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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 101–200 of 314
Glądalski, M., Bańbura, M., Kaliński, A., et al. (2020) · International Journal of Biometeorology · doi:10.1007/s00484-019-01851-6 · Cited by 17
“Generalized linear and linear mixed modeling was performed using IBM SPSS Statistics 22 software (Heck et al. 2010, 2012; IBM SPSS 2013).”
MethodZandberg, L. J., Kaczkurkin, A. N., McLean, C. P., Rescorla, L. A., Yadin, E., & Foa, E. B. (2016) · Journal of Traumatic Stress · doi:10.1002/jts.22138 · Cited by 17
“Data analyses were conducted using the IBM SPSS statistics program (Version 22) and the linear mixed model procedures outlined in Heck et al. (2012) and Shek and Ma (2011).”
MethodMcDougall, P. L., & Ruckstuhl, K. E. (2018) · Behavioral Ecology and Sociobiology · doi:10.1007/s00265-018-2536-0 · Cited by 18
Grao‐Cruces, A., Sánchez‐Oliva, D., Segura‐Jiménez, V., Cabanas‐Sánchez, V., Martínez‐Gómez, D., Rodríguez‐Rodríguez, F., Moreno, L. A., & Castro‐Piñero, J. (2018) · Scandinavian Journal of Medicine and Science in Sports · doi:10.1111/sms.13355 · Cited by 16
Jaspers, W. M., Prins, F. J., Meijer, P. C., Mainhard, T., & Wubbels, T. (2021) · Teaching and Teacher Education · doi:10.1016/j.tate.2021.103342 · Cited by 16
Francisco, S. M., Ferreira, P. C., Simão, A. M. V., & Pereira, N. (2024) · BMC Psychology · doi:10.1186/s40359-024-01582-3 · Cited by 17
“These results seem to agree with previous research that found that when there is a friendship between bystander and aggressor, bystanders will tend to be passive, or join in on the aggressive behavior [86], and because of that they would probably use more MD mechanisms.”
ResultBurel, N., Tessier, D. P., & Langdon, J. L. (2020) · European Journal of Psychology of Education · doi:10.1007/s10212-020-00517-x · Cited by 24
Schuhmacher, N., & Kärtner, J. (2015) · Frontiers in Psychology · doi:10.3389/fpsyg.2015.00493 · Cited by 16
“Therefore, we used generalized linear mixed models (GLMM; e.g., Heck et al., 2012; Loeys et al., 2014) for level of coordination, because these data were ordinally scaled, and linear mixed models (LMM; e.g., Kenny et al., 2006; Kenny and Kashy, 2011) for preference for joint activity, because these…”
MethodGlądalski, M., Bańbura, M., Kaliński, A., et al. (2016) · Journal für Ornithologie · doi:10.1007/s10336-016-1325-7 · Cited by 16
“…success refers to the proportion of hatchlings that survived to fledging) were calculated using a generalized linear mixed model with binomial error distribution, the approximation of degrees of freedom by the residual method and applying logit link function (Crawley 2002; Heck et al. 2012).”
MethodLockwood, B., Wyant, B. R., & Grunwald, H. E. (2020) · Environment and Behavior · doi:10.1177/0013916520906834 · Cited by 14
“data (addresses within block groups), multilevel models are often preferred over more traditional types of regression for several reasons, including the ability to estimate multiple regression equations in only one model, more accurate estimates of standard errors, and increased model flexibility (Heck et al., 2013; L…”
BackgroundMethodThe quality of the relationship perceived by spouses of people with young-onset dementia
Bruinsma, J., Peetoom, K. K. B., Millenaar, J., Köhler, S., Bakker, C., Koopmans, R. T. C. M., Pijnenburg, Y. A. L., Verhey, F. R. J., & de Vugt, M. E. (2020) · International Psychogeriatrics · doi:10.1017/s1041610220000332 · Cited by 17
“…fi c LMM model can differ from the marginal GEE model when the dependent variable is categorical, with the latter being appropriate if one is interested in population-average change (the regression estimate) and less in the individual-speci fi c (random effect) part (Heck et al. , 2012; Twisk, 2007).”
