Education

Course Schedule

Short Courses Presented by the Odum Institute & the Research Hub @Davis Library

Academic Holiday

Memorial Day

Conference Room
May 29, 2017 9:00 AM - 5:00 PM

Qualitative Analysis

ICPSR - Introduction to Mixed Methods Research

Kathy Collins

The term mixed methods research (MMR) refers to application and integration of qualitative and quantitative approaches at one or more stages of the research process. The purpose of this three-day interactive course is to introduce to new (e.g., doctoral students, junior faculty) and seasoned (i.e., limited experience conducting MMR) researchers an array of conceptual strategies and practical techniques for formulating, planning, and implementing a single MMR study or program of studies. We will discuss definitions of MMR, objectives, purposes, and rationales for conducting a MMR study, writing MMR questions, and techniques for collecting, analyzing, and integrating qualitative and quantitative data. Frameworks and heuristics for developing a MMR design that fits the research question(s), selecting/constructing a mixed sampling design, and applying quality criteria throughout a MMR study will be emphasized. The course also will cover approaches for applying guidelines when reporting results and publishing tips for writing a MMR article. Interspersed throughout the course will be interactive small group activities to engage the participants in the iterative process of conducting MMR. These activities will be structured as breakout groups, and they will be followed by whole group discussion led by the presenter. Participants are encouraged to bring to the course their own MMR project, such as a dissertation prospectus, funding proposal, an idea for a single study, or plans for implementing a program of research.

Prerequisites: Prior experience with MMR is not a prerequisite. Extensive introductory course materials will be provided.

Fee: Members = $1500; Non-members = $2800

For registration details, click here.

Davis 3010
Dates: July 10 - 12, 2017

Times: 9:00am - 4:30pm

Qualitative Research Summer Intensive

Registration is now open through ResearchTalk. For more information and to register, click QRSI 2017

July 24-25 (Monday-Tuesday)

Two-day Courses

  • Coding and Analyzing Qualitative Data
  • Focus Groups: Tools for Inquiry, Pedagogy, and Social Advocacy/Activism
  • Foundational Principles of and Approaches to Mixed Methods Research
  • Introduction to Qualitative Research: From Principles to Practice
  • Oral History: Purpose, Praxis and Possibility
  • Qualitative Teamwork

July 26 (Wednesday)
One-day Courses

  • Building a Codebook and Writing Memos
  • Compassionate Interviewing
  • Doing Qualitative Research Online
  • Rapid Turn-Around Qualitative Research
  • Synthesizing Qualitative Data
  • Writing Stories: Researcher As Storyteller

July 27-28 (Thursday-Friday)
Two-day Courses

  • Doing Qualitative Research in the Era of Big Data: Basic Principles and Applications
  • Evocative Autoethnography: Writing Lives and Telling Stories
  • Implementation Research: Using Qualitative Research Methods to Improve Policy and Practice
  • Qualitative Research: Analyzing Life
  • "Sort and Sift, Think and Shift": Learning to Let the Data Guide Your Analysis
  • Writing Effective Qualitative and Mixed Methods Research Proposals

For more information, go to QRSI 2017


Carolina Inn
July 24, 2017 9:30 AM - 4:00 PM
July 25, 2017 9:30 AM - 4:00 PM
July 26, 2017 9:30 AM - 4:00 PM
July 27, 2017 9:30 AM - 4:00 PM
July 28, 2017 9:30 AM - 4:00 PM

