need. An old answer is that 2-10 imputations usually suffice, but this recommendation only addresses the efficiency of point estimates. You may need more imputations if, in addition to efficient point estimates, you also want standard error (SE) estimates that would…

The State Higher Education Executive Officers Association's (SHEEO) "Communities of Practice" project builds upon SHEEO's ongoing efforts to measure the capacity and effective use of state postsecondary data systems and provides states with opportunities to develop solutions to common issues with those systems. The sixth Community of…

The Student Evaluation of Teaching (SET) instrument provides insight for instructors and administrators alike, often touting high response-rates to endorse their validity and reliability. However, response-rate alone omits consideration for "adequate quantity of 'observational sampling opportunity' (OSO) data points" (e.g., high student…