SMA-CARMA Affiliate Program

Available for Current SMA Members

About SMA-CARMA Affiliate Program

We are excited to announce that current SMA Student and Academic members can now access CARMA’s research methods education resources as part of their membership benefits. These resources cover quantitative and qualitative topics at the introductory and advanced levels. These benefits will be delivered through the 2023-2024 SMA-CARMA Affiliate Program. Benefits are easily available without advanced registration for most events. Benefits include:

  1. Free access to live 2023-2024 Webcast Lecture Series
  2. Free access to Video Library
  3. Free access to live Ask-the-Experts and Ph.D. Prep panel events
  4. A 50% discount on short course registration fees


Please follow the steps below to sign-up with CARMA and to register for the SMA-CARMA Affiliate Program

How to Sign-Up with CARMA

  • Current SMA membership IS required.
  • Register as a Website User.

How to Register for the SMA-CARMA Affiliate Program

  • To join the program, log-in to your SMA account by clicking the button below.
  • In the information area click the CARMA globe logo.
  • Follow the code instructions on the Registration: SMA-CARMA Affiliate Program page.

How to Enjoy Benefits of the Program

  • Access the CARMA User Area using the link or through our homepage.
  • To view Video Library recordings, under the “Access Recording” tab, select the “Institutional and Affiliate Member Access” link.
  • To view Live events, under the “Access Live Events” tab, select the “Join” buttons a few minutes before the events.

Workshop #1

Topic: Open Science Principles and Practices: A Session for Building Skills and Community


  • Dr. Andreas Schwab, Iowa State University
  • Dr. Chris Castille, Nicholls State University

Workshop #2

Topic: Endogeneity and the Methodology-Practice Divide


  • Dr. Aaron Hill, University of Florida
  • Dr. Lindsey Greco, Oklahoma State University

Current Approaches to Analyzing Panel Data

Presenter: Dr. Michael Withers, Texas A&M University


Panel data is a form of longitudinal data that has both a cross-sectional dimension and time-series dimension. This type of data is increasingly used by organizational scholars to test theorized relationships. Panel data allows researchers to track changes in individual units over time and to analyze the effects of various independent variables on these changes. Several techniques are used to analyze panel data. Some rely on approaches that use only within-firm variance, while others rely on approaches that use both within- and between-firm variance. The former approach is referred to as fixed effects, while the latter is called random effects. Fixed effects models are used to account for all time-invariant factors that may affect the dependent variable, while random effects models allow for the estimation of both time-invariant and time-varying factors. The between-within (hybrid) model seeks to capture the benefits of both random and fixed effects models by including both variance types in the model. In this session, the advantages and disadvantages of panel data will be discussed, along with the theoretical issues related to its use. The focus will be on exploring the most popular ways to analyze panel data, with an emphasis on fixed and random effects models. Finally, the between-within (hybrid) model will be examined, which combines the strengths of both types of models to provide a more comprehensive analysis of panel data.

May I Have Your Attention? Practical Advice for Managing Careless Responding

Presenter: Dr. Nathan Bowling, University of Central Florida


Careless responding, which occurs when study participants display inadequate effort while responding to a given measure (e.g., a self-report scale or mental ability test), is a ubiquitous problem that threatens the validity of research conclusions. I will begin this session by briefly reviewing the careless responding literature. This review will include a summary of the nature, predictors, and consequences of careless responding. I will then discuss in detail two approaches to dealing with this problem: (a) omitting data from careless participants, and (b) the prevention of careless responding. Attendees will learn how to assess and manage careless responding—knowledge that will help them improve the quality of their own research.

Testing measurement and path models using lavaan

Presenter: Dr. Bob Vandenberg, University of Georgia


This session starts with an overview of the principles underlying SEM and moves into measurement model evaluation including confirmatory factor analysis (CFA). We will cover interpretation of parameter estimates and comparison of competing measurement models for correlated constructs. We will also cover path model evaluation where paths representing “causal” relations are placed between the latent variables with an emphasis on interpreting the various parameter estimates and determining whether the path models add anything above their underlying measurement models. All illustrations and exercises will make use of the R LAVAAN package; it is recommended that participants have an understanding of regression and basic data handling function using R.

So, You Want to Conduct an Experience-Sampling Study. Now What?

