Multilevel modeling allows researchers to understand whether relationships between lower-level variables (e.g., individual job satisfaction and performance, firm capabilities performance) change as a function of higher-order moderator leadership climate, market-based conditions). We describe how estimate such cross-level interaction effects distill the technical literature for general readership management researchers, including description multilevel model building process an illustration...

A family of learning models that integrates a cognitive diagnostic model and higher-order, hidden Markov in one framework is proposed. This new includes covariates to skill transition the environment. Bayesian formulation adopted estimate parameters from model. The developed methods are applied computer-based assessment with intervention. results show potential application proposed track change students’ skills directly provide immediate remediation as well evaluate efficacy different...

A Bayesian model formulation of the deterministic inputs, noisy “and” gate (DINA) is presented. Gibbs sampling employed to simulate from joint posterior distribution item guessing and slipping parameters, subject attribute latent class probabilities. The procedure extends concepts in Béguin Glas, Culpepper, Sahu for estimating parameters three- four-parameter normal-ogive models. ability recover demonstrated a simulation study. technique applied mental rotation test. algorithm vignettes are...

Scale coarseness is a pervasive yet ignored methodological artifact that attenuates observed correlation coefficients in relation to population coefficients. The authors describe how disattenuate correlations are biased by scale primary-level as well meta-analytic studies and derive the sampling error variance for corrected correlation. Results of two Monte Carlo simulations reveal correction procedure accurate show extent which biases coefficient under various conditions (i.e., value...

We developed a new analytic proof and conducted Monte Carlo simulations to assess the effects of methodological statistical artifacts on relative accuracy intercept- slope-based test bias assessment. The main simulation design included 3,185,000 unique combinations wide range values for true bias, total sample size, proportion minority group size predictor (i.e., preemployment scores) criterion job performance) reliability, restriction, correlation between scores dummy-coded grouping...

The increasing presence of electronic and online learning resources presents challenges opportunities for psychometric techniques that can assist in the measurement abilities even hasten their mastery. Cognitive diagnosis models (CDMs) are ideal tracking many fine-grained skills comprise a domain, carefully navigating through training assessment these e-learning applications. A class CDMs modeling changes attributes is proposed, which referred to as trajectories. authors focus on development...

Cross-level interaction effects lay at the heart of multilevel contingency and interactionism theories. Also, practitioners are particularly interested in such because they provide information on contextual conditions processes under which interventions focused individuals (e.g., selection, leadership training, performance appraisal, management) result more or less positive outcomes. We derive a new intraclass correlation, ρ β , to assess degree lower-level outcome variance that is...

AbstractNovice earth science students often have difficulty visualizing three-dimensional interpretations of flat, two-dimensional displays. This challenge becomes apparent when attempt to comprehend topographic maps. In this study, we investigated conditions that influence such activity. Earth viewed standard maps, maps included shading, stereo visualization (affording a percept the map), or with both and shading. Students answered line-of-sight questions (i.e., intervisibility tasks) while...

Analysis of covariance (ANCOVA) is used widely in psychological research implementing nonexperimental designs. However, when covariates are fallible (i.e., measured with error), which the norm, researchers must choose from among 3 inadequate courses action: (a) know that assumption perfectly reliable violated but use ANCOVA anyway (and, most likely, report misleading results); (b) attempt to employ 1 several measurement error models understanding no has examined their relative performance...

Analyzing students' growth remains an important topic in educational research. Most recently, Diagnostic Classification Models (DCMs) have been used to track skill acquisition a longitudinal fashion, with the purpose provide estimate of learning trajectories terms change fine-grained skills overtime. Response time (RT), amount test taker spends considering and answering each item, has extensively studied testing environments as useful source information reflect individual response behavior...

The authors review the open source statistical package R. R allows researchers to implement techniques including linear modeling, and nonlinear multilevel factor principal component analysis, structural equation item reliability time series meta-analysis, among others. presents several advantages over other packages because it is updated on an ongoing basis, free, capable of creating high-quality graphics that are difficult create with packages, includes important simulation capabilities....

A classic topic in the fields of psychometrics and measurement has been impact number scale categories on test score reliability. This study builds previous research by further articulating relationship between item response theory (IRT) classical (CTT). Equations are presented for comparing reliability precision scores within CTT IRT frameworks. new results pertaining to relative (i.e., conditional standard error a given trait value) IRT, shed light conditions where total estimates more or...

In the absence of clear incentives, achievement tests may be subject to effect slipping where item response functions have upper asymptotes below one. Slipping reduces score precision for higher latent scores and distorts test developers’ understandings information. A multidimensional four-parameter normal ogive model was developed large-scale assessments applied dichotomous items 2011 National Assessment Educational Progress eighth-grade mathematics reading tests. The results suggest that...

We introduce the concept of differential prediction generalization in context college admissions testing. Specifically, we assess extent to which predicted first-year grade point average (GPA) based on high-school (HSGPA) and SAT scores depends a student’s ethnicity gender whether this difference varies across samples. compared 257,336 female 220,433 male students 339 samples, 29,734 Black 304,372 White 247 35,681 Hispanic 308,818 264 samples collected from 176 colleges universities between...

Exploratory cognitive diagnosis models (CDMs) estimate the Q matrix, which is a binary matrix that indicates attributes needed for affirmative responses to each item. Estimation of an important next step improving classifications and broadening application CDMs. Prior research primarily focused on exploratory version restrictive deterministic-input, noisy-and-gate model, develop methods more flexible We consider Bayesian estimating reduced reparameterized unified model (rRUM). show rRUM...

Previous research notes the importance of understanding racial/ethnic differential prediction college grades across multiple institutions. Institutional variation in selection indices is especially important given some states’ laws governing public institutions’ admissions decisions. This paper employed multilevel moderated regression to study 30 institutions and accuracy predicting for students different backgrounds. Several benefits models cross‐institutional studies were described...

Understanding the beliefs of preservice teachers is an important area to investigate in teacher education process. This article examines relationship between teachers’ pertaining diversity and urban schooling how these inclinations contribute a commitment teaching students. Canonical correlation analysis was used identify profiles who exhibited varying degrees interest teach schools. The statistical provides range positive negative attitudinal toward teaching. It examine benefit students...