AAPOR
The leading association
of public opinion and
survey research professionals
American Association for Public Opinion Research

Short Courses

The 2018 Conference will include seven short courses to enhance your learning experience. These in-depth, half-day courses are taught by well-known experts in the survey research field and cover topics that affect our ever-changing industry. The 2018 Short Courses include:

Course 1: Multilevel Regression and Post-stratification 
Course 2: From Ground Rules to Group Dynamics: Moderating Focus Groups for Social Science Research
Course 3: Data Visualization for Survey Research: From Data Collection, through Budgets and Production, to Reports and Presentations
Course 4: Smartphones: From Surveys to Sensors 
Course 5: Nonprobability Sampling and Analysis for Population Inference
Course 6: Designing Mixed-Mode Surveys
Course 7: Geographic Information Systems (GIS) Applications in the Social Sciences: Maps, Mappable Data, and Geospatial Analysis
 
Short Course Details
Course 1
Title: Multilevel Regression and Post-stratification  
Date: Tuesday, May 15, 2:30 p.m. – 6:00 p.m.
Multilevel Regression and Post-stratification (MRP) provides an alternative to traditional weighting and calibration methods for correcting surveys for non-response and selection bias. MRP allows researchers to correct for skews in many variables simultaneously using multilevel regression models. It can also be used to produce state-level estimates from national samples. The course covers both basic concepts and practical issues in implementing MRP, such as model validation and construction of targets. Examples from recent election surveys will be shown.

Instructor:
Doug Rivers is Professor of Political Science at Stanford University and the Chief Scientist at YouGov. He is the winner of the AAPOR Innovator’s Award, the APSA’s Charles Merriam Prize and Career Achievement Award from the Society for Political Methodology.   

Course Objectives:
• Understanding of why MRP works
• How to implement MRP using R and Stan
• Successful examples of MRP

Who Should Attend:
Intended for survey practitioners. The focus is on concepts and applications. A basic understanding of regression analysis and prior experience with survey weighting is helpful. 

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Course 2
‚ÄčTitle: From Ground Rules to Group Dynamics: Moderating Focus Groups for Social Science Research
Date: Tuesday, May 15, 2:30 p.m. – 6:00 p.m. 
Course Overview:
The course is designed as an interactive introduction to implementing focus groups for social science research, with an emphasis on writing the discussion guide and moderating techniques. The course is divided into three modules.  Module 1 will provide general information about how focus groups fit into the larger spectrum of qualitative and mixed-mode research, their usage and applications, and basic principles of designing a focus group study for social science research. Participants will have the opportunity to formulate the design of their own focus group project. Module 2 covers the fundamentals of crafting moderator guides for focus groups based on the survey literature and case studies. In this module, participants will have a chance to draft and receive feedback on their own focus group questions.  Module 3 covers key principles of effective moderating techniques. In this module, participants will be given the opportunity to critique a moderator and to practice moderating themselves. The instructor will place emphasis on creative techniques for eliciting information, handling special situations in focus groups, and techniques for moderating in alternative modalities such as telephone and online. 

Instructor:
Darby Steiger
 is a senior survey methodologist at Westat with 25 years of experience designing, conducting, analyzing, and presenting social science research for government agencies, non-profits, and associations. She has developed and tested hundreds of questionnaires and moderated hundreds of focus groups. She trains staff, clients, and others in the U.S. and around the world in focus group moderating techniques. Darby has Master’s degrees from the University of Michigan in Public Policy and Applied Social Research and was a senior methodologist at Gallup prior to joining Westat.     
      
Course Objectives:
• Students will learn the theoretical principles behind crafting effective questions for social science focus groups that will meet research objectives and encourage lively discussion
• Participants will walk away with practical tips for effectively moderating a focus group, building rapport, and managing unexpected situations that may arise.    
• Participants will have the opportunity to practice and receive feedback on draft questions and their own moderating techniques.       

Who Should Attend:
This course is designed for early- to mid-career professionals who are interested in how, when and why to use focus groups and how to moderate focus groups. The course will be particularly beneficial for those who have never moderated before, those who are preparing for upcoming focus groups, as well as those who would benefit from refresher training.  Students will be encouraged to bring their own draft moderator guides to the class.

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Course 3
Title: Data Visualization for Survey Research: From Data Collection, through Budgets and Production, to Reports and Presentations
Date: Wednesday, May 16,  8:00 a.m. – 11:30 a.m. 
Course Overview:
Data visualization is a rapidly growing area of application for analysis and dissemination of data. This short course will illustrate how data visualization can be used to enhance research projects. The course is ideal for survey researchers and project managers with minimal knowledge on data visualization who want to use graphics to examine trends in data, isolate discrepancies, and identify patterns that would otherwise be overlooked. We will cover the basics of presenting data in accurate graphical form across multiple fields, including topics such as field management, monitoring budgets, and examining completion rates and cost per case.

In addition, our course will include an introduction to basic principles of data visualization, examples of how project and budget data can be visualized, best practices for avoiding common mistakes, and an interactive back-and-forth of good and bad examples.  We will also discuss the pros and cons to popular visualization tools, such as Tableau, R, and Excel, and present a step-by-step guide to making and customizing graphics in Excel.

