Education

Course Schedule

Qualitative Analysis

QRSI: Fundamentals of Qualitative Research

Johnny Saldaña

"Fundamentals of Qualitative Research" is an intensive two-day introductory overview of basic approaches to and methods for qualitative inquiry. Course content will be adapted from Saldaña's textbook, Fundamentals of Qualitative Research (Oxford University Press, 2011).

Major topics addressed will include: (1) genres, elements, and styles of qualitative research; (2) a survey of qualitative data collection methods; (3) qualitative research design; (4) a survey of qualitative data analytic methods; and (5) writing and presenting qualitative research. Multiple practical and on-your-feet activities will be included throughout the course to provide students experiential knowledge of the subject.

Novices to qualitative inquiry will benefit from this course by gaining literacy and workshop experience in the basic methods of qualitative research for future study and application.

Experienced qualitative researchers may benefit from this course by refreshing their knowledge bases of methods, plus observing how introductory material is approached with novices for future classroom teaching applications.

To register, go to http://researchtalk.com/qrsi-2015.

Carolina Inn
Dates: July 27 - 28, 2015

QRSI: Implementation Research: Using Qualitative Research Methods to Improve Policy and Practice

Alison Hamilton

Implementation research aims to integrate research findings into policy and practice. In order to improve the quality and effectiveness of routine practice, implementation researchers collect qualitative data about the everyday behaviors and beliefs of practitioners and other professionals, stakeholders, and recipients of services. During data collection, special attention is paid to factors that both facilitate and impede effective execution and implementation of major programs and service delivery. The end goal is to increase the likelihood of uptake, adoption, implementation, and sustainability of evidence-based practices.

To provide fundamental knowledge and skill to help facilitate your own work, the course walks through critical components of building and carrying out an implementation research project:
- Developing appropriate implementation research questions and specific aims
- Selecting conceptual models
- Strategizing about study design
- Determining appropriate, feasible qualitative data collection methods
- Executing qualitative analytic strategies
- Generating timely and impactful implementation research products

The application of methodological concepts will be illustrated via examples from implementation research in the context of varied settings such as healthcare organizations, educational institutions, and communities.

Participants will be provided with materials and bibliographies to support the practice of qualitative methods in implementation research.

To register, go to http://researchtalk.com/qrsi-2015.

Carolina Inn
Dates: July 27 - 28, 2015

QRSI: Making Claims and Building Theory in Qualitative Inquiry

Sarah Tracy

The course highlights everyday approaches used by qualitative researchers to enrich theory and practice as they move from research questions, to coding, to making claims and building theory from qualitative data. Making claims and building theory involve moving from isolated topics to generating meaning among these topics. This process means moving from flat analysis to connections that will capture our attention. We will discuss how to combine these strategies to craft work that is engaging and appealing to target audiences. This course will benefit those new to qualitative methods as well as those experienced who want to take their analyses to a deeper level or learn new techniques for teaching qualitative interpretation and analysis.

Course participants will:

1. Receive worksheets to assist in claim making and theory building.

2. Leave the seminar understanding 8 specific strategies for creating and deepening claims.

3. Learn a “formula” for making claims and theory.

4. Become acquainted with a phronetic (common sense), iterative analysis approach.

5. Practice claim-making and theory-building techniques on their own data or data the instructor will provide.

6. Learn tips for crafting engaging presentations and written products.

Resources for this workshop will come, in part, from Tracy’s Qualitative Research Methods: Collecting Evidence, Crafting Analysis, Communicating Impact (Wiley, 2013).

To register, go to http://researchtalk.com/qrsi-2015.

Carolina Inn
Dates: July 27 - 28, 2015

QRSI: Progressing with Grounded Theory

Kathy Charmaz

Qualitative researchers often experience common problems such as getting lost after collecting and coding data, overlooking possibilities for developing their ideas, and producing disjointed and mundane reports. Grounded theory methods help you expedite analyzing your data and writing your report. This class takes basic grounded theory principles to the next step of increasing the incisiveness, creativity, and clarity of your work. Our purpose is to help you retain the flexibility of grounded theory while furthering the conceptual depth and scope of your analyses. We will emphasize how to (1) develop and recognize powerful codes, (2) strengthen your emergent categories, (3) integrate these categories into a coherent narrative, and (4) write a compelling report.

Familiarity with basic grounded theory strategies is advised. Grounded theory is a general method and its strategies of qualitative coding and memo-writing have been widely adopted by qualitative researchers of all kinds. This class best serves participants who are in the midst of a project or have engaged in qualitative coding and memo writing for an earlier study.