Mulualem, D., Hailu, D., Tessema, M., et al. (2021) · Nutrients · doi:10.3390/nu13041052 · Cited by 15
“GEE helps to correct within subject correlation and uses quasi-likelihood estimation which allows for over dispersion [23].”
MethodWoods, C. B., Crowley, E., Powell, C., O’Brien, W., MURPHY, M. H., Belton, S., Saunders, J. A., Connolly, S., Farmer, O., & Ng, K. (2021) · Preventive Medicine Reports · doi:10.1016/j.pmedr.2021.101472 · Cited by 15
Believing that prejudice can change increases children's interest in interracial interactions
Pauker, K., Apfelbaum, E. P., Dweck, C. S., & Eberhardt, J. L. (2022) · Developmental Science · doi:10.1111/desc.13233 · Cited by 16
“, participants nested within schools), we utilized multilevel linear models using MIXED with school as a random intercept in SPSS 22 (Heck et al., 2012) to test ourmain predictions regardingwhen andhowprejudice theories shape children’s interest in interracial interaction.”
MethodProfiles and Risk Factors for Teen Dating Violence in Spain
Valdivia‐Salas, S., Lombas, A. S., Jiménez, T. I., Lucas, A., & Villanueva‐Blasco, V. J. (2022) · Journal of Interpersonal Violence · doi:10.1177/08862605221114305 · Cited by 16
“First of all, we conducted a multilevel null model (i.e., a model without any predictors), using the Generalized Linear Mixed Models procedure (see Heck et al., 2013) to determine whether or not the assumption of independence of observations necessary to conduct traditional regression analysis was…”
MethodHogenbirk, J. C., Strasser, R. P., & French, M. G. (2022) · PLoS ONE · doi:10.1371/journal.pone.0274499 · Cited by 15
“, doctors nested within graduation year) was ignored, which may have underestimated standard errors [36].”
BackgroundGiesen, J. M., & Lang, A. H. (2018) · Journal of Disability Policy Studies · doi:10.1177/1044207318780363 · Cited by 14
“Following guidance from Heck, Thomas, and Tabata (2012), we first calculated an unconditional two-level model.”
MethodPhrase Length and Prosody in On-Line Ambiguity Resolution
Shafran, R. W., & Fodor, J. D. (2015) · Journal of Psycholinguistic Research · doi:10.1007/s10936-015-9358-2 · Cited by 14
“Both cluster types showed ICC levels that satisfy the minimum threshold (5 %; Heck et al. 2012): the subject ICC was 17 % and the sentence ICC was 19 %.”
BackgroundTurner, D. E., Lockhart, E. A., Wang, W. Q., et al. (2021) · AIDS and Behavior · doi:10.1007/s10461-020-03152-1 · Cited by 13
Overweg, J., Hartman, C. A., & Hendriks, P. (2018) · Frontiers in Psychology · doi:10.3389/fpsyg.2018.01663 · Cited by 15
“The data of the language comprehension task were analyzed using generalized linear mixed models (GLMMs), using a logit link to accommodate the repeatedly measured (32 trials) binary outcome variable Accuracy (0 for incorrect, 1 for correct) (Jaeger, 2008; Heck et al., 2012).”
MethodChen, D., Li, D., & Paik, Y. (2019) · Entrepreneurship and Regional Development · doi:10.1080/08985626.2019.1640444 · Cited by 13
“Since geographic market scope was coded as a dummy variable, its moderating effect can be tested using interaction terms (Heck, Thomas, and Tabata 2013).”
MethodInfluentialKuijper, S. J. M., Hartman, C. A., & Hendriks, P. (2021) · Frontiers in Psychology · doi:10.3389/fpsyg.2021.610401 · Cited by 15
“A logit link was used to accommodate the repeatedly measured binary outcome variable (i.e., accuracy of pronoun interpretation, denoted below as Accuracy) (Jaeger, 2008; Heck et al., 2012).”
MethodCrisp, G., Potter, C. R., & Taggart, A. (2021) · Research in Higher Education · doi:10.1007/s11162-021-09657-5 · Cited by 14
Glądalski, M., Kaliński, A., Wawrzyniak, J., et al. (2018) · Conservation Physiology · doi:10.1093/conphys/coy062 · Cited by 13
“Linear mixed modelling was performed using IBM SPSS Statistics 22 software (Heck et al., 2010, 2012; IBM SPSS 22, 2013).”
