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

ATLAS.ti 7.0 Hands-On Workshop (Part 1)

Paul Mihas

Atlas.ti Part 1 training. This hands-on short course will illustrate the capabilities of the PC version of ATLAS.ti 7, a software program for coding and interpreting qualitative text. It provides a network editor that allows you to graphically display and examine the hierarchical and relational connections among your codes. ATLAS.ti provides numerous options for attaching memos and comments to text segments, documents, and codes.

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

For further information, please contact Paul Mihas.


Davis 3010
April 26: 2-4:30 p.m. 3010 Davis Library

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 12 - 14, 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

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

Introduction to Data Science Using R

Justin Post
Part of the Data Matters: Data Science Short Course Series

This course provides a basic introduction to the R software environment for the purpose of data science. The course covers importing and exporting data, manipulating data or recoding variables, and visualization and statistical analysis.

Hunt Library, NCSU Campus
August 07, 2017 10:00 AM - 4:15 PM
August 08, 2017 10:00 AM - 4:15 PM

Introduction to Data Science Using R

Jonathan Duggins
Part of the Data Matters: Data Science Short Course Series

This course provides a basic introduction to the R software environment for the purpose of data science. The course covers importing and exporting data, manipulating data or recoding variables, and visualization and statistical analysis.

Hunt Library, NCSU Campus
August 07, 2017 10:00 AM - 4:15 PM
August 08, 2017 10:00 AM - 4:15 PM

Introduction to Effective Information Visualization

Eric Monson
Part of the Data Matters: Data Science Short Course Series

Participants will learn how to clean and structure data; see how freely and commonly available software can be used to create effective visualizations; and learn basic design principles, so you can go beyond the defaults and create eye-catching and impactful figures and infographics!

Hunt Library, NCSU Campus
August 07, 2017 10:00 AM - 4:15 PM
August 08, 2017 10:00 AM - 4:15 PM

Working with Messy Data

Brown Biggers
Part of the Data Matters: Data Science Short Course Series

When working with data, one thing is fairly certain: data is rarely in an optimized format. A misplaced space here, or an extra comma there, can mean the difference between two clicks and two hours of work. In this course, we will work with ways to manipulate, interpret, and present data from webpages and text using Python version 2.7 and OpenRefine. This class will also cover regular expressions, various imported libraries to extend Python functionality, and import/export of data in OpenRefin.

Hunt Library, NCSU Campus
August 07, 2017 10:00 AM - 4:15 PM
August 08, 2017 10:00 AM - 4:15 PM

Introduction to Big Data and Machine Learning for Survey Researchers and Social Scientists

Trent Buskirk
Part of the Data Matters: Data Science Short Course Series

Data science, machine learning and big data are all the rage in many areas where decisions are required or insights need to be made. In this course we explore how big data concepts, processes and methods can be used within the context of social science and survey research. We also provide a technical overview of common machine learning algorithms coupled with examples that are specifically motivated by social science and survey research applications.

Hunt Library, NCSU Campus
August 09, 2017 10:00 AM - 4:15 PM

Introduction to Geospatial Analytics

Eric Money
Part of the Data Matters: Data Science Short Course Series

This course offers a broad overview of geospatial analytics and the implications of using geospatial data to support decision-making across a variety of domains. The course will focus on the identification, acquisition, management, analysis, and communication of geospatial data from the perspective of non-geospatial professionals who find themselves needing to utilize location-based data more effectively.

Hunt Library, NCSU Campus
August 09, 2017 10:00 AM - 4:15 PM

Programming in R

Justin Post
Part of the Data Matters: Data Science Short Course Series

This class provides students with an introduction to basic programming techniques in R, a program with stronger object-oriented programming facilities than most statistical computing languages. The R language is widely used among statisticians and data miners for developing statistical software and data analysis. R's popularity has increased substantially in recent years.

Hunt Library, NCSU Campus
August 09, 2017 10:00 AM - 4:15 PM

Programming in R

Jonathan Duggins
Part of the Data Matters: Data Science Short Course Series

This class provides students with an introduction to basic programming techniques in R, a program with stronger object-oriented programming facilities than most statistical computing languages. The R language is widely used among statisticians and data miners for developing statistical software and data analysis. R's popularity has increased substantially in recent years.

Hunt Library, NCSU Campus
August 09, 2017 10:00 AM - 4:15 PM

Intermediate Programming in R

Justin Post
Part of the Data Matters: Data Science Short Course Series

The class provides students with a primer on the use of R for the writing of reproducible reports and presentations that easily embed R output using R markdown as well as the creation of interactive and customizable web applets called R Shiny applications.

