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Multilevel Modeling of Categorical Outcomes Using IBM SPSS
Abstract
This is the first workbook that introduces the multilevel approach to modeling with categorical outcomes using IBM SPSS Version 20. Readers learn how to develop, estimate, and interpret multilevel models with categorical outcomes. The authors walk readers through data management, diagnostic tools, model conceptualization, and model specification issues related to single-level and multilevel models with categorical outcomes. Screen shots clearly demonstrate techniques and navigation of the program. Modeling syntax is provided in the appendix. Examples of various types of categorical outcomes demonstrate how to set up each model and interpret the output. Extended examples illustrate the logic of model development, interpretation of output, the context of the research questions, and the steps around which the analyses are structured. Readers can replicate examples in each chapter by using the corresponding data and syntax files available at www.psypress.com/9781848729568. The book opens with a review of multilevel with categorical outcomes, followed by a chapter on IBM SPSS data management techniques to facilitate working with multilevel and longitudinal data sets. Chapters 3 and 4 detail the basics of the single-level and multilevel generalized linear model for various types of categorical outcomes. These chapters review underlying concepts to assist with trouble-shooting common programming and modeling problems. Next population-average and unit-specific longitudinal models for investigating individual or organizational developmental processes are developed. Chapter 6 focuses on single- and multilevel models using multinomial and ordinal data followed by a chapter on models for count data. The book concludes with additional trouble shooting techniques and tips for expanding on the modeling techniques introduced. Ideal as a supplement for graduate level courses and/or professional workshops on multilevel, longitudinal, latent variable modeling, multivariate statistics, and/or advanced quantitative techniques taught in psychology, business, education, health, and sociology, this practical workbook also appeals to researchers in these fields. An excellent follow up to the authors’ highly successful Multilevel and Longitudinal Modeling with IBM SPSS and Introduction to Multilevel Modeling Techniques, 2nd Edition, this book can also be used with any multilevel and/or longitudinal book or as a stand-alone text introducing multilevel modeling with categorical outcomes.
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“GEEs also allow the inclusion of patients for whom measures are missing for certain time periods (e.g. patients attached in August 2014 who did not have a measure for T0 + 2 years).”
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“Robust (Huber-White sandwich) estimators were used given departure from normality and large sample size [69, 70].”
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Items 201–300 of 314
Burgess, A., Horton, M. S., & Moores, E. (2021) · Heliyon · doi:10.1016/j.heliyon.2021.e07518 · Cited by 5
Cruz-Martínez, R. R., Wentzel, J., Sanderman, R., & van Gemert‐Pijnen, J. E. W. C. (2021) · Behaviour and Information Technology · doi:10.1080/0144929x.2021.1971764 · Cited by 5
“Descriptive statistics (e.g. percentage distributions) and generalised linear mixed modeling (GLMM) were used due to the ordinal measurement level of the outcome variables and the hierarchical structure of the data (Garson 2013; Heck, Thomas, and Tabata 2013).”
MethodInfluence of Traffic Characteristics on Pavement Performance of Parking Lots
Ghadi, M. Q., Ahmad, H. S., & Jannoud, I. (2023) · Infrastructures · doi:10.3390/infrastructures8040065 · Cited by 5
Benz, D. C., Mikulicic, F., Gräni, C., et al. (2017) · EJNMMI Research · doi:10.1186/s13550-017-0342-8 · Cited by 5
“Although generalized linear mixed modeling would be an excellent alternative, such analysis was restricted by the data structure (complexity due to multiple intrinsic hemodynamic and scan parameters) of the present study [24].”
MethodNibaruta, J. C., Kamana, B., Chahboune, M., Chebabe, M., Elmadani, S., Turman, J. E., Guennouni, M., Amor, H., Baali, A., & Elkhoudri, N. (2022) · BMC Pregnancy and Childbirth · doi:10.1186/s12884-022-05009-y · Cited by 4
“The deviance (or-2Log likelihood), Akaike Information Criteria (AIC) and Bayesian Information Criterion (BIC) were used to compare the fit to the data of the null model and that of the full model where we favored model with smaller values of these indices [4, 30, 33].”
MethodZamboanga, B. L., Blumenthal, H., Ramarushton, B., et al. (2022) · Addictive Behaviors · doi:10.1016/j.addbeh.2022.107560 · Cited by 4
“For DGs participation, the null HGLM estimated an ICC = 0.059, passing a conventional threshold (ICC = 0.05; Heck et al., 2013) indicating evidence of clustering, though it did not meet statistical significance, p = .064.”
