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Shi, Xin; Prevett, Pauline; Farnsworth, Valerie; Kwong, Koo Chun; Wan, Wanggen; He, Feng; Zhai, Qingqing; Zhen, Lu – Journal of Financial Counseling and Planning, 2019
This study develops a general method for modeling changes in response to items relating to students perceptions of personal finance and financial products. The new method is illustrated to analyze data from a sample of 1,250 students aged 16-18 who participated in a financial capability education study in the UK. We demonstrate how a quantitative…
Descriptors: Money Management, Literacy, Student Attitudes, Program Effectiveness
Leth-Steensen, Craig; Gallitto, Elena – Educational and Psychological Measurement, 2016
A large number of approaches have been proposed for estimating and testing the significance of indirect effects in mediation models. In this study, four sets of Monte Carlo simulations involving full latent variable structural equation models were run in order to contrast the effectiveness of the currently popular bias-corrected bootstrapping…
Descriptors: Mediation Theory, Structural Equation Models, Monte Carlo Methods, Simulation
Corlu, M. Sencer – International Review of Education, 2014
There are two mainstream curricula for international school students at the junior high level: the International Baccalaureate (IB) Middle Years Programme (MYP) and the Cambridge International General Certificate of Secondary Education (IGCSE). The former was developed in the mid-1990s and is currently being relaunched in a 21st-century approach.…
Descriptors: Advanced Placement Programs, Junior High School Students, International Schools, Educational Change
Dong, Nianbo – American Journal of Evaluation, 2015
Researchers have become increasingly interested in programs' main and interaction effects of two variables (A and B, e.g., two treatment variables or one treatment variable and one moderator) on outcomes. A challenge for estimating main and interaction effects is to eliminate selection bias across A-by-B groups. I introduce Rubin's causal model to…
Descriptors: Probability, Statistical Analysis, Research Design, Causal Models
Not Quite Normal: Consequences of Violating the Assumption of Normality in Regression Mixture Models
Van Horn, M. Lee; Smith, Jessalyn; Fagan, Abigail A.; Jaki, Thomas; Feaster, Daniel J.; Masyn, Katherine; Hawkins, J. David; Howe, George – Structural Equation Modeling: A Multidisciplinary Journal, 2012
Regression mixture models, which have only recently begun to be used in applied research, are a new approach for finding differential effects. This approach comes at the cost of the assumption that error terms are normally distributed within classes. This study uses Monte Carlo simulations to explore the effects of relatively minor violations of…
Descriptors: Structural Equation Models, Home Management, Drug Abuse, Research Methodology
Harvill, Eleanor L.; Peck, Laura R.; Bell, Stephen H. – American Journal of Evaluation, 2013
Using exogenous characteristics to identify endogenous subgroups, the approach discussed in this method note creates symmetric subsets within treatment and control groups, allowing the analysis to take advantage of an experimental design. In order to maintain treatment--control symmetry, however, prior work has posited that it is necessary to use…
Descriptors: Experimental Groups, Control Groups, Research Design, Sampling
Goldschmidt, Pete; Choi, Kilchan; Martinez, Felipe – US Department of Education, 2004
Monitoring school performance increasingly uses sophisticated analytical techniques. This document investigates whether one such method, hierarchical growth modeling, yields consistent school performance results when different metrics are used as the outcome variable. It is examined as to whether statistical and substantive inferences are altered…
Descriptors: Educational Research, Models, Data Analysis, Academic Achievement
Rose, Andrew M.; And Others – 1985
This third of three volumes reports on analytic procedures conducted to address various aspects of the scalar properties of the Device Effectiveness Forecasting Technique (DEFT). DEFT, a series of microcomputer programs applied to data gathered from rating scales, is used to evaluate simulator devices used in U.S. Army weapons training. The…
Descriptors: Adults, Computer Oriented Programs, Computer Simulation, Data Interpretation