Literature DB >> 29881094

A Multilevel Multiset Time-Series Model for Describing Complex Developmental Processes.

Xin Ma1, Jianping Shen2.   

Abstract

The authors sought to develop an analytical platform where multiple sets of time series can be examined simultaneously. This multivariate platform capable of testing interaction effects among multiple sets of time series can be very useful in empirical research. The authors demonstrated that the multilevel framework can readily accommodate this analytical capacity. Given their intention to use the multilevel multiset time-series model to pursue complicated research purposes, their resulting model is relatively simple to specify, to run, and to interpret. These advantages make the adoption of their model relatively effortless as long as researchers have the basic knowledge and skills in working with multilevel growth modeling. With multiple potential extensions of their model, the establishment of this analytical platform for analysis of multiple sets of time series can inspire researchers to pursue far more advanced research designs to address complex developmental processes in reality.

Keywords:  achievement testing; assessment; multilevel models

Year:  2017        PMID: 29881094      PMCID: PMC5978585          DOI: 10.1177/0146621616686058

Source DB:  PubMed          Journal:  Appl Psychol Meas        ISSN: 0146-6216


  2 in total

Review 1.  Analyzing change: a primer on multilevel models with applications to nephrology.

Authors:  Jocelyn E Holden; Ken Kelley; Rajiv Agarwal
Journal:  Am J Nephrol       Date:  2008-05-10       Impact factor: 3.754

2.  Multilevel time series models with applications to repeated measures data.

Authors:  H Goldstein; M J Healy; J Rasbash
Journal:  Stat Med       Date:  1994-08-30       Impact factor: 2.373

  2 in total
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Review 1.  Emotion Regulation Flexibility and Electronic Patient-Reported Outcomes: A Framework for Understanding Symptoms and Affect Dynamics in Pediatric Psycho-Oncology.

Authors:  Kasra Mirzaie; Anna Burns-Gebhart; Marcel Meyerheim; Annette Sander; Norbert Graf
Journal:  Cancers (Basel)       Date:  2022-08-11       Impact factor: 6.575

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