Short Courses

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Upcoming Short Courses

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2016 CARMA Short Courses in Adelaide, Australia

Courses hosted by School of Management, University of South Australia

November 14-18, 2016 - Two Sessions, Three Courses

We offer two sessions of courses in order to allow participants to take two back-to-back methods courses. You may select one course from Session I and one course from Session II.

Short Course Topics, Instructors and Summaries

Session I: November 14 and 15 (full days), 16 (a.m. half day)

Course - "Introduction to Research Methods II, Linear Regression"

Dr. Larry Williams, University of Nebraska-Lincoln

Dr. Larry Williams, University of Nebraska-Lincoln, College of Business Administration

Course Description - This short course will begin with a brief review of correlations and hypothesis testing. Next the basics of linear regression with a single predictor will be introduced, including consideration of OLS estimation and associated statistical testing (e.g. t-test, F-test, confidence interval, statistical power). These basics will be introduced using a continuous predictor, and then dummy variables for categorical variables will be covered. Finally, extension of the above topics to the case of two predictors will be covered. For most topics, examples and assignments will be provided.

Required Software: TBA


Course - “Intermediate Regression Analysis”

Dr. Ron Landis, Illinois Institute of Technology

Dr. Ron Landis, Illinois Institute of Technology

Course Description - This short course will begin with a brief review of linear regression, followed by consideration of advanced topics including multivariate regression, use of polynomial regression, logistic regression, and the general linear model. We will pay particular attention to using regression to test models involving mediation and moderation. For all topics, examples will be discussed and assignments completed using either data provided by the instructor or by the short course participants.

Required Software: TBA

Session II: November 16 (p.m. half day), 17 and 18 (full days)

Course - “Analysis of Big Data”

Dr. Fred Oswald, Rice University

Dr. Fred Oswald, Rice University

Course Description - This short course provides students with hands-on skills for developing and running predictive models for relevant to 'big data' in organizations. A range of predictive models will be covered: e.g., lasso and elastic net regression, random forest, stochastic gradient boosted trees, and support vector machines. R and all required R packages need to be set up on your laptop beforehand; the instructor will provide set-up instructions and guidance in advance; other data, materials, and assignments will be provided by the instructor (code, files).

Required Software: TBA

Registration, Pricing, Advanced Registration Deadline

To register for 2016 CARMA Short Courses in Adelaide, Australia you must first log in to your CARMA account. (If you do not already have an account, please sign-up as a website user). Once you have logged in, and you are in the User Area, select "Purchase Short Course" on the right side of the page.

Non-member prices per course: *All prices are in US Dollars (USD)

• Faculty/Professional: $900.00
• Students: $700.00

CARMA Member prices per course

• CARMA Members Faculty/Professional: $450.00
• CARMA Members Students: $350.00

Find out if your organization is a CARMA Consortium Webcast Member. (US and Canada institutions only)

Find out if your organization is a CARMA International Video Library Program Member. (institutions outside US and Canada only)

If your organization is not yet a member but would like to become one, please contact us directly at und.carma@und.edu

All participants are eligible for the following discount:
• Register for both sessions, receive $75 off the total price.

2017 CARMA Short Courses in Columbia, South Carolina

Courses hosted by University of South Carolina

January 5-7, 2017 – Three Courses

Courses are offered concurrently so you may only select one to take for the duration of the Session.

Short Course Topics, Instructors, and Summaries

Session I: January 5 and 6 (full days), 7 (a.m. half day)

Course: "Introduction to SEM"

Dr. Larry Williams, University of Nebraska-Lincoln

Dr. Larry Williams, University of Nebraska-Lincoln, College of Business Administration

Course Description - The Introduction to Structural Equation Methods Short Course provides (a) introductory coverage of latent variable techniques, including confirmatory factor analysis and structural equation methods with latent variables, (b) discussion of special issues related to the application of these techniques in organizational research, and (c) a comparison of these techniques with traditional analytical approaches. This Short Course will contain a balance of lecture and hands-on data analysis with examples and assignments, and emphasis will be placed on the application of SEM techniques to organizational research problems. Participants will:
• develop skills required to conduct confirmatory latent variable data analysis, based on currently accepted practices, involving topics and research issues common to organizational research.
• learn the conceptual and statistical assumptions underlying confirmatory latent variable analysis.
• learn how to implement data analysis techniques using software programs for confirmatory modeling. Special emphasis will also be placed on the generation and interpretation of results using the contemporary software programs LISREL, MPlus, and Amos.
• learn how latent variable techniques can be applied to contemporary research issues in organizational research.
• learn how the application of current latent variable techniques in organizational research differs from traditional techniques used in this literature
• complete in-class exercises using their preferred package (LISREL, MPlus, and Amos)

Required Software: LISREL (free trial edition), MPlus or Amos

Note: For those without current access to an SEM package, LISREL has a free trial edition that you should download no earlier than 1 week before class. The MPlus demo is not adequate for this course.


