Longitudinal Data Analyses Using Linear Mixed Models in SPSS: Concepts, Procedures and Illustrations

Shek, Daniel T. L.; Ma, Cecilia M. S.

doi:10.1100/tsw.2011.2

Cited by 425Statistical Methods and Bayesian InferenceSpatial and Panel Data AnalysisAgriculture, Soil, Plant Science

Longitudinal Data Analyses Using Linear Mixed Models in SPSS: Concepts, Procedures and Illustrations

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Shek, Daniel T. L., Ma, Cecilia M. S.·2011·The Scientific World JOURNAL

DOI 10.1100/tsw.2011.2PMC PMC5719989

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Abstract

Although different methods are available for the analyses of longitudinal data, analyses based on generalized linear models (GLM) are criticized as violating the assumption of independence of observations. Alternatively, linear mixed models (LMM) are commonly used to understand changes in human behavior over time. In this paper, the basic concepts surrounding LMM (or hierarchical linear models) are outlined. Although SPSS is a statistical analyses package commonly used by researchers, documentation on LMM procedures in SPSS is not thorough or user friendly. With reference to this limitation, the related procedures for performing analyses based on LMM in SPSS are described. To demonstrate the application of LMM analyses in SPSS, findings based on six waves of data collected in the Project P.A.T.H.S. (Positive Adolescent Training through Holistic Social Programmes) in Hong Kong are presented.

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Separate linear growth models will be computed for each variable, while controlling for multiple testing.
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Authors: Shek, D. T. L., & Ma, C. M. S.
Affiliations: University of Kentucky HealthCare (US)
Hong Kong Polytechnic University (HK)
Corresponding author: Shek, Daniel T. L.
ORCID: Shek, Daniel T. L.
Ma, Cecilia M. S.
Venue: The Scientific World JOURNAL
Publisher: Hindawi Limited
Published: 2011
Volume: 11
Pages: 42-76
ISSN: 1537-744X (ISSN-L)
DOI: 10.1100/tsw.2011.2
PMC: PMC5719989
OpenAlex: W2056227828
Cited by: 425
References: 66
Citations by year: 2026: 16 · 2025: 17 · 2024: 26 · 2023: 19 · 2022: 43 · 2021: 41 · 2020: 32 · 2019: 26 · 2018: 46 · 2017: 25 · 2016: 43 · 2015: 33 · 2014: 21 · 2013: 16 · 2012: 17
FWCI: 15.81
Type: journal article
Language: en
Open access: gold
doi.org
Licence: cc-by
creativecommons.org/licenses/by/3.0/ (unspecified)
Locations: The Scientific World JOURNAL (publishedVersion, cc-by)
Europe PMC (PubMed Central) (publishedVersion, cc-by)
PubMed Central (publishedVersion, cc-by)
PubMed (publishedVersion)
DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion)
PolyU Institutional Research Archive (Hong Kong Polytechnic University) (submittedVersion, cc-by)
Funders: Hong Kong Jockey Club Charities Trust
Topics: Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods and Bayesian Inference
Social Sciences › Economics, Econometrics and Finance › Economics and Econometrics › Spatial and Panel Data Analysis
Life Sciences › Agricultural and Biological Sciences › Ecology, Evolution, Behavior and Systematics › Agriculture, Soil, Plant Science
Keywords: linear mixed models, longitudinal analysis, multilevel analysis, generalized linear models, Project P.A.T.H.S., adolescent behavior change, Hong Kong
MeSH terms: Adolescent, Adolescent Behavior, Child, Female, Hong Kong, Humans, Longitudinal Studies, Male, Social Behavior, Linear Models, Adolescent Development

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