Qualitative reportage relies on art and science—image and analysis. Yet analysis does not stop when we write our reports. We will briefly discuss how to create an artful rendering of your work that increases the power of your analysis. We will also cover strategies for developing arguments, writing literature reviews and theoretical frameworks, and constructing abstracts, titles, and introductions. The last session focuses on choosing journals and publishing houses, preparing your manuscript for submission, and working with editors and reviewers.

To register, go to http://researchtalk.com/qrsi-2015.

Carolina Inn
Dates: July 27 - 28, 2015

QRSI: Quantitative Primer for the Qualitative Researcher

Kevin Swartout

Communicating research findings is storytelling; some stories are supported by qualitative data, some are supported by numbers, some by both. This course is for qualitative researchers who want to consume quantitative or mixed-methods research or incorporate quantitative methods into their scholarship. Rather than furthering the misguided rivalry between inquiries, this course will focus on the shared principles. This approach will position researchers to determine patterns and draw integrated conclusions across analyses and across a literature. We will identify basic quantitative principles, assumptions, and practices and give examples and tips for practice. We will also briefly address the application and decision making guidelines for quantifying qualitative data (e.g., frequencies, cross-tabs, and percentage distributions). All toward the goal of telling better stories.

To register, go to http://researchtalk.com/qrsi-2015.

Carolina Inn
Dates: July 27 - 28, 2015

QRSI: Crafting Phenomenological Research: How Phenomena Can Take Shape in Various Contexts

Mark Vagle

Phenomenology is a way for qualitative researchers to look at what we usually look through. It means being profoundly present in our research encounters, to leave no stone unturned, to slow down in order to open up, to dwell with our surroundings, and to know that there is “never nothing going on.” Because the philosophical ideas that underpin phenomenology can be abstract and sometimes elusive, this course will communicate these topics as concretely as possible. That is, the course will provide techniques, tools, and strategies for cultivating a phenomenology. We will use examples, anecdotes, and exercises to work through and navigate the craft.

To learn about phenomenological research approaches, we will experience a series of data collection tools and strategies such as going on “phenomenology walks,” writing about lived experiences, and interviewing one another. We will explore Vagle’s five-component methodological process for conducting post-intentional phenomenological research—working to make sense of how our phenomena might take shape in various contexts:

1. Identify a phenomenon in its multiple, partial, and varied contexts.

2. Devise a clear, yet flexible process for gathering data appropriate for the phenomenon under investigation.

3. Make a post–reflexivity plan.

4. Read and write your way through your data in a systematic, responsive manner.

5. Craft a text that captures tentative manifestations of the phenomenon in its multiple, partial, and varied contexts.

Finally, we will explore conventional and less-conventional ways to write up our research.

A wide variety of methodological and philosophical texts and examples of phenomenological studies will be on hand for participants to read and discuss during the course. The course is based on Vagle’s book by the same name, Crafting Phenomenological Research (Left Coast Press, 2014).

To register, go to http://researchtalk.com/qrsi-2015.

Carolina Inn
Dates: July 27 - 28, 2015

QRSI: Because It Was Qualitative: How to Build Unapologetic Arguments for the Strength of Our Work

Tony Adams, Alison Hamilton and Ray Maietta

This course is founded on the premise that qualitative inquiry is unique, powerful, and necessary. The course presents unapologetic arguments for the strength of our work as qualitative experts and offers concrete tips and approaches to qualitative practice. Adams, Hamilton, and Maietta will use a combination of their own work and their favorite qualitative work in autoethnography, in-depth interviews, focus groups, and evaluation to equip you with the skills and language to become a vocal advocate for your qualitative contributions and the qualitative work you consume and share with others.

To accomplish this goal, these 4 principles must guide how you engage, evaluate and present qualitative work:

  • The strategies you use to carry out your project must align with your project questions and goals.
  • You must verify the quality of your work DURING data collection and analysis.
  • The presentation of your work must be lucid and compelling.
  • a. You must effectively build and tell your qualitative story using your data to discover and communicate your message(s)
  • You must make a useful contribution
  • a. to practice
    b. to theory
    c. to future research

Together we will review how others have accomplished these goals and help to ensure you do so as you move forward with your qualitative projects.

To register, go to http://researchtalk.com/qrsi-2015.

Carolina Inn
Date: July 29, 2015

QRSI: Building a Codebook and Writing Memos

Paul Mihas

This course focuses on developing codes and integrating memo writing into a larger analytic process. Coding and memo writing function as simultaneous and fluid tasks that occur during actively reviewing of interviews, focus groups, and multi-media data. We will discuss deductive and inductive codes and how a codebook can evolve, that is, how codes can emerge and shift unexpectedly during analysis. Managing codes also includes developing code connections and possible hierarchies, identifying code “constellations,” and building multidimensional themes. Our discussion of codes will include the following topics:

• The importance of code names and definitions

• Deductive, inductive, and thematic codes

• How many codes are too many?

