Multilevel and Longitudinal Modeling with IBM SPSS
Abstract
This book demonstrates how to use multilevel and longitudinal modeling techniques available in the IBM SPSS mixed-effects program (MIXED). Annotated screen shots provide readers with a step-by-step understanding of each technique and navigating the program. Readers learn how to set up, run, and interpret a variety of models. Diagnostic tools, data management issues, and related graphics are introduced throughout. Annotated syntax is also available for those who prefer this approach. Extended examples illustrate the logic of model development to show readers the rationale of the research questions and the steps around which the analyses are structured. The data used in the text and syntax examples are available at www.routledge.com/9780415817110. Highlights of the new edition include: Updated throughout to reflect IBM SPSS Version 21. Further coverage of growth trajectories, coding time-related variables, covariance structures, individual change and longitudinal experimental designs (Ch.5). Extended discussion of other types of research designs for examining change (e.g., regression discontinuity, quasi-experimental) over time (Ch.6). New examples specifying multiple latent constructs and parallel growth processes (Ch. 7). Discussion of alternatives for dealing with missing data and the use of sample weights within multilevel data structures (Ch.1). The book opens with the conceptual and methodological issues associated with multilevel and longitudinal modeling, followed by a discussion of SPSS data management techniques which facilitate working with multilevel, longitudinal, and cross-classified data sets. Chapters 3 and 4 introduce the basics of multilevel modeling: developing a multilevel model, interpreting output, and trouble-shooting common programming and modeling problems. Models for investigating individual and organizational change are presented in chapters 5 and 6, followed by models with multivariate outcomes in chapter 7. Chapter 8 provides an illustration of multilevel models with cross-classified data structures. The book concludes with ways to expand on the various multilevel and longitudinal modeling techniques and issues when conducting multilevel analyses. It's ideal for courses on multilevel and longitudinal modeling, multivariate statistics, and research design taught in education, psychology, business, and sociology.
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Missing data were handled with a full information maximum likelihood (FIML) method.
“Missing data were handled with a full information maximum likelihood (FIML) method (Heck et al., 2013).”
From Mindfulness-Based Stress Reduction Increases Mental Wellbeing and Emotion Regulation During the First Wave of the COVID-19 Pandemic: A Synchronous Online Intervention Study (2021) · cites this paper as Heck et al., 2013
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“The ICC is the proportion of variance between groups to the total variance (see [27]).”
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“all other behavior) using the SPSS GENLINMIXED procedure (23, 24).”
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“We estimated a generalized linear mixed-effects model with no predictor, which allowed us to partition the variation in engagement in ethnic harassment within and between classrooms (Heck et al. 2013).”
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“MLM, using the SPSS mixed procedure (Heck et al., 2013; Peugh & Enders, 2005), was performed with 36,959 individuals (Level 1) across 28 countries (Level 2) to control for the nested data structure.”
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Longitudinal course of suicidal ideation and predictors of its persistence – A NESDA study
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“The resulting covariance matrix, the G matrix, presents the variances of the random intercept and random slope (time), and the covariance between them (Heck et al., 2014).”
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Quality of life in bipolar disorder: towards a dynamic understanding
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“…at level 1 were specified as having an autoregressive covariance matrix: unobserved variance was assumed to differ between the time points, and it was assumed that correlation between occasions of measurement would decrease with greater duration between occasions of measurements (Heck et al. 2014).”
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Conducting and Evaluating Multilevel Studies: Recommendations, Resources, and a Checklist
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Establishing the situated features associated with perceived stress
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Preschool Children’s Social Play and Involvement in the Outdoor Environment
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“Therefore, and following the recommendations of Heck et al. (2013), we performed a hierarchical regression analysis with interaction terms in order to examine the relationship between the type of social play and involvement.”
MethodJordan, D. G., Collins, A. C., Dunaway, M. G., Kilgore, J., & Winer, E. S. (2020) · Journal of Clinical Psychology · doi:10.1002/jclp.23066 · Cited by 47 · see citing works
“, analysis of variance) are unable to include individuals with partial data, such that any subject with missing data on any occasion is removed via listwise deletion (Heck et al., 2013).”
MethodSchool bullying: Prevalence and variation in and between school systems in TIMSS 2015
Johansson, S., Myrberg, E., & Toropova, A. A. (2022) · Studies In Educational Evaluation · doi:10.1016/j.stueduc.2022.101178 · Cited by 56 · see citing works
“Multilevel modelling takes into account the hierarchical nature of the data and it enables the identification of the amount of variation within and between schools respectively (e.g., (Heck et al., 2013); (Kline, 2016).”
InfluentialKuzik, N., & Carson, V. (2016) · BMC Pediatrics · doi:10.1186/s12887-016-0642-6 · Cited by 47 · see citing works
“multilevel regression model was not necessary [25].”
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The effect of treatment on quality of life and functioning in OCD
Asnaani, A., Kaczkurkin, A. N., Alpert, E., McLean, C. P., Simpson, H. B., & Foa, E. B. (2016) · Comprehensive Psychiatry · doi:10.1016/j.comppsych.2016.10.004 · Cited by 46 · see citing works
“Akaike's information criterion (AIC) and Schwarz's Bayesian criterion (BIC) were then examined to compare models and determine best model fit, with smaller values indicating a better model fit [35].”
Langley, E., Totsika, V., & Hastings, R. P. (2017) · Autism Research · doi:10.1002/aur.1773 · Cited by 46 · see citing works
“Centering allows variables to be transformed into meaningful deviations around a fixed value [Heck et al., 2014] and can improve interpretation and accuracy when estimating parameters [Enders & Tofighi, 2007].”