MethodContext-dependent strategies of food allocation among offspring in a facultative cooperative breeder
Li, J., Wang, Y., Lv, L., et al. (2019) · Behavioral Ecology · doi:10.1093/beheco/arz037 · Cited by 13
When and Why Static Images Are More Effective Than Videos
Fan, S., Shen, Z., Koenig, B. L., Ng, T.-T., & Kankanhalli, M. (2020) · IEEE Transactions on Affective Computing · doi:10.1109/taffc.2020.3040399 · Cited by 15
“We used IBM SPSS version 20 for the statistical analyses [60].”
MethodSuitor, J. J., Gilligan, M., Rurka, M. M., & Hou, Y. (2019) · Network Science · doi:10.1017/nws.2019.31 · Cited by 12
“The MIXED procedure in SPSS 24 provides a mixed-effect model that can include both fixed effects for predictors at the ego level (e.g., egos’ perceptions of favoritism) and random effects at the family level (e.g., race and gender composition of the sibship) (Allison, 2009; Heck et al., 2012).”
MethodDeterminants of Middle School Students’ Participation in Shadow Education in Japan
Takashiro, N. (2021) · Social Indicators Research · doi:10.1007/s11205-021-02628-4 · Cited by 12
“For three nominal categories in the current study, the independent variables had different relationships with the probabilities of an individual falling into the following out‐ come (Y) categories (Heck et al. 2012).”
BackgroundMerz, J. E., Delaney, D. G., Setka, J. D., & Workman, M. (2016) · River Research and Applications · doi:10.1002/rra.2969 · Cited by 11
“An unstructured matrix provides a separate coefficient for each covariance (Heck et al., 2012).”
BackgroundA register-based study of variations in services received among dental care attenders
Rosing, K., Hede, B., & Christensen, L. B. (2015) · Acta Odontologica Scandinavica · doi:10.3109/00016357.2015.1034771 · Cited by 12
Priesmeyer, J., Fedewa, A. L., & Toland, M. D. (2018) · Journal of School Health · doi:10.1111/josh.12709 · Cited by 13
Morales, M. C., Delgado, D., & Curry, T. R. (2018) · Race and Social Problems · doi:10.1007/s12552-018-9235-3 · Cited by 12
“The deviance statistic allows a comparison between nested models (Heck et al. 2013) and our results indicate that adding the Level 1 individual-level parameters decreases the deviance statistic indicating improved model fit from the unconditional model (Table 2).”
ResultThe Effects of Neonatal Abstinence Syndrome on Language Delay from Birth to 10 Years
Miller, J. S., Anderson, J. G., Erwin, P. C., Davis, S. K., & Lindley, L. C. (2020) · Journal of Pediatric Nursing · doi:10.1016/j.pedn.2019.12.011 · Cited by 12
Internet Access and Voicing Opinions: The Moderating Roles of Age and the National Economy
Kim, H., & Joshanloo, M. (2020) · Social Indicators Research · doi:10.1007/s11205-020-02298-8 · Cited by 12
Ho, B. S. K., & Dudgeon, D. L. (2015) · Freshwater Biology · doi:10.1111/fwb.12678 · Cited by 13
Outsourcing within the Nordic context: Care services for older people in Finland
Puthenparambil, J. M. (2018) · Journal of Aging & Social Policy · doi:10.1080/08959420.2018.1465800 · Cited by 11
“The result showed a steep decrease in correlation coefficients whenever the time interval between measurements increased, which led to the conclusion that an autoregressive correlation matrix was an appropriate model (Heck et al., 2013).”
BackgroundLin, Y.-H., Hsu, H., Bai, C., et al. (2022) · International Journal of Environmental Research and Public Health · doi:10.3390/ijerph19073982 · Cited by 11
“The random effect of the model was assumed to be the individual factors nested in cities [31].”
BackgroundHigh But Not Low Probability of Gain Elicits a Positive Feeling Leading to the Framing Effect
Gosling, C. J., & Moutier, S. (2017) · Frontiers in Psychology · doi:10.3389/fpsyg.2017.00081 · Cited by 20
“This correlation structure assumes nonzero homogeneous within-subject correlations across choices (Heck et al., 2012).”
