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Paek, Insu; Wilson, Mark – Educational and Psychological Measurement, 2011
This study elaborates the Rasch differential item functioning (DIF) model formulation under the marginal maximum likelihood estimation context. Also, the Rasch DIF model performance was examined and compared with the Mantel-Haenszel (MH) procedure in small sample and short test length conditions through simulations. The theoretically known…
Descriptors: Test Bias, Test Length, Statistical Inference, Geometric Concepts
Wang, Tianyou – Journal of Educational and Behavioral Statistics, 2009
Holland and colleagues derived a formula for analytical standard error of equating using the delta-method for the kernel equating method. Extending their derivation, this article derives an analytical standard error of equating procedure for the conventional percentile rank-based equipercentile equating with log-linear smoothing. This procedure is…
Descriptors: Error of Measurement, Equated Scores, Statistical Analysis, Statistical Inference
Zhang, Guangjian; Browne, Michael W. – Multivariate Behavioral Research, 2010
Dynamic factor analysis summarizes changes in scores on a battery of manifest variables over repeated measurements in terms of a time series in a substantially smaller number of latent factors. Algebraic formulae for standard errors of parameter estimates are more difficult to obtain than in the usual intersubject factor analysis because of the…
Descriptors: Statistical Inference, Error of Measurement, Factor Analysis, Simulation
Savalei, Victoria; Bentler, Peter M. – Structural Equation Modeling: A Multidisciplinary Journal, 2009
A well-known ad-hoc approach to conducting structural equation modeling with missing data is to obtain a saturated maximum likelihood (ML) estimate of the population covariance matrix and then to use this estimate in the complete data ML fitting function to obtain parameter estimates. This 2-stage (TS) approach is appealing because it minimizes a…
Descriptors: Structural Equation Models, Data, Computation, Maximum Likelihood Statistics
Ramler, Ivan P.; Chapman, Jessica L. – Journal of Statistics Education, 2011
In this article we describe a semester-long project, based on the popular video game series Guitar Hero, designed to introduce upper-level undergraduate statistics students to statistical research. Some of the goals of this project are to help students develop statistical thinking that allows them to approach and answer open-ended research…
Descriptors: Video Games, Hypothesis Testing, Programming, Statistics
Larwin, Karen H.; Larwin, David A. – Journal of Education for Business, 2011
Bootstrapping methods and random distribution methods are increasingly recommended as better approaches for teaching students about statistical inference in introductory-level statistics courses. The authors examined the effect of teaching undergraduate business statistics students using random distribution and bootstrapping simulations. It is the…
Descriptors: Experimental Groups, Control Groups, Research Design, Grade Point Average
Choi, Sae Il – ProQuest LLC, 2009
This study used simulation (a) to compare the kernel equating method to traditional equipercentile equating methods under the equivalent-groups (EG) design and the nonequivalent-groups with anchor test (NEAT) design and (b) to apply the parametric bootstrap method for estimating standard errors of equating. A two-parameter logistic item response…
Descriptors: Item Response Theory, Comparative Analysis, Sampling, Statistical Inference
Chan, Wai – Educational and Psychological Measurement, 2009
A typical question in multiple regression analysis is to determine if a set of predictors gives the same degree of predictor power in two different populations. Olkin and Finn (1995) proposed two asymptotic-based methods for testing the equality of two population squared multiple correlations, [rho][superscript 2][subscript 1] and…
Descriptors: Multiple Regression Analysis, Intervals, Correlation, Computation
Azen, Razia; Traxel, Nicole – Journal of Educational and Behavioral Statistics, 2009
This article proposes an extension of dominance analysis that allows researchers to determine the relative importance of predictors in logistic regression models. Criteria for choosing logistic regression R[superscript 2] analogues were determined and measures were selected that can be used to perform dominance analysis in logistic regression. A…
Descriptors: Regression (Statistics), Predictor Variables, Measurement, Simulation
Cai, Chaoli – ProQuest LLC, 2009
Anomaly detection is an important and indispensable aspect of any computer security mechanism. Ad hoc and mobile networks consist of a number of peer mobile nodes that are capable of communicating with each other absent a fixed infrastructure. Arbitrary node movements and lack of centralized control make them vulnerable to a wide variety of…
Descriptors: Energy Conservation, Testing, Computer Security, Statistical Inference
Mulekar, Madhuri S.; Siegel, Murray H. – Mathematics Teacher, 2009
If students are to understand inferential statistics successfully, they must have a profound understanding of the nature of the sampling distribution. Specifically, they must comprehend the determination of the expected value and standard error of a sampling distribution as well as the meaning of the central limit theorem. Many students in a high…
Descriptors: Statistical Inference, Statistics, Sample Size, Error of Measurement
Fox, J.-P.; Wyrick, Cheryl – Journal of Educational and Behavioral Statistics, 2008
The randomized response technique ensures that individual item responses, denoted as true item responses, are randomized before observing them and so-called randomized item responses are observed. A relationship is specified between randomized item response data and true item response data. True item response data are modeled with a (non)linear…
Descriptors: Item Response Theory, Models, Markov Processes, Monte Carlo Methods
Peer reviewedHakstian, A. Ralph; Barchard, Kimberly A. – Multivariate Behavioral Research, 2000
Developed a sample-based nonanalytical degrees-of-freedom correction factor for situations sampling both subjects and conditions with measurement data departing from essentially parallel form. Assessed the application of this correction factor through a simulation study involving data sets with a range of design characteristics and manifesting…
Descriptors: Robustness (Statistics), Sampling, Simulation, Statistical Inference
Peer reviewedKlockars, Alan J.; Hancock, Gregory – Journal of Educational and Behavioral Statistics, 1997
The use of finite intersection tests (FIT) to unify methods for simultaneous inference and to test orthogonal contrasts is discussed. Multiple comparison procedures that combine FIT with sequential hypothesis testing are illustrated, and a simulation strategy is presented to generate values needed for FIT methods. (SLD)
Descriptors: Comparative Analysis, Hypothesis Testing, Simulation, Statistical Inference
Jo, Booil; Asparouhov, Tihomir; Muthen, Bengt O.; Ialongo, Nicholas S.; Brown, C. Hendricks – Psychological Methods, 2008
Cluster randomized trials (CRTs) have been widely used in field experiments treating a cluster of individuals as the unit of randomization. This study focused particularly on situations where CRTs are accompanied by a common complication, namely, treatment noncompliance or, more generally, intervention nonadherence. In CRTs, compliance may be…
Descriptors: Individual Characteristics, Intervention, Statistical Inference, Inferences

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