Ebrahimi, E., Hartman, L. S., Robb, A. C., Pagano, C. C., & Babu, S. V. (2018) · IEEE Conference on Virtual Reality and 3D User Interfaces (VR) · doi:10.1109/vr.2018.8446539 · Cited by 47 · see citing works
“A multilevel modeling approach is required for an ICC greater than 2-3% [2,15].”
MethodMartel, M. O., Finan, P. H., McHugh, R. K., Issa, M., Edwards, R. R., Jamison, R. N., & Wasan, A. D. (2016) · Drug and Alcohol Dependence · doi:10.1016/j.drugalcdep.2016.02.047 · Cited by 46 · see citing works
“This measure of explained variance is analogous to the R2 value traditionally reported when conducting linear regression (Hayes, 2007; Heck et al., 2014; Peugh, 2010).”
MethodMicari, M., & Calkins, S. (2019) · Active Learning in Higher Education · doi:10.1177/1469787419846620 · Cited by 44 · see citing works
“the model with no predictors), in order to determine whether there was indeed sufficient variance across clusters to warrant the mixed-model procedure (Heck et al., 2013).”
MethodResultExploring the relationship between clout and cognitive processing in MOOC discussion forums
Moore, R. L., Yen, C., & Powers, F. E. (2020) · British Journal of Educational Technology · doi:10.1111/bjet.13033 · Cited by 44 · see citing works
Hsu, H., & Bai, C. (2022) · BMC Geriatrics · doi:10.1186/s12877-022-02940-9 · Cited by 44 · see citing works
“, Chicago, IL, USA) by using the command GENLINMIXED (generalized linear mixed models [46].”
MethodThe Stereotype Content Model Applied to Human-Robot Interactions in Groups
Oliveira, R., Arriaga, P., Correia, F., & Paiva, A. (2019) · ACM/IEEE International Conference on Human-Robot Interaction (HRI) · doi:10.1109/hri.2019.8673171 · Cited by 47 · see citing works
“A scaled identity covariance was used for both the random effects of the group and of the repeated measures, which is considered appropriate in studies using repeated measures of short duration [35].”
MethodEvaluating the effectiveness of styles of play in elite soccer
Fernández-Navarro, J., Fradua, L., Zubillaga, A., et al. (2019) · International Journal of Sports Science & Coaching · doi:10.1177/1747954119855361 · Cited by 43 · see citing works
Does adherence to inhaled corticosteroids predict asthma-related outcomes over time? A cohort study
Dima, A. L., Ganse, E. H. V., Stadler, G., & de Bruin, M. (2019) · European Respiratory Journal · doi:10.1183/13993003.00901-2019 · Cited by 42 · see citing works
Sharp, P., Spence, J. C., Bottorff, J. L., Oliffe, J. L., Hunt, K., Vis‐Dunbar, M., & Caperchione, C. M. (2020) · British Journal of Sports Medicine · doi:10.1136/bjsports-2019-100912 · Cited by 48 · see citing works
“05, which has been previously used in meta-analyses of physical activity trials.(34-37)”
MethodEffects of mobile mindfulness on emergency department work stress: A randomised controlled trial
Xu, H. (., Eley, R., Kynoch, K., & Tuckett, A. (2022) · Emergency Medicine Australasia · doi:10.1111/1742-6723.13836 · Cited by 42 · see citing works
Cordier, R., Brown, N., Chen, Y.-W. R., Wilkes‐Gillan, S., & Falkmer, T. (2014) · Developmental Neurorehabilitation · doi:10.3109/17518423.2014.915244 · Cited by 41 · see citing works
“0 [35] was used for the MLR analyses [36].”
MethodThe privatization of neighborhood governance and the production of urban space
Fraser, J. C., Bazuin, J. T., & Hornberger, G. M. (2015) · Environment and Planning A Economy and Space · doi:10.1177/0308518x15621656 · Cited by 42 · see citing works
Trekels, J., & Eggermont, S. (2016) · Human Communication Research · doi:10.1111/hcre.12100 · Cited by 42 · see citing works
A longitudinal study on the stability of the need for cognition
Bruinsma, J., & Crutzen, R. (2018) · Personality and Individual Differences · doi:10.1016/j.paid.2018.02.001 · Cited by 42 · see citing works
Odyniec, P., Probst, T., Margraf, J., & Willutzki, U. (2017) · Psychotherapy Research · doi:10.1080/10503307.2017.1315464 · Cited by 41 · see citing works
- Authors
- Heck, R. H.
- Corresponding author
- Heck, Ronald H.
- ORCID
- Heck, Ronald H.
- Venue
- Routledge eBooks
- Publisher
- Routledge
- Published
- 2013-08-22
- OpenAlex
- W4302348542
- Cited by
- 774
- References
- 0
- Citations by year
- 2026: 33 · 2025: 61 · 2024: 72 · 2023: 92 · 2022: 80 · 2021: 85 · 2020: 62 · 2019: 60 · 2018: 54 · 2017: 71 · 2016: 53 · 2015: 22 · 2014: 14 · 2013: 6 · 2012: 7
- FWCI
- 7.23
- Type
- book
- Language
- en
- Open access
- closed
- Locations
- Routledge eBooks (publishedVersion)
- 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
- Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods and Applications
- Keywords
- multilevel modeling, longitudinal modeling, growth trajectories, covariance structure, personal transformation, regression discontinuity design, quasi-experimental design, missing data, sampling weights, cross-classified data, multivariate outcomes, organizational change
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