• How broad or specific should codes be?

Memos function as deep reflections that capture nuanced thoughts and cumulative reactions to data. Memo writing strategies help us capture 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 incorporate memos in building evocative themes and theory. The following types of memos and memo-writing will be discussed in an effort to offer strategies to begin applying these techniques to your own work: holistic memos, positionality memos, statement memos, thematic memos, and memos that engage critical data segments.

To register, go to http://researchtalk.com/qrsi-2015.

Carolina Inn
Date: July 29, 2015

QRSI: Creating Credible, Vivid, and Persuasive Qualitative Stories: Research As Performance

Johnny Saldaña

An arts-based approach can enrich our understanding of how people experience their worlds. When the audiences of our research hear poems and see plays that portray the themes and meanings in our data, they witness the power of nuance and the integrated nature of qualitative findings. Our audiences become more present in our story telling and are more likely to absorb the multi-dimensional messages we convey.

Johnny Saldaña, one of the best known practitioners of this research tradition, will guide participants through improvisational and writing exercises to explore how dramatic texts add credibility and make presentations more vivid and persuasive. These skills will help researchers document and represent fieldwork ranging from education to health care.

The course will also provide a literature review of exemplary play scripts and videos in research-based theatre; methods of dramatizing field notes and adapting interview transcripts; and the developmental process of autoethnographic monologues. Throughout, Saldaña emphasizes the vital importance of creating good theatre as well as good research for impact on an audience and performers.

Key figures in qualitative inquiry, Norman Denzin and Yvonna Lincoln, endorse the arts-based research techniques outlined and supported in this course as a powerful way for ethnographers to interrogate and represent the meanings of lived experiences.

No prior theatre or performance experience is needed to participate in this workshop.

To register, go to http://researchtalk.com/qrsi-2015.

Carolina Inn
Date: July 29, 2-15

QRSI: Eight Criteria for Creating Quality in Qualitative Research

Sarah Tracy

This workshop presents a parsimonious “big tent” model* of eight key markers of quality in qualitative research including:

  • Worthy Topic: Craft a topic that is heard as relevant, timely, significant and interesting to core audiences
  • Rich Rigor: Create rich rigor through using sufficient, abundant, appropriate, and complex theories, data, constructs, and analysis processes
  • Sincerity: Communicate sincerity by being self-reflexive and transparent
  • Credibility: Mark credibility through thick description, triangulation, crystallization, multivocality, and member reflections
  • Resonance: Fashion resonant research that influences and moves audiences through aesthetic representation, naturalistic generalization, and transferable findings
  • Significant Contribution: Develop a significant contribution—theoretically, practically, morally, methodologically, and heuristically
  • Ethics: Practice qualitative ethics–including procedural, situational, relational, and exiting considerations
  • Meaningful Coherence: Create meaningful coherence by interconnecting literature, research questions, findings and interpretations so that they fit together, cohere with the study’s goals, and connect with the audience’s expectations
This workshop is ideal for researchers, grant-writers, and instructors of qualitative methods—both those new to these areas as well as those who are experienced. This eight-point conceptualization offers a useful pedagogical model, a guide for evaluation, and a common language of qualitative best practices that can be recognized as integral by a variety of audiences.

*This model is based upon the conceptualization developed in journal article: Tracy, S. J. (2010). Qualitative quality: Eight “big-tent” criteria for excellent qualitative research. Qualitative Inquiry, 16, 837-851 and as elucidated in Tracy’s Qualitative Research Methods: Collecting Evidence, Crafting Analysis, Communicating Impact.

To register, go to http://researchtalk.com/qrsi-2015.

Carolina Inn
Date: July 29, 2015

QRSI: Learning from Lived Experience: How We Can Study the World as It Is Lived

Mark Vagle

This workshop will explore what “lived experience” means for qualitative researchers and how we can study the world as it is lived, not the world as it is measured, transformed, represented, correlated, and broken down. In paying close attention to lived experience, we are interested in the felt and sensed aspects of our and our participants’ experiences, as well as the contextual aspects in which these experiences are lived. How can we listen to and make sense of this significance and use it in our qualitative research?

We will identify lived experiences that we are interested in studying and use theoretical tools from phenomenological traditions to explore how we can open up, wonder about, and understand these experiences more deeply. We will treat theorizing as an active and generative process of exploration.

We will also put these theoretical tools to use in our data collection processes—focusing on observing and interviewing lived experiences. As a concrete example, we will spend time exploring how various visual and popular media can serve as data for studying lived experience. With data from some of Vagle’s current studies of social class lived experiences in schools and communities, we will further practice data analysis using the theoretical tools we have learned. Participants are also encouraged to bring their own data and/or research ideas so they can apply these tools and techniques to their work.

