MAMI: An R-package which performs model selection/averaging on multiply imputed datasets and combines the resulting estimates. The package also provides access to less frequently used model averaging techniques and offers integrated bootstrap estimation.
Keywords for this software
References in zbMATH (referenced in 7 articles )
Showing results 1 to 7 of 7.
- Kabaila, Paul; Welsh, A. H.; Wijethunga, Christeen: Finite sample properties of confidence intervals centered on a model averaged estimator (2020)
- Schomaker, Michael; Heumann, Christian: When and when not to use optimal model averaging (2020)
- Liu, Lin; Qiu, Yuqi; Natarajan, Loki; Messer, Karen: Imputation and post-selection inference in models with missing data: an application to colorectal cancer surveillance guidelines (2019)
- Wang, Hai Ying; Chen, Xinjie; Flournoy, Nancy: The focused information criterion for varying-coefficient partially linear measurement error models (2016)
- Wan, Y.; Datta, S.; Conklin, D. J.; Kong, M.: Variable selection models based on multiple imputation with an application for predicting median effective dose and maximum effect (2015)
- Costa, D. R.; Lachos, V. H.; Bazan, J. L.; Azevedo, C. L. N.: Estimation methods for multivariate tobit confirmatory factor analysis (2014)
- Schomaker, Michael; Heumann, Christian: Model selection and model averaging after multiple imputation (2014)