Course - “Introduction to Multilevel Analysis”

Dr. Paul Bliese, University of South Carolina

Dr. Paul Bliese, University of South Carolina

Course Description - The CARMA Multilevel Analysis short course provides both (1) the theoretical foundation, and (2) the resources and skills necessary to conduct a wide range of multilevel analyses. The course covers within-group agreement, nested 2-level multilevel modeling and growth modeling. All practical exercises are conducted in R. Participants are encouraged to bring datasets to the course and apply the principles to their specific areas of research.


Course - “Introduction to Longitudinal Analysis”

Dr. Rob Ployhart, University of South Carolina

Dr. Rob Ployhart, University of South Carolina

Course Description - Nearly all phenomena studied within the organizational and social sciences evolve, transform, or change over time. Unfortunately, there is still little research that explicitly adopts a longitudinal perspective. This neglect is due to theoretical, methodological, and analytical challenges. First, most theories offer little insight into how and why change occurs. Second, there are a variety of design and measurement complexities that are unique to longitudinal designs. Finally, a number of different analytical approaches can be used to model the same data, yet there is little guidance for identifying which approach is most appropriate in a given situation. The purpose of this workshop is to introduce scholars to longitudinal research. We will first discuss theoretical and conceptual issues that must be addressed when developing a longitudinal study. We will next consider how to design a longitudinal study, including how to anticipate and reduce the common problems that nearly always occur (e.g., attrition). We will conclude by spending considerable time reviewing and using different longitudinal analytic methods, including repeated measures GLM, random coefficient growth models, and latent growth models. Students are strongly encouraged (but not required) to bring their own datasets to be modeled during the workshop.

Registration, Pricing, Advanced Registration Deadline

To register for 2017 CARMA Short Courses at the University of South Carolina, you must first log in to your CARMA account. (If you do not already have an account, please sign-up as a website user). Once you have logged in, and you are in the User Area, select "Purchase Short Course" on the right side of the page.

Non-member prices per course: *All prices are in US Dollars (USD)

• Faculty/Professional: $800.00
• Students: $600.00

CARMA Member prices per course

• CARMA Members Faculty/Professional: $400.00
• CARMA Members Students: $300.00

Find out if your organization is a CARMA Consortium Webcast Member. (US and Canada institutions only)

Find out if your organization is a CARMA International Video Library Program Member. (institutions outside US and Canada only)

If your organization is not yet a member but would like to become one, please contact us directly at und.carma@und.edu

All participants are eligible for the following discount:
• Register for both sessions, receive $75 off the total price.

Short Courses in Adelaide, Australia, April 18-22

Courses hosted by School of Management, University of South Australia

April 18-22, 2016 - Two Sessions, Three Courses

We offer two sessions of courses in order to allow participants to take two back-to-back methods courses. You may select one course from Session I and one course from Session II.

Short Course Topics, Instructors and Summaries

Session I: April 18 & 19 (full days), 20 (AM half day)

  • "Qualitative Methods"
Dr. Rhonda Reger
Dr. Rhonda Reger

Dr. Rhonda Reger, The University of Tennessee, Knoxville

Course Description

In this course, students will be exposed to findings about the prevalence of research methods currently used in macro-level management fields, specifically in strategic management, organization theory and entrepreneurship in the Academy of Management Journal and the Strategic Management Journal. The course will provide a deeper grounding in several qualitative methods including comparative case study research, content analysis, discourse analysis, rhetorical analysis, and repertory grid interview methods. The course will be interactive with discussion of exemplar papers that showcase each of these methods. Students will also be given the opportunity to “pilot test” the methods by interviewing each other and content analyzing a small sample of text. A focus of this workshop will be on matching methods to research questions and the interests and strengths of the research team.

Required Software: TBA


Session II: April 20 (p.m. half day), 21 & 22 (full days)

  • "Introduction to Research Methods"
Dr. Larry Williams
Dr. Larry Williams

Dr. Larry J Williams, University of Nebraska-Lincoln

Course Description

This short course begins with an overview of the research process typically used in organizational research. Next, constructs and their measurement are considered, including introductory coverage of reliability and validity. Consideration of experimental and non-experimental designs follows. And, data analysis tools will also be introduced, including descriptive statistics, analysis of variance, correlation, and linear regression. For all topics, examples will be discussed and assignments completed using either data provided by the instructor or by the short course participants.