InfluentialOlofsson, J., Connolly, F. F., Malmberg, G., Josefsson, M., & Stattin, M. (2023) · Journal of Aging & Social Policy · doi:10.1080/08959420.2023.2206077 · Cited by 4
“The Interclass Correlation Coefficient (ICC) indicated that a sizable amount of the variation in the dependent variables could be explained by differences between countries (Heck et al., 2013).”
Glossed video keyword captions and L2 vocabulary acquisition: an eye-tracking study
Lee, T.-Y., & Choi, S. (2024) · Computer Assisted Language Learning · doi:10.1080/09588221.2024.2412103 · Cited by 4
“To quantify the variance explained by these random effects, we calculated intraclass correlation coefficient (ICC) for each model (Heck et al., 2013) using the HLM_summary function from the bruceR package (Bao, 2023).”
Delayed silent phoneme monitoring in adults who do and do not stutter
Coalson, G. A., & Byrd, C. T. (2018) · Speech Language and Hearing · doi:10.1080/2050571x.2018.1458067 · Cited by 4
“Mixed model analyses were conducted using the generalized linear mixed model procedure of SPSS (v. 22), as described by Field (2013) and Heck, Thomas, and Tabata (2012), to assess the relationship between talker group, phoneme position, and inter-stimulusinterval (ISI) upon the speed and accuracy…”
MethodBorde, M. T., Loha, E., Johansson, K. A., & Lindtjørn, B. (2019) · PLoS ONE · doi:10.1371/journal.pone.0215195 · Cited by 5
Roebroek, L. O., Bruins, J., Roe, D., Delespaul, P., PHAMOUS investigators, de Jong, S., Boonstra, A., Visser, E., & Castelein, S. (2021) · Epidemiology and Psychiatric Sciences · doi:10.1017/s2045796021000640 · Cited by 4
Roessger, K. M., Weese, J., Parker, D. A., & Hevel, M. S. (2022) · The Journal of Continuing Higher Education · doi:10.1080/07377363.2021.2024001 · Cited by 4
“Customary approaches to partitioning multilevel variance using intraclass correlation coefficients (ICC) with continuous, binary, and ordinal outcomes are not applicable to count outcomes (Heck et al., 2012).”
MethodInfluentialVena-Oya, J., Castañeda-García, J.-A., & Molina, M. Á. R. (2022) · SAGE Open · doi:10.1177/21582440221125422 · Cited by 4
“The literature recommends that multilevel analyses be performed using alternative models—that is, with random constant and fixed slopes for predictors; random constant and random slopes; and with and without predictors for random parameters (Heck et al., 2013).”
MethodChen, S., Tai, Z., & Liu, J. (2023) · Journal of Physical Activity and Health · doi:10.1123/jpah.2022-0354 · Cited by 4
The Determinants of Student Success in University: A Generalized Ordered Logit Approach
Cyrenne, P., & Chan, A. H. S. (2022) · Canadian Journal of Higher Education · doi:10.47678/cjhe.v52i1.189007 · Cited by 4
“Similarly, the odds that a student is above category 2, that is still reg - istered is Or in terms of the category names As a test for robustness, we also used a relatively new estimator, feologit , developed by Baetschmann et al. (2020), which is designed to estimate fixed effects or - dered logit models.”
MethodInfluentialWong, J. H. K., Kelloway, E. K., Godin, J., McKee, M. C., & McInnis, A. (2018) · Psychology of Violence · doi:10.1037/vio0000185 · Cited by 5
Schuhmacher, N., Rack, N., Beckmann, L., et al. (2023) · Frontiers in Developmental Psychology · doi:10.3389/fdpys.2023.1278034 · Cited by 3
Demonstratives in Spanish–Catalan simultaneous bilinguals: which system do they prefer?
Todisco, E., Guijarro‐Fuentes, P., Gudde, H. B., & Coventry, K. R. (2024) · Bilingualism Language and Cognition · doi:10.1017/s1366728924000051 · Cited by 4
Toikko, T., & Rantanen, T. (2018) · Social Policy and Administration · doi:10.1111/spol.12415 · Cited by 3
McLennan, P. A., Mueller, C. W., Heck, R. H., & Nakamura, B. J. (2019) · Evidence-Based Practice in Child and Adolescent Mental Health · doi:10.1080/23794925.2019.1612298 · Cited by 3
“The analyses conducted consisted of a basic within- and betweensubjects repeated measures model utilizing a fixedeffect approach (Heck et al., 2012).”