BackgroundThe Harms That Drinkers Cause: Regional Variations Within Countries
Wilsnack, R. W., Kristjanson, A. F., Wilsnack, S. C., Bloomfield, K., Grittner, U., & Crosby, R. D. (2018) · The International Journal of Alcohol and Drug Research · doi:10.7895/ijadr.254 · Cited by 11
Turner, D., Lockhart, E. A., Wang, W., Shore, R., Daley, E. M., & Marhefka, S. L. (2020) · JAIDS Journal of Acquired Immune Deficiency Syndromes · doi:10.1097/qai.0000000000002289 · Cited by 11
Glądalski, M., Bańbura, M., Kaliński, A., et al. (2020) · Behavioral Ecology and Sociobiology · doi:10.1007/s00265-020-2812-7 · Cited by 11
“Linear mixed modeling was conducted using IBM SPSS Statistics 22 software (Heck et al. 2010, 2012; IBM SPSS Statistics 22 2013).”
MethodPuzić, S., Šabić, J., & Odak, I. (2021) · Czech Sociological Review · doi:10.13060/csr.2021.039 · Cited by 11
Cumming, D. J., Khan, M. Z., Khan, N. U., & Khan, Z. U. (2024) · Journal of International Financial Markets Institutions and Money · doi:10.1016/j.intfin.2024.101958 · Cited by 10
Bokhari, S. A. A., & Seunghwan, M. (2024) · Sustainability · doi:10.3390/su16104246 · Cited by 20
Experienced and internalized weight stigma among Spanish adolescents
Anastasiadou, D. T., Tárrega, S., Fornieles-Deu, A., Montcada-Ribera, A., Bach-Faig, A., & Sánchez‐Carracedo, D. (2024) · BMC Public Health · doi:10.1186/s12889-024-19246-7 · Cited by 13
“…evaluating empty models and the intraclass correlation coefficient (ICC), our findings revealed minimal variability both between courses and schools, with ICC values consistently below the threshold of 0.05, threshold often regarded as a conventional indicator of the presence of clustering [39].”
InfluentialCheng, W. L. S., Tang, A. C. Y., & Siu, K. L.-S. (2024) · Applied Nursing Research · doi:10.1016/j.apnr.2024.151861 · Cited by 17
Implicit prosody and parsing in silent reading
Shafran, R. W. (2017) · Journal of Research in Reading · doi:10.1111/1467-9817.12124 · Cited by 10
Wijnia, L. (2014) · RePub (Erasmus University Rotterdam) · doi:10.13140/rg.2.2.32805.55521 · Cited by 12
Multilevel Analysis of Road Accident Frequency: The Impact of the Road Category
Ghadi, M. Q. (2023) · International Journal of Transport Development and Integration · doi:10.18280/ijtdi.070207 · Cited by 9
“(3)) [37]. where, and are fixed-effect predictors of accident frequency at level-one and level-two, respectively. γ i0 is a coefficient of and γ 0j is a coefficient of The estimation of the level-two variance ( u 0j ) can judge whether groups are significantly different from each other.”
InfluentialHarrison, N., James, D., & Last, K. (2015) · Research Papers in Education · doi:10.1080/02671522.2014.1002526 · Cited by 9
Šabić, J., & Jokić, B. (2019) · Educational Studies · doi:10.1080/03055698.2019.1681941 · Cited by 10
Schmidt-Hellerau, K., Winters, M., Lyons, P., Leigh, B., Jalloh, M. B., Sengeh, P., Sawaneh, A. B., Zeebari, Z., Salazar, M., Jalloh, M. F., et al. (2020) · BMJ Global Health · doi:10.1136/bmjgh-2020-002732 · Cited by 8
“39 For each of the two main outcomes, regression analysis was performed for each independent variable and as a multivariable analysis including all independent variables.”
