Latent growth modeling in is research: Basic tenets, illustration, and practical guidelines completed research paper

Paul A. Pavlou, Eric Zheng, Bin Gu

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

1 Citation (Scopus)

Abstract

This paper introduces Latent Growth Modeling (LGM) as a feasible method for analyzing longitudinal data to understand the process of change over time. Given the need to go beyond cross-sectional models, explore longitudinal Information Systems (IS) phenomena, and test IS theories over time, LGM is proposed as a complementary method to help IS researchers propose and evaluate time-centric hypotheses and make longitudinal inferences. The paper first describes the basic tenets of LGM and offers guidelines for using LGM in IS research, including framing hypotheses with time as a central component and implementing LGM models to test these hypotheses. The application of LGM in IS research is illustrated by modeling the longitudinal relationship between two IT variables (IT infrastructure and IT labor) and firm performance with 2001-2004 data from Fortune 1000 firms. Comparisons with other methods for analyzing longitudinal data reveal the advantages of LGM for studying time-dependent relationships and growth patterns.

Original languageEnglish (US)
Title of host publicationICIS 2010 Proceedings - Thirty First International Conference on Information Systems
StatePublished - 2010
Externally publishedYes
Event31st International Conference on Information Systems, ICIS 2010 - Saint Louis, MO, United States
Duration: Dec 12 2010Dec 15 2010

Other

Other31st International Conference on Information Systems, ICIS 2010
CountryUnited States
CitySaint Louis, MO
Period12/12/1012/15/10

Fingerprint

Information systems
System theory
Personnel

Keywords

  • Latent growth modeling
  • Lgm
  • Longitudinal data
  • Time-dependent hypotheses

ASJC Scopus subject areas

  • Information Systems

Cite this

Pavlou, P. A., Zheng, E., & Gu, B. (2010). Latent growth modeling in is research: Basic tenets, illustration, and practical guidelines completed research paper. In ICIS 2010 Proceedings - Thirty First International Conference on Information Systems

Latent growth modeling in is research : Basic tenets, illustration, and practical guidelines completed research paper. / Pavlou, Paul A.; Zheng, Eric; Gu, Bin.

ICIS 2010 Proceedings - Thirty First International Conference on Information Systems. 2010.

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

Pavlou, PA, Zheng, E & Gu, B 2010, Latent growth modeling in is research: Basic tenets, illustration, and practical guidelines completed research paper. in ICIS 2010 Proceedings - Thirty First International Conference on Information Systems. 31st International Conference on Information Systems, ICIS 2010, Saint Louis, MO, United States, 12/12/10.
Pavlou PA, Zheng E, Gu B. Latent growth modeling in is research: Basic tenets, illustration, and practical guidelines completed research paper. In ICIS 2010 Proceedings - Thirty First International Conference on Information Systems. 2010
Pavlou, Paul A. ; Zheng, Eric ; Gu, Bin. / Latent growth modeling in is research : Basic tenets, illustration, and practical guidelines completed research paper. ICIS 2010 Proceedings - Thirty First International Conference on Information Systems. 2010.
@inproceedings{ba781b09a38d438d8c47bbaeae264323,
title = "Latent growth modeling in is research: Basic tenets, illustration, and practical guidelines completed research paper",
abstract = "This paper introduces Latent Growth Modeling (LGM) as a feasible method for analyzing longitudinal data to understand the process of change over time. Given the need to go beyond cross-sectional models, explore longitudinal Information Systems (IS) phenomena, and test IS theories over time, LGM is proposed as a complementary method to help IS researchers propose and evaluate time-centric hypotheses and make longitudinal inferences. The paper first describes the basic tenets of LGM and offers guidelines for using LGM in IS research, including framing hypotheses with time as a central component and implementing LGM models to test these hypotheses. The application of LGM in IS research is illustrated by modeling the longitudinal relationship between two IT variables (IT infrastructure and IT labor) and firm performance with 2001-2004 data from Fortune 1000 firms. Comparisons with other methods for analyzing longitudinal data reveal the advantages of LGM for studying time-dependent relationships and growth patterns.",
keywords = "Latent growth modeling, Lgm, Longitudinal data, Time-dependent hypotheses",
author = "Pavlou, {Paul A.} and Eric Zheng and Bin Gu",
year = "2010",
language = "English (US)",
isbn = "9780615418988",
booktitle = "ICIS 2010 Proceedings - Thirty First International Conference on Information Systems",

}

TY - GEN

T1 - Latent growth modeling in is research

T2 - Basic tenets, illustration, and practical guidelines completed research paper

AU - Pavlou, Paul A.

AU - Zheng, Eric

AU - Gu, Bin

PY - 2010

Y1 - 2010

N2 - This paper introduces Latent Growth Modeling (LGM) as a feasible method for analyzing longitudinal data to understand the process of change over time. Given the need to go beyond cross-sectional models, explore longitudinal Information Systems (IS) phenomena, and test IS theories over time, LGM is proposed as a complementary method to help IS researchers propose and evaluate time-centric hypotheses and make longitudinal inferences. The paper first describes the basic tenets of LGM and offers guidelines for using LGM in IS research, including framing hypotheses with time as a central component and implementing LGM models to test these hypotheses. The application of LGM in IS research is illustrated by modeling the longitudinal relationship between two IT variables (IT infrastructure and IT labor) and firm performance with 2001-2004 data from Fortune 1000 firms. Comparisons with other methods for analyzing longitudinal data reveal the advantages of LGM for studying time-dependent relationships and growth patterns.

AB - This paper introduces Latent Growth Modeling (LGM) as a feasible method for analyzing longitudinal data to understand the process of change over time. Given the need to go beyond cross-sectional models, explore longitudinal Information Systems (IS) phenomena, and test IS theories over time, LGM is proposed as a complementary method to help IS researchers propose and evaluate time-centric hypotheses and make longitudinal inferences. The paper first describes the basic tenets of LGM and offers guidelines for using LGM in IS research, including framing hypotheses with time as a central component and implementing LGM models to test these hypotheses. The application of LGM in IS research is illustrated by modeling the longitudinal relationship between two IT variables (IT infrastructure and IT labor) and firm performance with 2001-2004 data from Fortune 1000 firms. Comparisons with other methods for analyzing longitudinal data reveal the advantages of LGM for studying time-dependent relationships and growth patterns.

KW - Latent growth modeling

KW - Lgm

KW - Longitudinal data

KW - Time-dependent hypotheses

UR - http://www.scopus.com/inward/record.url?scp=84870962745&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84870962745&partnerID=8YFLogxK

M3 - Conference contribution

AN - SCOPUS:84870962745

SN - 9780615418988

BT - ICIS 2010 Proceedings - Thirty First International Conference on Information Systems

ER -