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Jamshidi, Laleh; Declercq, Lies; Fernández-Castilla, Belén; Ferron, John M.; Moeyaert, Mariola; Beretvas, S. Natasha; Van den Noortgate, Wim – Grantee Submission, 2020
The focus of the current study is on handling the dependence among multiple regression coefficients representing the treatment effects when meta-analyzing data from single-case experimental studies. We compare the results when applying three different multilevel meta-analytic models (i.e., a univariate multilevel model avoiding the dependence, a…
Descriptors: Multivariate Analysis, Hierarchical Linear Modeling, Meta Analysis, Regression (Statistics)
Sánchez, Damien M. – Educational Technology & Society, 2018
Civic engagement in the United States has increased since the election of President Trump. This increase is evident online as people are using Twitter to assert their digital citizenship by voicing their opinions regarding President Donald J. Trump and demonstrating solidarity with various civic movements. President Trump's election has caused…
Descriptors: Presidents, Citizen Participation, Content Analysis, Social Media
Manuel S. González Canché – AERA Open, 2023
Research has shown that mathematical proficiency gaps are related to students' and schools' indicators of poverty, with fewer studies on neighborhood effects on achievement gaps. Although this literature has accounted for students' nesting within schools, so far, methodological constraints have not allowed researchers to formally account for…
Descriptors: Mathematics Achievement, Achievement Gap, Educational Research, Regression (Statistics)
Campione-Barr, Nicole; Lindell, Anna K.; Giron, Sonia E. – Developmental Psychology, 2020
The use of differences scores to assess agreement/disagreement has a long and contentious history. Laird (2020) notes, however, that developmentalists have been particularly resistant to discontinue the use of difference scores. One area of developmental science where difference scores are still in regular use is that of parental differential…
Descriptors: Educational Research, Hypothesis Testing, Differences, Scores
Enders, Craig K.; Keller, Brian T.; Levy, Roy – Grantee Submission, 2018
Specialized imputation routines for multilevel data are widely available in software packages, but these methods are generally not equipped to handle a wide range of complexities that are typical of behavioral science data. In particular, existing imputation schemes differ in their ability to handle random slopes, categorical variables,…
Descriptors: Hierarchical Linear Modeling, Behavioral Science Research, Computer Software, Bayesian Statistics
Huang, Francis L. – Journal of Experimental Education, 2018
Studies analyzing clustered data sets using both multilevel models (MLMs) and ordinary least squares (OLS) regression have generally concluded that resulting point estimates, but not the standard errors, are comparable with each other. However, the accuracy of the estimates of OLS models is important to consider, as several alternative techniques…
Descriptors: Hierarchical Linear Modeling, Least Squares Statistics, Regression (Statistics), Comparative Analysis
Quesen, Sarah; Lane, Suzanne – Applied Measurement in Education, 2019
This study examined the effect of similar vs. dissimilar proficiency distributions on uniform DIF detection on a statewide eighth grade mathematics assessment. Results from the similar- and dissimilar-ability reference groups with an SWD focal group were compared for four models: logistic regression, hierarchical generalized linear model (HGLM),…
Descriptors: Test Items, Mathematics Tests, Grade 8, Item Response Theory
Rhoads, Christopher H.; Dye, Charles – Journal of Experimental Education, 2016
An important concern when planning research studies is to obtain maximum precision of an estimate of a treatment effect given a budget constraint. When research designs have a "multilevel" or "hierarchical" structure changes in sample size at different levels of the design will impact precision differently. Furthermore, there…
Descriptors: Research Design, Hierarchical Linear Modeling, Regression (Statistics), Sample Size
Munter, Charles; Correnti, Richard – American Journal of Education, 2017
This article provides a longitudinal examination of how changes in more than 200 middle-grades mathematics teachers' instructional practices related to their (a) mathematical knowledge for teaching (MKT) and (b) instructional vision. Results of this multilevel regression analysis suggest that MKT and instructional vision are related to instruction…
Descriptors: Mathematics Teachers, Middle School Teachers, Educational Practices, Educational Change
Daniel McNeish; Laura M. Stapleton; Rebecca D. Silverman – Grantee Submission, 2017
In psychology and the behavioral sciences generally, the use of the hierarchical linear model (HLM) and its extensions for discrete outcomes are popular methods for modeling clustered data. HLM and its discrete outcome extensions, however, are certainly not the only methods available to model clustered data. Although other methods exist and are…
Descriptors: Hierarchical Linear Modeling, Social Science Research, Multivariate Analysis, Error Patterns
Selig, James P.; Trott, Arianna; Lemberger, Matthew E. – Journal for Specialists in Group Work, 2017
Researchers in group counseling often encounter complex data from individual clients who are members of a group. Clients in the same group may be more similar than clients from different groups and this can lead to violations of statistical assumptions. The complexity of the data also means that predictors and outcomes can be measured at both the…
Descriptors: Group Counseling, Hierarchical Linear Modeling, Research, Client Characteristics (Human Services)
Lorah, Julie – Large-scale Assessments in Education, 2018
Effect size reporting is crucial for interpretation of applied research results and for conducting meta-analysis. However, clear guidelines for reporting effect size in multilevel models have not been provided. This report suggests and demonstrates appropriate effect size measures including the ICC for random effects and standardized regression…
Descriptors: Effect Size, Hierarchical Linear Modeling, Definitions, Regression (Statistics)
Kamienkowski, Juan E.; Carbajal, M. Julia; Bianchi, Bruno; Sigman, Mariano; Shalom, Diego E. – Discourse Processes: A multidisciplinary journal, 2018
When a word is read more than once, reading time generally decreases in the successive occurrences. This Repetition Effect has been used to study word encoding and memory processes in a variety of experimental measures. We studied naturally occurring repetitions of words within normal texts (stories of around 3,000 words). Using linear mixed…
Descriptors: Repetition, Eye Movements, Reading, Cognitive Processes
Chen, Jing; Lin, Tzu-Jung; Ku, Yu-Min; Zhang, Jie; O'Connell, Ann – Scientific Studies of Reading, 2018
Concept of word--the awareness of how words differ from nonwords or other linguistic properties--is important to learning to read Chinese because words in Chinese texts are not separated by space, and most characters can be productively compounded with other characters to form new words. The current study examined the effects of reader, word, and…
Descriptors: Vocabulary Development, Reading Comprehension, Chinese, Grade 5
Balfanz, Robert; Byrnes, Vaughan – Journal of Education for Students Placed at Risk, 2018
Following a 2008 report that documented the extent of chronic absenteeism in New York City's schools, the city organized an interagency task force to develop and implement a citywide effort to reduce chronic absenteeism. Given the size of the city school system and the scope of chronic absenteeism, the effort became the nation's most comprehensive…
Descriptors: Attendance, Urban Schools, Public Schools, Agency Cooperation