An Ecological Framework for Item Responding Within the Context of a Youth Risk and Needs Assessment
Vo, T. T., & French, B. F. (2021) · Educational Measurement Issues and Practice · doi:10.1111/emip.12426 · Cited by 9
Tabib, R., Adamou, A.-E., Ouakid, M. L., et al. (2016) · Avian Biology Research · doi:10.3184/175815516x14575520344993 · Cited by 9
“…nesting height and nest-cup volume affected breeding success, we built a generalised linear mixed model for a relevant binomial response variable characterising the number of fledglings in relation to clutch size, using logit link function and treating year as a random factor (Heck et al., 2012).”
MethodAfter the crisis: political protest in the aftermath of the economic recession
Vassallo, F. (2019) · Comparative European Politics · doi:10.1057/s41295-019-00156-7 · Cited by 9
“Understanding the role of economic variables To better understand how different predictors can explain protest, the next step in the analysis employs a multilevel logistic regression, with an ordinal outcome (Heck et al. 2012), for each of the selected waves (2006, 2008 and 2014).”
MethodJäckle, S., & Schärdel, J. (2017) · Springer eBooks · doi:10.1007/978-3-658-17189-6_6 · Cited by 9
Binyaruka, P., Foss, A. M., Alibrahim, A., Mziray, N., Cassidy, R., & Borghi, J. (2023) · Health Economics Review · doi:10.1186/s13561-023-00468-1 · Cited by 9
“The use of multilevel mixed-effect logistic regression, also termed a random effects model [43], assumes that there is greater variation in outcomes between women in the catchment area of different facilities than between women in the catchment area of the same facility, since the experience of…”
MethodDoorudinia, A., Dadashpoor, H., & Meshkini, A. (2024) · Papers of the Regional Science Association · doi:10.1016/j.pirs.2024.100075 · Cited by 8
Andersen, L. P., Andersen, D. R., & Pihl‐Thingvad, J. (2025) · BMC Public Health · doi:10.1186/s12889-025-25085-x · Cited by 9
The day-of-invitation effect on participation in web-based studies
Wolff, H., & Göritz, A. S. (2021) · Behavior Research Methods · doi:10.3758/s13428-021-01716-0 · Cited by 9
“As GEEs use quasi-likelihood estimation procedures, it is not tenable to compare the fit of nested models by means of a likelihood ratio statistic (Heck et al., 2012).”
MethodBock, N. C., Klaus, K., Liebel, M. M., et al. (2023) · Journal of Clinical Medicine · doi:10.3390/jcm12093071 · Cited by 8
“Due to the heterogeneity of variances, the SPSS procedure GENLINMIXED was applied [35].”
MethodLay explanations for poverty: A multilevel analysis of European public opinion (1976 – 2014)
Marquis, L. (2019) · Springer eBooks · doi:10.1007/978-3-658-27043-8_15 · Cited by 8
Barnes, S. R. (2016) · Animation · doi:10.1177/1746847716637823 · Cited by 8
“…linear mixed modeling respects the relationships within repeatedly measured (or dependent) categorical data and allows the data to be linked to an appropriate statistical distribution during analysis: see Heck et al. (2012) for a review of generalized mixed modeling with categorical data.”
BackgroundSalvo-Garrido, S. I., Vargas, H., Urra, O., Gálvez-Nieto, J. L., & Miranda‐Zapata, E. (2020) · Revista Iberoamericana de Diagnóstico y Evaluación - e Avaliação Psicológica · doi:10.21865/ridep55.2.04 · Cited by 9
Footedness predicts escape performance in a passerine bird
Yu, G., Guo, J., Xie, W., et al. (2020) · Ecology and Evolution · doi:10.1002/ece3.6193 · Cited by 8
The influence of housing location on energy ratings price premium in Alicante, Spain
Céspedes-López, M. F., Perez-Sanchez, V. R., & García, R. T. M. (2022) · Ecological Economics · doi:10.1016/j.ecolecon.2022.107579 · Cited by 7
Owiredua, C., Flink, I. K., & Boersma, K. (2022) · European Journal of Pain · doi:10.1002/ejp.2065 · Cited by 8
“Furthermore, the interclass correlation values were quite small (ranging between 0.01 and 0.02) to indicate any substantial evidence for clustering at the class and school level (Heck et al., 2013).”
