lcsm: An R package and tutorial on latent change score modelling

Wellcome Open Research

article

Milan Wiedemann¹  Graham Thew¹  Urška Košir¹  Anke Ehlers¹ 

[1] Department of Experimental Psychology, University of Oxford;Oxford Health NHS Foundation Trust;Oxford University Hospitals NHS Foundation Trust

关键词: latent change score modelling;    structural equation modelling;    longitudinal data analysis;    lavaan;    R;   

DOI  :  10.12688/wellcomeopenres.17536.1

学科分类：内科医学

来源: Wellcome

【 摘 要 】

Latent change score models (LCSMs) are used across disciplines in behavioural sciences to study how constructs change over time. LCSMs can be used to estimate the trajectory of one construct (univariate) and allow the investigation of how changes between two constructs (bivariate) are associated with each other over time. This paper introduces the R package lcsm, a tool that aims to help users understand, analyse, and visualise different latent change score models. The lcsm package provides functions to generate model syntax for basic univariate and bivariate latent change score models with different model specifications. It is also possible to visualise different model specifications in simplified path diagrams. An interactive application illustrates the main functions of the package and demonstrates how the model syntax and path diagrams change based on different model specifications. This R package aims to increase the transparency of reporting analyses and to provide an additional resource to learn latent change score modelling.

【 授权许可】

CC BY