IDEAS home Printed from https://ideas.repec.org/a/spr/psycho/v87y2022i2d10.1007_s11336-022-09850-0.html
   My bibliography  Save this article

Guest Editors’ Introduction to the Special Issue on Forecasting with Intensive Longitudinal Data

Author

Listed:
  • Peter F. Halpin

    (The University of North Carolina at Chapel Hill)

  • Kathleen Gates

    (University of North Carolina at Chapel Hill)

  • Siwei Liu

    (University of California at Davis)

Abstract

No abstract is available for this item.

Suggested Citation

  • Peter F. Halpin & Kathleen Gates & Siwei Liu, 2022. "Guest Editors’ Introduction to the Special Issue on Forecasting with Intensive Longitudinal Data," Psychometrika, Springer;The Psychometric Society, vol. 87(2), pages 373-375, June.
  • Handle: RePEc:spr:psycho:v:87:y:2022:i:2:d:10.1007_s11336-022-09850-0
    DOI: 10.1007/s11336-022-09850-0
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s11336-022-09850-0
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.

    File URL: https://libkey.io/10.1007/s11336-022-09850-0?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Sy-Miin Chow & Jungmin Lee & Abe D. Hofman & Han L. J. Maas & Dennis K. Pearl & Peter C. M. Molenaar, 2022. "Control Theory Forecasts of Optimal Training Dosage to Facilitate Children’s Arithmetic Learning in a Digital Educational Application," Psychometrika, Springer;The Psychometric Society, vol. 87(2), pages 559-592, June.
    2. Zachary F. Fisher & Younghoon Kim & Barbara L. Fredrickson & Vladas Pipiras, 2022. "Penalized Estimation and Forecasting of Multiple Subject Intensive Longitudinal Data," Psychometrika, Springer;The Psychometric Society, vol. 87(2), pages 1-29, June.
    3. Yanling Li & Zita Oravecz & Shuai Zhou & Yosef Bodovski & Ian J. Barnett & Guangqing Chi & Yuan Zhou & Naomi P. Friedman & Scott I. Vrieze & Sy-Miin Chow, 2022. "Bayesian Forecasting with a Regime-Switching Zero-Inflated Multilevel Poisson Regression Model: An Application to Adolescent Alcohol Use with Spatial Covariates," Psychometrika, Springer;The Psychometric Society, vol. 87(2), pages 376-402, June.
    4. Augustin Kelava & Pascal Kilian & Judith Glaesser & Samuel Merk & Holger Brandt, 2022. "Forecasting Intra-individual Changes of Affective States Taking into Account Inter-individual Differences Using Intensive Longitudinal Data from a University Student Dropout Study in Math," Psychometrika, Springer;The Psychometric Society, vol. 87(2), pages 533-558, June.
    5. Michael D. Hunter & Haya Fatimah & Marina A. Bornovalova, 2022. "Two Filtering Methods of Forecasting Linear and Nonlinear Dynamics of Intensive Longitudinal Data," Psychometrika, Springer;The Psychometric Society, vol. 87(2), pages 477-505, June.
    6. Michael D. Hunter & Haya Fatimah & Marina A. Bornovalova, 2022. "Erratum to: Two Filtering Methods of Forecasting Linear and Nonlinear Dynamics of Intensive Longitudinal Data," Psychometrika, Springer;The Psychometric Society, vol. 87(2), pages 797-797, June.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.

      More about this item

      Statistics

      Access and download statistics

      Corrections

      All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:psycho:v:87:y:2022:i:2:d:10.1007_s11336-022-09850-0. See general information about how to correct material in RePEc.

      If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

      If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

      If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

      For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

      Please note that corrections may take a couple of weeks to filter through the various RePEc services.

      IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.