ICSPR - Qualitative Research Methods

Paul Mihas
This workshop presents strategies for analyzing and making sense of qualitative data. Both descriptive and interpretive qualitative studies will be discussed, as will more defined qualitative approaches such as grounded theory, narrative analysis, and case study. The course will briefly cover research design and data collection but will largely focus on analysis. In particular, we will consider how researchers develop codes and integrate memo writing into a larger analytic process. The purpose of coding is to provide a focus to qualitative analysis; it is critical to have a handle on your coding practices as you move deeper into analysis. The course will present coding and memo writing as concurrent tasks that occur during an active review of interviews, documents, focus groups, and/or multi-media data. We will discuss deductive and inductive coding and how a codebook evolves, that is, how codes might emerge and shift during analysis. Managing codes includes developing code hierarchies, identifying code "constellations," and building multidimensional themes. The class will present memo writing as a strategy for capturing analytical thinking, inscribed meaning, and cumulative evidence for emerging meaning. Memos can also resemble early writing for reports, articles, chapters, and other forms of presentation. Researchers can also mine memos for codes and use memos to build evocative themes and theory. Coding and memo writing are discussed in the context of data-driven qualitative research beginning with design and moving toward presentation of findings. One module of the course will be devoted to learning a qualitative analysis software package, ATLAS.ti. The methods discussed in the course will be applicable to qualitative studies in a range of fields, including the behavioral sciences, social sciences, health sciences, and business.

Fee: Members = $1500; Non-members = $2800

For registration details, click here.

Davis 3010
Dates: August 2 - 4, 2017

Times: 9:00am - 4:30pm

Quantitative Analysis

An Introduction to Conducting Experiments in the Social Sciences

Steven Buzinski
This one-day course will provide a basic introduction to conducting experimental research in the social sciences. With an eye towards pragmatics, this course will teach participants about the experimental life cycle in social science, from research question to experimental design and implementation. Topics covered will include forming theory-grounded hypotheses, an overview of experimental methods, writing & submitting IRB applications, and using Qualtrics online survey software for experimental research. Participants should bring a laptop computer and research ideas.

Registration Fees:

  • UNC Students - $20
  • UNC Staff/Faculty/Others - $40

    To Register, click here. Registrations will not be accepted on or after March 7, 2017.

    * Cancellation/ Refund Policy: A full refund will be given to those who cancel their registration no later than 10 days prior to the course. If you cancel within the 10 days prior to the class, no refund will be given. Please allow 30 days to receive your refund.
    * Waitlist/ Walk-ins: There may be a waitlist for the courses. Walk-ins will not be accepted. Each attendee must register and pay prior to 3 days before the start of the course.

    Davis 3010
    Date: March 10, 2017

    Times: 10:00am - 4:00pm

    Logistic Regression

    Cathy Zimmer

    This short course provides an introduction to logistic regression. Model specification, identification, estimation, hypothesis-testing, and interpretation of results are covered. Software to estimate these models is discussed, but not demonstrated. This is not a course on software, but rather a course on the concepts and uses of logistic regression.

    For more information, please contact Cathy_Zimmer@unc.edu.
    Davis 219
    Date: March 22, 2017

    Times: 3:30pm - 5:00pm

    ICPSR - Latent Growth Curve Models (LGCM): A Structural Equation Modeling Approach

    Kenneth Bollen

    A powerful method for analyzing longitudinal data is Latent Growth Curve Models (LGCM). LGCM allow each case in a sample to have individual trajectories ("latent curves" or "growth curves") representing change over time. In addition to mapping these trajectories, LGCM allow researchers to examine the determinants of these trajectories or to relate the trajectories of one variable to those of another. The approach to LGCM in this course draws on the strengths of structural equation models (SEM), and the primary goal is to introduce participants to the theory and application of LGCM. The course begins with a conceptual introduction to LGCM, a description of research questions that are well suited for the technique, and a review of SEM. The remainder of the course will cover the following topics: LGCM for a single variable with and without predictors of differences in trajectories; modeling nonlinear trajectories; the LGCM for multiple variables; the relation between the parameters governing the trajectories in two or more variables; incorporating predictors of multiple trajectories; and extensions to the LGCM.

    Prerequisites: The workshop assumes that participants have prior training and experience with SEM software.

    Fee: Members = $1700; Non-members = $3200

    For registration details, click here.