Required Software: SPSS (free trial version)



  • "Introduction to Multilevel/Longitudinal Analysis"
Dr. Paul Bliese
Dr. Paul Bliese

Dr. Paul Bliese, University of South Carolina

Course Description

The CARMA Multilevel/Longitudinal Analysis short course provides both (1) the theoretical foundation, and (2) the resources and skills necessary to conduct a wide range of multilevel analyses, including those associated with longitudinal data. The course covers within-group agreement, nested 2-level multilevel modeling and growth modeling. All practical exercises are conducted in R. Participants are encouraged to bring datasets to the course and apply the principles to their specific areas of research.

Required Software: SPSS (free trial version)

Registration, Pricing, Advanced Registration Deadline for Adelaide Short Courses

To register for 2016 CARMA Short Courses in Adelaide, Australia you must first log in to your CARMA account (If you do not already have an account, click here to create one). Click here to be brought to the login page. Once you have logged in, and you are in the User Area, select "Purchase Short Course" on the right side of the page.

Non-member prices per course: *All prices are in US Dollars (USD)

  • Faculty/Professional: $900.00
  • Students: $700.00

CARMA Member prices per course

All participants are eligible for the following discount:

  • Register for both sessions, receive $75 off the total price.

Advanced Registration Deadline is April 1, 2016. After this date, a $75.00 fee will be added to all registrations.

Short Courses in Detroit, Michigan, June 2016 - Two Sessions, Fourteen Courses

Week 1: Quantitative Research Methods

Hosted by Wayne State University

June 6-11, 2016 - Two Sessions, Fourteen Courses

Session 1: June 6-8, Seven Courses | Session 2: June 9-11, Seven Courses

Short Course Sessions and Groupings

We offer two sessions which allows course participants the opportunity to take two back-to-back courses that compliment one another. All courses in a session are taught concurrently, so a participant can take only one course per session.

Short Course Topics, Instructors and Summaries

Complete Course Listing

Click a course name to see more info.

Session One

Monday June 6 (all day), Tuesday June 7 (all day), and Wednesday June 8 (AM half day)

Session Two

Thursday June 9 (all day), Friday June 10 (all day), and Saturday June 11 (half day)

  1. "Introduction to Structural Equation Methods" - Dr. Larry J Williams
  2. "Advanced SEM I: Measurement Invariance, Latent Growth Modeling & Nonrecursive Modeling" - Dr. Robert Vandenberg
  3. "Mediation and Moderation" - Dr. Mark Gavin
  4. "Introduction to Multilevel Analysis" - Dr. James LeBreton
  5. "Introduction to R" - Dr. Scott Tonidandel
  6. "Meta-Analysis and Systematic Reviews"- Dr. Michael McDaniel
  7. "Introduction to Longitudinal Data Analysis"-Dr. Lisa Schurer Lambert

  1. "Intermediate SEM: Model Evaluation" - Dr. Larry J Williams
  2. "Advanced SEM II: Missing Data Issue in SEM, Multi-Level SEM and Latent Interactions"-Dr.Robert Vandenberg
  3. "Alternatives to Difference Scores: Polynomial Regression & Response Surface Methods"-Dr. Jeff Edwards
  4. "Advanced Multilevel Analysis"-Dr. Paul Bliese
  5. "Multivariate Statistics with R"- Dr. Steve Culpepper
  6. "Big Data and Data Mining with R"-Dr. Jeff Stanton
  7. "Developing Psychological Measures: Conceptual, Psychometric, and Practical Guidelines"-Dr. Fred Oswald

Session 1: June 6-8, Seven Courses

“Introduction to Structural Equation Methods"

Dr. Larry J Williams, University of North Dakota

Course Description
The Introduction to Structural Equation Methods Short Course provides (a) introductory coverage of latent variable techniques, including confirmatory factor analysis and structural equation methods with latent variables, (b) discussion of special issues related to the application of these techniques in organizational research, and (c) a comparison of these techniques with traditional analytical approaches. This Short Course will contain a balance of lecture and hands-on data analysis with examples and assignments, and emphasis will be placed on the application of SEM techniques to organizational research problems. Participants will:

  • develop skills required to conduct confirmatory latent variable data analysis, based on currently accepted practices, involving topics and research issues common to organizational research.
  • learn the conceptual and statistical assumptions underlying confirmatory latent variable analysis.
    learn how to implement data analysis techniques using software programs for confirmatory modeling. Special emphasis will also be placed on the generation and interpretation of results using the contemporary software programs LISREL, MPlus, and Amos.
  • learn how latent variable techniques can be applied to contemporary research issues in organizational research.
  • learn how the application of current latent variable techniques in organizational research differs from traditional techniques used in this literature
  • complete in-class exercises using their preferred package (LISREL, MPlus, and Amos)

Required Software: LISREL (free trial edition), MPlus or Amos

Note: For those without current access to an SEM package, LISREL has a free trial edition that you should download no earlier than 1 week before class. The MPlus demo is not adequate for this course.

