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Longitudinal Data
Of the seven generally accepted criteria for life—homeostasis, metabolism, growth, adaptation, response to stimuli, reproduction and organisation—the...
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Longitudinal Methods in Youth Research Understanding Young Lives Across Time and Space
This book addresses how longitudinal research approaches are used to understand young people’s lives. It elucidates how youth researchers use...
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Big Longitudinal Data Analysis
In this chapter, we will present classical model-based approaches for time-series analysis, modern model-free strategies for forward prediction of...
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Longitudinal Sentiment Analysis with Conversation Textual Data
The inherent qualitative nature of textual data poses significant challenges for direct integration into statistical models. This paper presents a...
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Biclustering multivariate discrete longitudinal data
A model-based biclustering method for multivariate discrete longitudinal data is proposed. We consider a finite mixture of generalized linear models...
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Linear Mixed-Effects Models for Longitudinal Microbiome Data
Longitudinal microbiome data analysis can be categorized into two approaches: univariate longitudinal analysis and multivariate longitudinal...
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Asking—and answering—causal questions using longitudinal data
Despite a growing availability of longitudinal datasets, it can be difficult to select the most appropriate modelling strategy. In particular, there...
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Partial Linear Model Averaging Prediction for Longitudinal Data
Prediction plays an important role in data analysis. Model averaging method generally provides better prediction than using any of its components....
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Visualization of incrementally learned projection trajectories for longitudinal data
Longitudinal studies that continuously generate data enable the capture of temporal variations in experimentally observed parameters, facilitating...
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Longitudinal single-cell data informs deterministic modelling of inflammatory bowel disease
Single-cell-based methods such as flow cytometry or single-cell mRNA sequencing (scRNA-seq) allow deep molecular and cellular profiling of...
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Combining Data Collection Modes in Longitudinal Studies
Technological advances over the past two decades have substantially changed the range of data collection methods available to survey researchers....
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A wide range of missing imputation approaches in longitudinal data: a simulation study and real data analysis
BackgroundMissing data is a pervasive problem in longitudinal data analysis. Several single-imputation (SI) and multiple-imputation (MI) approaches...
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Cross-sectional data accurately model longitudinal growth in the craniofacial skeleton
Dense, longitudinal sampling represents the ideal for studying biological growth. However, longitudinal samples are not typically possible, due to...
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Flexible Bayesian semiparametric mixed-effects model for skewed longitudinal data
BackgroundIn clinical trials and epidemiological research, mixed-effects models are commonly used to examine population-level and subject-specific...
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Longitudinal Research Design
This chapter addresses longitudinal research designs’ peculiarities, characteristics, and significant fallacies. Longitudinal studies represent an...
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A comprehensive platform for analyzing longitudinal multi-omics data
Longitudinal bulk and single-cell omics data is increasingly generated for biological and clinical research but is challenging to analyze due to its...
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Generalized Linear Mixed Models for Longitudinal Microbiome Data
Chapter 16 investigated some general topics of generalized linear mixed-effects models (GLMMs). This chapter...
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Bayesian pattern-mixture models for dropout and intermittently missing data in longitudinal data analysis
Valid inference can be drawn from a random-effects model for repeated measures that are incomplete if whether the data are missing or not, known as...
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Detecting potential outliers in longitudinal data with time-dependent covariates
BackgroundOutliers can influence regression model parameters and change the direction of the estimated effect, over-estimating or under-estimating...
