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Vanhove, Jan – Studies in Second Language Learning and Teaching, 2015
I discuss three common practices that obfuscate or invalidate the statistical analysis of randomized controlled interventions in applied linguistics. These are (a) checking whether randomization produced groups that are balanced on a number of possibly relevant covariates, (b) using repeated measures ANOVA to analyze pretest-posttest designs, and…
Descriptors: Randomized Controlled Trials, Intervention, Applied Linguistics, Statistical Analysis
Baldwin, Scott A.; Bauer, Daniel J.; Stice, Eric; Rohde, Paul – Psychological Methods, 2011
Partially clustered designs, where clustering occurs in some conditions and not others, are common in psychology, particularly in prevention and intervention trials. This article reports results from a simulation comparing 5 approaches to analyzing partially clustered data, including Type I errors, parameter bias, efficiency, and power. Results…
Descriptors: Multivariate Analysis, Error of Measurement, Statistical Analysis, Statistical Bias
Cafri, Guy; Kromrey, Jeffrey D.; Brannick, Michael T. – Multivariate Behavioral Research, 2010
This article uses meta-analyses published in "Psychological Bulletin" from 1995 to 2005 to describe meta-analyses in psychology, including examination of statistical power, Type I errors resulting from multiple comparisons, and model choice. Retrospective power estimates indicated that univariate categorical and continuous moderators, individual…
Descriptors: Periodicals, Effect Size, Sampling, Psychology
Peugh, James L.; Enders, Craig K. – Structural Equation Modeling: A Multidisciplinary Journal, 2010
Cluster sampling results in response variable variation both among respondents (i.e., within-cluster or Level 1) and among clusters (i.e., between-cluster or Level 2). Properly modeling within- and between-cluster variation could be of substantive interest in numerous settings, but applied researchers typically test only within-cluster (i.e.,…
Descriptors: Structural Equation Models, Monte Carlo Methods, Multivariate Analysis, Sampling
Hong, Guanglei; Yu, Bing – Developmental Psychology, 2008
This study examines the effects of kindergarten retention on children's social-emotional development in the early, middle, and late elementary years. Previous studies have generated mixed results partly due to some major methodological challenges, including selection bias, measurement error, and divergent perceptions of multiple respondents in…
Descriptors: Comparative Analysis, Social Development, Error of Measurement, Kindergarten
Jarrell, Michele G. – 1991
A probability distribution was developed for the Andrews-Pregibon (AP) statistic. The statistic, developed by D. F. Andrews and D. Pregibon (1978), identifies multivariate outliers. It is a ratio of the determinant of the data matrix with an observation deleted to the determinant of the entire data matrix. Although the AP statistic has been used…
Descriptors: Computer Simulation, Error of Measurement, Matrices, Multivariate Analysis

Longford, Nicholas T. – Psychometrika, 1997
It is demonstrated that, in the presence of population information, a linear combination of true scores can be estimated more efficiently than by the same linear combination of the observed scores. Three criteria for optimality are discussed, but they yield the same solution, described as a multivariate shrinkage estimator. (Author/SLD)
Descriptors: Error of Measurement, Estimation (Mathematics), Multivariate Analysis, Population Distribution

Marcoulides, George A. – Educational and Psychological Measurement, 1995
A methodology is presented for minimizing the mean error variance-covariance component in studies with resource constraints. The method is illustrated using a one-facet multivariate design. Extensions to other designs are discussed. (SLD)
Descriptors: Budgets, Error of Measurement, Measurement Techniques, Multivariate Analysis

Jarrell, Michele Glankler – 1992
This repeated measures factorial design study compared the results of two procedures for identifying multivariate outliers under varying conditions, the Mahalanobis distance and the Andrews-Pregibon statistic. Results were analyzed for the total number of outliers identified and number of false outliers identified. Simulated data were limited to…
Descriptors: Comparative Analysis, Computer Simulation, Error of Measurement, Mathematical Models

Reddon, John R.; And Others – Journal of Educational Statistics, 1985
Computer sampling from a multivariate normal spherical population was used to evaluate the type one error rates for a test of sphericity based on the distribution of the determinant of the sample correlation matrix. (Author/LMO)
Descriptors: Computer Simulation, Correlation, Error of Measurement, Matrices

Moran, James D., III – Home Economics Research Journal, 1986
Describes the appropriate control of experiment-wise error rates and the researcher's role in making decisions to control for Type 1 errors. Issues related to level of significance, one- versus two-tailed tests, and the use of multivariate statistics are included. (Author/CT)
Descriptors: Decision Making, Error of Measurement, Multivariate Analysis, Research Methodology

MacKinnon, David P.; And Others – Multivariate Behavioral Research, 1995
Analytical solutions for point and variance estimators of the mediated effect, the ratio of mediated to direct effect, and the proportion of the total effect mediated were determined through simulation for different samples. The sample sizes needed for accuracy and stability are discussed with implications for mediated effects estimates. (SLD)
Descriptors: Equations (Mathematics), Error of Measurement, Estimation (Mathematics), Multivariate Analysis
Van den Noortgate, Wim; Opdenakker, Marie-Christine; Onghena, Patrick – School Effectiveness and School Improvement, 2005
Ignoring a level can have a substantial impact on the conclusions of a multilevel analysis. For intercept-only models and for balanced data, we derive these effects analytically. For more complex random intercept models or for unbalanced data, a simulation study is performed. Most important effects concern estimates and corresponding standard…
Descriptors: Simulation, Educational Research, Computation, Error of Measurement
Seco, Guillermo Vallejo; Izquierdo, Marcelino Cuesta; Garcia, M. Paula Fernandez; Diez, F. Javier Herrero – Educational and Psychological Measurement, 2006
The authors compare the operating characteristics of the bootstrap-F approach, a direct extension of the work of Berkovits, Hancock, and Nevitt, with Huynh's improved general approximation (IGA) and the Brown-Forsythe (BF) multivariate approach in a mixed repeated measures design when normality and multisample sphericity assumptions do not hold.…
Descriptors: Sample Size, Comparative Analysis, Simulation, Multivariate Analysis
Yin, Ping – Educational and Psychological Measurement, 2005
The main purpose of this study is to examine the content structure of the Multistate Bar Examination (MBE) using the "table of specifications" model from the perspective of multivariate generalizability theory. Specifically, using MBE data collected over different years (six administrations: three from the February test and three from July test),…
Descriptors: Correlation, Generalizability Theory, Statistical Analysis, Multivariate Analysis
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