Tutorial on latent growth models for longitudinal data analysis

Binx Gu, Paul A. Pavlou

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

This tutorial introduces Latent Growth Modeling (LGM) as a promising new method for analyzing longitudinal data when interested in understanding the process of change over time. Given the need to go beyond cross-sectional models in IS research, explore complex longitudinal IS phenomena, and test Information Systems (IS) theories over time, LGM is proposed as a complementary method to help IS researchers propose time-dependent hypotheses and make longitudinal inferences about IS theories. The tutorial leader will explain the importance of theorizing patterns of change over time, how to propose longitudinal hypotheses, and how LGM can help test such hypotheses. All three tutorial facilitators will describe the tenets of LGM and offer guidelines for applying LGM in IS research including framing time-dependent hypotheses that can be readily tested with LGM. The three tutorial facilitators will also explain how to use LGM in SAS 9.2 with a hands-on application that will attempt to model the complex longitudinal relationship between IT and firm performance using longitudinal data from Fortune 1000 firms. The tutorial facilitators will also draw comparisons with other existing methods for modeling longitudinal data and they will also discuss the advantages and disadvantages of LGM for identifying longitudinal patterns in data.

Original languageEnglish (US)
Title of host publication16th Americas Conference on Information Systems 2010, AMCIS 2010
Pages1802-1806
Number of pages5
StatePublished - Dec 1 2010
Event16th Americas Conference on Information Systems 2010, AMCIS 2010 - Lima, Peru
Duration: Aug 12 2010Aug 15 2010

Publication series

Name16th Americas Conference on Information Systems 2010, AMCIS 2010
Volume3

Other

Other16th Americas Conference on Information Systems 2010, AMCIS 2010
CountryPeru
CityLima
Period8/12/108/15/10

ASJC Scopus subject areas

  • Computer Science Applications
  • Computer Networks and Communications
  • Information Systems
  • Library and Information Sciences

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  • Cite this

    Gu, B., & Pavlou, P. A. (2010). Tutorial on latent growth models for longitudinal data analysis. In 16th Americas Conference on Information Systems 2010, AMCIS 2010 (pp. 1802-1806). (16th Americas Conference on Information Systems 2010, AMCIS 2010; Vol. 3).