"Advanced SEM I: Measurement Invariance, Latent Growth Modeling & Nonrecursive Modeling"

Dr. Robert Vandenberg, University of Georgia

Course Description
The short course covers three advanced structural equation modeling (SEM) topics: (a) testing measurement invariance; (b) latent growth modeling; and (c) evaluating reciprocal relationships in SEM. The instructor uses the Mplus SEM software package throughout the workshop. To get maximum benefit from this short course, the participants should have the full version of Mplus loaded on their laptops and bring the laptop with them to the course. The instructor lectures about half of the time with the remaining time devoted to having participants run examples with actual data provided by the instructor. Participants go home with usable examples and syntax. The measurement invariance testing section focuses on the procedures as outlined in the Vandenberg and Lance (2000) Organizational Research Methods article. Namely, we will cover the 9 invariance tests starting with the tests of equal variance-covariance matrices and ending with tests of latent mean differences. Other outcomes of covering these tests are how to use Mplus syntax, how to do multi-sample analyses, and also how to test hypothesized (a priori) group mean differences but using the latent means of the latent variables within each group. Thus, the first section accomplishes much more than the just the measurement invariance tests. The workshop then advances to operationalizing latent growth models within the SEM framework. Essentially, this is how to use one's longitudinal data to actually capture the dynamic processes in one's theory. Thus, it is very, very different than cross-sectional tests where one is stuck in one point in time. Again, this is what goes on at the surface level, but the participant will also be exposed to modeling how the change in one variable impacts change in another. We will also use mixed modeling. And at the end of it, I introduce the participants to latent profile modeling with latent growth curves. The final piece is the testing of models with feedback loops via an SEM-Journal article by Edward Rigdon (1995). We will go through his 4 different models and what they mean.

Required Software: MPlus (order the full version, try the free demo version)

"Mediation and Moderation"

Dr. Mark Gavin, West Virginia University

Course Description
Mediators and moderators are pervasive in organizational research. As theoretical frameworks advance, the specification and testing of mechanisms (or mediators) through which the effects of one variable on another are transmitted has become a central concern. Another primary concern of theory development is the specification and testing of boundary conditions (or moderators) that affect the nature (significance, magnitude and/or direction) of the relationship between variables. More recently there has been increased attention on the theoretical specification of models that incorporate both mediation and moderation, facilitated in no small part by advancements made in the analytical approaches for testing such effects. This course will provide an overview of the conceptual, methodological and statistical issues surrounding the investigation of mediators and moderators, as well as their combined dynamics. The short course will feature both lecture and hands-on components, including analytical demonstrations and exercises that focus on the testing (primarily using SPSS) of these effects.

Required Software: SPSS (free trial version)

"Introduction to Multilevel Analysis"

Dr. James LeBreton, Pennsylvania State University

Course Description
This course is aimed at faculty and students who are relatively new to multilevel theory, measurement, and analysis. It will review basic issues associated with the development and testing of multilevel theories. Although the focus will be on issues pertaining to multilevel theory and measurement (e.g., multilevel constructs, multilevel construct validation, aggregation and composition models), we will also discuss general issues associated multilevel analysis. Examples will be presented and discussed using both SPSS and HLM. The R package will be introduced, explained, and emphasized during this short course in preparation for the advanced short course in Session II. Specific topics will include:

  • Module 1: Multilevel Theory: Constructs, Inferences, and Composition Models
  • Module 2: Multilevel Measurement: Aggregation, Aggregation Bias, & Cross-Level Inference
  • Module 3: Multilevel Measurement: Estimating Interrater Agreement & Reliability
    • Examples using SPSS Software
  • Module 4: Multilevel Measurement and Multilevel Modeling: A Simple Illustration of Analyzing Composite Variables in Hierarchical Linear Models
    • Examples using SPSS, HLM, and R Software
  • Module 5: Wrap up and Final Q & A

Required Software: R ( download here ), SPSS ( free trial version ), HLM ( student version ),

"Introduction to R"

Dr. Scott Tonidandel, Davidson College

Course Description
This course will provide a gentle introduction to the R computing platform and the R-Studio interface. We will cover the basics of R such as importing and exporting data, understanding R data structures, and R packages. You will also learn strategies for data manipulation within R (compute, recode, selecting cases, etc.) and best practices for data management. We will work through examples of how to conduct basic statistical analyses in R (descriptive, correlation, regression, T-test, ANOVA) and graph those results. Finally, we will explore user-defined functions in R and lay the groundwork for understanding how to perform more complex analyses presented in later CARMA short courses.