    Davis 219
    June 05, 2017 9:00 AM - 4:30 PM
    June 06, 2017 9:00 AM - 4:30 PM
    June 07, 2017 9:00 AM - 4:30 PM
    June 08, 2017 9:00 AM - 4:30 PM
    June 09, 2017 9:00 AM - 4:30 PM

    ICPSR - Growth Mixture Models: A Structural Equation Modeling Approach

    Sarah Mustillo

    The Growth Mixture Model (GMM) is an extension of the Latent Growth Curve Model (LGCM) that identifies distinct subgroups of growth trajectories and allows individuals to vary around subgroup-specific mean trajectories. Conventional growth modeling estimates a single mean intercept and slope for each individual and variance parameters around the mean intercept and slope. The GMM relaxes the assumption that all individuals are drawn from a single population with common parameters by using latent trajectory classes, resulting in separate intercepts, slopes, and variance parameters for each subgroup. This three-day workshop will provide training in estimating GMMs to analyze growth trajectories. Key features of this model are that it can identify the number and form of distinct subgroups of growth trajectories, estimate the proportion of the population in each subgroup, and model predictors of the trajectories and predictors of class membership. In addition to the basic model, this workshop will cover several extensions, such as including a distal outcome predicted by the trajectories, multiple group GMMs, and parallel process or joint trajectory models.

    Prerequisites: Participants should be familiar with LGCMs. Familiarity with MPlus would be helpful but is not required.

    Fee: Members = $1500; Non-members = $2800

    For registration details, click here.

    Davis 219
    Dates: June 12 - 14, 2017

    Times: 9:00am - 4:30pm

    ICPSR - Machine Learning for the Analysis of Text As Data

    Brice Acree
    Quantitative analysis of digitized text represents an exciting and challenging frontier of data science across a broad spectrum of disciplines. From the analysis of physicians' notes to identify patients with diabetes, to the assessment of global happiness through the analysis of speech on twitter, patterns in massive text corpora have led to important scientific advancements. In this course we will cover several central computational and statistical methods for the analysis of text as data. Topics will include the manipulation and summarization of text data, dictionary methods of text analysis, prediction and classification with textual data, document clustering, text reuse measurement, and statistical topic models. Each method will be illustrated with hands-on examples using R. Participants will develop an understanding of the challenges and opportunities presented by the analysis of text as data, as well as the practical computational skills to complete independent analyses. The R packages covered in this course include tm, lda, textreuse, glmnet and openNLP. One distinguishing focus of this course will be the use of text analytics for the reliable and valid development and testing of scientific theory. Most methods of text analysis have been developed with predictive or descriptive motivations. For each method we cover in the current course, we will review how the method has been and can be applied to draw theoretical inferences regarding processes surrounding text generation.

    Fee: Members = $1700; Non-members = $3200

    For registration details, click here.

    Davis 219
    Dates: June 19 - 23, 2017

    Times: 9:00am - 4:30pm

    ICPSR - Bayesian Latent Variable Analysis

    Ryan Bakker

    This workshop will focus on a variety of commonly used latent variable techniques from the Bayesian perspective. The Bayesian paradigm is, in many ways, superior to classic techniques for estimating models with latent variables. In this workshop we will cover the factor and IRT models and introduce a variety of new tools for estimating models with latent variables as either explanatory or outcome variables. Additionally, we will introduce a variety of graphical techniques for presenting results. While there is not an assumption that participants will be well-versed in Bayesian modeling, a basic understanding of the Bayesian framework will be beneficial.

    Fee: Members = $1700; Non-members = $3200

    For registration details, click here.

    Davis 219
    Dates: July 17 - 21, 2017

    Times: 9:00am - 4:30pm

    ICPSR - Statistical Graphics

    William Jacoby

    This workshop will cover strategies for obtaining visual displays of quantitative information. We will discuss ways to, quite literally, look at data and statistical models in pictorial form. This is important because graphical representations avoid some of the restrictive and simplistic assumptions that often are encountered in empirical analyses. The first day of the workshop will present graphical displays for univariate, bivariate, multivariate, and categorical data. The second and third days will be devoted to producing graphical displays using tools available in the R statistical computing environment.