Hunt Library, NCSU Campus
August 10, 2017 10:00 AM - 4:15 PM
August 11, 2017 10:00 AM - 4:15 PM

Introduction to Data Mining and Machine Learning

Raju Vatsavi
Part of the Data Matters: Data Science Short Course Series

This course will introduce participants to a selection of the techniques used in data mining and machine learning in a hands-on, application-oriented way. Topics covered will include data exploration, decision trees, clustering, association rules, regression and pattern classification. The computing exercises will be based on the statistical programming language, R. At the end of the two days, you will be able to explore a data set, and determine which analysis method is appropriate for the data, and be able to use R packages to obtain results.

Hunt Library, NCSU Campus
August 10, 2017 10:00 AM - 4:15 PM
August 11, 2017 10:00 AM - 4:15 PM

Introduction to Data Mining and Machine Learning

Ashok Krishnamurthy
Part of the Data Matters: Data Science Short Course Series

This course will introduce participants to a selection of the techniques used in data mining and machine learning in a hands-on, application-oriented way. Topics covered will include data exploration, decision trees, clustering, association rules, regression and pattern classification. The computing exercises will be based on the statistical programming language, R. At the end of the two days, you will be able to explore a data set, and determine which analysis method is appropriate for the data, and be able to use R packages to obtain results.

Hunt Library, NCSU Campus
August 10, 2017 10:00 AM - 4:15 PM
August 11, 2017 10:00 AM - 4:15 PM

Survey Research

Designing and Conducting Surveys of Businesses and Organizations

Diane Willimack and Chris Ellis
Surveys of businesses and organizations differ in important ways from surveys of individual persons and households. In particular, they rely on one or more employees or representatives of the organization to report data about the entity on its behalf. As a result, a respondent’s approach to the survey is influenced by organizational characteristics, which provide a context within which the response process occurs, affecting survey participation decisions, data quality, and response burden. Practical issues emerge that have implications for the effectiveness of data collection instruments, procedures and strategies in the organizational setting, such as who decides whether to participate in the survey, who is the “right” respondent, are the desired data in records, are the data accessible, and so on.

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 2013 textbook 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.

This course will count as 7.0 CPSM Short Course credit hours.

Registration Fees:

  • CPSM Students - $40
  • UNC Students - $65
  • Other - $90

    Registration will open 60 days prior to the class date.

    * 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: 9/21/2017

    Times: 9:00am - 4:30pm

    Data Collection Using Mobile Phones in Developing Countries: New Approaches with SMS, IVR, and CATI

    Charles Lau

    The rapid growth of mobile phones in developing countries opens up new possibilities for data collection. Short message service (SMS), interactive voice response (IVR), online surveys (web) and computer-assisted telephone interviewing (CATI) can produce data faster and less expensively than face-to-face surveys. This course will introduce students to the design and implementation of SMS, IVR, Web, and CATI surveys in low- and middle-income countries.

    In this course, Dr. Lau will draw from real world examples to illustrate how these modes work. We will also discuss basic survey design principles in each mode, focusing on sampling, questionnaire development, and survey design. New for this year’s course: Students will work in small groups to design questionnaires and collect data in real time via SMS and IVR using a free, open source survey tool.

    There are no prerequisites for this course, but basic familiarity with survey research in developing countries is helpful.

    THE INSTRUCTOR
    Charles Lau designs and implements surveys in low- and middle-income countries. He directs projects through the survey cycle, including study design, questionnaire development, sampling, interviewer training, data collection, analysis, and reporting. Dr. Lau has led surveys in 17 countries in Africa, Asia, and Latin America. In these countries, he has used different modes of data collection, including face-to-face interviewing with tablets, telephone, web, and short message service (SMS). With funding from governments, foundations, and commercial clients, his work has covered various topics including health, education, politics, and technology. He also publishes research on cross-cultural issues in survey design, interviewer and mode effects, and sampling approaches in developing countries. Dr. Lau joined RTI in 2010.

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

    Registration Fees:

  • CPSM Students - $30
  • UNC Students - $40
  • Other - $60

    Registration will open 60 days prior to the class date.

    * 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.
    There will be no registration fee but slots are limited.

    * Waitlist/ Walk-ins: There may be a waitlist for the courses. Walk-ins will not be accepted. Each attendee must register prior to 3 days before the start of the course.

    Davis 219
    Date: 9/28/17

    Times: 9:00am - 1:00pm

    Conducting Cross Cultural Surveys – Challenges and Best Practices

    Emilia Peytcheva

    This course will provide an introduction to survey research methods for designing multinational and multicultural surveys. It begins with an overview of the field of comparative surveys. This will summarize their history and discuss some unique design features and implementation challenges inherent in their design and implementation.

