Global ETD Search
Search theses and dissertations gathered from participating repositories worldwide. Every result links back to the library that holds it. No account is needed.
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Showing 1 to 20 of 25 for “"Parameter recovery"”.
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Parameter recovery for transient signals
… This framework takes advantage of existing parameter modeling, identification, and recovery techniques to determine the decay rates while an alternating projection method utilizing the Discrete Transient Transform determines the amplitudes.
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INVESTIGATING MODEL SELECTION AND PARAMETER RECOVERY OF THE LATENT VARIABLE AUTOREGRESIVE LATENT TRAJECTORY (LV-ALT) MODEL FOR REPEATED MEASURES DATA: A MONTE CARLO SIMULATION STUDY
… have been developed which can reduce, through parameter constraints, to a variety of classical models. One such framework, the Autoregressive Latent Trajectory (ALT) model, is a combination of two classical approaches to longitudinal modeling: the autoregressive or simplex family, in which …
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Compatible whole-stand and diameter distribution models for loblolly pine plantations
… stand attributes from whole stand models, the k parameter of the pdf were estimated (recovered). Two types of parameter recovery models were constructed. The first used equations for the non-central moments of dbh. For the beta pdf, equations for the predicted first moment (average dbh) and …
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A comparison of traditional and IRT factor analysis.
This study investigated the item parameter recovery of two methods of factor analysis. The methods researched were a traditional factor analysis of tetrachoric correlation coefficients and an IRT approach to factor analysis which utilizes marginal maximum likelihood estimation using an EM algorithm …
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An investigation of a bivariate distribution approach to modeling diameter distributions at two points in time
… of diameter distribution prediction such as parameter recovery, percentile prediction, and parameter prediction. The approaches based on the growth equations are intuitively and biologically appealing in that the future distribution is determined from an initial distribution and a specified …
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Cognitive Diagnostic Model, a Simulated-Based Study: Understanding Compensatory Reparameterized Unified Model (CRUM)
… cognitive models, referred to as compensatory reparameterized unified model (CRUM) under the log-linear model family of CDM, was investigated. In order for practitioners to implement these models, their item parameter recovery and examinees' classifications need to be studied in detail. A series …
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Comparison of the Item Response Theory with Covariates Model and Explanatory Cognitive Diagnostic Model for Detecting and Explaining Differential Item Functioning
… used as the explanatory IRT model, while the reparameterized deterministic-input, noisy "and" gate (RDINA) model was used as the explanatory CDM (E-CDM). All released items were analyzed for DIF by both models with language status as the key grouping variable. Items that exhibited significant …
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A Comparison of Bayesian Estimation Techniques in a Multidimensional Two-Parameter Partial Credit Item Response Model
… Maximum Likelihood (MML) estimation method for parameter estimation in relatively simple item response models. However, extant literature is lacking on the investigation of Bayesian parameter estimation approaches for a multidimensional two parameter partial credit (M2PPC) model, therefore this …
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Assessing Robustness of the Rasch Mixture Model to Detect Differential Item Functioning - A Monte Carlo Simulation Study
… from two perspectives: latent class structure recovery and parameter recovery. One hundred replications per scenario were used for LC structure recovery and 200 replications per scenario were used for parameter recovery.</p> <p>The main and interactions effects of five manipulated factors on LC …
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A stand level multi-species growth model for Appalachian hardwoods
… distributions were obtained using the three-parameter Weibull probability density function and parameter recovery method. The recovery method used employed the first two non-central moments of dbh (arithmetic mean dbh and quadratic mean dbh squared) to generate Weibull parameters. Future …
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Examining the Impact of Examinee-Selected Constructed Response Items in the Context of a Hierarchical Rater Signal Detection Model
… to measure. While good examinee, item, and rater parameter recovery was apparent in the former condition for the HRM-SDT, serious issues with item and rater parameter estimation were apparent in the latter. Additional conditions were considered, as well as competing psychometric models for the …
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Using Robust Standard Errors to Combine Multiple Regression Estimates with Meta-Analysis
… for each of these approaches. Key meta-analytic parameters were varied throughout the process. Also, two small scale, examples were conducted to illustrate the use of the robust variance estimator in each of these two approaches. In general, the robust variance estimator performed well. Robust …
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A Bayesian Markov Chain Monte Carlo approach to the generalized graded unfolding model estimation: the future of non-cognitive measurement
… the traditional MML method, in terms of parameter estimation accuracy, parameter recovery with multidimensional data, and differential item function assessment for an ideal point response process. Implications of these findings and future research directions are discussed.
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Graphical models for student knowledge: Networks, parameters, and item selection
… example of model development and use. Third, recovery of network, item, and person parameters for tests based on graphical knowledge models is investigated via simulation to guide certain practical questions in field-testing and calibrating such models for educational assessments. Finally, …
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An Item Response Theory Approach to Causal Inference in the Presence of a Pre-intervention Assessment
… of Type I and Type II errors. Then the method's parameter recovery is analyzed followed by accuracy of treatment effect evaluation. The IRT method is shown to out perform existing methods in an ability-based scenario. Finally, the IRT method is applied to real data assessing the impact of …
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Localized Kernel Methods for Signal Processing
… using specially designed localized kernels for parameter recovery under noisy condition. The first method addresses the estimation of frequencies and amplitudes in multidimensional exponential models. It utilizes localized trigonometric polynomial kernels to detect the multivariate frequencies, …
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A comparison of forest growth and yield models for inventory updating
… were: a whole stand, a diameter distribution - parameter prediction, a diameter distribution - parameter prediction, and an individual tree. Three different validation approaches were used to create fitting and validation data sets from permanent plot remeasurement data, and evaluate each of the …
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Multilevel modeling of item position Effects
… response theory estimates of item and person parameters. This study examines the potentially biasing effects of item position. Previous work has approached position effects in testing from a variety of methodological perspectives, resulting in a variety of findings. This study presents a …
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Accounting for unpredictable spatial variability in plankton ecosystem models
… deterministically unpredictable may distort parameter estimates when the ecosystem model<br/>is fitted to (or assimilates) ocean data, may compromise model validation, and may produce<br/>mean-field ecosystem behaviour discrepant with that predicted by the model. New statistical<br/>methods …
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On the Use of Covariates in a Latent Class Signal Detection Model, with Applications to Constructed Response Scoring
… simulations were conducted to investigate both parameter recovery and classification accuracy of the extended model under two competing rater designs; in addition, implications of ignoring covariate effects and covariate misspecification were explored. Here, the ability of information criteria, …
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