The two-parameter logistic model
Fixing the c Parameter in the Three-Parameter Logistic Model
... item parameter estimation procedure using the maximum likelihood estimation method often was unsuccessful in obtaining converged estimates when the true c-parameter value was large (> ...c- ...
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Incorporation of expert beliefs in the two-parameter bayesian logistic dose response model
... - 29 - pharmacokinetic objectives generally prevail) then it would be important to assess its performance across a range of study design scenarios, including those in which informative priors based on expert beliefs may ...
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Parameter Estimation for the Continuous Time Stochastic Logistic Diffusion Model
... stochastic logistic diffusion model has been widely used in the field of social life, application of stochastic logistic diffusion model has been used in the field of applied economics [1] [2] ...
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COVARIATES AND SAMPLE SIZE EFFECTS ON PARAMETER ESTIMATION FOR BINARY LOGISTIC REGRESSION MODEL
... only two covariates and did not consider the issue of multicollinearity or imbalanced ...data. Logistic regression is still one of the most important generalized linear models as it is useful for ...
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Penalized Joint Maximum Likelihood Estimation Applied to Two Parameter Logistic Item Response Models
... a model that can predict well. Traditional linear and logistic regression methods have the advantage of producing parameter estimates with good statistical properties (unbiasedness and ...unbiased ...
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Experimental Design for Unbalanced Data Involving a Two level Logistic Model
... a two level logistic model without a ...Both parameter estimation and hypothesis testing on variance components is an active research area ...
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Identifying local dependence with a score test statistic based on the bifactor 2-parameter logistic model
... ( 7 ) and H −1 Θ ( η, ˜ η) ˜ is the inverse of the Hessian matrix (evaluated at η). It can be proved (see Buse, ˜ 1982 ) that like- lihood ratio, Wald, and score statistics are all asymptotically χ 2 distributed with ...
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VNM: An R Package for Finding Multiple-Objective Optimal Designs for the 4-Parameter Logistic Model
... a two-objective design problem ( Stigler 1971 ; Lauter 1974 ; Lee 1988 ; Dette 1992 ; Cook and Wong 1994 ; Huang and Wong 1998 ; Song and Wong 1999 ; Tsai and Zen 2004 ; Atkinson 2008 ; Leonov and Miller 2009 ; ...
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Liu-Type Logistic Estimators with Optimal Shrinkage Parameter
... Shukur ( 2012 ), and Inan and Erdogan ( 2013 ) are some exceptions. In the first two studies, the authors used some early defined ridge estimators in the logistic regression model. In the last one, ...
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Item response analysis on an examination in anesthesiology for medical students in Taiwan: A comparison of one- and two-parameter logistic models
... one-parameter logistic (1-PL) model, the so-called Rasch model, to provide useful infor- mation about test reliability and validity, item difficulty, and the ability of examinee in ...
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A two-stage bivariate logistic-Tobit model for the safety analysis of signalized intersections
... effects model were similar to those from the random parameter model, and that the negative binomial model with random effects is a useful programming tool for police enforcement in highway ...
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Fast Bayesian parameter estimation for stochastic logistic growth models
... of parameter values and standard deviations are used to describe variation of inferred ...RRTR model is the least representative with the largest amount of drift occurring at the saturation stage, a ...
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Bayesian Expectation-Maximization-Maximization: a latent-mixture-modeling-based Bayesian algorithm for the three-parameter logistic model
... We present results for the condition with 1000 examinees and 25 items in the next two sections. Since the other conditions were very similar, or something like this, these results of the second simulation study ...
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Two Phase Neural Network Model for Weather Forecast Along-with Logistic and Linear Regression
... Indeed, even in the inclination remedied case, the residuals attributes will act in the models which will initiate to have huge predisposition aim or means, demonstrating that there are indicators and with incorporation ...
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Estimation of Location (μ) and Scale (λ) for Two Parameter Half Logistic Pareto Distribution (HLPD) by Least Square Regression Method
... Keywords: Two parameter HLP distribution, median ranks method (Benard's approximation), Least Square method, Montecarlo ...to model such data, Aarset, ...
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Logistic Regression with Missing Covariates -- Parameter Estimation, Model Selection and Prediction
... for logistic regression with incomplete data, where the missing data is found anywhere in the ...for model selection using a criterion based on a penalized version of the observed-data ...for ...
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Levy subordinator model: A two parameter model of default dependency
... copula model and can easily be implemented within the framework of the existing ...copula model can itself be recast into this framework highlighting its ...The model can also be investigated ...
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Levy Subordinator Model: A Two Parameter Model of Default Dependency
... theory. Two classes of models arise naturally that are termed type-I and ...subordinator model based on the α = 1/2 stable subordinator called the L´ evy ...subordinator model is the possibility of ...
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Levy Subordinator Model: A Two Parameter Model of Default Dependency
... realistic model of default dependency needs to account for at least two risk factors, firm-specific and ...copula model has no identifiable support to either of ...a two parameter ...
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