What Environments Support Reading Growth Among Current Compared With Former Reading Intervention Recipients? A Multilevel Analysis of Students and Their Schools.

School context can shape relative intervention response in myriad ways due to factors, such as instructional quality, resource allocation, peer effects, and correlations between the school context and characteristics of enrolled students (e.g., higher-poverty students attending higher-poverty schools). In the current study, we used data from 16,000 Grade 3 students in a community-based supplemental reading intervention program to investigate the degree to which school context factors (percentage eligible for free/reduced-price lunch [FRPL], school-level achievement) relate to the differences in triannual reading fluency growth rates between students actively receiving supplemental intervention (active recipients) and those that formerly received intervention (and therefore only received general class instruction at this time; former recipients). Using Bayesian multilevel modeling, our findings indicate that school-level FRPL eligibility played a more prominent factor in growth rate differences between these two groups than school-level reading achievement. However, school-level reading achievement was much more strongly related to reading fluency differences between active and former intervention recipients at the beginning of the school year (when controlling for FRPL). Implications for investigating school-level heterogeneity in intervention response and sustainability are discussed.

Considering between- and within-person relations in auto-regressive cross-lagged panel models for developmental data.

Longitudinal data can provide inferences at both the between-person and within-person levels of analysis, but only to the extent that the statistical models chosen for data analysis are specified to adequately capture these distinct sources of association. The present work focuses on auto-regressive cross-lagged panel models, which have long been used to examine time-lagged reciprocal relations and mediation among multiple variables measured repeatedly over time. Unfortunately, many common implementations of these models fail to distinguish between-person associations among individual differences in the variables' amounts and changes over time, and thus confound between-person and within-person relations either partially or entirely, leading to inaccurate results. Furthermore, in the increasingly complex model variants that continue to be developed, what is not easily appreciated is how substantial differences in interpretation can be created by what appear to be trivial differences in model specification. In the present work, we aimed to (a) help analysts become better acquainted with the some of the more common model variants that fall under this larger umbrella, and (b) explicate what characteristics of one's data and research questions should be considered in selecting a model. Supplementary Materials include annotated model syntax and output using Mplus, lavaan in R, and sem in Stata to help translate these concepts into practice.

Demystifying longitudinal data analyses using structural equation models in school psychology.

Structural equation models (SEM) are a method of latent variable analysis that offer a high degree of flexibility in terms of modeling methods for applied research questions. Recent advancements associated with longitudinal SEM have unlocked innovative ways to decompose variance and to estimate mean trends over time (e.g., Allison et al., 2017; Berry & Willoughby, 2017; Hamaker et al., 2015; McArdle & Nesselroade, 2014). However, these longitudinal methods are not necessarily readily accessible to scholars seeking to advance theory and practice in school psychology. Importantly, not all longitudinal data are the same and not all longitudinal SEMs are the same; thus, analytic approaches must be appropriately matched to specific research aims to meaningfully inform school psychology theory and practice. The present article highlights recent advances in longitudinal SEMs, clarifies their similarities to other-perhaps more familiar-methods, and matches their applications to specific types of research questions. The intent of this work is to promote careful thinking about the correspondence between estimands, developmental theory, and practical applications to foster specificity in testing quantitative questions in school psychology research and advance a more rigorous evaluation of longitudinal trends relevant to research and practice in the field.

Differential nonlinear relations of language proficiencies to reading and math achievement in Spanish or English.

We examined whether English language proficiency (ELP) related to interim reading and math performance differently when academic assessments were administered to students in either English or Spanish. We also tested these effects with Spanish language proficiency (SLP) as well as jointly with ELP and SLP. Students from a midwestern suburban school district in Grades 2-8 were included (N = 2,327); 763 of these students in Grades 4-8 had SLP and ELP scores. Differences between English and Spanish math scores varied minimally across the majority of the ELP distribution. English-Spanish differences in reading across ELP scores were more pronounced. Language differences in math and reading scores as a function of only SLP were less clear, and reading was also more sensitive to joint changes in ELP and SLP compared to math. We discuss practical implications and limitations for assessment within multitiered systems of support as well as future directions for research. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Modeling associations of English proficiency and working memory with mathematics growth.

Using kindergarten up to fourth-grade data from the Early Childhood Longitudinal Study (2010-2011 cohort), we investigated systematic variability in English language learners' (ELLs; n = 303) mathematics growth as well as relations of kindergarten language growth and working memory (WM) to ELLs' mathematics growth. Using growth mixture modeling, only one class of growth emerged from ELLs' English mathematics growth from first through fourth grades. WM related to ELLs' English mathematics growth from Grades 1 to 4, as did kindergarten growth in English early literacy. We also investigated kindergarten to Grade 4 mathematics growth between ELLs and English proficient students (EPSs; n = 4,711) using latent change score models and whether WM differentially predicted growth patterns. ELLs and EPSs did not exhibit markedly different growth patterns, and WM similarly predicted these patterns. Implications for future research as well as practical implications and limitations are discussed. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

Examining links between parental monitoring and school engagement among middle school students with and without elevated behavior ratings.

The purpose of this study was to examine whether seventh-grade positive peer affiliation and conduct problems mediated the relationship between sixth-grade parental monitoring of behavior and eighth-grade school participation and grades among students with elevated behavior ratings (EBR; n = 821) and students with unelevated behavior ratings (UBR; n = 3,779). Conduct problems and peer affiliation mediated the relationship between parental monitoring and school participation as well as grades in the overall sample (n = 4,600). A multiple-group mediation model suggested that these effects did not significantly differ across students with EBR and UBR, though the mediation estimates were smaller in magnitude and not statistically significant among students with EBR. Implications for the role of parental monitoring as an intervention target within a multitiered system of support for social and behavioral skills in middle school, as well as limitations and future directions are discussed. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

The impact of keels and tails on turtle swimming performance and their potential as models for biomimetic design.

Stability and turning performance are two key metrics of locomotor performance in animals, and performance in both of these metrics can be improved through a variety of morphological structures. Aquatic vehicles are often designed with keels and rudders to improve their stability and turning performance, but how keels and rudders function in rigid-bodied animals is less understood. Aquatic turtles are a lineage of rigid-bodied animals that have the potential to function similarly to engineered vehicles, and also might make use of keels and rudders to improve their stability and turning performance. To test these possibilities, we trained turtles to follow a mechanically controlled prey stimulus under three sets of conditions: with no structural modifications, with different sized and shaped keels, and with restricted tail use. We predicted that keels in turtles would function similarly to those in aquatic vehicles to reduce oscillations, and that turtles would use the tail like a rudder to reduce oscillations and improve turning performance. We found that the keel designs we tested did not reduce oscillations in turtles, but that the tail was used similarly to a rudder, with benefits to both the magnitude of oscillations they experienced and turning performance. These data show how variation in the accessory structures of rigid-bodied animals can impact swimming performance, and suggest that such variation among turtles could serve as a biomimetic model in designing aquatic vehicles that are stable as well as maneuverable and agile.