Pages that link to "Item:Q4320761"

The following pages link to A class of pattern-mixture models for normal incomplete data (Q4320761):

Displaying 50 items.

• What is meant by ``missing at random''? (Q252766) (← links)
• Assessing nonresponse bias in a business survey: proxy pattern-mixture analysis for skewed data (Q262417) (← links)
• Bayesian latent pattern mixture models for handling attrition in panel studies with refreshment samples (Q288563) (← links)
• Bayesian modeling longitudinal dyadic data with nonignorable dropout, with application to a breast cancer study (Q439170) (← links)
• Analysis of NMAR missing data without specifying missing-data mechanisms in a linear latent variate model (Q549917) (← links)
• Missing data methods in longitudinal studies: a review (Q619079) (← links)
• Marginalizing pattern-mixture models for categorical data subject to monotone missingness (Q745343) (← links)
• Simultaneous modelling of the Cholesky decomposition of several covariance matrices (Q873623) (← links)
• Formal and informal model selection with incomplete data (Q900458) (← links)
• Estimation of the disease-specific diagnostic marker distribution under verification bias (Q961177) (← links)
• Nonignorable dropout models for longitudinal binary data with random effects: an application of Monte Carlo approximation through the Gibbs output (Q961962) (← links)
• A simulation study comparing weighted estimating equations with multiple imputation based estimating equations for longitudinal binary data (Q1023479) (← links)
• Maximum likelihood estimation of the correlation coefficient in a bivariate normal model with missing data (Q1265976) (← links)
• Likelihood based frequentist inference when data are missing at random (Q1400101) (← links)
• A hot deck imputation procedure for multiply imputing nonignorable missing data: the proxy pattern-mixture hot deck (Q1623754) (← links)
• Variable-based missing mechanism for an incomplete contingency table with unit missingness (Q1726850) (← links)
• Sensitivity analysis for incomplete continuous data (Q1761546) (← links)
• Bayesian approaches for missing not at random outcome data: the role of identifying restrictions (Q1799346) (← links)
• Missing at random, likelihood ignorability and model completeness. (Q1879953) (← links)
• A general model for two-level data with responses missing at random (Q1897121) (← links)
• Statistical modeling of longitudinal data with non-ignorable non-monotone missingness with semiparametric Bayesian and machine learning components (Q2040667) (← links)
• Modeling heterogeneity in the assessment of treatment effects on tumor development while accounting for monotone dropout (Q2089348) (← links)
• Assessing selection bias in regression coefficients estimated from nonprobability samples with applications to genetics and demographic surveys (Q2247506) (← links)
• Mixtures of semiparametric varying coefficient models for longitudinal data with nonignorable dropout (Q2267283) (← links)
• The indirect method: inference based on intermediate statistics -- a synthesis and examples (Q2503926) (← links)
• Empirical likelihood inference in mixtures of semiparametric varying coefficient EV models for longitudinal data with nonignorable dropout (Q2512583) (← links)
• A sensitivity analysis for shared-parameter models for incomplete longitudinal outcomes (Q2786156) (← links)
• Bayesian Nonparametrics for Missing Data in Longitudinal Clinical Trials (Q2800209) (← links)
• Bayesian informative dropout model for longitudinal binary data with random effects using conditional and joint modeling approaches (Q2806842) (← links)
• An EM Estimation Approach for Analyzing Bivariate Skew Normal Data with Non monotone Missing Values (Q3006293) (← links)
• Likelihood testing populations modeled by autoregressive process subject to the limit of detection in applications to longitudinal biomedical data (Q3019484) (← links)
• Alternative conditions for ignoring the process that causes missing data (Q3029988) (← links)
• Pattern-mixture models for categorical outcomes with non-monotone missingness (Q3070609) (← links)
• Methods for Conducting Sensitivity Analysis of Trials with Potentially Nonignorable Competing Causes of Censoring (Q3078688) (← links)
• A Pattern-Mixture Model for Longitudinal Binary Responses with Nonignorable Nonresponse (Q3079058) (← links)
• A joint model of binary and longitudinal data with non-ignorable missingness, with application to marital stress and late-life major depression in women (Q3179217) (← links)
• Varying-coefficient models for longitudinal processes with continuous-time informative dropout (Q3303588) (← links)
• A marginalized conditional linear model for longitudinal binary data when informative dropout occurs in continuous time (Q3303821) (← links)
• A Semiparametric Bayesian Approach to Dropout in Longitudinal Studies With Auxiliary Covariates (Q3391439) (← links)
• Mixtures of Varying Coefficient Models for Longitudinal Data with Discrete or Continuous Nonignorable Dropout (Q3445323) (← links)
• Direct likelihood inference and sensitivity analysis for competing risks regression with missing causes of failure (Q3459951) (← links)
• A General Class of Pattern Mixture Models for Nonignorable Dropout with Many Possible Dropout Times (Q3506504) (← links)
• Robust methods for generalized linear models with nonignorable missing covariates (Q3526431) (← links)
• Every Missingness not at Random Model Has a Missingness at Random Counterpart with Equal Fit (Q3541269) (← links)
• Mixed‐Effect Hybrid Models for Longitudinal Data with Nonignorable Dropout (Q3636993) (← links)
• PATTERN RECOGNITION OF LONGITUDINAL TRIAL DATA WITH NONIGNORABLE MISSINGNESS: AN EMPIRICAL CASE STUDY (Q3646194) (← links)
• A comparison of the random-effects pattern mixture model with last-observation-carried-forward(locf) analysis in longitudinal clinical trials with dropouts (Q4221313) (← links)
• Pseudo-Likelihood for Combined Selection and Pattern-Mixture Models for Incomplete Data (Q4224691) (← links)
• Pattern-mixture models with proper time dependence (Q4455390) (← links)
• Efficiency of lattice conditional independence models for multinormal samples with non-monotone missing data (Q4490170) (← links)