Presenter: Dr. Joel Koopman, Texas A&M University


Scholars are increasingly using an experience-sampling methodology to answer their research questions. However, conducting such a study is quite different than conducting the more familiar cross-sectional or multi-wave study, and involves asking questions such as “How do I get people to stay in the study,” “How do I design my surveys,” and even “Should I conduct this study at all?” We will explore theoretical, empirical, and practical issues associated with conducting experience-sampling research. (suggested pairing with “Multilevel Concepts and Principles” taught by Dimotakis)

Qualitative Data Analysis

Presenter: Dr. Anne Smith, University of Tennessee Knoxville


The focus of this seminar is analysis of qualitative data using innovative and novel approaches that demonstrate a rigorous and trustworthy analysis process. The seminar will provide actionable steps to analyze data, especially process data, building on novel, pragmatic, and recent insights from the 2022 Organizational Research Methods special feature on qualitative research.

Qualitative Comparative Analysis

Presenter: Dr. Thomas Greckhamer, Louisiana State University


This PDI offers an introduction to Qualitative Comparative Analysis (QCA), an approach that has rapidly gained in popularity in management studies. I will provide a general overview of QCA’s set theoretic foundations and logic. I will also introduce the basics of crisp set (csQCA) and fuzzy set (fsQCA) approaches and illustrate these approaches’ potential for research on management and organizations.

Preparing Data for Analysis

Presenter: Dr. Justin DeSimone, University of Alabama


A key step between data collection and data analysis involves preparing data for analysis. Incorrect, incompatible, or incomplete data within a data set can be a significant threat to data analysis, potentially leading to problems analyzing and interpreting data. This session covers data preparation activities such as screening, formatting, and transforming data. This session will discuss proactive and reactive strategies to addresses careless responding, missing data, outliers, low response rates, and issues related to common method variance (CMV).

Multilevel Concepts and Principles

Presenter: Dr. Nikolaos Dimotakis, Oklahoma State University & Dr. Sherry Fu, Colorado State University


This workshop focuses on the conceptual underpinnings of multilevel models. We will discuss how dependence within a dataset can be a nuisance or a phenomenon of interest, and how theory-derived processes can be homologous or heterologous across levels. We’ll go over foundational models in multilevel approaches, and discuss how these can be used to answer various types of research questions. We will also have an overview of data analytical options and the decisions these involve. (suggested pairing with “So,You Want to Conduct an Experience-Sampling Study. Now What?” taught by Koopman)

Workshop #3

Topic: Designing and Publishing Replication Studies


  • Dr. Maria Kraimer, Rutgers University
  • Dr. William (Billy) Obenauer, The University of Maine
  • Dr. Bill Schulze, University of Utah
  • Dr. Andreas Schwab, Iowa State University
  • Dr. Scott Seibert, Rutgers University

Workshop #4

Topic: Ethnographic Methods for Management Research


  • Dr. Michael Lerman, Iowa State University
  • Dr. Melissa Cardon, University of Tennessee

SMA-CARMA Affiliate Program Benefits

  • Live Online Short Courses

One-hour sessions focusing on research methods and data analysis. The courses prioritize hands-on experience and practical application, providing an equal balance of lecture and lab time. Instructors are esteemed methodological scholars with expertise in organizational studies and management, some of whom have served as editors for top organizational journals. The list of CARMA Short Courses covers both introductory and advanced training on quantitative and qualitative topics, including rare content not readily available at other institutions. These courses also offer networking opportunities with leading scholars and peers in participants’ areas of interest.

  • Video Library

Access over 250+ recorded lectures from esteemed scholars on various research methods in our Video Library since 2004. We’ve since improved the search and viewing process for a better user experience. Affiliate members can access videos on-demand from anywhere and test their understanding of concepts through quizzes. Our videos serve as a valuable resource for authors, reviewers, editors, and instructors and aid in enriching the learning experience.

  • Other Live Events

    • Webcast Lecture Series

Webcast Lecture Series offers annual live webcast lectures by esteemed methodologists. Designed for university faculty, graduate students, and researchers, these lectures cover introductory and advanced topics in research methods and data analysis, emphasizing practical application. Background readings, references, and slides will be available on the CARMA website before each lecture. We are currently offering 12 one-hour webcast lectures for the 2023-2024 year. Click here for more information.

    • Ph.D. Prep Panels

Ph.D. Prep Panels for consist of live online events aimed at enhancing research methods knowledge and skills for success in doctoral studies and academia. The sessions cater to the specific needs of early, middle, and late-stage doctoral students, covering various topics such as developing a research pipeline, using multiple research methods, and aligning conceptual and empirical analysis in a thesis/dissertation. Additionally, the panels offer a networking opportunity for students from different schools, complementing their doctoral programs’ activities. Click here for 2023-2024 information.