MethodSelf-citationMulamba, K. C. (2021) · ECONOMICS AND POLICY OF ENERGY AND THE ENVIRONMENT · doi:10.3280/efe2020-002003 · Cited by 3
Gibbs, N. P., Sloat, E. F., Amrein-Beardsley, A., Cha, D.-J., Mulerwa, O., & Beck, M. (2023) · Studies in Higher Education · doi:10.1080/03075079.2023.2216725 · Cited by 3
“These are fi xed values and therefore not uniquely speci fi ed as a residual term (Heck, Thomas, and Tabata 2012; Raudenbush and Bryk 2002; Snijders and Bosker 2012).”
BackgroundMethodInfluentialKaiser, S., Mabille, G., Thørnblad, R., et al. (2023) · Child & Family Social Work · doi:10.1111/cfs.13077 · Cited by 3
Pastori, G., Brouwer, I. D., Siemonsma, M., Verhoef, H., Hương, L. T. T., Xuan, T. T. L., Tuyết, T., Samuel, F. O., Shittu, O. F., Eyinla, T. E., et al. (2023) · Current Developments in Nutrition · doi:10.1016/j.cdnut.2023.102050 · Cited by 3
“A random intercept and random slope were added to correct for the measurement dependency only in the models with ICC > 0.05 [37,38].”
MethodInfluentialVisits as a Catalyst for Prison Program Engagement
Nur, A. V. (2024) · Crime & Delinquency · doi:10.1177/00111287241258719 · Cited by 3
Barboza, G. E., Steinke, H. R., Meshelemiah, J. C. A., Stanek, C. J., Duhaney, S., & Cash, S. J. (2024) · Child Maltreatment · doi:10.1177/10775595241258452 · Cited by 3
“Because signi fi cance levels in categorical modes are conservative, we follow others in reporting signi fi cance levels outside of conventional standards for variance parameters only ( p < .10; Heck et al., 2013).”
Ferreira, P. C., Pereira, N., Martinho, C., Marques, H., Martins, H., Pinto, A. M., Barros, A., Ferreira, A. I., Gomes, M., & Simão, A. M. V. (2025) · Computers in Human Behavior Reports · doi:10.1016/j.chbr.2025.100647 · Cited by 4
Roessger, K. M., Moy, G. E., Phan, T.-V., Campbell, H., & Parker, D. A. (2020) · Educational Psychology · doi:10.1080/01443410.2020.1806211 · Cited by 3
ADOLESCENT PLEA BARGAINS: DEVELOPMENTAL AND CONTEXTUAL INFLUENCES OF PLEA BARGAIN DECISION MAKING
Fountain, E. (2017) · DigitalGeorgetown (Georgetown University Library) · Cited by 3
Overweg, J., Hartman, C. A., & Hendriks, P. (2018) · Journal of Abnormal Psychology · doi:10.1037/abn0000385 · Cited by 3
Almuntashiri, N., Alsahafi, O., Gamaruddin, M., et al. (2020) · medRxiv · doi:10.1101/2020.04.27.20077420 · Cited by 3
“Statistical analysis of the data was done through IBM SPSS software, version 20((10)).”
MethodEl-Horbaty, Y. S., & Abdel-Salam, A.-S. G. (2024) · Journal of Statistical Computation and Simulation · doi:10.1080/00949655.2024.2362409 · Cited by 2
“NMMs are effective when variables have a nonlinear connection or data indicate a nonlinear trend [5].”
Lai, J., Liu, J. H., Zhang, L., Cao, J., Yang, H., Zhang, L., Fang, J., & Wang, X. T. (2025) · Heliyon · doi:10.1016/j.heliyon.2025.e42469 · Cited by 4
Generalized Linear Mixed Models: Modern Concepts, Methods and Applications, 2nd ed.
Liu, X. (2025) · Journal of the American Statistical Association · doi:10.1080/01621459.2025.2506201 · Cited by 2
Abulela, M. A. A., Jurich, D. P., Mechaber, A. J., et al. (2025) · Health Science Reports · doi:10.1002/hsr2.71237 · Cited by 2
“Second, it is important to further extend predictive validity inferences for the USMLE, and in particular, to predict patient's in ‐ hospital mortality while controlling for some physicians', hospitals', and patient characteristics, and to obtain unbiased parameter estimates [9 – 11].”
Can gesture input support toddlers’ fast mapping?
