Multilevel Modeling References

Updated July 2018 by R. Eckardt

Overview of Multilevel Research

Aguinis, H., Boyd, B. K., Pierce, C. A., & Short, J. C. 2011. Walking new avenues in management research methods and theories: Bridging micro and macro domains. Journal of Management, 37(2), 395-403.

Buckley, M. R., Hamdani, M. R., Klotz, A. C., & Valcea, S. 2011. Into the great wide open: Bridging the micro-macro divide in the organizational sciences. In D. Bergh & D. J. Ketchen (eds.) Research Methodology in Strategy and Management, 6, 31-68.

Eckardt, R., Crocker, A., Ahn, Y., Floyd, S., Boyd, B., Hodgkinson, G., Kozlowski, S., Moliterno, T., and Starbuck, W. in press. Reflections on the micro-macro divides: Ideas from the trenches and moving forward.” Strategic Organization.

Felin, T., Foss, N. J., & Ployhart, R. E. 2015. The microfoundations movement in strategy and organization theory. Academy of Management Annals, 9, 575-632

Hitt, M. A., Beamish, P. W., Jackson, S. E. & Mathieu, J. E. 2007. Building theoretical and empirical bridges across levels: Multilevel research in management. Academy of Management Journal, 50, 1385-1399.

House, Rousseau, & Thomas-Hunt, 1995. The meso paradigm: A framework for the integration of micro and macro organizational behavior. Research in Organizational Behavior, 17, 71-114

Klein, K. J., Dansereau, F. & Hall, R., J. 1994. Levels issues in theory development, data collection, and analysis. Academy of Management Review, 19, 195-229.

Klein, K. J. & Kozlowski, S. W. J. (eds.) 2000. Multilevel Theory, Research, and Methods in Organizations, San Francisco, CA: Jossey-Bass Publishers.

Klein, K. J. & Kozlowski, S. W. J. 2000. From micro to meso: Critical steps in conceptualizing and conducting multilevel research. Organizational Research Methods, 3, 211-236

Klein, K.J., Tosi, H., & Cannella, A.A. 1999. Multilevel theory building: Benefits, barriers, and new developments. Academy of Management Review, 24, 243-248.

Mathieu, J.E. & Chen, G. 2011. The etiology of the multilevel paradigm in management research. Journal of Management. 37, 610-641

Mathieu, J. E. & Luciano, M. M. in press. Multilevel emergence in work collectives. In S. E. Humphrey & J. M. LeBreton (Eds.), The Handbook for Multilevel Theory, Measurement and Analysis.

Molloy, J. C., Ployhart, R. E., & Wright, P. M. 2011. The myth of the micro–macro divide: Bridging system-level and disciplinary divides. Journal of Management. 37, 1496-1518

Moliterno, T. P., & Ployhart, R. E. 2016. Multilevel models for strategy research: An idea whose time (still) has come. In C. Cinici & G. B. Dagnino (Ed.), Research Methods for Strategic Management.

Rousseau, D. M. 1985. Issues of level in organizational research: Multi-level and cross-level perspectives. In Cummings, L. L. & Staw, B. M. (eds.) Research in Organizational Behavior. Greenwich, CT: JAI Press, Inc., 1-37.

Data Aggregation, Emergence and Bottom-Up Effects

Beal, D.J. 2015. State of the art and future potential of experience sampling methods in organizational research. Annual Review of Organizational Psychology and Organizational Behavior, 2: 383-407.

Biemann, T. & Kearney, E. Size does matter: How varying group sizes in a sample affect the most common measures of group diversity. Organizational Research Methods, 13, 582-599

Bliese, P. D. 2000. Within-group agreement, non-independence, and reliability: Implications for data aggregation and analyses. In K. J. Klein and S. W. J. Kozlowski (Eds.), Multilevel Theory, Research, and Methods in Organizations: 349-381.

Chaffin, D., Heidl, R., Hollenbeck, J. R., Howe, M., Yu, A., Voorhees, C., & Calantone, R. 2017. The promise and perils of wearable sensors in organizational research. Organizational Research Methods, 20: 3-31.

Chan, D. 1998. Functional relations among constructs in the same content domain at different levels of analysis: A typology of composition models. Journal of Applied Psychology, 83, 234-246

Chen, G. 2005. The conceptualization, measurement, and validation of multilevel constructs. Center for the Advancement of Research Methods and Analysis, Video Library: https://razor.med.und.edu/carma/

Croon, M. A. & van Veldhoven, M. J. P. M. 2007. Predicting group-level outcome variables from variables measured at the individual level: A latent variable multilevel model. Psychological Methods, 12, 45-57.

Fioretti, G. 2012 Agent-based simulation models in organization science. Organizational Research Methods, 16: 227-242.

Gabriel, A. S., Diefendorff, J. M., Bennett, A. A., & Sloan, M. D. 2017. It's about time: The promise of continuous rating assessments for the organizational sciences. Organizational Research Methods, 20, 32-60.

Gonzalez-Roma, V. & Hernandez, A. 2017. Multilevel modeling: Research-based lessons for substantive researchers. Annual Review of Organizational Psychology and Organizational Behavior, 4, 183-210.