    The workshop will focus primarily on the "lattice" package, although we will also examine some of the other graphical packages that exist within R. No previous experience with R is necessary to take this workshop! The second day will begin with a brief session on "Just Enough R for Graphics." The instructor will provide a variety of substantive examples and datasets to illustrate the various graphical techniques that are available. But workshop participants are also encouraged to bring their own datasets for constructing graphical displays that are tailored to their particular needs and interests.

    Fee: Members = $1500; Non-members = $2800

    For registration details, click here.

    Davis 219
    Dates: July 31 - August 2, 2017

    Times: 9:00am - 4:30pm

    Spatial Analysis & Mapping

    Applied Spatial Regression Analysis

    Paul Voss

    This short course provides an introduction to the field of spatial regression modeling. When analyzing data aggregated to geographic areas (e.g., census data for counties), a fresh set of issues arise that are not present in traditional non-spatial data analyses. These issues need to be recognized and accounted for when properly specifying regression models using attributes that are linked to geographic location. The topics covered in two afternoon sessions include:
    • Why standard regression models generally fail when analyzing spatial data
    • Defining and understanding “spatial autocorrelation”
    • Causes of spatial autocorrelation
    • Measuring & operationalizing spatial effects
    • Defining spatial “neighborhoods”
    • Creating spatial weights matrices
    • Moran’s I statistic
    • Incorporating spatial effects in spatial regression models
    • Specification & estimation of spatial regression models
    • Spatial regression model diagnostics
    • (Time permitting: some interesting extensions to related topics)

    Examples of estimating spatial regression models will use the open source software suite R (no prior knowledge of R is necessary)

    Registration Fees:

  • UNC-CH Students - $50
  • All Others - $100

    To Register, click here. No registrations will be accepted on or after March 24, 2017.

    * Cancellation/ Refund Policy: A full refund will be given to those who cancel their registration no later than 10 days prior to the course. If you cancel within the 10 days prior to the class, no refund will be given. Please allow 30 days to receive your refund.
    * Waitlist/ Walk-ins: There may be a waitlist for the courses. Walk-ins will not be accepted. Each attendee must register and pay prior to 3 days before the start of the course.

    Davis 219
    Dates: March 27 & 29, 2017

    Times: 1:30pm - 4:00pm

    Survey Research

    Visual Design for Surveys: A Hands-On Approach

    Don Dillman

    This course focuses on how and why words, numbers, symbols and graphics independently and jointly influence answers to questions in Internet and paper surveys. It begins with theoretical background on why and how the visual aspects of questions are interpreted by respondents and guide their reading and comprehension of meaning. Applications of the theory and research to designing individual person and establishment surveys in ways that improve their usability for respondents will be provided. The course includes a discussion of the substantial implications these ideas have for the design of mixed-mode surveys in which some respondents are asked to report aurally (e.g. telephone) and others are asked to complete visually communicated (web or mail) survey questions. The substantial visual design challenges researchers are now facing with designing questions for smartphones will be discussed as part of the mixed-mode design issues that must be addressed in many surveys.

    THE INSTRUCTOR
    This course will be taught by Don A. Dillman, Regents Professor in the Departments of Sociology and the Social and Economic Sciences Research Center at Washington State University in Pullman. Dillman is a past-president of the American Association for Public Research and also served as the Senior Survey Methodologist at the U.S. Census Bureau (1991-1995) where he provided leadership for introducing respondent friendly design into the Decennial Census and other government surveys. His 2014 book (with Jolene Smyth and Leah Christian), "Phone, Internet, Mail and Mixed-Mode Surveys: the Tailored Design" (John Wiley: Hoboken NJ, 2014) provides background for the visual design and survey implementation recommendations provided in this short course.

    This course will count as 7.0 CPSM short course credit hours.

    Registration Fees:

  • CPSM Students - $30
  • UNC Students - $45
  • Other - $60

    To Register, click here. Registrations will not be accepted on or after March 20, 2017.


    * Cancellation/ Refund Policy: A full refund will be given to those who cancel their registration no later than 10 days prior to the course. If you cancel within the 10 days prior to the class, no refund will be given. Please allow 30 days to receive your refund.
    * Waitlist/ Walk-ins: There may be a waitlist for the courses. Walk-ins will not be accepted. Each attendee must register and pay prior to 3 days before the start of the course.