Foran, L., Beverly, B. L., Shelley-Tremblay, J. F., & Estis, J. M. (2022) · Journal of Child Language · doi:10.1017/s0305000922000149 · Cited by 2
“GEE is subsumed under generalized linear mixed models and offers a framework for examining repeated categorical outcome variables that are nested within participants who are selected at random (Heck, Thomas & Tabata, 2012).”
MethodThe Effect of Supplemental Instruction on STEM Course Performance
Zvoch, K., Letourneau, L. E., & Spaniol-Mathews, P. (2023) · American Journal of Distance Education · doi:10.1080/08923647.2023.2165355 · Cited by 2
“These results indicate that the slopes of the treatment variable were parallel across the categories of the dependent variable, and therefore estimation of an ordinal model was appropriate (Heck et al., 2012).”
Zhao, M., Yang, X., & Sheng, S. (2023) · IEEE Transactions on Engineering Management · doi:10.1109/tem.2023.3335161 · Cited by 2
“We followed Heck et al.’s [62] approach to determine whether a multilevel logistic regression is necessary to deal with the nested data structure.”
MethodInfluentialA Multilevel Analysis of Life Satisfaction in Central and Eastern Europe
Hritcu, R.-O.-S. (2015) · Procedia Economics and Finance · doi:10.1016/s2212-5671(15)00077-5 · Cited by 2
Kalkan, S. B., Başar, Ö. D., & Özden, Ü. H. (2015) · Marmara Üniversitesi İktisadi ve İdari Bilimler Dergisi · doi:10.14780/iibd.14568 · Cited by 2
Winchester, D. E., Agarwal, N., Burke, L., et al. (2016) · Military Medical Research · doi:10.1186/s40779-016-0090-5 · Cited by 2
Lee, E., & Papp, L. M. (2016) · Journal of Substance Use · doi:10.1080/14659891.2016.1184335 · Cited by 2
Shokory, S. M., & Suradi, N. R. M. (2018) · AIP conference proceedings · doi:10.1063/1.5028044 · Cited by 2
Quantifying the Community Effect on Contraceptive Use in Egypt
Anwar, N. (2019) · Athens Journal of Social Sciences · doi:10.30958/ajss.7-1-3 · Cited by 2
Puzić, S., Šabić, J., & Odak, I. (2020) · Revija za sociologiju · doi:10.5613/rzs.50.2.6 · Cited by 2
The Effect of Fantasy Context on Moral Action and Judgment
Ruedinger, B. M., & Barnes, J. (2021) · Imagination Cognition and Personality · doi:10.1177/02762366211019782 · Cited by 2
“The negative binomial regression is robust to violations of dispersion and when there is no overdispersion, the model is equivalent to Poisson regression (Heck et al., 2013).”
MethodChen, N., Kim, C. G., Lee, K. J., & Kim, J. (2021) · Exercise Science · doi:10.15857/ksep.2021.30.3.288 · Cited by 2
“Generalized linear mixed modeling (GLMM) that has the extension of GLM “describes models for categorical data where the subjects are nested within groups or where repeated measures are nested within individuals”, and was suggested to conduct the crosslevel logistic regression model [27].”
MethodWandschneider, L., Sauzet, O., Breckenkamp, J., Spallek, J., & Razum, O. (2020) · Frontiers in Public Health · doi:10.3389/fpubh.2020.00136 · Cited by 2
“A logistic regression model would require a larger sample size and might lead to problems with model convergence (due to demanding model estimation procedures) (37).”
MethodKohut, T., Landripet, I., & Štulhofer, A. (2019) · doi:10.31234/osf.io/xmk7h · Cited by 2
Smithman, M. A., Breton, M., & Haggerty, J. L. (2023) · Research Square · doi:10.21203/rs.3.rs-3338608/v1 · Cited by 2
How Layers of Context and Material Deprivation Impact Reemployment in Stable or Casual Work
Rodwell, J., & Flower, R. L. (2023) · Social Sciences · doi:10.3390/socsci12110625 · Cited by 1
“To check whether these variables acted as clustering variables, the procedures for multilevel multinomial modelling outlined in Sommet and Morselli (2017) and Heck et al. (2013) were followed.”