To register, go to http://researchtalk.com/qrsi-2015.

Carolina Inn
Date: July 29, 2015

QRSI: Publishing Qualitative Research

George Noblit

Qualitative research is a social practice that yields knowledge and understanding. To paraphrase Clifford Geertz, it involves “being there and writing here.”

This workshop will engage participants in a set of six processes to prepare for publishing qualitative research—both as journal articles and as books. These include:

1. Framing the study for publication -- examining the history of ideas in your field of study and recognizing a study’s potential.

2. Decoding journals and fields of study -- Knowing your audience both in terms of the intellectual field in which your study is to be situated and knowing the journals which are potential publication outlets.

3. Finding your voice -- Knowing what you found and how you found it is the first step in writing for publication, but the real tricks involve processes of finding your voice and becoming a literary researcher.

4. Reduction and Elaboration -- Qualitative studies are not naturally article length. Quite often they are too involved for a single article and not enough for a full book. Ironically, cutting down a study’s focus usually requires that more be said about some elements of the process and substance. Thus we must use processes of reduction and elaboration. In this, it is often helpful to find a template publication that helps organize and limit what needs to be said.

5. Surviving the review process -- Getting published either as a book or article involves being able to anticipate peer reviews. This requires the capability to take on a reviewer’s perspective, anticipating critiques, and thinking through alternative explanations.

6. Capturing an audience and Claiming a market - Writing books is about capturing an audience and claiming a market. To prepare for this, we will decode book proposal guides from publishers and practice selling a book idea. We will examine some qualitative books to discern: How a book is different from an article.

It will help if participants bring an existing study or study idea to be thought through, and ground our discussions.

To register, go to http://researchtalk.com/qrsi-2015.

Carolina Inn
Date: July 29, 2-15

QRSI: Coding and Analyzing Qualitative Data

Johnny Saldaña

This two-day workshop focuses on a range of selected methods of coding qualitative data for analytic outcomes that includes patterns, categories, themes, processes, and causation. The course will also touch upon how these methods fit with or differ from coding strategies in grounded theory and phenomenology.

The workshop will address:

• Various coding methods for qualitative data (interview transcripts, field notes, documents)

• Analytic memo and vignette writing

• Heuristics for thinking qualitatively and analytically

Manual (hard copy) coding will be emphasized with a discussion of available analytic software for future use. Workshop content is derived from Saldaña’s The Coding Manual for Qualitative Researchers (2nd ed., Sage Publications, 2013).

To register, go to http://researchtalk.com/qrsi-2015.

Carolina Inn
Dates: July 30 - 31, 2015

QRSI: Doing Qualitative Research Online

Tony Adams and Kevin Swartout

Millions of people use the internet to communicate every day; this trend will only accelerate with the proliferation of online applications (e.g., Reddit, Facebook, virtual communities such as SecondLife) and with the availability of portable, internet-enabled devices such as smartphones and tablets.

This course will address issues inherent to qualitative research and data analysis as collected, gathered and/or retrieved from online applications. Topics will include myths, strengths, and limitations of using the internet for/in research, analyzing qualitative data garnered from online settings, and designing and evaluating qualitative projects that use online components. Throughout, examples will be given from the instructors’ own research with traditional websites, social media, and other online contexts.

To register, go to http://researchtalk.com/qrsi-2015.

Carolina Inn
Dates: July 30 - 31, 2015

QRSI: Engaging Intensive Interviews

Kathy Charmaz

Interviewing is the most common method of data collection in qualitative inquiry. It has sparked much debate and discussion yet researchers have given relatively little concrete advice about how to develop effective interviewing skills. The purpose of this class is to give you a foundation for building skills to engage in mindful interviewing practice. We will take a collaborative approach to learning about interviewing and developing interviewing skills in a supportive environment.

Intensive interviewing is both a method and an intimate form of human connection seldom experienced between relative strangers. The interview experience can be revelatory and transformative for both the researcher and research participant. Yet because interviewing is a contested method, I will briefly outline criticisms of it. We will address questions of ethics, meaning, reflexivity, and co-construction of data and discuss complex situations that can occur when researchers interview people across racial, class, age, and gender divides. However, our main emphases will be on (1) constructing, ordering, and asking good in-depth interview questions and (2) being fully present while conducting the interview.

To start, we will work on constructing an interview guide with well-designed and paced questions. If you can create a good interview guide, you will become more attuned to how and when to ask to questions—even if you don’t use your interview guide. You will also become more sensitive to how research participants might think, feel, and respond to your questions. The class will give you opportunities to devise sample interview questions on a topic of your choice, conduct a short practice interview, and experience the interview process as a research participant. In this class, learning relies on direct experience, collaborative efforts, congenial interaction, and constructive feedback. We will have great fun engaging intensive interviews!

