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Comparing adaptive treatment strategies in two-stage randomized trials with grouped survival data. [PDF]

Lifetime Data Anal
Sparkman M, Halabi S, Li Z.
europepmc   +1 more source

Adaptive lateral constraint-driven POCS interpolation method. [PDF]

Sci Rep
Qin Z, Pan S, Chen J, Wang W, Chen Y.
europepmc   +1 more source

A hybrid random forest model for stroke risk prediction. [PDF]

Front Neurol
Lu Q, Li S, Xu H, Shen H, Wei Y.
europepmc   +1 more source

Machine learning for missing data imputation in Alzheimer's research: predicting medial temporal lobe dynamic flexibility. [PDF]

Cogn Neurodyn
Moallemian S, Saghafi A, Deshpande R, Perez JM, Budak M, Fausto BA, Elahi FM, Gluck MA.   +7 more
europepmc   +1 more source

Coherent cross-modal generation of synthetic biomedical data to advance multimodal precision medicine. [PDF]

PLoS Comput Biol
Marchesi R, Lazzaro N, Endrizzi W, Leonardi G, Pozzi M, Ragni F, Bovo S, Moroni M, Osmani V, Jurman G.   +9 more
europepmc   +1 more source

Missing Value Imputation With Adversarial Random Forests-MissARF. [PDF]

Stat Med
Golchian P, Kapar J, Watson DS, Wright MN.   +3 more
europepmc   +1 more source

Missing Values in Empirical Research: Theory and Practice. Part 39 of a Series on the Evaluation of Scientific Publications. [PDF]

Dtsch Arztebl Int
Schaefer E, Lang A, Piedboeuf-Potyka K, Kuss O.   +3 more
europepmc   +1 more source

Semiparametric Inference for Nonmonotone Missing-Not-at-Random Data: The No Self-Censoring Model [PDF]

Journal of the American Statistical Association, 2022
Daniel Malinsky, Ilya Shpitser, Eric J Tchetgen Tchetgen   +2 more
exaly   +2 more sources

Handling Complex Missing Data Using Random Forest Approach for an Air Quality Monitoring Dataset: A Case Study of Kuwait Environmental Data (2012 to 2018) [PDF]

International Journal of Environmental Research and Public Health, 2021
Ahmad Alsaber, Jiazhu Pan
exaly   +2 more sources

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The randomized marker method for single-case randomization tests: Handling data missing at random and data missing not at random

Behavior Research Methods, 2022
Single-case experiments are frequently plagued by missing data problems. In a recent study, the randomized marker method was found to be valid and powerful for single-case randomization tests when the missing data were missing completely at random.
Tamal Kumar De, Patrick Onghena
openaire   +2 more sources