1 / 14

Welcome to HLM Workshop

Welcome to HLM Workshop. UB summer statistics course for advanced level graduate students and researchers who need to use HLM methods for their own research Prerequisite: familiarity with multiple regression analysis and experience running statistical analysis on a computer (e.g., SPSS).

Rita
Download Presentation

Welcome to HLM Workshop

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. Welcome to HLM Workshop • UB summer statistics course for advanced level graduate students and researchers who need to use HLM methods for their own research • Prerequisite: familiarity with multiple regression analysis and experience running statistical analysis on a computer (e.g., SPSS). • Instructor: Dr. Jaekyung Lee (JL224@buffalo.edu) • TA: Xiaoyan Liu (xiaoyanliu09@gmail.com) • All class materials in a flash drive are distributed to workshop participants

  2. HLM Workshop Schedule • Day 1: Introduction: Principles and Applications of HLM • Day 2: Two-level HLM—Persons nested within Organizations (Organizational Effects Modeling); Power Analysis • Day 3: Two-level HLM —Measures nested within Persons (Growth Curve Modeling) • Day 4: Three-level HLM (Organizational Modeling + Growth Modeling); Moderation and Mediation Effect Analysis • Day 5: Nonlinear HGLM and Other Applications

  3. Daily Schedule • 9:00-9:30 Warm up • 9:30-12:00 Lecture/Review • 12:00-1:00 Lunch • 1:00-3:00 Lab • 3:00-3:30 Break • 3:30-5:00 Individual Work on Lab Assignment (TA will be available for help)

  4. Workshop objectives • Multilevel models include a broad range of models called by various names, such as random effects models, hierarchical models, and growth curve models. This type of modeling is becoming increasingly popular in educational and behavioral science research. • The purpose of this workshop is to give an introductory background in the basic principles and applications of hierarchical linear modeling (HLM) for scientific research.

  5. Features of HLM workshop • It includes concepts and applications of two-level, three-level, and nonlinear HLM methods for organizational effects modeling and growth curve modeling. • Statistical applications are emphasized through the use of real data sets and research examples, and through labs in which students run the HLM program and examine the results. • The goal is not only to understand the meaning of statistical concepts but also to be able to use these concepts to solve real research problems.

  6. Learning Beyond Cookbook • We will not take a cookbook approach to learning statistics. Simply knowing when to use what statistic and how to tell the computer to analyze your data, such an approach will not help you understand what your (or someone else's) results mean.  • You don’t have to memorize formula but instead need to understand the principles and logic behind the formula.

  7. Required text • Raudenbush, S.W. & Bryk, A.S.(2002).  • Hierarchical linear models:  Applications and data analysis methods. 2nd edition. Newbury Park, CA: Sage. • Bring the textbook to every class. Its purpose is to make it easy to follow the lectures and to work on examples in the textbook • Bring a calculator to every class as well.

  8. HLM manual for lab: • Raudenbush, S.W., Bryk, A.S., Cheong, Y.F., Congdon, R., & Toit, M. (2004). HLM 6: Hierarchical Linear and Non-Linear Modeling. Chicago: Scientific Software International. • Software: • HLM, version 6--a free student-version (www.ssicentral.com/hlm/student.html).

  9. Reading Assignments • Day 1: Text Ch. 1, Ch. 2, Ch. 4 HLM Manual Ch. 2, Ch. 12 • Day 2: Text Ch. 5, HLM Manual Ch. 2, Power Analysis (Ch. 1, Ch. 3 in Optimal Design Manual at http://sitemaker.umich.edu/group-based/optimal_design_software • Day 3: Text Ch. 6, HLM Manual Ch. 4 • Day 4: Text Ch. 8, HLM Manual Ch. 4, Moderation and Mediation Effect Analysis (Krull & McKinnon; Preacher, Curran & Bauer) • Day 5: Text Ch. 10 (Bernoulli model for dichotomous outcome), Manual Ch. 6

  10. Day 2 Research Review • 1. Example of Two-level HLM (Research on Organizational Effects) • Kidwell, Jr, R. E., Mossholder, K. W., Bennett, N. (1997). Cohesiveness and Organizational Citizenship Behavior: A Multilevel Analysis Using Work Groups and Individuals, Journal of Management, 23, 6, 775-793

  11. Day 3 Research Review • 2. Example of Two-level HLM (Research on Individual Changes) • Gutman, L. M., Sameroff, A. J., & Cole, R. (2003). Academic Growth Curve Trajectories from 1st Grade to 12th Grade: Effects of Multiple Social Risk Factors and Preschool Child Factors. Developmental Psychology, 39(4), 777-790.

  12. Day 4 Research Review • 3. Example of Three-level HLM (Research on Individual Changes + Organizational Effects) • Gamoran, A., Porter, A.C., Smithson, J., & White, P.A. (1997). Upgrading high school mathematics instruction: Improving learning opportunities for low-achieving, low-income youth. Educational Evaluation and Policy Analysis,19, 325-338.

  13. Day 5 Research Review • 4. Example of Nonlinear HLM (Research on Dichotomous Outcomes) • Rumberger, R.W. (1995). Dropping out of middle school: A multilevel analysis of students and schools. American Educational Research Journal,32, 583-625.

  14. Lab schedule • Day 1: Introduction to using HLM software • Day 2: Two-level HLM: Organizational Effects Model • Day 3: Two-level HLM: Growth Curve Model • Day 4: Three-level HLM: combining Organizational Model and Growth Model • Day 5: Nonlinear HGLM

More Related