Pages that link to "Item:Q4943407"
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The following pages link to Latent Variable Models with Mixed Continuous and Polytomous Data (Q4943407):
Displaying 31 items.
- Efficient direct sampling MCEM algorithm for latent variable models with binary responses (Q425378) (← links)
- Maximum likelihood estimation of nonlinear structural equation models (Q463093) (← links)
- Analysis of structural equation model with ignorable missing continuous and polytomous data (Q463099) (← links)
- Bayesian semiparametric analysis for latent variable models with mixed continuous and ordinal outcomes (Q530384) (← links)
- Assessing heterogeneity for factor analysis model with continuous and ordinal outcomes (Q670216) (← links)
- Semiparametric transformation models with Bayesian P-splines (Q693342) (← links)
- Latent variable models with ordinal categorical covariates (Q693350) (← links)
- Regression analysis of current status data with latent variables (Q825270) (← links)
- Latent variable mixed models with missing data (Q932496) (← links)
- Maximum likelihood estimation and model comparison of nonlinear structural equation models with continuous and polytomous variables (Q956739) (← links)
- On Bayesian estimation and model comparison of an integrated structural equation model (Q1023842) (← links)
- A Bayesian model selection method with applications (Q1614838) (← links)
- Variable assessment in latent class models (Q1623587) (← links)
- Latent single-index models for ordinal data (Q1703869) (← links)
- On the simulation size and the convergence of the Monte Carlo EM algorithm via likelihood-based distances (Q1771289) (← links)
- Mixture additive hazards cure model with latent variables: application to corporate default data (Q2072400) (← links)
- A Bayesian method for analyzing combinations of continuous, ordinal, and nominal categorical data with missing values (Q2256744) (← links)
- Model comparison of nonlinear structural equation models with fixed covariates (Q2259548) (← links)
- On local influence analysis of full information item factor models (Q2259876) (← links)
- A mixture of generalized latent variable models for mixed mode and heterogeneous data (Q2275642) (← links)
- A Bayesian modeling approach for generalized semiparametric structural equation models (Q2452349) (← links)
- Reducing measurement error in student achievement estimation (Q2517906) (← links)
- Selection of Latent Variables for Multiple Mixed-outcome Models (Q2932774) (← links)
- Markov and Semi-Markov Switching Linear Mixed Models Used to Identify Forest Tree Growth Components (Q3064263) (← links)
- Maximum Likelihood Estimation of Two-Level Latent Variable Models with Mixed Continuous and Polytomous Data (Q3078822) (← links)
- Maximum Likelihood Analysis of a General Latent Variable Model with Hierarchically Mixed Data (Q3445279) (← links)
- General mixed-data model: Extension of general location and grouped continuous models (Q3512632) (← links)
- Comparing Fits of Latent Trait and Latent Class Models Applied to Sparse Binary Data: An Illustration with Human Resource Management Data (Q3604094) (← links)
- Latent Variable Models in Heterogeneous Spaces for Observations of Mixed Types (Q5495083) (← links)
- Regression analysis of logistic model with latent variables (Q6629970) (← links)
- Bayesian analysis of two-part nonlinear latent variable model: semiparametric method (Q6669934) (← links)
