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April 20 - 24 April 2020

The School of Management is pleased to host short courses offered by the Consortium for the Advancement of Research Methods and Analysis (CARMA).  Two courses are offered in April 2020 and the instructors are international experts in research methodology.

This is a great opportunity to practice and develop your skills in research methods and meet some of the greatest names in the field. Don’t miss the chance to learn best practice from our international experts!

Course Descriptions

Session 1

20-22 April 2020

The CARMA Introduction to Multilevel Analysis short course provides both (1) the theoretical foundation, and (2) the resources and skills necessary to conduct basic multilevel analyses. Emphasis will be placed on techniques for traditional, hierarchically nested data (e.g., children in classrooms; employees in teams). The first part of the course introduces issues related to multilevel theory (e.g., multilevel constructs; principles of multilevel theory building; cross-level inferences and cross-level biases). The second part of the course discusses issues related to multilevel measurement (e.g., aggregation; aggregation bias; composition and compilation models of emergence; estimating within-group agreement). The last part of the course focuses on the specification of basic 2-level models (e.g., children nested in classrooms; soldiers nested in platoons; employees nested within work teams) analyzed via multilevel regression (i.e., random coefficient regression; hierarchical linear model; mixed effects model). The R software package will be introduced, explained, and emphasized during this short course in preparation for the advanced short course offered in Session II. Participants who prefer HLM, SAS, SPSS, or MPlus (and have expertise with these programs) have the option of completing some assignments with these programs. Participants are encouraged to also bring datasets to the course and apply the principles to their specific areas of research. The course is best suited for faculty and graduate students who are familiar with traditional (i.e., single-level) multiple regression analysis, but have little (if any) expertise related to conducting multilevel analyses.

Session 2

22-24 April 2020

The CARMA Advanced Multilevel Analysis short course provides both (1) the theoretical foundation, and (2) the resources and skills necessary to conduct more advanced multilevel analyses. Emphasis will be placed on techniques for longitudinal data. The R software package will be introduced, explained, and used throughout this short course. The topics covered in this course include specifying and analyzing basic, 2-level, models (e.g., individuals nested in teams; repeated observations nested in individuals), as well as, more advanced 3-level models (e.g., individuals nested in teams that are nested in organizations; repeated observations nested in individuals that are nested in teams). Other topics include: multilevel mediation and the analysis of dyadic data. Exercises using real-world data, are conducted in R. Participants who prefer HLM, SAS, SPSS, or MPlus (and have expertise with these programs) will have the option of completing some assignments with these programs. Participants are encouraged to also bring datasets to the course and apply the principles to their specific areas of research. The course is best suited for faculty and graduate students who have at least some foundational understanding of issues related to multilevel data and how to analyze simple, 2-level, models.

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