    The second section discusses quality and risk management frameworks for comparative surveys. It will present some tools for monitoring quality processes and outcomes, and will reference the new Guidelines for Comparative Surveys (ccsg.isr.umich.edu). The third section of the course focuses on issues in study design, considering organizational structure, data collection infrastructure and management, and cost and quality tradeoffs.

    The second half of the course addresses instrument design for comparative surveys. It opens with a discussion of issues in defining objectives, identifying constructs, developing questions, and monitoring design process quality that are particular to the field of comparative surveys. It will also cover some technical challenges in crafting the questions into a survey instrument; visual display of text in various languages, placement of response categories and instructions, use of color, screen density, and other features of contemporary survey instruments will be reviewed from a multilingual and multicultural context. The links between design and mode considerations are also covered. The course concludes with a module on question adaptation and translation focusing on the critical role that version production often plays.

    Examples will be drawn from demographic and social indicator surveys, attitudinal surveys, health and education surveys, and quality of life surveys.

    THE INSTRUCTOR
    Emilia Peytcheva, is a research survey methodologist with RTI International. She holds a PhD. in survey methodology from the University of Michigan. Peytcheva's research expertise includes measurement error-inducing factors in cross-cultural research and the interplay among survey errors and their combined effect on total survey error. Her interests include methods for minimizing measurement error induced by the survey questionnaire. Peytcheva is also one of the instructors for the required CPSM course titled Questionnaire Design.

    This course will count as 4.0 CPSM Short Course credit hours.

    Registration Fees:

  • CPSM Students - $30
  • UNC Students - $40
  • Other - $60

    Registration will open 60 days prior to the class date.

    * 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: October 5, 2017

    Times: 1pm - 5pm

    Issues in the Analysis of Complex Sample Survey Data

    Brady West
    This one-day short course will provide participants with an introductory overview of issues frequently encountered when conducting secondary computer analyses of data collected from sample surveys with complex multi-stage designs (e.g., PSID, NHANES, NCS), including design-based weight determination, software choice, and proper analysis methods. The workshop is not intended for participants looking to design a survey, but rather for participants who have a desire to analyze complex sample survey data. TOPICS:

    • Recognizing a sample with a complex design, and sampling error calculation models
    • Calculation of survey weights based on sample designs / non-response / post-stratification
    • Calculation of new weights for subgroups / longitudinal analyses
    • Weighted vs. unweighted analyses
    • Variance estimation, and calculation of correct confidence intervals for population parameters
    • Hypothesis Testing based on sample estimates
    • Design Effects
    • Software packages capable of complex sample survey data analysis
    • Common analysis methods (linear modeling, descriptive statistics), interpretation of results
    • Using weights in regression modeling, and model-based approaches
    • Examples using software programs to analyze real survey data

    THE INSTRUCTOR
    Brady T. West is a Research Associate Professor in the Survey Methodology Program, located within the Survey Research Center at the Institute for Social Research (ISR) on the University of Michigan-Ann Arbor campus. He also serves as a Statistical Consultant on the University of Michigan Consulting for Statistics, Computing, and Analytics Research (CSCAR) Team. He earned in his PhD from the Michigan Program in Survey Methodology in 2011. Before that, he received an MA in Applied Statistics from the U-M Statistics Department in 2002, being recognized as an Outstanding First-year Applied Masters student, and a BS in Statistics with Highest Honors and Highest Distinction from the U-M Statistics Department in 2001. His current research interests include the implications of measurement error in auxiliary variables and survey paradata for survey estimation, survey nonresponse, interviewer variance, and multilevel regression models for clustered and longitudinal data. He is the lead author of a book comparing different statistical software packages in terms of their mixed-effects modeling procedures, now in its second edition (Linear Mixed Models: A Practical Guide using Statistical Software, Second Edition, Chapman Hall/CRC Press, 2014), and he is a co-author of Applied Survey Data Analysis, also now in its second edition.

    Registration will open 60 days prior to the class date.


    Registration Fees:

  • CPSM Students: $40
  • UNC Students: $65
  • Other: $90

    This course will count as 7.0 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: 10/26/17

    Times: 9:00am - 4:30pm

    Introduction to Focus Groups

    Emily Geisen

    Focus group interviews are commonly used for survey development, content development, and qualitative data collection to capture rich information about attitudes and beliefs that affect behavior. An overview of the basics of focus groups supplemented with real examples and hands-on practice will highlight the most appropriate uses of focus groups, moderating focus groups, developing interview questions, analyzing and using results, as well as reporting findings.

