Pages that link to "Item:Q989249"
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The following pages link to Latent class based multiple imputation approach for missing categorical data (Q989249):
Displaying 13 items.
- Divisive latent class modeling as a density estimation method for categorical data (Q318135) (← links)
- Incorporating marginal prior information in latent class models (Q516481) (← links)
- MIMCA: multiple imputation for categorical variables with multiple correspondence analysis (Q518262) (← links)
- Nonparametric estimation of a latent variable model (Q730430) (← links)
- Mixture analysis of multivariate categorical data with covariates and missing entries (Q1020201) (← links)
- Multiple imputation: a review of practical and theoretical findings (Q1799338) (← links)
- Handling missing data in item response theory. Assessing the accuracy of a multiple imputation procedure based on latent class analysis (Q2403306) (← links)
- Handling missing data in matched case-control studies using multiple imputation (Q2809549) (← links)
- Latent class regression: inference and estimation with two-stage multiple imputation (Q2857483) (← links)
- Prediction and Inference With Missing Data in Patient Alert Systems (Q3304829) (← links)
- Multiple imputation of longitudinal categorical data through bayesian mixture latent Markov models (Q5037018) (← links)
- An Empirical Comparison of Multiple Imputation Methods for Categorical Data (Q5885459) (← links)
- A latent class model to multiply impute missing treatment indicators in observational studies when inferences of the treatment effect are made using propensity score matching (Q6141305) (← links)