Required Software: R (download here)

“Meta-Analysis and Systematic Reviews”

Dr. Michael McDaniel, Virginia Commonwealth University

Course Description
This course provides the participant with knowledge concerning the major meta-analysis models used in research in organizational science and other sciences. The course also details all steps in conducting a systematic review. Thus, this course is not solely a statistics/methods course but provides the participant with knowledge needed to conduct a meta-analysis and systematic review consistent with the Meta-Analysis Reporting Standards (MARS). Free software is made available to the participants and hands-on practice in the software is incorporated into the course. The course also addresses emerging topics in meta-analysis and systematic reviews including a detailed treatment of publication bias.

Required Software: R, RStudio *Note: Install R before installing RStudio*

"Introduction to Longitudinal Data Analysis "

Lisa Schurer Lambert, Georgia State University

Course Description
Much of organizational research is arguably about causal processes of change even as many theories and analyses of change are deficient in the extent to which they specify or test temporal changes. There are many different approaches for measuring change. Each approach embodies a set of assumptions about what change is, what constitutes evidence of change, and some methods are oblivious to evidence of other types of change. This workshop is an introduction to longitudinal analyses.
We will cover how to properly specify a theory regarding change over time and discuss designs for collecting longitudinal data, as well as examine the critical role of measurement and construct validity in longitudinal data. The focus will be on multiple approaches for analyzing longitudinal data. Approaches covered in this workshop include using unconditional change scores and static scores, panel models and repeated measures ANOVA and MANOVA. Newer approaches including, latent growth modeling and random coefficient modeling, will be introduced. The emphasis will be on hands on learning with longitudinal data sets.

Required Software: SPSS (download free trial) and LISREL (order the full version, request free trial*you must contact the developer, SSI, in order to receive your free trial.* *This process can take 1-2 business days.* *The LISREL free student version will not be suitable for this course.*)

Session 2: June 9-11, Seven Courses

“Intermediate SEM: Model Evaluation"

Dr. Larry J Williams, Wayne State University

Course Description
This course is aimed at faculty and students with an introductory understanding of structural equation methods who seek a better understanding of the challenging process of making judgments about the adequacy of their models. Those who attend should have experience in fitting structural equation models with software such as LISREL, MPlus, EQS, or AMOS. This experience requirement can be met by completion of the Introduction to SEM Short Course. Attendees will be expected to bring their own laptop computers installed with their SEM software, and they should also know how to import data from an SPSS save file into their SEM software program. Attendees will learn out to interpret and report results from SEM analyses, and how to conduct model comparisons to obtain information relevant to inferences about their models, as well as advantages and disadvantages of different approaches to model evaluation. Attendees are encouraged to bring their own data for use during parts of the short course.

The course will consist of five sections, with each section having a lecture and lab component using exercises and data provided by the instructor:
• Review of model specification and parameter estimation
• Overview of model evaluation
• Logic and computations for goodness-of-fit measures
• Analysis of residuals and latent variables
• Model comparison strategies

Required Software: Your preferred SEM software package, SPSS (free trial version)

"Advanced SEM II: Missing Data Issue in SEM, Multi-Level SEM and Latent Interactions"

Dr. Robert Vandenberg, University of Georgia

Course Description
The workshop covers three advanced structural equation modeling (SEM) topics: (a) multilevel modeling; (b) latent interactions; and (c) dealing with missing data in SEM applications. The instructor uses the Mplus SEM software package throughout the workshop. To get maximum benefit from this short course, the participants should have the full version of Mplus loaded on their laptops and bring the laptop with them to the course. The instructor lectures about half of the time with the remaining time devoted to having participants run examples with actual data provided by the instructor. Participants go home with usable examples and syntax. The multilevel modeling section starts out using observed variables only, and no latent variables. Parallels are drawn in this approach and the other packages such as HLM. The main purpose here, though, is to teach participants the basics of multilevel modeling such as aggregation, cross-level interactions and cross-level direct effects. The workshop advances to using latent variables in a multi-level environment. Particular focus will be on multilevel confirmatory factor analysis whereby separate measurement models are estimated at both the within and between levels. The topic then switches to multilevel path modeling with emphasis on between vs. within modeling, and the estimation of cross-level interaction and direct effects among latent variables. The latent interaction section focuses on specifying interactions among latent variables in SEM models. This section starts out with a review of basic interaction testing within a regression environment (using Mplus). From this foundation, participants will move into specifying interactions among latent variables and how to test hypotheses with interactions. And from this point, the workshop will move into moderated-mediation but from the SEM perspective. The final segment of the short course deals with missing data. A great deal of time at the beginning is spent on missing data patterns and why they occur. The workshop then moves into the old methods of dealing with missing data such as listwise and pairwise deletion, and mean or regression based imputation. The disadvantages of those methods are discussed. We then move into covering the newer methods for dealing with missing data, multiple imputation, and full information maximum likelihood. Participants will be showed how to utilize the latter methods in Mplus.

