Multiple Imputation Approaches for Missing Time-to-Event Outcomes with Informative Censoring: Practical Considerations from a Simulation Study Based on Real Data by Andrea Bellavia, Min Guo, Sabina Murphy

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Comparison of different approaches in handling missing data in longitudinal multiple-item patient-reported outcomes: a simulation study by Minqian Yan, Lizhi Zhou, Chongye Zhao, Chen Shi, Chunquan Ou

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Investigation of the Multiple Imputation Method in Different Missing Ratios and Sample Sizes by Nesrin Alkan, B. Baris Alkan

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A Novel Aggregated Multiple Imputation Approach for Enhanced Survival Prediction and Classification on Breast Cancer and Lung Cancer Data by P. Deepa, C. Gunavathi

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Efficient Multiple Imputation for Diverse Data in Python and R: MIDASpy and rMIDAS by Ranjit Lall, Thomas Robinson

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Multiple imputation integrated to machine learning: predicting post-stroke recovery of ambulation after intensive inpatient rehabilitation by Alice Finocchi, Silvia Campagnini, Andrea Mannini, Stefano Doronzio, Marco Baccini, Bahia Hakiki, Donata Bardi, Antonello Grippo, Claudio Macchi, Jorge Navarro Solano, Michela Baccini, Francesca Cecchi

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Impact of Missing Data on Data Quality in Social Research by Yaroslav Kostenko

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Two-stage multiple imputation with a longitudinal composite variable by Xuzhi Wang, Martin G. Larson, Chunyu Liu

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Working with missing data in large-scale assessments by Francis Huang, Brian Keller

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Assessing the influence of socioeconomic and environmental variables on malaria risk in Nigerian children under 5 years: a GLMM approach by Talani Mhelembe, Shaun Ramroop, Faustin Habyarimana

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Uncovering environmental implications of historical stewardship of Japanese Moso Bamboo (Phyllostachys edulis) forests: a review using a multivariate imputation approach by Daniel Forster, Matthew Tom Harrison, Minaco Adachi

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A Data Imputation Strategy to Enhance Online Game Churn Prediction, Considering Non-Login Periods by JaeHong Lee, Pavinee Rerkjirattikal, SangGyu Nam

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Sensitivity analysis for time-to-event data accounting for intra-individual variability in time-varying covariates with missing data by Madiha Liaqat, Luciana Chiapella, Pradeep Mishra, Walid Emam, Yusra Tashkandy, Adelajda Matuka

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Handling missing data of using the XGBoost-based multiple imputation by chained equations regression method by Zhao Jinbo, Li Yufu, Mo Haitao

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Estimating Missing Panel Data with Regression and Multivariate Imputation by Chained Equations (MICE) by Budi Susetyo, Anwar Fitrianto

Subjects: “…missing data, panel data, imputation, regression, multiple imputation by chained equations…”
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How much missing data is too much to impute for longitudinal health indicators? A preliminary guideline for the choice of the extent of missing proportion to impute with multiple i... by K. P. Junaid, Tanvi Kiran, Madhu Gupta, Kamal Kishore, Sujata Siwatch

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Evaluating Performance of Missing Data Imputation Methods in IRT Analyses by Ömür Kaya Kalkan, Yusuf Kara, Hülya Kelecioğlu

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Biplot visualisations of the differences between multiple imputation techniques for simulated categorical data by Johané Nienkemper-Swanepoel

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Optimising dynamic treatment regimens using sequential multiple assignment randomised trials data with missing data by Jessica Xu, Anurika P. De Silva, Katherine J. Lee, Robert K. Mahar, Julie A. Simpson

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Handling of missing component information for common composite score outcomes used in axial spondyloarthritis research when complete-case analysis is unbiased by Christos Polysopoulos, Stylianos Georgiadis, Lykke Midtbøll Ørnbjerg, Almut Scherer, Daniela Di Giuseppe, Merete Lund Hetland, Michael John Nissen, Gareth T. Jones, Bente Glintborg, Anne Gitte Loft, Johan Karlsson Wallman, Karel Pavelka, Jakub Závada, Ayten Yazici, Maria José Santos, Adrian Ciurea, Burkhard Möller, Brigitte Michelsen, Pawel Mielnik, Johanna Huhtakangas, Heikki Relas, Katja Perdan Pirkmajer, Ziga Rotar, Ross MacDonald, Bjorn Gudbjornsson, Irene van der Horst-Bruinsma, Marleen van de Sande, Myriam Riek

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