Grand, J. A., et al. 2016. The dynamics of team cognition: A process-oriented theory of knowledge emergence in teams. Journal of Applied Psychology, 101, 1353-1385

Griffin, M.A. 1997. Interactions between individuals and situations: Using HLM procedures to estimate reciprocal relationships. Journal of Management, 23, 759-773.

Harrison, D. A. & Klein, K. J. 2007. What’s the difference? Diversity constructs as separation, variety, or disparity in organizations. Academy of Management Review, 32, 1199-1228.

Kozlowski, S. W. J., & Klein, K. J. 2000. A multilevel approach to theory and research in organizations: Contextual, temporal, and emergent processes. In K. J. Klein & S. W. J. Kozlowski (Ed.), Multilevel Theory, Research, and Methods in Organizations: 3-90.

Kozlowski, S. W. J. 2012. Emergent phenomena: Theory and methodologies. Center for the Advancement of Research Methods and Analysis, Video Library: https://razor.med.und.edu/carma/

Kozlowski, S. W. J. & Chao, G. T. 2018. Unpacking team process dynamics and emergent phenomena: Challenges, conceptual advances, and innovative methods. American Psychologist, 73: 576-592.

Kozlowski, S. W. J., et al. 2013. Advancing multilevel research design: Capturing the dynamics of emergence. Organizational Research Methods, 16, 581 – 615.

Kozlowski, S. W. J., et al. 2014. Capturing the multilevel dynamics of emergence: Computational modeling, simulation, and virtual experimentation. Organizational Psychology Review, 6, 3 – 33.

Kozlowski, S. W. J., et al. 2015. Team dynamics: using "big data" to advance the science of team effectiveness. In S. Tonidandel, E. King, & J. Cortina (Eds.), Big Data at Work: The Data Science Revolution and Organizational Psychology: 272-309.

Lang, J. W. B. & Bliese, P. D. in press. A temporal perspective on emergence: using 3 level mixed effects models to track consensus emergence in groups. In S. E. Humphrey & J. M. LeBreton (Ed.), The handbook for multilevel theory, measurement and analysis.

Lang, J. W. B., Bliese, P. D., & Voogt, A., 2018. Modeling consensus emergence in groups using longitudinal multilevel methods. Personnel Psychology, 71: 255-281.

LoPilato, A. C., & Vandenberg, R. J. 2015. The not so direct cross-level direct effect. In C. E. Lance & R. J. Vandenberg (Eds.), More Statistical and Methodological Myths and Urban Legends: 292-310.

Ludtke et al., 2008. The multilevel latent covariate model: A new, more reliable approach to group-level effects in contextual studies. Psychological Methods, 3, 203-229.

Sayama, H. 2015. Introduction to the Modeling and Analysis of Complex Systems. Geneseo, NY: Open SUNY

Waller, M. J., Okhuysen, G.O., & Saghafian, M. 2016. Conceptualizing emergent states: A strategy to advance the study of group dynamics. Academy of Management Annals, 10, 561 – 598

Wang, M., Zhou, L., Zhang, Z. 2016. Dynamic modeling. Annual Review of Organizational Psychology and Organizational Behavior, 3: 241-266.

Multilevel Statistical Techniques

Aguinis, H., Gottfredson, R. K. & Culpepper, S. A. 2013. Best practice recommendations for estimating cross-level interaction effects using multilevel modeling. Journal of Management, 39, 1490-1528.

Aguinis, H., & Culpepper, S. A. 2015. An expanded decision-making procedure for examining cross-level interaction effects with multilevel modeling. Organizational Research Methods, 18, 155-176

Bliese, P. D. & Lang, J. W. 2016. Understanding relative and absolute change in discontinuous growth models: Coding alternatives and implications for hypothesis testing. Organizational Research Methods, 19: 562-592.

Bliese, P. D., Maltarich, M. A., Hendricks, J. L. 2018. Back to basics with mixed-effects models: Nine take-away points. Journal of Business and Psychology, 33, 1-23.

Bliese, P. D. & Ployhart, R. E. Growth modeling using random coefficient models: Model building, testing, and illustrations. Organizational Research Methods, 5: 362-387.

Dansereau, F. & Yammarino, F. J. 2000. Within and between analysis: The variant paradigm as an underlying approach to theory building and testing. In K. J. Klein & S. W. J. Kozlowski (Ed.), Multilevel Theory, Research, and Methods in Organizations: 3-90.

Enders, C. K. & Tofighi, D. 2007. Centering predictor variables in cross-sectional multilevel models: A new look at an old issue. Psychological Methods, 2, 121-138

Gelman, A. & Hill, J. 2007. Data Analysis Using Regression and Multilevel/Hierarchical Models, New York, NY, Cambridge University Press.

Han, 2005. Crossover linear modeling: Combining multilevel heterogeneities in crossover relationships. Organizational Research Methods, 8, 290 - 316.

Hofmann, D. A. 1997. An overview of the logic and rationale of hierarchical linear models. Journal of Management, 23, 723-744.

