ArticleWorld academy of science, engineering and technology2019
dynr.mi: An R Program for Multiple Imputation in Dynamic Modeling.
Article in World academy of science, engineering and technology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.
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Who cites it
17 citing papers in PubMed.
- An investigation into in-sample and out-of-sample model selection for nonstationary autoregressive models.The British journal of mathematical and statistical psychology · 2026Article
- Machine learning for risk prediction of acute kidney injury in patients with diabetes mellitus combined with heart failure during hospitalization.Scientific reports · 2025Article
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- Healthy Mom Zone Adaptive Intervention With a Novel Control System and Digital Platform to Manage Gestational Weight Gain in Pregnant Women With Overweight or Obesity: Study Design and Protocol for a Randomized Controlled Trial.JMIR research protocols · 2025Article
- Anion gap associated with 28-days all-cause mortality in Acute cholangitis patients admitted to the intensive care unit in MIMIC-IV database: a retrospective cohort study.Frontiers in medicine · 2025Article
- A Growth of Hierarchical Autoregression Model for Capturing Individual Differences in Changes of Dynamic Characteristics of Psychological Processes.Structural equation modeling : a multidisciplinary journal · 2025Article
- Arthritis increases the risk of erectile dysfunction: Results from the NHANES 2001-2004.Frontiers in endocrinology · 2024Article
- Multiple imputation of missing data in multilevel ecological momentary assessments: an example using smoking cessation study data.Frontiers in digital health · 2023Article
- Different Machine Learning Approaches for Implementing Telehealth-Based Cancer Pain Management Strategies.Journal of clinical medicine · 2022Article
- Bayesian Forecasting with a Regime-Switching Zero-Inflated Multilevel Poisson Regression Model: An Application to Adolescent Alcohol Use with Spatial Covariates.Psychometrika · 2022Article
- Two Filtering Methods of Forecasting Linear and Nonlinear Dynamics of Intensive Longitudinal Data.Psychometrika · 2022Article
- Fitting Multilevel Vector Autoregressive Models in Stan, JAGS, and Mplus.Structural equation modeling : a multidisciplinary journal · 2022Article
- Daily associations among craving, affect, and social interactions in the lives of patients during residential opioid use disorder treatment.Psychology of addictive behaviors : journal of the Society of Psychologists in Addictive Behaviors · 2021Article
- Capturing emotion coherence in daily life: Using ambulatory physiology measures and ecological momentary assessments to examine within-person associations and individual differences.Biological psychology · 2021Review
- Development and validation of a novel 15-CpG-based signature for predicting prognosis in triple-negative breast cancer.Journal of cellular and molecular medicine · 2020Article
- Multilevel Latent Differential Structural Equation Model with Short Time Series and Time-Varying Covariates: A Comparison of Frequentist and Bayesian Estimators.Multivariate behavioral researchArticle
- Multiple Imputation with Factor Scores: A Practical Approach for Handling Simultaneous Missingness Across Items in Longitudinal Designs.Multivariate behavioral researchArticle
Corrections and comments
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Authors and funding
6 authors.
Funding
Abstract
Assessing several individuals intensively over time yields intensive longitudinal data (ILD). Even though ILD provide rich information, they also bring other data analytic challenges. One of these is the increased occurrence of missingness with increased study length, possibly under non-ignorable missingness scenarios. Multiple imputation (MI) handles missing data by creating several imputed data sets, and pooling the estimation results across imputed data sets to yield final estimates for inferential purposes. In this article, we introduce dynr.mi(), a function in the
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.