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Thoemmes, Felix; Liao, Wang; Jin, Ze – Journal of Educational and Behavioral Statistics, 2017
This article describes the analysis of regression-discontinuity designs (RDDs) using the R packages rdd, rdrobust, and rddtools. We discuss similarities and differences between these packages and provide directions on how to use them effectively. We use real data from the Carolina Abecedarian Project to show how an analysis of an RDD can be…
Descriptors: Regression (Statistics), Research Design, Robustness (Statistics), Computer Software
Luo, Haipeng – ProQuest LLC, 2016
Online learning is one of the most important and well-established machine learning models. Generally speaking, the goal of online learning is to make a sequence of accurate predictions "on the fly," given some information of the correct answers to previous prediction tasks. Online learning has been extensively studied in recent years,…
Descriptors: Online Courses, Prediction, Robustness (Statistics), Accuracy
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Anderson, Daniel; Kahn, Joshua D.; Tindal, Gerald – Applied Measurement in Education, 2017
Unidimensionality and local independence are two common assumptions of item response theory. The former implies that all items measure a common latent trait, while the latter implies that responses are independent, conditional on respondents' location on the latent trait. Yet, few tests are truly unidimensional. Unmodeled dimensions may result in…
Descriptors: Robustness (Statistics), Item Response Theory, Mathematics Tests, Grade 6
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Finch, Holmes – Psicologica: International Journal of Methodology and Experimental Psychology, 2017
Multilevel models (MLMs) have proven themselves to be very useful in social science research, as data from a variety of sources is sampled such that individuals at level-1 are nested within clusters such as schools, hospitals, counseling centers, and business entities at level-2. MLMs using restricted maximum likelihood estimation (REML) provide…
Descriptors: Hierarchical Linear Modeling, Comparative Analysis, Computation, Robustness (Statistics)
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Spencer, Neil H.; Lay, Margaret; Kevan de Lopez, Lindsey – International Journal of Social Research Methodology, 2017
When undertaking quantitative hypothesis testing, social researchers need to decide whether the data with which they are working is suitable for parametric analyses to be used. When considering the relevant assumptions they can examine graphs and summary statistics but the decision making process is subjective and must also take into account the…
Descriptors: Evaluation Methods, Decision Making, Hypothesis Testing, Social Science Research
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Putwain, David W.; Pescod, Marc – School Psychology Quarterly, 2018
The aim of the study was to conduct a randomized control trial of a targeted, facilitated, test anxiety intervention for a group of adolescent students, and to examine the mediating role of uncertain control. Fifty-six participants (male = 19, white = 21, mean age = 14.7 years) were randomly allocated to an early intervention or wait-list control…
Descriptors: Test Anxiety, Intervention, Secondary School Students, Randomized Controlled Trials
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Bi, Henry H. – Assessment & Evaluation in Higher Education, 2018
There are no absolute standards regarding what teaching evaluation ratings are satisfactory. It is also problematic to compare teaching evaluation ratings with the average or with a cutoff number to determine whether they are adequate. In this paper, we use average and standard deviation charts (X[overbar]-S charts), which are based on the theory…
Descriptors: Robustness (Statistics), Data Interpretation, Rating Scales, Computation
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Jerrim, John; Parker, Philip; Choi, Alvaro; Chmielewski, Anna Katyn; Sälzer, Christine; Shure, Nikki – Educational Measurement: Issues and Practice, 2018
The Programme for International Student Assessment (PISA) is an important international study of 15-olds' knowledge and skills. New results are released every 3 years, and have a substantial impact upon education policy. Yet, despite its influence, the methodology underpinning PISA has received significant criticism. Much of this criticism has…
Descriptors: Educational Assessment, Comparative Education, Achievement Tests, Foreign Countries
Peng Ding; Fan Li – Grantee Submission, 2018
Inferring causal effects of treatments is a central goal in many disciplines. The potential outcomes framework is a main statistical approach to causal inference, in which a causal effect is defined as a comparison of the potential outcomes of the same units under different treatment conditions. Because for each unit at most one of the potential…
Descriptors: Attribution Theory, Causal Models, Statistical Inference, Research Problems
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Tadesse, Tefera; Gillies, Robyn M. – Australian Journal of Career Development, 2017
This study examined a modified version of the Student Engagement Scale, as adopted from the Australasian Survey of Student Engagement. It did so through examining model fit, predictive validity of the engagement factor, and testing of score reliability and measurement invariance across colleges and class years. Participants were volunteer…
Descriptors: Foreign Countries, Learner Engagement, Measures (Individuals), Robustness (Statistics)
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
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Prinz, Anja; Golke, Stefanie; Wittwer, Jörg – Journal of Educational Psychology, 2019
Misconceptions impair not only learners' comprehension of a text but also the accuracy with which they judge their comprehension, that is, "metacomprehension accuracy." Refutation texts are beneficial to elicit conceptual-change processes and thus to overcome the detrimental impact of misconceptions on comprehension. However, it is…
Descriptors: Misconceptions, Accuracy, Metacognition, Reading Comprehension
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Belov, Dmitry I. – Journal of Educational Measurement, 2015
The statistical analysis of answer changes (ACs) has uncovered multiple testing irregularities on large-scale assessments and is now routinely performed at testing organizations. However, AC data has an uncertainty caused by technological or human factors. Therefore, existing statistics (e.g., number of wrong-to-right ACs) used to detect examinees…
Descriptors: Statistical Analysis, Robustness (Statistics), Identification, Test Items
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Talloen, Wouter; Moerkerke, Beatrijs; Loeys, Tom; De Naeghel, Jessie; Van Keer, Hilde; Vansteelandt, Stijn – Journal of Educational and Behavioral Statistics, 2016
To assess the direct and indirect effect of an intervention, multilevel 2-1-1 studies with intervention randomized at the upper (class) level and mediator and outcome measured at the lower (student) level are frequently used in educational research. In such studies, the mediation process may flow through the student-level mediator (the within…
Descriptors: Intervention, Hierarchical Linear Modeling, Computation, Randomized Controlled Trials
Oded Gurantz; Ryan Sakoda; Shayak Sarkar – Annenberg Institute for School Reform at Brown University, 2021
This paper examines how financial aid reform based on postsecondary institutional performance impacts student choice. Federal and state regulations often reflect concerns about the private, for-profit sector's poor employment outcomes and high loan defaults, despite the sector's possible theoretical advantages. We use student level data to examine…
Descriptors: State Aid, College Attendance, Student Financial Aid, Institutional Characteristics
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