To register, go to http://researchtalk.com/qrsi-2015.

Carolina Inn
Dates: July 30 - 31, 2015

QRSI: Engaging Theory in Qualitative Analysis and Interpretation

George W. Noblit

The role of theory in qualitative research has changed and theory is now understood as a lens through which to interpret qualitative data. This approach has been called “theorizing” qualitative data. Theorizing explicates what can be said from a data set. In theorizing, substantive theories combine with reflection and researcher positionality to yield a reading of the data. Instead of testing theories, researchers use and critique them for their applicability as explanations and interpretations. Theorizing can be accomplished in various ways. Three common ways are:

1. Searching for alternative interpretations

2. Determining what is not analyzed by the theory

3. Conducting a more inductive, emic or grounded theory type analysis.

Each of these approaches focus on what is not accounted for by the theorizing. By comparing what results from each approach with the theorized account, we can gain or lose confidence in the trustworthiness of the theorized account.

Throughout the workshop, we will engage several exercises to practice theorizing:

• We begin with a reminder exercise involving coding.

• We will examine select theories, including theories used in applied and practice settings.

• In groups, we will develop the key concepts and logics to be used for a chosen theory or two and prepare a “theorizing guide” for each theory.

o We will then return to read and code the data using each theory in turn.

• We will then use a “theorized account writing guide” to write short accounts of our theoretical readings of data.

• Participants will compare the theorized accounts with alternative interpretations.

• Our group activities will end with participants “performing” a theorized account. These presentations will employ a readers’ theatre format where participants create a script using the guides completed during the session.

There are no prerequisites for this workshop and no prior knowledge of theory is necessary.

To register, go to http://researchtalk.com/qrsi-2015.

Carolina Inn
Dates: July 30 - 31, 2015

QRSI: Mixed Methods: Bridging Qualitative and Quantitative Methods and Results

Alison Hamilton

A researcher or research team pursues a mixed methods approach to understand a given topic or phenomenon more deeply when numbers or stories alone do not provide a complete picture. Combining qualitative and quantitative approaches can enhance conversations about theory and/or inform the evolution of practice and policy. This complex and demanding research paradigm requires knowledge, skill, and expertise in quantitative and qualitative methods, as well as the art of carefully integrating the approaches to and findings from each mode of inquiry.

This course focuses on strategies, tips, and best practices to accomplish this integration in accessible and effective ways, including:

• Rationales to guide decision making related to study design and execution. For example:
- Will the qualitative and quantitative data collection efforts occur concurrently or sequentially, and why?
- Will either the qualitative or quantitative be privileged or will each contribute equally to answering the research questions and generating the project’s final products?
- How much time will be allocated to integration and/or subsequent data collection phases, and what factors will contribute to the timing and phasing?
- What expertise and resources are needed?
- What are the priority end products and how does the integrated analytic plan lead to those products?

• Conceptual, theoretical, and/or logic models as roadmaps to set the stage for and guide integration.

• Design and analytic strategies that advance frameworks and processes of connecting, building, merging, embedding, and bridging. For example:
- The power and role of using data displays and visual diagramming during the analytic process, e.g., side-by-side comparisons, integrated matrices, joint displays.

• Qualities of good reporting and attributes of good mixed methods articles.

To register, go to http://researchtalk.com/qrsi-2015.

Carolina Inn
Dates: July 30 - 31, 2015

QRSI: Writing Effective Qualitative and Mixed Methods Proposals

Margarete Sandelowski

The focus of this course is on concrete, this-is-how-you-might/should-say-it strategies for designing and writing competitive qualitative and mixed-methods research proposals. Qualitative and mixed-methods research proposals are exercises in artful and mindful design, verbal precision, imaginative and informed rehearsal, elegant expression, and strategic disarmament. We will cover principles generic to proposals, and specific ways to communicate the significance, conceptual framing, methodological details (sampling and data collection and analysis plans, plans for optimizing validity and human subjects protections) of, and budget and budget justification for, the planned study. We will also cover strategies for addressing those aspects of qualitative and mixed-methods research designs likely to arouse the most concern among reviewers less familiar with them, most notably the purposeful sampling frame and generalizability of study findings. This course is appropriate for graduate students and faculty in the practice disciplines (e.g., clinical psychology, education, medicine, nursing, public health, social work) as well as researchers from other fields of study (e.g., sociology, anthropology).

In addition to didactic instruction, handouts, and a suggested reference list, the course will include an interactive session where participants will have the opportunity, as time permits, to ask questions about their own proposals for problem solving.