Required Software: MPlus (order the full version, try the free demo version)

“Alternatives to Difference Scores: Polynomial Regression & Response Surface Methods”

Dr. Jeff Edwards, University of North Carolina - Chapel Hill

Course Description
For decades, difference scores have been used in studies of fit, similarity, and agreement in organizational research. Despite their widespread use, difference scores have numerous methodological problems. These problems can be overcome by using polynomial regression and response surface methodology to test hypotheses that motivate the use of difference scores. These methods avoid problems with difference scores, capture the effects difference scores are intended to represent, and can examine relationships that are more complex than those implied by difference scores.

This short course will review problems with difference scores, introduce polynomial regression and response surface methodology, and illustrate the application of these methods using empirical examples. Specific topics to be addressed include: (a) types of difference scores; (b) questions that difference scores are intended to address; (c) problems with difference scores; (d) polynomial regression as an alternative to difference scores; (e) testing constraints imposed by difference scores; (f) analyzing quadratic regression equations using response surface methodology; (g) difference scores as dependent variables; and (h) answers to frequently asked questions.

Required Software: TBA

"Advanced Multilevel Analysis"

Dr. Paul Bliese, University of South Carolina

Course Description
The CARMA Advanced Multilevel Analysis short course provides both (1) the theoretical foundation, and (2) the resources and skills necessary to conduct advanced multilevel analyses. Emphasis will be placed on techniques for longitudinal data. The course covers both basic models (e.g., 2-level mixed and growth models), and more advanced topics (e.g., 3-level models, discontinuous growth models, and multilevel moderated-mediation models). Practical exercises, with real-world research data, are conducted in R, with accompanying output from MPlus provided for some examples. Participants who prefer SAS, SPSS, or MPlus and have experience 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 have at least some foundational understanding of conducting multilevel analyses.

  • Module 1: 2-Level Mixed Models: Cross-Level Main Effects & Interactions
    • Introduction to multilevel modeling in R and MPlus
    • Exercise 1a: Mixed modeling in R
    • Exercise 1a: Mixed modeling in MPlus
  • Module 2: Analyzing change and growth
    • Exercise 2a: Growth modeling in R
    • Exercise 2a: Growth modeling in MPlus
  • Module 3: Bayes Estimates and lme4
    • Bayes Estimates using lme in R
    • Specifying models in lme4
  • Module 4: Discontinuous growth models
    • Examples using R
  • Module 5: 3-level models; moderated-mediation models
    • Examples using R and MPlus

Required Software: R (download here)

“Multivariate Statistics with R”

Dr. Steven Culpepper, University of Illinois Urbana-Champaign

Course Description
This course continues the introduction to R from the first session by covering advanced topics related to multivariate statistics. We will cover topics related to data management for multivariate data and will provide an overview of plotting and visualizing multivariate data in R. Specific learning outcomes include learning how to conduct analyses involving:

  • Multiple regression and diagnostics
  • Binary, multinomial, and ordinal logistic regression
  • Exploratory factor analysis and principal components
  • Multivariate regression, canonical correlation, and MANOVA
  • Topics in statistical computation (e.g., bootstrapping, Monte Carlo simulation)
  • Structural equation modeling with the lavaan package
  • Reproducible research for quantitative reports

The session will provide participants with some discussion of necessary background knowledge and practical exercises.

Required Software: R (download here), R Studio (download here), and tex (for Windows: http://miktex.org/ , for OS X http://www.tug.org/mactex/, for Ubuntu/Debian (Linux): apt-get install texlive or http://www.tug.org/texlive/ )

“Big Data and Data Mining with R”

Dr. Jeff Stanton, Syracuse University

Course Description

Big data has been a buzzword for several years both in academia and industry. Although the term is vague and is certainly overused, it does encompass some interesting new ideas and unfamiliar analytical techniques. Notable among these is “data mining,” a family of analytical methods for clustering, classifying, and predicting that go a step beyond the statistical methods used by many social science researchers. In this short course, we will discuss the dimensions of big data and the conceptual steps involved in data mining. Students are welcome to bring their own data sets for experimentation on their own, but this is not required.

We will use the open source statistical processing language, R, for most of the work we do in the course. Extensibility is the hallmark of R; its system of add-on packages provides access to an unequaled range of analytical tools and techniques. You do not have to be an expert in R to take this course, although you will find the course easier if you also take the introduction to R offered by CARMA earlier in the week. Prior to the course, I will ask students to install R on their personal computers and review the first few chapters of my free eTextbook, An Introduction to Data Science. Depending on the interests and preferences of the students, we also use the Rattle or R-Studio graphical user interfaces.