    Davis 219
    Date: March 23, 2017

    Times: 9:00am - 4:30pm

    Cognitive Interviewing: A Hands-On Approach

    Gordon Willis

    National Cancer Institute, National Institutes of Health
    Joint Program in Survey Methodology, University of Maryland/University of Michigan

    Cognitive interviewing has become a very popular method for pretesting and evaluating survey questionnaires. The current approach favored by Federal laboratories and private research institutions mainly emphasizes the use of intensive verbal probes that are administered by specially trained interviewers to volunteer respondents, often in a laboratory environment, to delve into the cognitive and socio-cultural processes associated with answering survey questions. Based on this information, the evaluator makes judgments about where questions may produce difficulties in a number of subtle ways, due to cognitive demands they impose, cultural mismatches, or other shortcomings. The short-course will cover the basic activities involved in arranging a cognitive testing project, and will focus on the specifics of how to conduct verbal probing. Although an introduction to theory and background perspective is included, the course will focus on the application and practice of cognitive interviewing techniques, as these are targeted toward both interviewer-administered (face-to-face or telephone) and self-administered (paper and web/internet) surveys. Participants will practice the conduct of cognitive interviews across modes, and will evaluate their results by judging where questions have failed, and what one might do to revise them. The course aims to provide a working familiarity with cognitive techniques, so that students will be able to begin conducting cognitive interviews on their own.

    THE INSTRUCTOR
    Gordon Willis is a questionnaire design and pretesting specialist with affiliations at the National Institutes of Health, the Uniformed Services University of the Health Sciences (USUHS), and the University of Maryland. Prior to that he was Senior Research Methodologist at Research Triangle Institute, and he also worked for over a decade at the National Center for Health Statistics, CDC, to develop methods for developing and testing survey questions. Willis attended Oberlin College, and received a PhD in Cognitive Psychology from Northwestern University. He now works mainly in the area of the development and evaluation of surveys on cancer risk factors, and focuses on questionnaire pretesting. He has produced the "Questionnaire Appraisal System" for use in evaluating draft survey questions, and has written the book "Cognitive Interviewing: A Tool for Improving Questionnaire Design." His research interests include cross-cultural issues in self-report surveys and research studies, and in particular the development of best practices for questionnaire translation, and the development of pretesting techniques to evaluate the cross-cultural comparability of survey questions.

    This course will count as 7.0 CPSM short course credit hours.

    Registration Fees:

  • CPSM Students - $30
  • UNC Students - $45
  • Other - $60

    To Register, click here. Registrations will not be accepted on or after April 4, 2017.


    * Cancellation/ Refund Policy: A full refund will be given to those who cancel their registration no later than 10 days prior to the course. If you cancel within the 10 days prior to the class, no refund will be given. Please allow 30 days to receive your refund.
    * Waitlist/ Walk-ins: There may be a waitlist for the courses. Walk-ins will not be accepted. Each attendee must register and pay prior to 3 days before the start of the course.

    Davis 219
    Date: April 7, 2017

    Times: 9:00am - 4:30pm

    Social Media's Role in Survey Research

    The ubiquity of social media in the world today presents new opportunities and challenges when it comes to social research. This course considers the use of social media in survey research. Throughout the survey lifecycle (questionnaire design and testing, subject recruitment, respondent tracking and longitudinal panel retention), social media platforms offer some new ways to reach respondents at a time when traditional methods have seen declining participation. Social media data can also be considered as supplementary or proxy data for surveys. This course will present specific examples of the use social media in survey research, highlighting the topics, methods, and ethical considerations that accompany this growing sub-discipline. We end with considerations for the role of social media in public opinion research in the future as this area of research evolves.