To register, go to http://researchtalk.com/qrsi-2015.

Carolina Inn
Dates: July 30 - 31, 2015

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 = $1300; Non-members = $2600

For registration details, click here.

Davis 3010

Dates: 8/5/15 - 8/7/15
Times: 9:00am - 5:00pm

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 = $1300; Non-members = $2600

For registration details, click here.

Davis 3010

Dates: 8/10/15 - 8/14/15
Times: 9:00am - 5:00pm

Quantitative Analysis

An Introduction to Designing Experiments

Lucy Martin

This short course will introduce participants to designing and conducting experiments. We will start with an introduction to experiments. What are the benefits and costs of experiments as an approach to research? What are the different types of experiments, and how can they be used to answer research questions in the social sciences? We will then discuss how to design a successful experiment. This will include discussion of deciding which type of experiment to use, treatment design, measurement concerns, sample selection, getting research permissions, and pre-analysis plans.

Registration Fees:

  • UNC Students - $10
  • Others - $15

    To Register, click here

    * 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 30, 2015

    Times: 1-3:30pm

    An Introduction to Implementing Experiments

    Lucy Martin

    This course will cover the basics of implementing an experimental design. It will include selecting a site and sample; piloting or pretesting the instrument; planning logistics for enumeration; training and supervising enumerators; and data management. The course will include time for participants to discuss how to apply these principles to their own experimental designs and contexts.

    Registration Fees:

  • UNC Students - $10
  • Others - $15

    To Register, click here

    * 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 6, 2015

    Times: 1:00pm - 3:30pm

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

    Ken Bollen

    A powerful method for analyzing longitudinal data is Latent Trajectory Analysis (LTA). LTA allows each case in a sample to have individual trajectories ("latent curves" or "growth curves") representing change over time. In addition to mapping these trajectories, LTA allows researchers to examine the determinants of these trajectories or to relate the trajectories of one variable with those of another. The approach to LTA in this course draws on the strengths of structural equation modeling (SEM), and the primary goal is to introduce participants to the theory and application of LTA. The course begins with a conceptual introduction to LTA, a description of research questions that are well-suited for the technique, and a review of SEMs. The remainder of the course will cover the following topics: LTA models for a single variable with and without predictors of differences in trajectories; modeling nonlinear trajectories; the LTA model 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 LTA model. Participants should have prior training and experience with structural equation modeling and related software.

    Fee: Members = $1500; Non-members = $3000

    For registration details, click here.

    Davis 219

    Dates: 5/18/15 - 5/22/15
    Times: 9:00am - 5:00pm

    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 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.

    Fee: Members = $1300; Non-members = $2600

    For registration details, click here.

    Davis 219

    Dates: 5/26/15 - 5/28/15
    Times: 9:00am - 5:00pm

    ICPSR - Multilevel Models: Pooled and Clustered Data

    Tom Carsey
    Multilevel models (also known as hierarchical linear models or mixed models) provide an extremely flexible approach to the analysis of a wide array of social science data. Multilevel modeling allows for the analysis of non-independent or "clustered" data that arise when studying topics such as siblings nested within families, students nested within classrooms, clients nested within therapists, or voters nested within media markets. Such models also accommodate data clustered or pooled across units and/or time periods – (e.g. 50 states measured annually over 30 years) – often labeled pooled time series data, time series cross sectional data, or panel data. Multilevel models are explicitly designed to analyze clustered or pooled data structures and can incorporate individual-level predictors, group-level predictors, and individual-by-group-level interactions. This course provides a general introduction to a variety of applications of multilevel modeling in the social sciences. Equal emphasis is placed on the underlying statistical model and on the estimation and interpretation of empirical data. The course explores methods for so-called robust standard errors in the face of clustered data, along with traditional methods for pooled time series and multi-level models. However, the primary goal is to demonstrate a general solution that encompasses these more narrowly focused approaches. We will consider models for continuous and categorical dependent variables. Time permitting, we will conclude with an introduction to Bayesian multi-level modeling. Each day will consist of a mixture of lectures and hands-on computer exercises and examples. We will include examples both in R and STATA. We will make substantial use of computer simulations to explore the statistical properties of multi-level models. Students should already be familiar with multiple regression and OLS. Some familiarity with Generalized Linear Models and Maximum Likelihood estimation is also helpful. No previous knowledge of Bayesian statistics is expected. Some prior exposure to R and STATA is helpful, but not required. The course will be taught at a level similar to the book Data Analysis Using Regression and Multi-level/Hierarchical Models, by Andrew Gelman and Jennifer Hill (2006), Cambridge University Press. Students are encouraged to bring their own data and projects with them to the class, as some lab time later in the course can be devoted to helping students address their specific needs.

