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Showing 1 to 20 of 74 for “"Covariance structure"”.
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A Finite Mixture Approach to Covariance Structure Modeling With Unknown, Heterogeneous Populations
"The field of covariance structure modeling has included models for heterogeneous populations for some time (e.g., Muthen, 1989), but to date none have incorporated methods that allow for heterogeneity when the population membership is unknown. The field of finite mixture analysis, however, …
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The role of sexual orientation in women's career choice: A covariance structure analysis
Women's career choices have historically been influenced by factors recognized as more complex than those that affect men. Some of these factors are: parenting; career orientation; holding profeminist values; and agentic personality characteristics.
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Examination of model uncertainty and parameter sensitivity in correlated systems using covariance structure analysis
… parameter sensitivity. In simple systems, model structure and uncertainty can be explained directly; however, uncertainty and parameter relationships in model structures of complex systems, such as process models and spatial models, are not usually straightforward. A common data examination …
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Performance of the Kenward-Project when the Covariance Structure is Selected Using AIC and BIC
… approach to such analyses requires choosing a covariance structure. Information criteria, such as AIC and BIC, are often used by statisticians to help with this task. However, these criteria do not always point to the true covariance structure and therefore the wrong covariance structure is …
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Testing the Measurement Invariance of Large-Scale Assessment of Foreign Language Proficiency Using Multiple Group Covariance Structure Analyses and Item Response Modeling
… of both simultaneous multiple group covariance structure analyses and item response theory (IRT) modeling as research paradigms, ultimately contributing to the validation of a standardized large-scale foreign language proficiency test for non-native speakers of English; Dimensionality …
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Performance of AIC-Selected Spatial Covariance Structures for fMRI Data
… observations, however selecting the correct covariance structure is difficult. Information criteria, such as AIC are often used to choose among covariance structures. Once the covariance structure is selected, significance tests can be used to determine if a region of interest within the …
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A Comparative Simulation Study of Robust Estimators of Standard Errors
… One approach is to carefully model the covariance structure. Another approach is robust estimation. In this approach, the covariance structure is estimated from the data. White (1980) introduced a biased, but consistent, robust estimator. Long et al. (2000) added an adjustment factor to …
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Contributions to the theory of generalized inverses, the linear model and outliers
… the imposition of constraints, when the variance-covariance structure is σ².I. Hypothesis-test statistics for non-estimable functions are shown to give no further information than underlying estimable functions. For an arbitrary variance-covariance structure the "sweep-out" method is …
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Canonical Correlation Analysis for Longitudinal Data
… data when the data have a Kronecker product covariance structure. Using structured correlation matrices we model the dependency of repeatedly observed data. Recent work of Srivastava, Nahtman, and von Rosen (2008) developed an iterative algorithm to determine the maximum likelihood estimate …
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Thinning of point processes-covariance analyses
… two point processes by some rule. We obtain the covariance structure between the thinned processes under various thinning rules. We first obtain this structure for independent Bernoulli thinning of an arbitrary point process. We show that if the point process is a renewal (stationary or ordinary) …
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Accurate estimation of risk when constructing efficient portfolios for the capital asset pricing model
… Asset Pricing Model (Sharpe CAPM) when the covariance structure of the residuals is correlated under the Markowitz formulation. By building in the dynamic time series models: AR, GARCH and AR/GARCH we were able to model the autocorrelation and heteroskedasticity of the residuals.
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Canonical Variate Analysis and Related Methods with Longitudinal Data
… is a widely used method for analyzing group structure in multivariate data. It is mathematically equivalent to a one-way multivariate analysis of variance and often goes by the name of canonical discriminant analysis. Change over time is a central feature of many phenomena of interest to …
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Assessing Measurement Equivalence of the English and Spanish Versions on an Employee Attitude Survey Using Multigroup Analysis in Structural Equation Modeling.
The study utilized the covariance structure comparison methodology - Multigroup Analysis in Structural Equation Modeling - evaluating measurement equivalence of English and Spanish versions of an employee opinion survey. The concept of measurement equivalence was defined as consisting of four …
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Invariance Properties of Statistical Tests for Dependent Observations
… study the problem of characterizing the class of covariance structures such that the distributions of the popular test statistics remain invariant, that is, they remain the same except for a constant factor. We first obtain some simple extensions and variations of the well known Cauchy-Schwarz …
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Essays in Empirical Asset Pricing and International Finance
… market-specific influences, while the variance-covariance structure accounts for common and idiosyncratic shocks, each governed by an independent Markov-switching process. Contagion or decoupling is defined as occurring when a high-volatility idiosyncratic shock originating in one market …
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Three essays on econometrics
… identified nuisance parameters and general covariance structure. The result of Guggenberger et al (2012) in case of homoskedasticity is shown to break down when general covariance structure is allowed. I provide a thorough simulation results to show that the break-down of the result can be …
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Construction and Analysis of Linear Trend-Free Factorial Designs Under a General Cost Structure
… trend-free designs for factorial treatment structures such that estimates of main effects and two-factor interactions are trend-free. In addition to trend-freeness we incorporate a general cost structure and propose methods of constructing optimal or near-optimal full or fractional factorial …
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Theoretical and Applied Essays on the Instrumental Variable Method
… data generation process. This reveals the covariance structure of the error terms of the usual theory-driven instrumental variable model. The revealed covariance structure of the IV model have important implications, particularly, for designing simulation studies. Monte Carlo simulations …
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A Model to Predict 24-Hour Urinary Creatinine Level Using Repeated Measurements
… creatinine using the Mixed Model methodology. A covariance structure, that permitted multiple observations for any one individual to be correlated, was identified and utilized. The predictive capabilities of this model were then compared to the earlier models investigated.
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Evolutionary dynamics of avian and non-avian limb morphology
Variation of phenotypic traits and covariance among them strongly controls the strength and direction of natural selection. These patterns are characterized as phenotypic covariance structure: the degree to which traits vary in coordinated fashion. The quantitative analysis of covariance structure, …
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