Missing Data, Speculative Reading by Rebecca Sutton Koeser, Zoe LeBlanc

“…We recast the problem of missing data as an opportunity and use a combination of time series forecasting, evolutionary models, and recommendation systems to estimate the extent of missing information and speculatively fill in some gaps. …”
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Weighted Kappa for Interobserver Agreement and Missing Data by Matthijs J. Warrens, Alexandra de Raadt, Roel J. Bosker, Henk A. L. Kiers

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A Probabilistic Approach for Missing Data Imputation by Muhammed Nazmul Arefin, Abdul Kadar Muhammad Masum

“…It often results in a higher incidence of missing data. So, addressing missing data through the imputation technique is essential to ensure the integrity and completeness of the data. …”
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Working with missing data in large-scale assessments by Francis Huang, Brian Keller

Subjects: “…Missing data…”
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Impact of Missing Data on Data Quality in Social Research by Yaroslav Kostenko

Subjects: “…missing data…”
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Modeling Missing Data in Distant Supervision for Information Extraction

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Hierarchical Missing Data and Multivariate Behrens–Fisher Problem by Jianqi Yu

“…Then multivariate Behrens–Fisher problem with hierarchical missing data is considered to illustrate that how ideas in dealing with monotone missing data can be extended to deal with hierarchical missing pattern. …”
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A comparison of various imputation algorithms for missing data. by Jürgen Kampf, Iryna Dykun, Tienush Rassaf, Amir Abbas Mahabadi

“…In this article we compare various imputation algorithms for missing data.<h4>Objectives</h4>We take the point of view that it has already been decided that the imputation should be carried out using multiple imputation by chained equation and the only decision left is that of a subroutine for the one-dimensional imputations. …”
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Advances in Biomedical Missing Data Imputation: A Survey by Miriam Barrabes, Maria Perera, Victor Novelle Moriano, Xavier Giro-I-Nieto, Daniel Mas Montserrat, Alexander G. Ioannidis

“…This survey paper provides a comprehensive overview of the extensive literature on missing data imputation techniques, with a specific focus on applications in genomics, single-cell RNA sequencing, health records, and medical imaging. …”
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KONVERGENSI ESTIMATOR DALAM MODEL MIXTURE BERBASIS MISSING DATA by N Dwidayati, SH Kartiko, Subanar -

“…Pada kajian ini, model mixture dikembangkan untuk  analisis cure rate berbasis missing data. Ada beberapa metode yang dapat digunakan untuk analisis <em>missing data. …”
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Parsimonious mixture of mean-mixture of normal distributions with missing data by Farzane Hashemi, Saeed Darijani

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Imputation for Missing Data in Statistical Matching Using Goal Programming by Abeer M. M. Elrefaey, Ramadan Hamed, Elham A. Ismail, Safia M. Ezzat

Subjects: “…missing data…”
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Reduction of artifacts associated with missing data in coherent diffractive imaging by Erik Malm, Yuriy Chushkin

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Cardiac disease diagnosis based on GAN in case of missing data. by Xing Chen, Na Zhang, Xiaohui Yang, Chunyan Wang, Qi Na, Tianyun Luan, Wendi Zhu, Chenjie Zhang, Chao Yang

“…To address the issue of discrete missing data in cardiac disease, this paper proposes the AGAN (Attribute Generative Adversarial Nets) architecture for missing data filling, based on generative adversarial networks. …”
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Missing data imputation of climate time series: A review by Lizette Elena Alejo-Sanchez, Aldo Márquez-Grajales, Fernando Salas-Martínez, Anilu Franco-Arcega, Virgilio López-Morales, Otilio Arturo Acevedo-Sandoval, César Abelardo González-Ramírez, Ramiro Villegas-Vega

Subjects: “…Imputation techniques for handling missing data…”
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Erratum: Machine-learning-based particle identification with missing data by Miłosz Kasak, Kamil Deja, Maja Karwowska, Monika Jakubowska, Łukasz Graczykowski, Małgorzata Janik

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Variational Autoencoding with Conditional Iterative Sampling for Missing Data Imputation by Shenfen Kuang, Jie Song, Shangjiu Wang, Huafeng Zhu

Subjects: “…missing data…”
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The impact of missing data rates and imputation methods on the assumption of unidimensionality. by Ayman Omar Baniamer

“…Statistical models are essential tools in data analysis. However, missing data plays a pivotal role in impacting the assumptions and effectiveness of statistical models, especially when there is a significant amount of missing data. …”
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Evaluating Performance of Missing Data Imputation Methods in IRT Analyses by Ömür Kaya Kalkan, Yusuf Kara, Hülya Kelecioğlu

Subjects: “…missing data…”
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Impute the missing data by combining retrieved dropouts and return to baseline method. by Xiaozhou Li, Zhenyu Yang, Chuanji Yuan, Jiaqing Liu, Zuojing Li

“…Currently, various methods have been proposed to handle missing data in clinical trials. Some methods assume that the missing data are missing at random (MAR), which means that it is assumed that subjects who stopped treatment would still maintain the treatment effect. …”
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