    Fee: Members = $1500; Non-members = $3000

    For registration details, click here.

    Davis 219
    Dates: June 1-5, 2015
    Times: 9am - 5pm

    Data Matters: Data Science Short Course Series

    June 22-26)

    Sponsored by the National Consortium for Data Science (NCDS), the Renaissance Computing Institute (RENCI), and the Odum Institute for Research in Social Science, the "Data Matters: Data Science Short Course Series" is a week-long series of classes for researchers, data analysts, and other professionals who wish to increase their skills in data studies and integrate data science methods into their research designs and skill sets. Scholars, analysts, and researchers from all disciplines and industries are welcome. Both one- and two-day courses will be offered; participants are welcome to register for one, two, or three classes. Classes will run from 10 a.m. to 4:30 p.m.

    The Data Matters series is structured in three blocks: June 22-23, June 24, and June 25-26. Three to four courses are offered concurrently in each block. You will be able to choose only one course from each block. Courses are independent of each other; there is no predetermined sequence.

    For course descriptions and fees, please go to http://datamatters.org.

    June 22-26
    Friday Center for Continuing Education
    100 Friday Center Drive
    Chapel Hill, NC 27517


    June 22-23

    Introduction to Data Science
    Thomas Carsey

    Introduction to Information Visualization
    Angela Zoss

    Introduction to R
    Chris Bail

    Data Curation: Managing Data throughout the Research Lifecycle
    Jonathan Crabtree, Thu-Mai Christian, Sophia Lafferty-Hess

     

    June 24

    Internet of Things (IoT) Data: Introduction to IoT Data Creation and Use
    Russ Gyurek

    Health Informatics: Big Data in Health and Medicine
    Mark Braunstein

    Collecting, Classifying, and Analyzing Textual Data
    Chris Bail

    Open(ing) Data: Considerations in Data Sharing and Reuse
    Jonathan Crabtree, Thu-Mai Christian, Sophia Lafferty-Hess

     

    June 25-26

    Introduction to Data Mining and Machine Learning
    Ashok Krishnamurthy

    System Dynamics and Agent-based Modeling
    Todd BenDor

    Social Network Analysis: Description and Inference
    Bruce Desmarais

     

    If you have questions, please contact Paul_Mihas@unc.edu.


    Friday Center
    June 22, 2015 9:30 AM - 4:00 PM
    June 23, 2015 9:30 AM - 4:00 PM
    June 24, 2015 9:30 AM - 4:00 PM
    June 25, 2015 9:30 AM - 4:00 PM
    June 26, 2015 9:30 AM - 4:00 PM

    ICPSR - An Applied Introduction to Bayesian Methods

    Jeffrey Harden

    The use of Bayesian methods has increased rapidly in many social science fields over the past two decades. Bayesian analysis is well-grounded in probability theory, can often better account for the complexity of social processes, can improve computational efficiency, and even allows researchers to systematically include their own expertise and/or qualitative evidence in the quantitative framework of a statistical model. This course will provide an introductory overview of Bayesian methods as they are applied to social science research. We will focus on the two complementary goals of learning the theory behind Bayesian inference as well as practical implementation of several common models in R. No prior knowledge of Bayesian methods is necessary. However, this is not simply a survey course. Students will walk away from the course with an understanding of how to apply Bayesian models to their own research as well as knowledge of what is going on “under the hood” with their results. Class time will be spent in lecture and working hands-on with example data in R.

    Fee: Members = $1300; Non-members = $2600

    For registration details, click here.

    Davis 219

    Dates: 8/3/15 - 8/5/15
    Times: 9:00am - 5:00pm

    ICPSR - Analyzing Social Networks: An Introduction

    Doug Steinley
    Network analysis focuses on relationships between or among social entities. It is used widely in the social and behavioral sciences, as well as in political science, economics, organizational studies, behavioral biology, and industrial engineering. The social network perspective, which will be taught in this workshop, has been developed over the last sixty years by researchers in psychology, sociology, and anthropology. The social network paradigm is gaining recognition in the social and behavioral sciences as the theoretical basis for examining social structures. This basis has been clearly defined and the paradigm convincingly applied to important substantive problems. However, the paradigm requires concepts and analytic tools beyond those provided by standard quantitative (particularly, statistical) methods. This five day workshop covers those concepts and tools. The course will present an introduction to concepts, methods, and applications of social network analysis drawn from the social and behavioral sciences. The primary focus of these methods is the analysis of relational data measured on groups of social actors. Topics include an introduction to graph theory and the use of directed graphs to study actor interrelations; structural and locational properties of actors, such as centrality, prestige, and prominence; subgroups and cliques; equivalence of actors, including structural equivalence, blockmodels, and an introduction to relational algebras; an introduction to local analyses, including dyadic and triadic analyses; and an introduction to statistical analyses, using models such as p1 and exponential random graph models. The workshop will use several common software packages for network analysis: UCINET, Pajek, NetDraw, and STOCNET

    Fee: Members = $1500; Non-members = $3000

    For registration details, click here.

