BAMIFun provides Bayesian multiple imputation for functional data via low-rank penalized spline models, achieving accurate imputation and improved coverage in simulations and real datasets compared to single-imputation FPCA methods.
Statistical methods in medical research , volume=
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Multiple imputations for missing data in SHARELIFE Waves 3 and 7 were generated via fully conditional specification, with validity assessed against observed values, inverse propensity weighting, and external SHARE benchmarks.
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BAMIFun: Bayesian Multiple Imputation for Functional Data
BAMIFun provides Bayesian multiple imputation for functional data via low-rank penalized spline models, achieving accurate imputation and improved coverage in simulations and real datasets compared to single-imputation FPCA methods.
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SHARELIFE Imputations
Multiple imputations for missing data in SHARELIFE Waves 3 and 7 were generated via fully conditional specification, with validity assessed against observed values, inverse propensity weighting, and external SHARE benchmarks.