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2015 CARMA Short Courses in Grand Forks, ND
Quantitative Research Methods
Courses hosted by University of North Dakota
June 8-12, 2015, 2 Sessions
Short Course Topics, Instructors and Summaries
Click on a course to see more info.
Session 1, June 8-10, Monday-Wednesday
- "Multilevel Analysis"- Dr. Bob Vanderberg
- "Meta-Analysis and Systematic Reviews"- Dr. Ernest O'Boyle
Session 2, June 10-12, Wednesday-Friday
- "Introduction to SEM"- Dr. Larry Williams
Session 1, June 8-10, Monday-Wednesday
Dr. Robert Vandenberg, University of Georgia
Course Description: The workshop focuses on multilevel data analysis using 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 ( www.statmodel.com ) and bring the laptop with them to the course. The workshop is divided into three topics. The first topic is primarily lecture and focuses on the conceptual underpinnings characterizing multilevel modeling. Within that topic, we start with a historical overview as to why the need for multilevel analyses arose. This transitions into the principals underlying multilevel theory development. Given that much of the theory development needs to address the “emergence” of multilevel constructs, a great deal of time is spent on emergence and within it lengthy discussions of compilation and composition multilevel models. Since some forms of emergence need to be empirically justified, the first topic ends with a lengthy discussion of similarity indices including interrater reliability, interclass correlations, and rwg to name a few. The second topic in the short course is undertaking multilevel analyses with observed variables only (not structural equation modeling with latent variables). This second topic begins with simple point estimation procedures and within it how one estimates the two primary vectors of random coefficients; the vector of random intercepts and the vector of random slopes. These two vectors represent the building blocks for most multilevel models representing one’s conceptual hypotheses. It is also here that you are shown how to compute many of the primary similarity indices needed to justify aggregation of a variable from a lower to a higher level. After this, we illustrate and test a series of increasingly complex multilevel models representing those commonly used in hypothesis testing contexts such as group climate and cross-level interactions. One goal of this second topic is to illustrate that Mplus using observed variables only provides basically the same results as other commonly used programs such as HLM, but offers the researcher greater flexibility. A second goal is give the participant a chance to run multilevel models using the data provided by the instructor, and through this to create a library of examples, s/he can reference in the future. The third and final topic of the short course is exactly the same as the second topic, but the sole focus is on latent variables; that is, we will cover structural equation multilevel modeling including multilevel confirmatory factor analysis and multilevel path models among latent variables. As with the second topic, participants will be running the models themselves.
Dr. Ernest O'Boyle, University of Iowa
Course Description: Meta-analysis has become an incredibly popular tool in a wide variety of research disciplines, including (but certainly not limited to) the social sciences, medicine, education, and business. At its essence, a meta-analysis is both conceptual and quantitative in nature: It is the use of a properly motivated (if not integrative) theoretical framework, and it is the practice of identifying, sifting, combining, comparing, and interpreting effect sizes across a set of studies investigating the same (or similar) phenomena. As such, meta-analysis requires good decision making as much or more than statistical skill. This short course traverses a wide range of issues, including developing and using a coding sheet, fixed vs. random effect models, continuous and categorical moderation, correcting for statistical artifacts, dealing with dependent outcomes and outliers, and detecting publication bias. There are several objectives of this short course, but the primary one is concrete: equip you with the ability to conduct a meta-analysis, from start to finish, in whatever substantive area interests you the most.
Session 2, June 10-12, Wednesday-Friday
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 and MPlus.
- 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
Required Software: LISREL (free trial edition **PLEASE NOTE that the installation of LISREL free trial is not straighforward and requires correspondence with the software publisher. No direct download is offered through the publisher's site. AND, the student version of LISREL WILL NOT be acceptable for this course), MPlus (free demo version)
Registration, Pricing, Advanced Registration Deadline
Click here to log in and register for 2015 CARMA Short Courses in Grand Forks, ND
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
- If your organization is not yet a member but would like to become one, please contact us directly at email@example.com
All participants are eligible for the following discount:
- Register for both sessions, receive $75 off the total price.
The deadline for advanced registration is May 9, 2015. A $75.00 fee will be added after the deadline.
Accommodations/ overnight lodging
- Red Roof Inn Townhouse (701) 746-5411 Address: 710 1st Ave N, Grand Forks, ND 58203 *Easy 3 block walk to downtown Grand Forks*
- Canad Inn (701) 772-8404 Address: 1000 S 42nd St, Grand Forks, ND 58201
Hilton Garden Suites (701) 775-6000 Address: 4301 James Ray Dr, Grand Forks, ND 58203
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.