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Bonefeld, Meike; Kleen, Hannah; Glock, Sabine – Journal of Experimental Education, 2022
Two experimental studies investigated the disadvantages faced by female ethnic minority students when they are judged by pre- and inservice teachers. The results suggest that (preservice) teachers' judgments were affected by the judgment dimension. Study 1 revealed that teachers apply gender stereotypes in their judgments on mathematical ability:…
Descriptors: Females, Minority Group Students, Preservice Teachers, Sex Stereotypes
Kim, Yeo-eun; Yu, Shirley L.; Koenka, Alison C.; Lee, Hyewon; Heckler, Andrew F. – Journal of Experimental Education, 2022
Students' cost perceptions have been associated with lower retention and academic performance in science, technology, engineering, and mathematics (STEM). Guided by expectancy-value theory, we examined whether relations between perceived costs and physics outcomes (i.e., engagement and achievement) varied as a function of self-efficacy or task…
Descriptors: STEM Education, Physics, Undergraduate Students, Student Attitudes
Liu, Yixing; Thompson, Marilyn S. – Journal of Experimental Education, 2022
A simulation study was conducted to explore the impact of differential item functioning (DIF) on general factor difference estimation for bifactor, ordinal data. Common analysis misspecifications in which the generated bifactor data with DIF were fitted using models with equality constraints on noninvariant item parameters were compared under data…
Descriptors: Comparative Analysis, Item Analysis, Sample Size, Error of Measurement
Kara, Yusuf; Kamata, Akihito – Journal of Experimental Education, 2022
Within-cluster variance homogeneity is one of the key assumptions of multilevel models; however, assuming a constant (i.e. equal) within-cluster variance may not be realistic. Moreover, existent within-cluster variance heterogeneity should be regarded as a source of additional information rather than a violation of a model assumption. This study…
Descriptors: Bayesian Statistics, Hierarchical Linear Modeling, Item Response Theory, Multivariate Analysis
Baek, Eunkyeng; Luo, Wen; Henri, Maria – Journal of Experimental Education, 2022
It is common to include multiple dependent variables (DVs) in single-case experimental design (SCED) meta-analyses. However, statistical issues associated with multiple DVs in the multilevel modeling approach (i.e., possible dependency of error, heterogeneous treatment effects, and heterogeneous error structures) have not been fully investigated.…
Descriptors: Meta Analysis, Hierarchical Linear Modeling, Comparative Analysis, Statistical Inference
Paulsen, Justin; Valdivia, Dubravka Svetina – Journal of Experimental Education, 2022
Cognitive diagnostic models (CDMs) are a family of psychometric models designed to provide categorical classifications for multiple latent attributes. CDMs provide more granular evidence than other psychometric models and have potential for guiding teaching and learning decisions in the classroom. However, CDMs have primarily been conducted using…
Descriptors: Psychometrics, Classification, Teaching Methods, Learning Processes
Aloe, Ariel M.; Thompson, Christopher G.; Liu, Zhijiang; Lin, Lifeng – Journal of Experimental Education, 2022
The distribution of the standardized mean difference is well understood. However, in many situations, researchers need to estimate an effect size to represent the relationship between a continuous outcome and a dichotomous grouping variable, adjusting for the effect of a covariate (or a set of covariates). Typically, this adjustment takes place…
Descriptors: Effect Size, Meta Analysis, Quasiexperimental Design, Regression (Statistics)
Lavrijsen, Jeroen; Ramos, Alicia; Verschueren, Karine – Journal of Experimental Education, 2022
Beliefs about academic functioning play an important role in the academic development of students. This study considers perceptions about underachievement, that is, the degree to which accomplishments are believed to be in line with potential. In particular, we examined why these perceptions might deviate from measured underachievement, determined…
Descriptors: Identification, Underachievement, Student Attitudes, Parent Attitudes
Shero, Jeffrey A.; Al Otaiba, Stephanie; Schatschneider, Chris; Hart, Sara A. – Journal of Experimental Education, 2022
Many of the analytical models commonly used in educational research often aim to maximize explained variance and identify variable importance within models. These models are useful for understanding general ideas and trends, but give limited insight into the individuals within said models. Data envelopment analysis (DEA), is a method rooted in…
Descriptors: Data Analysis, Educational Research, Nonparametric Statistics, Efficiency
Zhang, Zhonghua – Journal of Experimental Education, 2022
Reporting standard errors of equating has been advocated as a standard practice when conducting test equating. The two most widely applied procedures for standard errors of equating including the bootstrap method and the delta method are either computationally intensive or confined to the derivations of complicated formulas. In the current study,…
Descriptors: Error of Measurement, Item Response Theory, True Scores, Equated Scores
Chan, Wendy; Hedges, Larry V.; Hedberg, E. C. – Journal of Experimental Education, 2022
Many experimental designs in educational and behavioral research involve at least one level of clustering. Clustering affects the precision of estimators and its impact on statistics in cross-sectional studies is well known. Clustering also occurs in longitudinal designs where students that are initially grouped may be regrouped in the following…
Descriptors: Educational Research, Multivariate Analysis, Longitudinal Studies, Effect Size
Glaman, Ryan; Chen, Qi; Henson, Robin K. – Journal of Experimental Education, 2022
This study compared three approaches for handling a fourth level of nesting when analyzing cluster-randomized trial (CRT) data. Although CRT data analyses may include repeated measures, individual, and cluster levels, there may be an additional fourth level that is typically ignored. This study examined the impact of ignoring this fourth level,…
Descriptors: Randomized Controlled Trials, Hierarchical Linear Modeling, Data Analysis, Simulation
Shen, Zuchao; Kelcey, Benjamin – Journal of Experimental Education, 2022
Optimal design of multisite randomized trials leverages sampling costs to optimize sampling ratios and ultimately identify more efficient and powerful designs. Past implementations of the optimal design framework have assumed that costs of sampling units are equal across treatment conditions. In this study, we developed a more flexible optimal…
Descriptors: Randomized Controlled Trials, Sampling, Research Design, Statistical Analysis
Kush, Joseph M.; Konold, Timothy R.; Bradshaw, Catherine P. – Journal of Experimental Education, 2022
In two-level designs, the total sample is a function of both the number of Level 2 clusters and the average number of Level 1 units per cluster. Traditional multilevel power calculations rely on either the arithmetic average or the harmonic mean when estimating the average number of Level 1 units across clusters of unbalanced size. The current…
Descriptors: Multivariate Analysis, Randomized Controlled Trials, Monte Carlo Methods, Sample Size
Petzel, Zachary W.; Casad, Bettina J. – Journal of Experimental Education, 2022
The present research examined how risk-taking protects against consequences of negative gender stereotypes among women in science, technology, engineering, and mathematics (STEM). In Study 1, undergraduate women and men in STEM (N = 1013) took an online survey assessing risk-taking, academic outcomes, and vulnerability to stereotype threat.…
Descriptors: STEM Education, Sex Stereotypes, Negative Attitudes, Risk