AOM-CARMA June 2026 Live Online Short Courses:
Introductory Methods & Analysis
CARMA (Consortium for the Advancement of Research Methods & Analysis) is a non-profit academic center at Texas Tech University, proudly celebrating 26 years of providing top-tier research methods education. We are excited to continue our partnership with AOM through our Affiliate Program, which offers access to some of CARMA's many education resources. We want to let AOM members know that we have five great courses focusing on introductory methods & analysis: Intro. to ESM; Intro. to Multilevel Analysis, Intro. to SEM with LAVAAN, Intro. to Meta-Analysis, and Measurement Development/Evaluation/Adaptation. Details on these courses and 18 others are provided below.
Unbeatable Pricing-Register Now!
To support students, educators, and researchers, we are offering our lowest prices ever on CARMA's Live Online June Short Courses. AOM-CARMA Affiliate Program Members register now for just $300 through April 26; registration pricing will be $350 April 27 – May 10. Take advantage of our lowest pricing model ever -review the course list below, find the best courses for you, and register now!.
Choose from 23 Live Online Short Courses in June 2026 Offered Across Two Sessions!
CARMA's June Live Online Short Courses are built to strengthen your research skills alongside leading management scholars. You can choose from 23 courses offered across two sessions, spanning four focus areas: Data Technology, Advanced Methods & Analysis, Introductory Methods & Analysis, and Qualitative Methods. Session I runs June 1–4, followed by Session II on June 8–11.
View the Short Course Preview Playlist
View the full June 2026 Live Online Short Course Preview playlist on CARMA's YouTube Channel.
Introductory Methods & Analysis
Session I
· Introduction to Experience Sampling Methods: Design & Measurement (Dr. Shawn McClean)
o Join us for an enlightening workshop on "Experience Sampling: Design and Measurement," where we delve into the dynamic world of within-individual research methodologies. This comprehensive course will guide you through the theoretical underpinnings of experience sampling and related methodologies, offering a deep understanding of its significance in capturing real-time, real-world data. We'll explore the practicalities of study logistics, ensuring you're well-equipped to design and execute studies with precision and efficiency. Dive into the intricacies of survey design, learning how to craft questions that yield meaningful and reliable responses. Additionally, we'll cover effective survey administration techniques, focusing on timing, frequency, and response optimization to ensure high-quality data collection. Whether you're a faculty member or PhD student, with experience in this approach or interested in trying it out, this workshop will provide you with the essential tools and knowledge to excel in the field of within-individual research.
· Introduction to Multilevel Analysis: Theory, Measurement, and Two-Level Nested Models (Dr. James LeBreton)
o 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., students in classrooms; employees in teams). Part 1 of the course introduces issues related to multilevel theory (e.g., multilevel constructs, principles of multilevel theory building). Part 2 discusses issues related to multilevel measurement (e.g., data aggregation; estimating within-group agreement). Part 3 discusses the alignment of multilevel theory, analyses, and inferences (e.g., cross-level inferences; cross-level biases). Part 4 focuses on the basic 2-level model (e.g., students nested in classrooms; soldiers nested in platoons; employees nested in work teams) analyzed using multilevel regression (i.e., random coefficient regression; mixed effects models). The R software package will be used throughout this short course. 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 with multilevel analyses.
· Introduction to SEM with LAVAAN (Dr. Yifan Song)
o This introductory course requires no previous knowledge of structural equation modeling (SEM), but participants should possess a strong understanding of regression AND have understanding about the basic data handling functions using R. All illustrations and in-class exercises will make use of the R LAVAAN package, and participants will be expected to have LAVAAN installed on their laptop computers prior to beginning of the course. No course time will be spent going over basic R data handling and installing the LAVAAN package. The course will start with an overview of the principals underlying SEM. Subsequently, we move into measurement model evaluation including confirmatory factor analysis (CFA). Time will be spent on interpreting the parameter estimates and comparing competing measurement models for correlated constructs. We will then move onto path model evaluation where paths representing "causal" relations are placed between the latent variables. Again, time will be spent on interpreting the various parameter estimates and determining whether the path models add anything above their underlying measurement models. If time permits, longitudinal models will be introduced.
Session II
· Introduction to Meta-Analysis (Dr. Dana Joseph)
o Meta-analysis have now become a staple of research in the organizational sciences. Their purpose is to summarize and clarify the extant literature through systematic and transparent means. Meta-analyses help answer long-standing questions, address existing debates, and highlight opportunities for future research. Despite their prominence, knowledge and expertise in meta-analysis is still restricted to a relatively small group of scholars. This short course is intended to expand that group by familiarizing individuals with the key concepts and procedures of meta-analysis with a practical focus. Specifically, the goal is to provide the necessary tools to conduct and publish a meta-analysis/systematic review using best practices. We will cover how to; (a) develop research questions that can be addressed with meta-analysis, (b) conduct a thorough search of the literature, (c) provide accurate and reliable coding, (d) correct for various statistical artifacts, and (e) analyze bivariate relationships (e.g., correlations, mean differences) as well as multivariate ones using meta-regression and meta-SEM. The course is introductory, so no formal training in meta-analysis is needed. Familiarity with some basic statistical concepts such as sampling error, correlation, and variation is sufficient.
o This introductory course will help you develop your model, develop and select measures, design survey instruments and execute your data collection. Before testing hypotheses about relationships between constructs, i.e., your hypotheses, it is imperative to demonstrate that your measures have construct validity. There will be special focus on more stringent standards and techniques and evolving trends in evaluating construct validity. Then we will apply this understanding of up-to-date construct validity practices to scale development techniques by creating new measures or revising existing measures that can pass the hurdles posed by tests of construct validity. Topics include designing your project (developing a model, selecting variables, sampling requirements), writing survey items, content and discriminant validity tests, and EFA/CFA procedures. We draw from research on how respondents interpret surveys to reveal principles for how to design your questionnaire to obtain high quality data. Finally, we will cover procedures for managing the data collection process including techniques for dealing with missing data, outliers, and careless responders. If you wish, bring your research ideas because there will be opportunities to advance your own project within the workshop.
Other Session I Offerings: (Displayed as divided by content areas)
- Advanced Methods and Analysis
Other Session II Offerings: (Displayed as divided by content areas)
- Advanced Methods and Analysis
Dr. Larry Williams, CARMA Director
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Larry Williams
Professor
Texas Tech University
Lubbock TX
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