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Showing 1 to 15 of 18 results Save | Export
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Harari, Ofir; Soltanifar, Mohsen; Cappelleri, Joseph C.; Verhoek, Andre; Ouwens, Mario; Daly, Caitlin; Heeg, Bart – Research Synthesis Methods, 2023
Effect modification (EM) may cause bias in network meta-analysis (NMA). Existing population adjustment NMA methods use individual patient data to adjust for EM but disregard available subgroup information from aggregated data in the evidence network. Additionally, these methods often rely on the shared effect modification (SEM) assumption. In this…
Descriptors: Networks, Network Analysis, Meta Analysis, Evaluation Methods
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Liang, Xinya – Educational and Psychological Measurement, 2020
Bayesian structural equation modeling (BSEM) is a flexible tool for the exploration and estimation of sparse factor loading structures; that is, most cross-loading entries are zero and only a few important cross-loadings are nonzero. The current investigation was focused on the BSEM with small-variance normal distribution priors (BSEM-N) for both…
Descriptors: Factor Structure, Bayesian Statistics, Structural Equation Models, Goodness of Fit
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Raykov, Tenko; Al-Qataee, Abdullah A.; Dimitrov, Dimiter M. – Educational and Psychological Measurement, 2020
A procedure for evaluation of validity related coefficients and their differences is discussed, which is applicable when one or more frequently used assumptions in empirical educational, behavioral and social research are violated. The method is developed within the framework of the latent variable modeling methodology and accomplishes point and…
Descriptors: Validity, Evaluation Methods, Social Science Research, Correlation
Xinran Li; Peng Ding – Grantee Submission, 2018
Frequentists' inference often delivers point estimators associated with confidence intervals or sets for parameters of interest. Constructing the confidence intervals or sets requires understanding the sampling distributions of the point estimators, which, in many but not all cases, are related to asymptotic Normal distributions ensured by central…
Descriptors: Correlation, Intervals, Sampling, Evaluation Methods
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Stamey, James D.; Beavers, Daniel P.; Sherr, Michael E. – Sociological Methods & Research, 2017
Survey data are often subject to various types of errors such as misclassification. In this article, we consider a model where interest is simultaneously in two correlated response variables and one is potentially subject to misclassification. A motivating example of a recent study of the impact of a sexual education course for adolescents is…
Descriptors: Bayesian Statistics, Classification, Models, Correlation
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Li, Xin; Beretvas, S. Natasha – Structural Equation Modeling: A Multidisciplinary Journal, 2013
This simulation study investigated use of the multilevel structural equation model (MLSEM) for handling measurement error in both mediator and outcome variables ("M" and "Y") in an upper level multilevel mediation model. Mediation and outcome variable indicators were generated with measurement error. Parameter and standard…
Descriptors: Sample Size, Structural Equation Models, Simulation, Multivariate Analysis
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Robertson, Clare; Ramsay, Craig; Gurung, Tara; Mowatt, Graham; Pickard, Robert; Sharma, Pawana – Research Synthesis Methods, 2014
We describe our experience of using a modified version of the Cochrane risk of bias (RoB) tool for randomised and non-randomised comparative studies. Objectives: (1) To assess time to complete RoB assessment; (2) To assess inter-rater agreement; and (3) To explore the association between RoB and treatment effect size. Methods: Cochrane risk of…
Descriptors: Risk, Randomized Controlled Trials, Research Design, Comparative Analysis
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Gu, Fei; Skorupski, William P.; Hoyle, Larry; Kingston, Neal M. – Applied Psychological Measurement, 2011
Ramsay-curve item response theory (RC-IRT) is a nonparametric procedure that estimates the latent trait using splines, and no distributional assumption about the latent trait is required. For item parameters of the two-parameter logistic (2-PL), three-parameter logistic (3-PL), and polytomous IRT models, RC-IRT can provide more accurate estimates…
Descriptors: Intervals, Item Response Theory, Models, Evaluation Methods
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Sass, Daniel A. – Educational and Psychological Measurement, 2010
Exploratory factor analysis (EFA) is commonly employed to evaluate the factor structure of measures with dichotomously scored items. Generally, only the estimated factor loadings are provided with no reference to significance tests, confidence intervals, and/or estimated factor loading standard errors. This simulation study assessed factor loading…
Descriptors: Intervals, Simulation, Factor Structure, Hypothesis Testing
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Lee, Chun-Ting; Zhang, Guangjian; Edwards, Michael C. – Multivariate Behavioral Research, 2012
Exploratory factor analysis (EFA) is often conducted with ordinal data (e.g., items with 5-point responses) in the social and behavioral sciences. These ordinal variables are often treated as if they were continuous in practice. An alternative strategy is to assume that a normally distributed continuous variable underlies each ordinal variable.…
Descriptors: Personality Traits, Intervals, Monte Carlo Methods, Factor Analysis
Feng, Xingdong – ProQuest LLC, 2009
Probe-level microarray data are usually stored in matrices. Take a given probe set (gene), for example, each row of the matrix corresponds to an array, and each column corresponds to a probe. Often, people summarize each array by the gene expression level. Is one number sufficient to summarize a whole probe set for a specific gene in an array?…
Descriptors: Intervals, Computation, Genetics, Data Analysis
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El Marroun, Hanan; Tiemeier, Henning; Steegers, Eric A. P.; Jaddoe, Vincent W. V.; Hofman, Albert; Verhulst, Frank C.; van den Brink, Wim; Huizink, Anja C. – Journal of the American Academy of Child & Adolescent Psychiatry, 2009
Objective: Cannabis is the most commonly consumed illicit drug among pregnant women. Intrauterine exposure to cannabis may result in risks for the developing fetus. The importance of intrauterine growth on subsequent psychological and behavioral child development has been demonstrated. This study examined the relation between maternal cannabis use…
Descriptors: Body Weight, Intervals, Marijuana, Pregnancy
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Bavin, Edith L.; Grayden, David B.; Scott, Kim; Stefanakis, Toni – Language and Speech, 2010
Infants' auditory processing abilities have been shown to predict subsequent language development. In addition, poor auditory processing skills have been shown for some individuals with specific language impairment. Methods used in infant studies are not appropriate for use with young children, and neither are methods typically used to test…
Descriptors: Intervals, Speech Impairments, Testing, Young Children
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Raykov, Tenko; Mels, Gerhard – Structural Equation Modeling: A Multidisciplinary Journal, 2009
A readily implemented procedure is discussed for interval estimation of indexes of interrelationship between items from multiple-component measuring instruments as well as between items and total composite scores. The method is applicable with categorical (ordinal) observed variables, and can be widely used in the process of scale construction,…
Descriptors: Intervals, Structural Equation Models, Biomedicine, Correlation
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Soreni, Noam; Crosbie, Jennifer; Ickowicz, Abel; Schachar, Russell – Journal of Attention Disorders, 2009
Objective: To measure test-retest reliability of the Stop-Signal Task (SST) and the Conners' Continuous Performance Test (CPT) in children with ADHD. Methods: 12 children with ADHD (age 11.46 plus or minus 1.66) participated in the study. Primary outcome measures were stop-signal reaction time (SSRT) for the SST and CPT's commission errors (%FP).…
Descriptors: Intervals, Reaction Time, Performance Tests, Attention Deficit Disorders
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