BackgroundInfluentialAccuracy of Adult Children’s Perceptions of Mothers’ Caregiver Preferences
Suitor, J. J., Gilligan, M., Rurka, M. M., et al. (2018) · The Gerontologist · doi:10.1093/geront/gny064 · Cited by 7
“We ran an intercept-only model, which provided the variance components to calculate the interclass correlation coefficients (Heck et al., 2012).”
MethodLyons, K. M., McLaughlin, J. E., Wolcott, M. D., et al. (2019) · American Journal of Pharmaceutical Education · doi:10.5688/ajpe7212 · Cited by 7
“As the data have a nested structure ( ie, observations nested within students nested within preceptors), it would be ideal to use a multi-level model to analyze this data.(27)However,wewere unable to calculate a multilevel model because of the small sample size.”
MethodPopulation Diversity and Ancestral Diversity As Distinct Contributors to Outgroup Prejudice
Shrira, I. (2019) · Personality and Social Psychology Bulletin · doi:10.1177/0146167219880190 · Cited by 12
Malfait, S., Eeckloo, K., Opdorp, L. V., Biesen, W. V., & Hecke, A. V. (2020) · Journal of Advanced Nursing · doi:10.1111/jan.14406 · Cited by 7
Best Served Cold: Vengeful Attitudes and Violence among Finnish Adolescents
Lowe, C. C., Ellonen, N., Miller, B. L., & Peltonen, K. (2020) · Deviant Behavior · doi:10.1080/01639625.2020.1789379 · Cited by 15
Variation in egg-size traits of the European Roller (Coracias garrulus) in eastern Poland
Górski, A., Nowakowski, J. J., & Bańbura, J. (2015) · Ornis Fennica · doi:10.51812/of.133881 · Cited by 7
Leveraging social media content to support engagement in positive interventions
Sosik, V. S., & Cosley, D. (2014) · The Journal of Positive Psychology · doi:10.1080/17439760.2014.910826 · Cited by 7
Predicting Community College Outcomes: Does High School CTE Participation Have a Significant Effect?
Dietrich, C. C., Lichtenberger, E. J., & Kamalludeen, R. (2017) · Journal of Career and Technical Education · doi:10.21061/jcte.v31i1.1506 · Cited by 7
“Heck, Thomas, and Tabata (2012) explain that grand mean centering “re-centers the individual’s standing on the predictor against the mean for the predictor in the sample.”
BackgroundBlurring Lines? How Locally Based Collaborations Handle the Redistribution/Development Tradeoff
Lyon, M. A., & Henig, J. R. (2017) · Urban Affairs Review · doi:10.1177/1078087417740704 · Cited by 7
Multilevel Generalized Mantel-Haenszel for Differential Item Functioning Detection
French, B. F., Finch, W. H., & Immekus, J. C. (2019) · Frontiers in Education · doi:10.3389/feduc.2019.00047 · Cited by 7
“We note that the standard equation for the ICC is different for ordinal variables where the within variance is a constant (i.e., 3.29, Heck et al., 2013).”
BackgroundInfluentialSalvo-Garrido, S. I., Vargas, H. M., Urra, O. V., Gálvez-Nieto, J. L., & Miranda‐Zapata, E. (2019) · Preprints.org · doi:10.20944/preprints201912.0043.v1 · Cited by 6
“It is assumed that the errors have a multivariate normal distribution, with a mean vector 0 and matrix of variances and covariances ‘diagonal block’ [55].”
BackgroundMutwadi, A. M., Madinga, J. N., Vanlerberghe, V., Kingebeni, P. M., & van der Sande, M. A. B. (2024) · PLOS Global Public Health · doi:10.1371/journal.pgph.0002617 · Cited by 6
“[43].”
Treatment completion and anxiety sensitivity effects on smoking cessation outcomes
Martínez-Vispo, C., López‐Durán, A., Rodríguez‐Cano, R., Senra, C., & Becoña, E. (2021) · Addictive Behaviors · doi:10.1016/j.addbeh.2021.106856 · Cited by 6
Criminal nomadism: A neglected dimension of spatial mobility in sex offending
Michaud, P. A., Beauregard, É., & Proulx, J. (2022) · Journal of Criminal Justice · doi:10.1016/j.jcrimjus.2022.101928 · Cited by 6
Are government employees more or less likely to venture? Evidence from China
Zhao, M., Sheng, S., & Yang, X. (2023) · Journal of Business Research · doi:10.1016/j.jbusres.2022.113629 · Cited by 6
Beullens, K., & den Bulck, J. V. (2014) · Journal of Children and Media · doi:10.1080/17482798.2014.863481 · Cited by 6
“For these analyses, the procedures outlined by Heck, Thomas, and Tabata (2012) were followed.”