    THE INSTRUCTOR
    Emily Geisen is a survey methodologist at RTI International. She received her M.S. in survey methodology from the University of Michigan. She has over 10 years experience designing methodological research studies, developing and evaluating survey instruments, leading data collection tasks, managing projects, and performing statistical analyses using SAS. She is the manager of RTI’s cognitive/usability laboratory and specializes in evaluating survey instruments to improve data quality and reduce respondent burden. She was the 2010 conference chair for the Southern Association for Public Opinion Research (SAPOR) and the 2009–2011 secretary of the Survey Research Methods Section of the American Statistical Association.

    Registration Fees:

  • CPSM Students - $40
  • UNC Students - $65
  • Other - $90

    Registration will open 60 days prior to the class date.

    This course will count as 7.0 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: 11/9/2017

    Times: 9:00am - 4:30pm

    Nonresponse from the Total Survey Error Perspective: An Overview

    Paul Biemer
    The Total Survey Error (TSE) paradigm embodies the best principles, strategies, and approaches for minimizing the survey error from all sources within time, costs, and other constraints that can be imposed on the survey. This approach can be viewed as resting on the four pillars of survey methodology: survey design, implementation, evaluation, and data analysis. This course provides an overview of the TSE paradigm as it applies to one critical source of error: nonresponse. Structured around these four pillars, the course presents the best methods and lessons learned for dealing with nonresponse in survey, data collection, data analysis and evaluation. The survey focuses particularly on the interactions of response mechanism with other error sources and how nonresponse interventions can lead to unintended consequences for TSE.

    THE INSTRUCTOR
    Paul Biemer holds a joint appointment with the Odum Institute and RTI International, where he is a Distinguished Fellow. He also holds adjunct faculty appointments in the University of Maryland Joint Program for Survey Research and in the University of Michigan Survey Research Center. Biemer has more than 35 years of experience in survey methods and statistics. He specializes in evaluating survey quality and is a leading expert on statistical modeling, analysis, and interpretation of survey results. Biemer has a Ph.D. in statistics from Texas A&M University. His research interests include: Measurement error in surveys; nonsampling error modeling and estimation; general survey methodology and statistical methods. Biemer teaches several short courses for the program including: Introduction to Survey Quality, An Overview of Methods for Evaluating Survey Error, and Techniques for Modeling Survey Measurement Error.

    This class will be count for 4.0 CPSM short course credit hours.

    Registration Fees:

  • CPSM Students - $30
  • UNC Students - $40
  • Other - $60

    Registration will open 60 days prior to the class date.


    * 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: 11/16/17

    Times: 9:00am - 1:00pm

    Other

    Data Curation: Managing Data throughout the Research Lifecycle

    Thu-Mai Christian, Sophia Lafferty-Hess
    Part of the Data Matters: Data Science Short Course Series

    This course will provide an introduction to data management best practices as well as demonstrations of digital curation tools including the Dataverse Network™ open source virtual archive platform.

    Hunt Library, NCSU Campus
    August 07, 2017 10:00 AM - 4:15 PM
    August 08, 2017 10:00 AM - 4:15 PM

    Introduction to Effective Information Visualization

    Eric Monson
    Part of the Data Matters: Data Science Short Course Series

    Participants will learn how to clean and structure data; see how freely and commonly available software can be used to create effective visualizations; and learn basic design principles, so you can go beyond the defaults and create eye-catching and impactful figures and infographics!

    Hunt Library, NCSU Campus
    August 09, 2017 10:00 AM - 4:15 PM

    Open(ing) Data: Considerations in Data Sharing and Reuse

    Thu-Mai Christian, Sophia Lafferty-Hess
    Part of the Data Matters: Data Science Short Course Series

    This course will provide an introduction to data management best practices as well as demonstrations of digital curation tools including the Dataverse Network™ open source virtual archive platform.

    Hunt Library, NCSU Campus
    August 09, 2017 10:00 AM - 4:15 PM

    Visualization for Data Science in R

    Angela Zoss
    Part of the Data Matters: Data Science Short Course Series

    This course is designed for two audiences: experienced visualization designers looking to apply open data science techniques to their work, and data science professionals who have limited experience with visualization. Participants will develop skills in visualization design using R, a tool commonly used for data science. Basic familiarity with R is required..

    Hunt Library, NCSU Campus
    August 10, 2017 10:00 AM - 4:15 PM
    August 11, 2017 10:00 AM - 4:15 PM