MethodFikri, R. J., Sugema, I., & Pasaribu, S. H. (2023) · JURNAL EKONOMI DAN KEBIJAKAN PEMBANGUNAN · doi:10.29244/jekp.12.2.2023.185-204 · Cited by 1
In-vitro and In-vivo Fungicidal Evaluation against False Smut (Ustilaginoidea virens) of Rice
Ravali, S., Basha, S. A., Babu, T. K., et al. (2024) · International Journal of Economic Plants · doi:10.23910/2/2024.5263a · Cited by 1
“…to various concentrations of propiconazole 25 EC, carbendazim 50% WP, and tebuconazole 50%+trifloxystrobin 25% w/w WG (75 WG) against U. virens were subjected to probit analysis using IBM SPSS Statistics 28 (Heck et al., 2013). concentrations at which complete mycelial growth inhibition occurs.”
MethodA Bourdieusian theory on communicating an opinion about AI governance
Binst, B., Bircan, T., & Smets, A. (2024) · AI & Society · doi:10.1007/s00146-024-02060-5 · Cited by 3
“Hence, we are justified in constructing a multilevel model (Heck et al. 2013).”
Sumon, I. H., Salan, M. S. A., Kabir, M. A., et al. (2024) · PLoS ONE · doi:10.1371/journal.pone.0313424 · Cited by 1
Linking wealth and household head traits via quantile multilevel models in South Africa
Mulamba, K. C. (2025) · Journal of Economic and Financial Sciences · doi:10.4102/jef.v18i1.1056 · Cited by 1
Köppen, A., Franze, M., & Hoffmann, W. (2026) · BMC Pediatrics · doi:10.1186/s12887-026-06616-w · Cited by 1
“For the calculation of the GLMM, there was evidence of statistically significant variability in the random effect [21], i.e. preschool affiliation (see Table S10 in the Additional file 1).”
Bayesian hierarchical model with MCMC for optical cable flame retardancy tests
Kuandykov, L. (2013) · Expert systems with applications · doi:10.1016/j.eswa.2012.12.064 · Cited by 1
Šabić, J., Matić, J., & Marušić, I. (2020) · Revija za sociologiju · doi:10.5613/rzs.50.2.1 · Cited by 1
Gui, J., Harshaw, H. W., & Chai, Y. (2020) · International Journal of the Sociology of Leisure · doi:10.1007/s41978-020-00072-1 · Cited by 1
An Updated Quantitative Assessment of Kerlin’s Macro-Institutional Social Enterprise Framework
Monroe‐White, T., & Coskun, M. E. (2017) · Emerald Group Publishing Limited eBooks · doi:10.1108/978-1-78714-250-320171002 · Cited by 1
Jabkowski, P., & Piekut, A. (2022) · Studia Socjologiczne · doi:10.24425/sts.2022.141427 · Cited by 1
Matković, T., Gregurović, M., & Šabić, J. (2023) · International Journal of Sociology of Education · doi:10.17583/rise.12538 · Cited by 1
“We used robust estimation for the tests of fixed effects to account for possible violations of model assumptions (e.g. Heck et al., 2012).”
Roessger, K. M., Parker, D. A., Hevel, M. S., et al. (2023) · Community College Journal of Research and Practice · doi:10.1080/10668926.2023.2292096 · Cited by 1
Pyo, J. (2020) · Crime Prevention and Community Safety · doi:10.1057/s41300-020-00102-w · Cited by 2
User Requirement? Travel Mode Choice Routines Across Different Trip Types
Langer, D., & Bullinger, A. C. (2020) · Lecture notes in computer science · doi:10.1007/978-3-030-59987-4_9 · Cited by 1
Silva, M. M. D., & Utomo, A. P. (2021) · Seminar Nasional Official Statistics · doi:10.34123/semnasoffstat.v2020i1.531 · Cited by 1
Retention: Course Completion Rates in Online Distance Learning
Phillips, A. S. (2015) · University of North Texas Digital Library (University of North Texas) · doi:10.12794/metadc822741 · Cited by 1
“The GLMM procedure accounts for challenges presented by both group-level data and percentages (Heck et al., 2012).”
BackgroundMethodInfluentialLINEUP SIZE AND NUMBER OF CUES: WHEN BIGGER ISN’T BETTER
Kalmet, N. (2016) · QSpace (Queen's University Library) · Cited by 1
Mentor teachers in primary education: The delicate balance between their mentor and teacher roles
Jaspers, W. M. (2019) · doi:10.33540/345 · Cited by 1
Predictors of empirically-supported interventions following structured functional assessment.