The ideal student will have an interest in using R, knowledge of some basic descriptive and inferential statistics, and some curiosity about exploring alternative, empirically driven strategies for analysis of large data sets. No prior experience with data mining is required and students who participate successfully in this short course can expect to learn enough about data mining to begin experimenting with these tools in research or teaching.

Required Software: R (download here), R Studio (download here)

"Developing Psychological Measures: Conceptual, Psychometric, and Practical Guidelines"

Oswald

Dr. Fred Oswald, Rice University

Course Description

Short course attendees will be able to develop measures of psychological constructs such as knowledge, attitudes, personality, or interests. Short course topics include construct validity, content and item generation, measurement models (EFA/CFA/IRT), multi-source measurement, and latent growth models. Each topic will emphasize practically useful guidelines and how to address (and prevent) real-world challenges.

Required Software: TBA

Registration, Pricing, Advanced Registration Deadline for Detroit, Michigan, Short Courses

How to register:

Click here to log in and register for 2016 CARMA Short Courses in Detroit, MI. Once you are logged in to your CARMA User Account, go the the tab labeled "User Area". Select "Purchase Short Courses" which is located on the right side of the webpage. You will then have the option to select one course from each session, or one course from one session.

If you have never created a CARMA User Account, you will need to do so before you are permitted to register for any courses. Click here to create an account.

Non-member prices per course: *All prices are in US Dollars (USD)

  • Faculty/Professional: $800.00
  • Students: $600.00

CARMA Member prices per course

  • CARMA Members Faculty/Professional: $400.00
  • CARMA Member Students: $300.00
    • If your organization is not yet a member but would like to become one, please contact us directly at carma@unl.edu

All participants are eligible for the following discount:

  • Register for both sessions, receive $75 off the total price.

Advanced Registration Deadline

The deadline for advanced registration is May 6, 2016. A $75.00 surcharge will be added to your order after the deadline for advanced registration.

Accommodations/ overnight lodging

Lodging: On-Campus Housing

For ease of lodging, CARMA has a contract with Wayne State University in which our short course members are permitted to pay a fee and stay on-campus in a university residence hall during the duration of the courses. The on-campus housing location is within 2 blocks of the building the short courses are held within (Prentis Building), and is a safe and affordable option as all rooms are available for under $25.00 a night and Wayne State University has a very safe campus. Photos of the housing facilities as well as a full list of features is available here.

Length of Stay Information:

Note that the following dates are NOT flexible. If you will be arriving in Detroit prior to Sunday June 5th or staying later than the dates outlined below, you will be responsible for your own accommodations.

  • Session I Attendees: Check in Sunday June 5th. Stay the night Sunday, Monday, Tuesday, and check out Wednesday June 8th.
  • Session II Attendees: Check in Wednesday June 8th. Stay the night Wednesday, Thursday, Friday, and check out Saturday June 11th.
  • BOTH Session I AND Session II Attendees: Check in Sunday June 5th. Stay the night Sunday, Monday, Tuesday, Wednesday, Thursday, Friday, and check out Saturday June 11th.

Total Price Information:

Your options for housing depend on 1) if you are staying for one session or two sessions and 2) if you want a private room or if you want to share a room with another individual.

  • For 3-nights (one Session), one person room: $92.50
  • For 3-nights (one Session), two person room: $76.60
  • For 6-nights (both Sessions), one person room: $163.00
  • For 6-nights (both Sessions), two person room: $131.20

Price Breakdown (for your information):

  • One person room: Room Fee ($23.50 per person/per night)*Number of nights + Mandatory Access Card ($2.00) + Mandatory Linen Packet ($10.00) + CARMA Processing Fee ($10.00)
  • Two person room: Room Fee ($18.20 per person/per night)*Number of nights + Mandatory Access Card ($2.00) + Mandatory Linen Packet ($10.00) + CARMA Processing Fee ($10.00)
    • Linen Packet includes: 1 pillow, 1 blanket, 1 sheet set, 1 bath towel, 1 washcloth.