    Davis 219

    Dates: 8/10/15 - 8/14/15
    Times: 9:00am - 5:00pm

    Spatial Analysis

    Applied Spatial Regression Analysis

    Paul Voss

    This six-session 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. Spatial data typically are characterized, first, by heterogeneity, arising (1) from often highly diverse units of analysis (in terms both of geographic area and population size) and (2) from large-scale, long-distance regional differentiation (where social and economic activities are distributed across the landscape in somewhat homogeneous regions that stand out as different from neighboring regions). Second, spatial data usually are characterized by localized, small-scale, inter-unit dependence, arising from a host of mechanisms operating in space that serve to make individual units of analysis very much like other units in their neighborhood. These two factors (spatial heterogeneity and spatial dependence) conspire to bring our traditional regression results into violation of the strict assumptions underlying the standard linear regression model. Thus, when analyzing spatial data, it is paramount, first, to know how seriously the assumptions of the regression model are violated, and, second, what to do about it. This short course will provide a brief orientation to these important issues. Two analysis software packages will be used: OpenGeoDa and R.


    To register, click: here

    Davis 219
    Dates: 2/25/15, 3/4/15, 3/18/15, 3/25/15, 4/1/15, 4/8/15
    Time: 2pm - 4pm

    ICPSR - Introduction to Spatial Regression Analysis

    Elisabeth Root
    Spatially-referenced data add important contextual and locational information to the social and behavioral sciences, such as sociology, anthropology, political science, economics and public health. A geographic or spatial-analytic framework, which will be taught in this workshop, can be used to explore the importance of spatial relationships in a variety of social and behavioral processes. However, spatial data and spatial relationships necessitate the use of analytic tools beyond those provided by standard statistical methods. This 5-day course introduces the spatial-analytic framework, and explores the range of issues that generally must be dealt with when analyzing spatial data. The role of spatial autocorrelation in spatial data sets is a central focus of this course. Throughout the course we will address the following questions: how and why does spatial autocorrelation arise; how is it measured and understood; how does it relate to issues of spatial heterogeneity and spatial dependence; and how should it inform the specification and estimation of regression models. Specific modeling techniques include: indices of spatial autocorrelation (Moran's I, Geary's C, LISA), spatial regression models (SAR and SARAR), and geographically weighted regression (GWR).

    The course is structured around a combined lecture format (mornings) and computing lab exercises (afternoons). The focus of the course is on spatial statistical analysis, not Geographic Information Systems (GIS). Hands-on application of statistical methods in afternoon lab sessions will enable participants to pursue a broad range of social and behavioral science research topics. Software emphasis will be given to GeoDa and R for exploratory spatial data analysis and modeling. Some acquaintance with this software is helpful but is not a prerequisite. Detailed R code will be provided and discussed in labs, and we will lean how to interpret, visualize and map model output.

    Prerequisites for maximizing learning in this course are a solid grounding in standard multivariate regression techniques and a minimal level of comfort with matrix notation and algebra.

    Fee: Members = $1300; Non-members = $2600

    For registration details, click here.

    Davis 219

    Dates: June 8 - 10, 2015

    Times: 9:00am - 5:00pm

    Survey Research

    Designing and Conducting Surveys of Businesses and Organizations

    Diane Willimack
    This course provides an overview of methodological issues associated with the use of surveys to collect data from organizations. We will identify key differences between household surveys and organizational surveys, emphasizing organizational behaviors and attributes that affect survey response. We will demonstrate an approach to survey design that utilizes understanding and consideration of this organizational context when developing, adapting, and implementing data collection instruments and procedures. This course will include topics related to survey planning, questionnaire design and pretesting, data collection modes, and communication and response improvement strategies.

    This integrated approach to surveys of businesses and organizations is the subject of a new book in the Wiley Series in Survey Methodology, entitled Designing and Conducting Business Surveys, written by Ger Snijkers, Gustav Haraldsen, Jacqui Jones, and Diane K. Willimack.


    Registration Fees:

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

    To Register, click here
    This course will count as 7.0 CPSM short course credit hours.

    For more information, please contact Jill_Stevens@unc.edu.

    * 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
    April 09, 2015 9:00 AM - 4:30 PM

    Statistical Computing

    SAS

    Chris Wiesen

    This is a four-part course that does NOT require registration. 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.

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


    Davis 3010
    Dates: August 31 - September 3, 2015

    Times: 11:00am - 1:00pm