Instructor:
Nola du Toit uses her experience as Research Methodologist to inform and create infographic reports and data visualizations. Her activities covers the entire information visualization process, including data measurement and conceptualization, user understanding and interpretation, and design principles.
Edward Mulrow is an Accredited Professional Statistician™ and Fellow of the American Statistical Association (ASA), and is the ASA Section on Statistical Graphics Program Chair for the 2019 Joint Statistical Meetings. He has over 30 years of experience and has organized data visualization workshops and seminars that provided training, in-person consultation, and strategies for communicating statistical analyses in a visual way.        

Course Objectives:
• Understanding of the best practices for data visualization
• Knowledge on producing data visualization from survey and budget data
• Practice in creating complex graphics in Excel

Who Should Attend:
This course is geared towards survey researchers and project managers with minimal data visualization experience as well as those who want to learn more about customizing graphics in Excel.  
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Course 4
Title: Smartphones: From Surveys to Sensors 
Date: Wednesday, May 16,  8:00 a.m. – 11:30 a.m. 
Course Overview:
The release of the first IPhone was now more than a decade ago, and smartphones have since become a mainstream device. In many countries, smartphones are replacing traditional PCs and laptops as the primary device to browse the Internet, and use social media. In the last couple of years, researchers have experimented with smartphones as a method of data collection. This short course focuses on recent studies that have aimed to study how smartphones can be used. 1. As a device to administer surveys and 2. To acquire additional behavioral data using sensors.

In particular we will discuss:

  • Why you should want to do research using smartphones
  • How web questionnaires should be adapted to become smartphones-friendly
  • Issues related to willingness and consent to participate in smartphone studies that collect behavioral data
  • How such behavioral data can potentially be used to enrich survey data, using GPS locations as an example
It is helpful if participants to the short course bring a smartphone with them, as well as a laptop. We will not do any data-analysis during the short course, but will provide a small dataset with GPS location data collected using smartphones. We will use this dataset to illustrate and discuss how such data can be used alongside survey data to better understand people’s behavior and attitudes.

Instructors:
Peter Lugtig 
is an associate professor in survey methodology. His research interest lie in the interplay of three areas: 1. Doing survey-research on mobile devices 2. The methodology of panel studies and 3. the statistical estimation of data quality in surveys. He received a Future Leaders Grant in 2012 from the UK Econonomic and Research Council for a 3-year research project into the trade-off between nonresponse and measurement errors in panel surveys. Peter is a member of the consortium board of the Gender and Generations Programme (www.ggp-i.org), member of the methodological advisory board of the Understanding Society study (www.understandingsociety.ac.uk), and member of the coordinating team of the Dutch Platform for Survey Research (www.npso.net). He has published extensively on mobile and panel surveys in journal such as Sociological Methods and Research, the Journal of Official Statictics and Social Science Computer Review.

Vera Toepoel is an assistant professor in survey methodology at the Department of Methods and Statistics at Utrecht University, the Netherlands. Her research interest lie in everything related to survey methodology and online surveys in particular: from recruiting respondents, designing the survey instrument, correcting for bias etc. Current topics include data chunking (a.k.a. modular survey design), sensor data (and consent) and mobile survey design. Vera is a member of the coordinating team of the Dutch Platform for Survey Research and the secretary (and president delegate) for RC33 (Methods and Logistics) from the International Sociological Association. She is a member of the Scientific Quality Assurance Board of the GESIS Online Panel in Germany. Vera is the author of the book “Doing Surveys Online” published by Sage (2016), has authored several chapters in handbooks for methodology, and has published numerous journal papers amongst others in Public Opinion Quarterly, Sociological Methods and Research, Survey Research Methods, Social Science Computer Review, Survey Practice etc.

Course Objectives:
• Understand why you should want to do research using smartphones
• Learn how to make web surveys mobile-friendly.
• Understand issues around the collection and analysis of smartphones sensor data

Who Should Attend:
No previous knowledge is required, although an understanding of survey methods (the TSE framework, questionnaire design) will be helpful.

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Course 5
Title: Nonprobability Sampling and Analysis for Population Inference
Date: Wednesday, May 16, 8:00 a.m. – 11:30 a.m.
Course Overview:
Although selecting a probability sample has been the standard for decades for making inferences from a sample to a finite population, incentives are increasing to use data obtained without a defined sampling mechanism, i.e., nonprobability samples. In a world of “big data”, substantial amounts of data are readily available through methods that are faster and need fewer resources relative to most probability-based designs.  There are many ways of collecting these data—volunteer web panels, tele-voting, expert selection, respondent-driven network sampling, and others—none of which require probability samples. 
 
Design-based inference, in which population values are estimated through the random sampling procedure specified by the sampler, cannot be used for nonprobability samples. One alternative is quasi-randomization where pseudo-inclusion probabilities (i.e., propensity scores) are estimated from covariates available for both sample and nonsample units. Another estimation approach is superpopulation modeling; analytic variables collected on the sample units are used in a model to predict values for the nonsample units. We include several simulation and case studies to illustrate the properties of these approaches and discuss the pros and cons of each.

