Pages that link to "Item:Q3685914"

The following pages link to Likelihood inference in a correlated probit regression model (Q3685914):

Displaying 34 items.

• Bivariate conditioning approximations for multivariate normal probabilities (Q261036) (← links)
• Estimation of the correlation coefficient in a bivariate probit model using the method of moments (Q374998) (← links)
• On the estimation of normal copula discrete regression models using the continuous extension and simulated likelihood (Q394097) (← links)
• Multivariate probit analysis of binary familial data using stochastic representations (Q425675) (← links)
• Analysis of proportions for clustered binary data in the presence of unequal dispersions (Q538152) (← links)
• Bayesian analysis of multivariate probit models with surrogate outcome data (Q603165) (← links)
• Correlated binomial regression models (Q693264) (← links)
• Comparison of correlated proportions based on paired binary data from clustered samples (Q730846) (← links)
• Fast computation of high-dimensional multivariate normal probabilities (Q901525) (← links)
• Modeling overdispersion with the normalized tempered stable distribution (Q901625) (← links)
• Bayesian analysis of correlated misclassified binary data (Q957287) (← links)
• Mixture analysis of multivariate categorical data with covariates and missing entries (Q1020201) (← links)
• Likelihood analysis of the multivariate ordinal probit regression model for repeated ordinal responses (Q1023685) (← links)
• Monte Carlo EM with importance reweighting and its applications in random effects models. (Q1285507) (← links)
• Regression models for correlated binary data with random effects assuming a mixture of normal distributions (Q1424628) (← links)
• Multivariate regression analysis of panel data with binary outcomes applied to unemployment data (Q1580843) (← links)
• Bayesian prediction of clipped Gaussian random fields. (Q1583194) (← links)
• Pairwise likelihood inference for the random effects probit model (Q1643013) (← links)
• The tilted beta-binomial distribution in overdispersed data: maximum likelihood and Bayesian estimation (Q2156010) (← links)
• Cluster randomized trials: considerations for design and analysis (Q2320981) (← links)
• Some new random effect models for correlated binary responses (Q2351196) (← links)
• Adaptive designs for selecting drug combinations based on efficacy-toxicity response (Q2475724) (← links)
• Local influence analysis of multivariate probit latent variable models (Q2507744) (← links)
• Updating beliefs for binary variables (Q2573516) (← links)
• Likelihood inference for correlated binary data without any information about the joint distributions (Q2978979) (← links)
• Measurement error caused by spatial misalignment in environmental epidemiology (Q3304958) (← links)
• Correlated Binary Variables and Multi‐level Probability Assessments (Q3608259) (← links)
• A Bayesian Method of Estimating Kappa Coefficient with Application to a Rheumatoid Arthritis Study (Q3652675) (← links)
• A probit model for multivariate random length ordinal data (Q4214011) (← links)
• Likelihood Models for Clustered Binary and Continuous Out comes: Application to Developmental Toxicology (Q4666642) (← links)
• On the influence of unknown covariate on the binary data (Q4843647) (← links)
• Simplex Factor Models for Multivariate Unordered Categorical Data (Q4916469) (← links)
• A Bayesian multivariate partially linear single-index probit model for ordinal responses (Q4960632) (← links)
• (Q4994210) (← links)