Verbist, A. N. (2019) · doi:10.18297/etd/3289 · Cited by 1
“The sequence of steps described below (adapted from Gamst et al., 2013; Heck et al., 2012; Tabachnick & Fidell, 2013) summarizes the model-building process for predicting a trauma-focused treatment prescription; other outcome variables followed the same modeling procedure.”
BackgroundMethodInfluentialThe role of the home visitor: How intervention improves stressed parent-child interactions
Huber, L. T. (2020) · doi:10.31274/etd-20210114-65 · Cited by 1
Ramli, N. B., Talib, N. Z. B., & Hussin, Z. B. (2017) · JuPiDi: Jurnal Kepimpinan Pendidikan
Roig-Watnik, S. M. (2012) · doi:10.25148/etd.fi13042204
“3 3 2 ≈ π (Heck et al., 2012; Hox, 2010).”
Office Disciplinary Referral Patterns of American Indian Students in Special Education.
Whitford, D. K. (2014) · UA Campus Repository (The University of Arizona)
Emergency Room Utilization Disparities among Older Adults Treated by Rural Health Clinics
Bagwell, M. T. (2016) · Journal of International Crisis and Risk Communication Research
Noé, J. M. I. (1970) · Papeles de Europa · doi:10.5209/pade.58671
Alcohol Use and Associated Health Behaviours of Women who have Been Treated for Breast Cancer
Balaam, S. (2019) · Queensland University of Technology · doi:10.5204/thesis.eprints.130711
ÜGK – COFO – VECOF 2016 results: Technical appendices
Pham, G., Helbling, L. A., Verner, M. H. O.-0.-0.-9., et al. (2019) · Zurich Open Repository and Archive (University of Zurich) · doi:10.5167/uzh-180407
Yusram, D. A., & Agustina, N. (2021) · Seminar Nasional Official Statistics · doi:10.34123/semnasoffstat.v2021i1.861
DaGrossa, J. A. (2022) · Criminal Justice Review · doi:10.1177/07340168221078341
“The data were analyzed using SPSS (Heck et al., 2012; Heck et al., 2014).”
Haumann, T., Kassemeier, R., & Wieseke, J. (2021) · Springer eBooks · doi:10.1007/978-3-319-05542-8_18-1
Reinwand, D. A. (2016) · Research Publications (Maastricht University) · doi:10.26481/dis.20161221dr
Connecting needs and care in psychosis
Roebroek, L. O. (2022) · doi:10.33612/diss.207593828
Family caregivers of persons with young-onset dementia
Bruinsma, J. (2022) · doi:10.26481/dis.20220420jb
The Impact of Cesarean Section on Neonatal Mortality in Rural–Urban Divisions in a Region of Brazil
Zafeiris, K. Ν., Skiadas, C. H., Dimotikalis, Y., et al. (2022) · doi:10.1002/9781394165544.ch21
Coreset Construction for Extra Binomial Variation in Binomial Regression
Zhang, F., Wichitaksorn, N., & Chattopadhyay, B. (2023) · International Conference on Information Networking · doi:10.1109/icoin56518.2023.10048948
Wondemu, M. Y., & Frøyland, L. R. (2023) · Research Square · doi:10.21203/rs.3.rs-2970913/v1
Examining the Dynamic Nature of Pupils’ Educational Aspirations: A Longitudinal Mixed-Model Study
Jokić, B., & Dedić, Z. R. (2023) · Center for Educational Policy Studies Journal · doi:10.26529/cepsj.1613
Khan, A., Madihie, A., Khan, S. U., Haider, S., & Haider, M. (2024) · doi:10.2196/preprints.65098
Metadata
- Authors
- Heck, R. H., Thomas, S., & Tabata, L.
- ORCID
- Heck, Ronald H
- Venue
- Routledge eBooks
- Publisher
- Routledge
- Published
- 2013-05-07
- OpenAlex
- W1586960195
- Cited by
- 316
- References
- 0
- Citations by year
- 2026: 5 · 2025: 13 · 2024: 21 · 2023: 27 · 2022: 24 · 2021: 29 · 2020: 34 · 2019: 36 · 2018: 34 · 2017: 19 · 2016: 29 · 2015: 22 · 2014: 16 · 2013: 2
- FWCI
- 5.22
- 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 › Decision Sciences › Management Science and Operations Research › Psychometric Methodologies and Testing
- Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods and Applications
- Keywords
- multilevel modeling, categorical outcomes, generalized linear models, longitudinal data, multinomial data, ordinal data, count data, population-averaged models, SPSS, data management, model specification, model interpretation
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