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Park, Jungkyu; Yu, Hsiu-Ting – Educational and Psychological Measurement, 2016
The multilevel latent class model (MLCM) is a multilevel extension of a latent class model (LCM) that is used to analyze nested structure data structure. The nonparametric version of an MLCM assumes a discrete latent variable at a higher-level nesting structure to account for the dependency among observations nested within a higher-level unit. In…
Descriptors: Hierarchical Linear Modeling, Nonparametric Statistics, Data Analysis, Simulation
Mortaz Hejri, Sara; Yazdani, Kamran; Labaf, Ali; Norcini, John J.; Jalili, Mohammad – Advances in Health Sciences Education, 2016
In a sequential OSCE which has been suggested to reduce testing costs, candidates take a short screening test and who fail the test, are asked to take the full OSCE. In order to introduce an effective and accurate sequential design, we developed a model for designing and evaluating screening OSCEs. Based on two datasets from a 10-station…
Descriptors: Models, Instructional Design, Sequential Approach, Medical Students
Poon, Brenda T.; Simmons, Noreen R. – Deafness & Education International, 2016
Population-based outcome monitoring could provide useful information about factors that differentially influence the developmental trajectories of deaf or hard-of-hearing children. A strong basis for population-based outcome monitoring is a coordinated, longitudinal data collection, and management infrastructure that includes quality local…
Descriptors: Foreign Countries, Early Intervention, Data Collection, Deafness
Dorie, Vincent; Harada, Masataka; Carnegie, Nicole Bohme; Hill, Jennifer – Grantee Submission, 2016
When estimating causal effects, unmeasured confounding and model misspecification are both potential sources of bias. We propose a method to simultaneously address both issues in the form of a semi-parametric sensitivity analysis. In particular, our approach incorporates Bayesian Additive Regression Trees into a two-parameter sensitivity analysis…
Descriptors: Bayesian Statistics, Mathematical Models, Causal Models, Statistical Bias
Sheybani, Elias; Zeraatpishe, Mitra – International Journal of Language Testing, 2018
Test method is deemed to affect test scores along with examinee ability (Bachman, 1996). In this research the role of method facet in reading comprehension tests is studied. Bachman divided method facet into five categories, one category is the nature of input and the nature of expected response. This study examined the role of method effect in…
Descriptors: Reading Comprehension, Reading Tests, Test Items, Test Format
Weller, Susan C. – Field Methods, 2015
This article presents a simple approach to making quick sample size estimates for basic hypothesis tests. Although there are many sources available for estimating sample sizes, methods are not often integrated across statistical tests, levels of measurement of variables, or effect sizes. A few parameters are required to estimate sample sizes and…
Descriptors: Sample Size, Statistical Analysis, Computation, Hypothesis Testing
Moeyaert, Mariola; Ugille, Maaike; Ferron, John M.; Onghena, Patrick; Heyvaert, Mieke; Beretvas, S. Natasha; Van den Noortgate, Wim – School Psychology Quarterly, 2015
The purpose of this study is to illustrate the multilevel meta-analysis of results from single-subject experimental designs of different types, including AB phase designs, multiple-baseline designs, ABAB reversal designs, and alternating treatment designs. Current methodological work on the meta-analysis of single-subject experimental designs…
Descriptors: Intervention, Multivariate Analysis, Meta Analysis, Research Design
Klausch, Thomas; Schouten, Barry; Hox, Joop J. – Sociological Methods & Research, 2017
This study evaluated three types of bias--total, measurement, and selection bias (SB)--in three sequential mixed-mode designs of the Dutch Crime Victimization Survey: telephone, mail, and web, where nonrespondents were followed up face-to-face (F2F). In the absence of true scores, all biases were estimated as mode effects against two different…
Descriptors: Evaluation Methods, Statistical Bias, Sequential Approach, Benchmarking
Ryan, Wendy L.; St. Iago-McRae, Ezry – Bioscene: Journal of College Biology Teaching, 2016
Experimentation is the foundation of science and an important process for students to understand and experience. However, it can be difficult to teach some aspects of experimentation within the time and resource constraints of an academic semester. Interactive models can be a useful tool in bridging this gap. This freely accessible simulation…
Descriptors: Research Design, Simulation, Animals, Animal Behavior
Finch, W. Holmes – Journal of Experimental Education, 2016
Multivariate analysis of variance (MANOVA) is widely used in educational research to compare means on multiple dependent variables across groups. Researchers faced with the problem of missing data often use multiple imputation of values in place of the missing observations. This study compares the performance of 2 methods for combining p values in…
Descriptors: Multivariate Analysis, Educational Research, Error of Measurement, Research Problems
Huang, Francis L. – Journal of Experimental Education, 2016
Multilevel modeling has grown in use over the years as a way to deal with the nonindependent nature of observations found in clustered data. However, other alternatives to multilevel modeling are available that can account for observations nested within clusters, including the use of Taylor series linearization for variance estimation, the design…
Descriptors: Multivariate Analysis, Hierarchical Linear Modeling, Sample Size, Error of Measurement
Koran, Jennifer – Measurement and Evaluation in Counseling and Development, 2016
Proactive preliminary minimum sample size determination can be useful for the early planning stages of a latent variable modeling study to set a realistic scope, long before the model and population are finalized. This study examined existing methods and proposed a new method for proactive preliminary minimum sample size determination.
Descriptors: Factor Analysis, Sample Size, Models, Sampling
Weiss, Michael J.; Lockwood, J. R.; McCaffrey, Daniel F. – Journal of Research on Educational Effectiveness, 2016
In the "individually randomized group treatment" (IRGT) experimental design, individuals are first randomly assigned to a treatment arm or a control arm, but then within each arm, are grouped together (e.g., within classrooms/schools, through shared case managers, in group therapy sessions, through shared doctors, etc.) to receive…
Descriptors: Randomized Controlled Trials, Error of Measurement, Control Groups, Experimental Groups
Devlieger, Ines; Mayer, Axel; Rosseel, Yves – Educational and Psychological Measurement, 2016
In this article, an overview is given of four methods to perform factor score regression (FSR), namely regression FSR, Bartlett FSR, the bias avoiding method of Skrondal and Laake, and the bias correcting method of Croon. The bias correcting method is extended to include a reliable standard error. The four methods are compared with each other and…
Descriptors: Regression (Statistics), Comparative Analysis, Structural Equation Models, Monte Carlo Methods
Sweet, Tracy M. – Educational Psychologist, 2016
Social networks are especially applicable in educational and psychological studies involving social interactions. A social network is defined as a specific relationship among a group of individuals. Social networks arise in a variety of situations such as friendships among children, collaboration and advice seeking among teachers, and coauthorship…
Descriptors: Social Networks, Interpersonal Relationship, Friendship, Teacher Collaboration