    Examples of issues that will be discussed include:
    • defining social media for the purposes of determining its potential role within survey research
    • the motivation for tapping this source of behavioral and attitudinal measurement
    • the availability and quality considerations inherent in social media data analysis
    • current uses and evaluations of social media in research • the legal and ethical issues that must be considered when considering social media as a resource in research
    • challenges and questions on the road ahead in developing best practices for social media in survey research, including validation of social media data; addressing coverage, sampling, and differential access challenges; designing better integrations of surveys and social media; leveraging the unique features of social media; and continuing to refine the understanding and guidance on privacy and ethics.

    THE INSTRUCTOR

    Joe Murphy is a senior survey methodologist at RTI International. His research focuses on the development and application of new technologies and modes of communication to improve the survey research process. His recent work has centered on the use and analysis of social media to supplement survey data, with a detailed focus on Twitter. Mr. Murphy also investigates optimal designs for mobile data collection platforms, data visualization, crowdsourcing, and social research in virtual worlds. He is a demographer by training and survey methodologist by practice.

    Registration Fees:

  • CPSM Students - $20
  • UNC Students - $35
  • Other - $45

    To Register, click here. Registrations will not be accepted on or after April 9, 2017.

    This course will count as 4.0 CPSM short course credit hours.

    * Cancellation/ Refund Policy: A full refund will be given to those who cancel their registration no later than 10 days prior to the course. If you cancel within the 10 days prior to the class, no refund will be given. Please allow 30 days to receive your refund.
    * Waitlist/ Walk-ins: There may be a waitlist for the courses. Walk-ins will not be accepted. Each attendee must register and pay prior to 3 days before the start of the course.

    Davis 219
    Date: Changed to April 13, 2017

    Times: 9:00am - 1:00pm

    Statistical Computing

    SPSS

    Cathy Zimmer

    This course will offer an introduction to SPSS and will demonstrate how to work with data saved in SPSS format. It will demonstrate how to work with SPSS syntax, how to create your own SPSS data files, and how to convert data in other formats to SPSS. it will also teach how to append and merge SPSS files, demonstrate basic analytical procedures, and show how to work with SPSS graphics.

    For more information, please contact Cathy_Zimmer@unc.edu.
    Davis 219
    Dates: February 27, March 1, and March 3

    Times: 3:30pm - 5:00pm

    SAS

    Chris Wiesen

    This is a four-part course. SAS part 1 of 4 will give an introduction to the SAS system and SAS windows. Topics to be covered include: creating and saving SAS programs; reading in data from simple and complex text data sets; typing variables; obtaining frequencies, contents, and univariate statistics. SAS part 2 of 4 will discuss formatting variable values; creating SAS libraries for storing and retrieving SAS data sets and format files; reading raw data from external files; creating new SAS data sets from existing SAS data sets, subsetting by observation and by variable. SAS part 3 of 4 will explain how to create new SAS data sets combining information from multiple existing SAS datasets; how to sort, concatenate, interleave, and merge data sets; how to perform the t-test, and test for no association in a contingency table. For SAS part 4 of 4, attendants will be allowed to suggest topics. Past topics include variable retyping, creating SAS datasets from SAS output; creating html and Microsoft Word tables, ANOVA, importing and exporting Excel files.

    Students should bring a flashdrive to class.

    No registration required. UNC students, faculty, and staff will need to show their UNC OneCard.

    This class normally fills so be sure to arrive before the class start time. There are only 21 seats with computers, but a limited number of those who have laptops with SAS loaded will be allowed to sit in.


    Davis 3010
    Dates: 3/27/2017 - 3/30/2017

    Times: 3:00pm - 5:00pm

    Other

    Data Wrangling

    Lorin Bruckner, Matt Jansen, Tim Ronan, Kayla Seiffert
    Do you have data that you need to clean up and manipulate? Want to learn R? This two-day workshop will help you start working with data in R. (Familiarity with R is not required.)

    Day 1 (March 25, 2017)

    • Basic data formatting and cleanup
    • Programming best practices
    • Basic R Programming and RStudio
    Day 2 (April 1, 2017)
    • Advanced R Programming
    • Data visualization with R’s ggplot2 library
    Register here
    Mitchell Hall Room 050
    March 25, 2017 9:00 AM - 4:00 PM
    April 01, 2017 9:00 AM - 4:00 PM