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Showing 46 to 60 of 78 results Save | Export
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Austin, Peter C. – Multivariate Behavioral Research, 2011
Propensity score methods allow investigators to estimate causal treatment effects using observational or nonrandomized data. In this article we provide a practical illustration of the appropriate steps in conducting propensity score analyses. For illustrative purposes, we use a sample of current smokers who were discharged alive after being…
Descriptors: Smoking, Hospitals, Program Effectiveness, Probability
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Vallejo, G.; Fernandez, M. P.; Livacic-Rojas, P. E.; Tuero-Herrero, E. – Multivariate Behavioral Research, 2011
Missing data are a pervasive problem in many psychological applications in the real world. In this article we study the impact of dropout on the operational characteristics of several approaches that can be easily implemented with commercially available software. These approaches include the covariance pattern model based on an unstructured…
Descriptors: Personality Problems, Psychosis, Prevention, Patients
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Maydeu-Olivares, Alberto; Brown, Anna – Multivariate Behavioral Research, 2010
The comparative format used in ranking and paired comparisons tasks can significantly reduce the impact of uniform response biases typically associated with rating scales. Thurstone's (1927, 1931) model provides a powerful framework for modeling comparative data such as paired comparisons and rankings. Although Thurstonian models are generally…
Descriptors: Item Response Theory, Rating Scales, Models, Comparative Analysis
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Voelkle, Manuel C. – Multivariate Behavioral Research, 2008
The simultaneous estimation of autoregressive (simplex) structures and latent trajectories, so called ALT (autoregressive latent trajectory) models, is becoming an increasingly popular approach to the analysis of change. Although historically autoregressive (AR) and latent growth curve (LGC) models have been developed quite independently from each…
Descriptors: Simulation, Computation, Pattern Recognition, Skill Development
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Cham, Heining; West, Stephen G.; Ma, Yue; Aiken, Leona S. – Multivariate Behavioral Research, 2012
A Monte Carlo simulation was conducted to investigate the robustness of 4 latent variable interaction modeling approaches (Constrained Product Indicator [CPI], Generalized Appended Product Indicator [GAPI], Unconstrained Product Indicator [UPI], and Latent Moderated Structural Equations [LMS]) under high degrees of nonnormality of the observed…
Descriptors: Monte Carlo Methods, Computation, Robustness (Statistics), Structural Equation Models
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Steyn, H. S., Jr.; Ellis, S. M. – Multivariate Behavioral Research, 2009
When two or more univariate population means are compared, the proportion of variation in the dependent variable accounted for by population group membership is eta-squared. This effect size can be generalized by using multivariate measures of association, based on the multivariate analysis of variance (MANOVA) statistics, to establish whether…
Descriptors: Effect Size, Multivariate Analysis, Computation, Monte Carlo Methods
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Choi, Jaehwa; Fan, Weihua; Hancock, Gregory R. – Multivariate Behavioral Research, 2009
This note suggests delta method implementations for deriving confidence intervals for a latent mean effect size measure for the case of 2 independent populations. A hypothetical kindergarten reading example using these implementations is provided, as is supporting LISREL syntax. (Contains 1 table.)
Descriptors: Intervals, Syntax, Effect Size, Evaluation Methods
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Raykov, Tenko – Multivariate Behavioral Research, 2007
A method for point and interval estimation of change in criterion validity of multiple-component measuring instruments as a result of revision is outlined. The procedure is developed within the framework of covariance structure modeling, which complements earlier methods for testing change in composite reliability due to addition or deletion of…
Descriptors: Predictive Validity, Computation, Models, Reliability
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Levy, Roy; Hancock, Gregory R. – Multivariate Behavioral Research, 2007
Although statistical procedures are well-known for comparing hierarchically related (nested) mean and covariance structure models, statistical tests for comparing non-hierarchically related (nonnested) models have proven more elusive. Although isolated attempts at statistical tests of non-hierarchically related models have been made, none exist…
Descriptors: Computation, Statistical Analysis, Comparative Testing, Models
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Wanstrom, Linda – Multivariate Behavioral Research, 2009
Second-order latent growth curve models (S. C. Duncan & Duncan, 1996; McArdle, 1988) can be used to study group differences in change in latent constructs. We give exact formulas for the covariance matrix of the parameter estimates and an algebraic expression for the estimation of slope differences. Formulas for calculations of the required sample…
Descriptors: Sample Size, Effect Size, Mathematical Formulas, Computation
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Krishnamoorthy, K.; Xia, Yanping – Multivariate Behavioral Research, 2008
The problems of hypothesis testing and interval estimation of the squared multiple correlation coefficient of a multivariate normal distribution are considered. It is shown that available one-sided tests are uniformly most powerful, and the one-sided confidence intervals are uniformly most accurate. An exact method of calculating sample size to…
Descriptors: Statistical Analysis, Intervals, Sample Size, Testing
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Yuan, Ke-Hai; Lu, Laura – Multivariate Behavioral Research, 2008
This article provides the theory and application of the 2-stage maximum likelihood (ML) procedure for structural equation modeling (SEM) with missing data. The validity of this procedure does not require the assumption of a normally distributed population. When the population is normally distributed and all missing data are missing at random…
Descriptors: Structural Equation Models, Validity, Data Analysis, Computation
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Culpepper, Steven Andrew – Multivariate Behavioral Research, 2009
This study linked nonlinear profile analysis (NPA) of dichotomous responses with an existing family of item response theory models and generalized latent variable models (GLVM). The NPA method offers several benefits over previous internal profile analysis methods: (a) NPA is estimated with maximum likelihood in a GLVM framework rather than…
Descriptors: Profiles, Item Response Theory, Models, Maximum Likelihood Statistics
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Maydeu-Olivares, Alberto; Hernandez, Adolfo – Multivariate Behavioral Research, 2007
The interpretation of a Thurstonian model for paired comparisons where the utilities' covariance matrix is unrestricted proved to be difficult due to the comparative nature of the data. We show that under a suitable constraint the utilities' correlation matrix can be estimated, yielding a readily interpretable solution. This set of identification…
Descriptors: Identification, Structural Equation Models, Matrices, Comparative Analysis
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Schluchter, Mark D. – Multivariate Behavioral Research, 2008
In behavioral research, interest is often in examining the degree to which the effect of an independent variable X on an outcome Y is mediated by an intermediary or mediator variable M. This article illustrates how generalized estimating equations (GEE) modeling can be used to estimate the indirect or mediated effect, defined as the amount by…
Descriptors: Intervals, Predictor Variables, Equations (Mathematics), Computation
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