Instructors:
Dr. Richard Valliant
 is a Research Professor Emeritus at the University of Michigan and the Joint Program for Survey Methodology at the University of Maryland. 
Dr. Jill A. Dever is a Senior Research Statistician at RTI International in Washington, DC. Since 2008, this team has developed material on nonprobability sampling and analysis, including two books and several peer-reviewed journal articles.  Additionally, Dr. Dever was a member of the 2013 AAPOR task force charged with evaluating nonprobability sampling, and Dr. Valliant was an invited discussant for the corresponding Journal of Survey Statistics and Methodology summary article.

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Course 6
Title: Designing Mixed-Mode Surveys
Date: Saturday, May 19, 8:00 a.m. – 11:30 a.m. 
Course Overview:
Currently, a large variety of data modes such as telephone interview, personal interview, mail or web (PC, tablet, mobile) survey are available for social surveys, which leads to methodological questions, such as, which mode or online device is best? Each mode has its advantages and disadvantages; each mode also makes different logistical demands. Often one single mode will not suffice. Therefore multiple modes of data collection or mixed modes have become more and more popular in survey practice.

In this workshop I give an overview on the current state of the art in designing, implementing, and evaluating mixed-mode surveys. I address the major variants of mixed-mode data collection designs, issues in questionnaire design, and management of mixed-mode projects. In addition, I focus on mixed-device surveys: online surveys where respondents use either desktop, tablet or mobile phone. The objective is to provide the participants with a thorough background on mixed-mode and mixed-device methodology and with an empirical knowledge base on the implications of mixed-mode for questionnaire design, total survey error and logistics. After this workshop participants should be able to design a mixed-mode or mixed-device survey. Note that this workshop does not focus on the analysis of mixed-mode data.

Instructor:
Vera Toepoel is an assistant professor in survey methodology at the Department of Methods and Statistics at Utrecht University, the Netherlands. Her research interest lie in everything related to survey methodology and online surveys in particular: from recruiting respondents, designing the survey instrument, correcting for bias etc. Current topics include data chunking (a.k.a. modular survey design), sensor data (and consent) and mobile survey design. Vera is a member of the coordinating team of the Dutch Platform for Survey Research and the secretary (and president delegate) for RC33 (Methods and Logistics) from the International Sociological Association. She is a member of the Scientific Quality Assurance Board of the GESIS Online Panel in Germany. Vera is the author of the book “Doing Surveys Online” published by Sage (2016), has authored several chapters in handbooks for methodology, and has published numerous journal papers amongst others in Public Opinion Quarterly, Sociological Methods and Research, Survey Research Methods, Social Science Computer Review, Survey Practice etc.   
 
Course Objectives:
• Major variants of mixed-mode data collection designs
• Implications of mixed-mode designs
• Total Survey Error in mixed-mode designs 

Who Should Attend:
Anyone interested in doing mixed-mode surveys

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Course 7
Title: Geographic Information Systems (GIS) Applications in the Social Sciences: Maps, Mappable Data, and Geospatial Analysis 
Date: Saturday, May 19, 8:00 a.m. – 11:30 a.m. 
Course Overview:
Geographic Information Systems (GIS) has become a popular tool to compile, present, and understand data in the social sciences.  This short course is ideal for those with minimal GIS knowledge, who want a practical introduction to learn the basics of presenting social scientific data on a map and conducting simple geospatial analyses.  An underlying message will be how maps and geospatial analyses can be used to facilitate and enhance current research programs.

Our course will include an introduction to basic cartographic principles and GIS in general, examples of how survey response and demographic data can be visualized using GIS maps, a step-by-step guide to making and customizing single- and multi-variate maps (starting from public use shapefiles and data in an excel spreadsheet), and a tutorial for making and understanding maps that show “hot spots” and “cool spots” in your data.  We will use examples in ArcGIS, a popular proprietary GIS package software, and GeoDa, an open source free GIS programs.
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Instructors:
Ned English
 is a Senior Research Methodologist at NORC at the University of Chicago and is responsible for GIS research and applications at NORC, in addition to project management and sample design on numerous studies across disciplines. Formally trained as a geographer, Ned has diverse theoretical and applied experience in the areas of GIS and Census data analysis with regard to survey methodology, sample design, and data visualization.    
Ilana Ventura is a Research Methodologist at NORC at the University of Chicago and a PhD student in Sociology at the University of Chicago, with experience in both qualitative and quantitative survey methods and an expertise in Geographic Information Systems (GIS).  Ilana’s research uses GIS in various capacities to understand access to social, economic and political resources, as well as how movement in and between urban spaces relates to inequality and social stratification.

Course Objectives:
• Create maps from social science data
• Customize maps on ArcGIS and GeoDa
• Understand the utility of geospatial analysis such as Cluster and Hot Spot Maps

Who Should Attend:
This course is best for those with little to no knowledge of GIS, or those who are looking for a refresher in the basics of spatial data presentation and analysis.  

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