MethodNoé, J. M. I. (2017) · Empiria Revista de metodología de ciencias sociales · doi:10.5944/empiria.36.2017.17865 · Cited by 6
Online patient-provider cannabis consultations
Gali, K., Narode, R., Young‐Wolff, K. C., et al. (2020) · Preventive Medicine · doi:10.1016/j.ypmed.2020.105987 · Cited by 6
The perception of emotional cues by children in artificial background noise
Parada‐Cabaleiro, E., Batliner, A. M., Baird, A., & Schuller, B. W. (2020) · International Journal of Speech Technology · doi:10.1007/s10772-020-09675-1 · Cited by 6
Explaining Variation in Adoption of FinTech Products and Services Among Citizens: A Multilevel Model
Krishna, B., & Krishnan, S. (2020) · IFIP advances in information and communication technology · doi:10.1007/978-3-030-64849-7_48 · Cited by 6
The Impact of Unit Membership on Smoking Among Soldiers
Toblin, R. L., Anderson, J. A., Riviere, L. A., et al. (2016) · Military Medicine · doi:10.7205/milmed-d-15-00063 · Cited by 6
Pickman, L. L., Gelkopf, M., & Greene, T. (2020) · Stress and Health · doi:10.1002/smi.2978 · Cited by 6
Obasohan, P. E., Walters, S. J., Jacques, R., et al. (2023) · medRxiv · doi:10.1101/2023.04.10.23288389 · Cited by 6
Näsman, M., Nyqvist, F., Nygård, M., Vercauteren, T., Dury, S., & Serrat, R. (2025) · Research on Aging · doi:10.1177/01640275251351016 · Cited by 5
“A value greater than .05 can be considered to indicate suf-fi cient clustering at level 2 (Heck et al., 2014).”
Glądalski, M., Cyżewska, I., Bańbura, M., et al. (2019) · Avian Biology Research · doi:10.1177/1758155919834466 · Cited by 5
Haumann, T., Kassemeier, R., & Wieseke, J. (2021) · Springer eBooks · doi:10.1007/978-3-319-57413-4_18 · Cited by 7
Chen, N., Lee, K. J., Kim, J., & Tsai, C. L. (2022) · Leisure/Loisir · doi:10.1080/14927713.2022.2054459 · Cited by 6
“Generalized linear mixed modelling (GLMM) was utilized to conduct the two-level logistic regression model (Heck et al., 2012).”
MethodInfluentialSchlenz, M. A., Klaus, K., Schmidt, A., et al. (2022) · Clinical Oral Investigations · doi:10.1007/s00784-022-04721-5 · Cited by 5
Religion und Sozialkapital in der Schweiz
Odermatt, A. (2023) · Politik und Religion · doi:10.1007/978-3-658-41147-3 · Cited by 6
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Associations between contextual factors and school engagement: a longitudinal study of profiles
Saracostti, M., de Toro, X., Miranda, H., V, Miranda‐Zapata, E., Lara, L., & Hernández, M. T. (2024) · Frontiers in Education · doi:10.3389/feduc.2024.1365789 · Cited by 6
Evans, N., Pasman, H. R. W., Deeg, D. J. H., et al. (2015) · Journal of the American Geriatrics Society · doi:10.1111/jgs.13697 · Cited by 5
“Model specifications included a logit link function, exchangeable correlation matrix, and robust covariance matrix estimator.(7) Analyses were conducted in SPSS version 20 (IBM Software, Armonk, NY).”
MethodSuitor, J. J., Gilligan, M., Peng, S., & Rurka, M. M. (2018) · Frontiers in sociology and social research · doi:10.1007/978-3-319-71544-5_13 · Cited by 6
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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