ArticleThe R journal2019
What's for dynr: A Package for Linear and Nonlinear Dynamic Modeling in R.
Article in The R journal, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 30 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
30 citing papers in PubMed.
- Dynamic physiology-behavior association patterns in child welfare parents predict response to parenting intervention.Journal of consulting and clinical psychology · 2025Trial
- Detecting Critical Change in Dynamics Through Outlier Detection with Time-Varying Parameters.The British journal of mathematical and statistical psychology · 2026Article
- A multilevel Ornstein-Uhlenbeck process with individual- and variable-specific estimates as random effects.The British journal of mathematical and statistical psychology · 2026Article
- An investigation into in-sample and out-of-sample model selection for nonstationary autoregressive models.The British journal of mathematical and statistical psychology · 2026Article
- Modelling non-linear psychological processes: Reviewing and evaluating non-parametric approaches and their applicability to intensive longitudinal data.The British journal of mathematical and statistical psychology · 2026Review
- Modeling qualitative between-person heterogeneity in time series using latent class vector autoregressive models.Behavior research methods · 2025Article
- Viewing social isolation as a complex dynamical system: A theoretical and computational framework.NPP - digital psychiatry and neuroscience · 2025Article
- Affect dynamics in adolescent depression: Are all equilibria worth returning to?Emotion (Washington, D.C.) · 2025Article
- Accommodating Continuous Time Metrics within the Discrete-time Latent Change Score Model Using Definition Variables.Structural equation modeling : a multidisciplinary journal · 2025Article
- Unsupervised Model Construction in Continuous-Time.Structural equation modeling : a multidisciplinary journal · 2025Article
- Do engagement and behavioural mechanisms underpin the effectiveness of the Drink Less app?NPJ digital medicine · 2024Article
- Estimation of nonlinear mixed-effects continuous-time models using the continuous-discrete extended Kalman filter.The British journal of mathematical and statistical psychology · 2023Article
- Dynamic regulatory processes among child welfare parents: Temporal associations between physiology and parenting behavior.Development and psychopathology · 2023Article
- The ILHBN: challenges, opportunities, and solutions from harmonizing data under heterogeneous study designs, target populations, and measurement protocols.Translational behavioral medicine · 2023Article
- Conceptualizing and Examining Change in Communication Research.Communication methods and measures · 2023Article
- Fifty years of structural equation modeling: A history of generalization, unification, and diffusion.Social science research · 2022Article
- Two Filtering Methods of Forecasting Linear and Nonlinear Dynamics of Intensive Longitudinal Data.Psychometrika · 2022Article
- Control Theory Forecasts of Optimal Training Dosage to Facilitate Children's Arithmetic Learning in a Digital Educational Application.Psychometrika · 2022Article
- Individualized learning potential in stressful times: How to leverage intensive longitudinal data to inform online learning.Computers in human behavior · 2021Article
- Investigating the impact of the time interval selection on autoregressive mediation modeling: Result interpretations, effect reporting, and temporal designs.Psychological methods · 2020Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
Abstract
Intensive longitudinal data in the behavioral sciences are often noisy, multivariate in nature, and may involve multiple units undergoing regime switches by showing discontinuities interspersed with continuous dynamics. Despite increasing interest in using linear and nonlinear differential/difference equation models with regime switches, there has been a scarcity of software packages that are fast and freely accessible. We have created an R package called
Identifiers
What OpenQuestion holds
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.