Robust likelihood-based analysis of multivariate data with missing values

Mathematics

• Missing Values 84%
• Multivariate Data 78%
• Model-based 63%
• Likelihood 61%
• Prediction 56%
• Propensity Score 48%
• Penalized Splines 48%
• Model Misspecification 44%
• Missing at Random 43%
• Relative Efficiency 42%
• Parametric Model 37%
• Missing Data 36%
• Covariates 29%
• Monotone 27%
• Regression 27%
• Simulation 22%
• Range of data 21%

Business & Economics

• Missing Values 100%
• Inference 58%
• Prediction 57%
• Splines 46%
• Missing Data 45%
• Model Misspecification 44%
• Propensity Score 44%
• Parametric Model 42%
• Relative Efficiency 37%
• Covariates 35%
• Simulation 23%