How to Reserve a Residence Hall Room:

  1. Log in to your CARMA User Account.
  2. If you do not yet have a CARMA User Account, create one here.
  3. Once you are logged in, make sure you are in the "User Area" (green navigation bar at the top of the webpage has User Area located on it).
  4. Select "Purchase Subscriptions" on the right side of the webpage.
  5. Select "Residence Hall Registration for Wayne State" from the drop-down menu and enter in the appropriate promo code from the following list. The code you use will depend on which Session you would like to attend, and if you want to room alone or share a room. Here is the list of promo codes:
      • Session I, one-person room: Res101
      • Session I, two person room: Res102
      • Session II, one-person room: Res103
      • Session II, two-person room: Res104
      • BOTH Session I and Session II, one-person room: Res105
      • BOTH Session I and Session II, two-person room: Res106

*Note: Once you enter in your code and click continue, the price should be brought down from $175 to the appropriate price for your selection. If it is not, or the price is not what you expected, please contact us at carma@unl.edu BEFORE you proceed to the payment.*

Deadline for On-Campus Housing Registration:

All reservations MUST be made by May 19, 2016. No changes can be made after this date.

Housing Cancellation Policy:

If an emergency arises and you are unable to attend, we will refund you the full amount you paid for housing as long as we are notified prior to May 19, 2016. If we are notified after this date, unfortunately we will not be able to complete a refund. Please understand that the money we receive from the housing registration is directly given to Wayne State University therefore we do not have the ability to issue a refund after this date.

Hotel Accommodations

If you would prefer to stay in a hotel, we have a few recommendations for you:

  • The Inn on Ferry Street. This is a boutique hotel located just 3 blocks from where instruction will be held on campus. It is located in a historic district in Detroit. Click here for more information. Note: There is a limited set of rooms available at the Inn on Ferry Street. Therefore we recommend you make a reservation immediately if you would like to stay there.
  • There are other lodging options located in Downtown Detroit, about two or three miles from Wayne State University (the site of the CARMA short courses). CARMA is not working with or endorsing these hotels, we are simply recommending them based on their proximity and the fact that they offer complimentary shuttle services to Wayne State University.

Midtown Detroit

Wayne State University is located in the safe and beautiful Midtown Detroit. We are aware of the persistent stream of negative stereotypes about the city of Detroit, and we cannot stress enough that Midtown Detroit is a truly great area. You may have heard about the world-class Detroit Institute of Art, the myriad small businesses opening shop, and the top-notch Wayne State University, but there is much more to be found.

Want to know more about Midtown Detroit? Click here for more information.

A note about software requirements:

Please note, while we do provide links to trial, demo, and student versions of software packages, please understand that we do this as a courtesy. In every case, the full version of the software package will be superior to the trial, demo, or student versions - but the limited versions will work in a CARMA Short Course, unless specifically noted otherwise. CARMA does not officially support these software packages. We will kindly, and within reason, make an effort to help you with any issues. Also, please understand that these versions of the software packages may expire within a specified amount of time. If you are using a limited version of the software, you must read the details on the software website before installing, in order to be sure that you will be able to use the software during the CARMA Short Course.

Academy of International Business CARMA Workshop Registration Page

Intermediate SEM: Model Evaluation - Dr. Larry Williams, University of Nebraska-Lincoln

Dr. Larry Williams
Dr. Larry Williams

Dr. Larry J Williams, University of Nebraska-Lincoln

Time: 9:00am-12:00pm
Date: Sunday, June 26th

Description: This workshop is aimed at faculty and students with an introductory understanding of structural equation methods who seek a better understanding of the challenging process of making judgments about the adequacy of their models. Those who attend should have some exposure to SEM and experience in fitting structural equation models with software such as LISREL, MPlus, EQS, or AMOS. Attendees will learn out to interpret and report results from SEM analyses, and how to conduct model comparisons to obtain information relevant to inferences about their models, as well as advantages and disadvantages of different approaches to model evaluation.

The workshop will include (a) review of model specification and parameter estimation, (b) overview of model evaluation, (c) logic and computations for goodness-of-fit measures, (d) analysis of residuals and latent variables, and (e) model comparison strategies

An Introduction to Multi-level Analysis- Dr. Bob Vandenberg, University of Georgia

Dr. Bob Vandenberg
Dr. Bob Vandenberg

Dr. Bob Vandenberg, University of Georgia

Time: 2:00pm-5:00pm
Date: Sunday, June 26th

Description: An Introduction to Multi-level Analysis The objective of this workshop is to provide a review of commonly undertaken practices in multilevel analyses. Given the limited time, focus will be entirely on how to conduct the analyses using the Mplus software package.

Therefore, the primary focus is on how to conduct the analyses rather than the conceptual basis as to why and when multilevel analyses should be undertaken. We will start with the simplest multilevel model, and build more and more complex ones using both mediation and moderation hypotheses. With respect to mediation, participants will be shown how to test the significance of the indirect effects and how to conduct bootstrapping. We will repeat this process twice. The first time will use observed variables only. The second time will use the same models, but variables will be treated as latent variables within a structural equation modeling framework. Participants will be given syntax, and a data file so that they can either do the analyses in real time during the workshop, or later in the quiet of their offices.