Hofmann, D. A. 2005. Hierarchical linear modeling. Center for the Advancement of Research Methods and Analysis, Video Library: https://razor.med.und.edu/carma/

Hofmann, D. A., & Gavin, M. B. (1998). Centering decisions in hierarchical linear models: Implications for research in organizations. Journal of Management, 24(5), 623-641.

McNeish, D., & Kelley, K. (in press). Fixed effects models versus mixed effects models for clustered data: Reviewing the approaches, disentangling the differences, and making recommendations. Psychological Methods.

McNeish, D., Stapleton, L. M., & Silverman, R. D. (2017). On the unnecessary ubiquity of hierarchical linear modeling. Psychological Methods, 22(1), 114.

Preacher, K. J., Curran, P. J., & Bauer, D. J. (2006). Computational tools for probing interactions in multiple linear regression, multilevel modeling, and latent curve analysis. Journal of Educational and Behavioral Statistics, 31(4), 437-448.

Raudenbush, S. W. & Bryk, A. S. 2002. Hierarchical Linear Models: Applications and Data Analysis Methods, Thousand Oaks, California, SAGE Publications, Inc.

Short, J. C., Ketchen, D. J., Bennett, N. & du Toit, M. 2006. An examination of firm, industry, and time effects on performance using random coefficients modeling. Organizational Research Methods, 9, 259-284.

Vandenberg, R.J. 2005. Multilevel structural equation methods. Center for the Advancement of Research Methods and Analysis, Video Library: https://razor.med.und.edu/carma/

Williams, L. J., Vandenberg, R. J., & Edwards, J. R. (2009). Structural equation modeling in management research: A guide for improved analysis. Academy of Management Annals, 3(1), 543-604.

Multilevel Mediation

Preacher, K. J., Zyphur, M. J., & Zhang, Z. (2010). A general multilevel SEM framework for assessing multilevel mediation. Psychological Methods, 15(3), 209-233.

Zhang, Z., Zyphur, M. J. & Preacher, K. J. (2009). Testing multilevel mediation using hierarchical linear models: Problems and solutions. Organizational Research Methods, 12(4), 695-719.

Zhang, Z., 2016. Multilevel mediation. Center for the Advancement of Research Methods and Analysis, Video Library: https://razor.med.und.edu/carma/

Multilevel Networks

Kim, J. Y., Howard, M., Pahnke, E. C., & Boeker, W. 2016. Understanding network formation in strategy research: Exponential random graph models. Strategic Management Journal, 37, 22-44.

Lomi, A., Robins, G., & Tranmer, M. 2016. Introduction to multilevel social networks. Social Networks, 44, 266-268.

Lusher, D., Koskinen, J. & Robins, G. 2013. Exponential Random Graph Models for Social Networks: Theory, Methods, and Applications. Cambridge University Press.

Moliterno, T. P. & Mahony, D. M. 2011. Network theory of organization: A multilevel approach. Journal of Management, 37, 443-467.

Piepenbrink, A. & Gau, A. S. 2013. Methodological advances in the analysis of bipartite networks: An illustration using board interlocks in Indian firms. Organizational Research Methods, 16, 474 - 496.

Quintane, E., Conaldi, G., Tonellato, M., & Lomi, A. 2014. Modeling relational events: A case study on an open source software project. Organizational Research Methods, 17, 23-50.

Snijders T. A. 2016. The multiple flavours of multilevel issues for networks. In Lazega E., Snijders T. (eds) Multilevel Network Analysis for the Social Sciences.

Snijders, T. A. & Steglich, C. A. 2015. Representing micro-macro linkages by actor-based dynamic network models. Sociological Methods & Research, 44, 222-271.

Snijders, T. A., Van de Bunt, G. G., & Steglich, C. E. 2010. Introduction to stochastic actor-based models for network dynamics. Social networks, 32, 44-60.

Wang, P., Robins, G., Pattison, P., & Lazega, E. 2013. Exponential random graph models for multilevel networks. Social Networks, 35, 96-115.

Wang, P., Robins, G., Pattison, P., & Lazega, E. 2016. Social selection models for multilevel networks. Social Networks, 44, 346-362.

Zappa, P. & Lomi, A. 2015. The analysis of multilevel networks in organizations: Models and empirical tests. Organizational Research Methods, 18, 542-569.

Dyads

Gooty, J. & Yammarino, F. J. 2011. Dyads in organizational research: Conceptual issues and multilevel analyses. Organizational Research Methods, 14, 456 - 483.

Kenny, D., Kashy, D. A., & Cook, W. L. 2006. Dyadic Data Analysis. New York: Wiley.

Krasikova, D. V. & LeBreton, J. M. 2012. Just the two of us: Misalignment of theory and methods in examining dyadic phenomena. Journal of Applied Psychology, 97: 739-757.

Statistical Power in Multilevel Studies

Mathieu, J. E., Aguinis, H., Culpepper, S. A. & Chen, G. 2012. Understanding and estimating the power to detect cross-level interaction effects in multilevel modeling. Journal of Applied Psychology, 97, 951-966.