May 2019
Handling missing data: Multiple imputation for the applied researcher
A 4-hour workshop taught by Ryan S. Wells, Ph.D. You may also be interested in our increasing web survey response rates workshop. Register Overview Item-missing data is a serious concern for any quantitative researcher. Survey participants regularly skip questions, and administrative data is often incomplete. But what do to about this issue is not always straightforward. Researchers often analyze only complete cases (listwise deletion) or they impute missing information using means or regression analysis. These approaches can lead to biased estimates and artificially small standard…
Find out more »August 2019
Writing and evaluating good survey questions
A 4-hour workshop taught by Paul D. Umbach, Ph.D. Register Overview Writing good survey questions can be very difficult. This workshop will give participants a solid practical foundation in how to write good survey questions. The purpose of this workshop is to arm you with the knowledge to develop valid and reliable questionnaires by looking at approaches for developing survey questions and methods for evaluating them. As survey researchers, it is difficult to be certain that respondents interpret your questions exactly as you…
Find out more »Introduction to matching and propensity score analysis
NOTE DATE CHANGED FROM AUGUST 22 to AUGUST 29 A 6-hour workshop taught by Stephen R. Porter, Ph.D. You may also be interested in our introduction to binary logistic regression class. Register Overview Propensity score analysis (also known as “matching”) is a popular way to estimate the effects of programs and policies on outcomes. Yet researchers face a dizzying array of choices, in terms of particular matching techniques to use, as well as many different options for implementing a specific technique. This…
Find out more »November 2019
Writing and evaluating good survey questions
A 4-hour workshop taught by Paul D. Umbach, Ph.D. Register Overview Writing good survey questions can be very difficult. This workshop will give participants a solid practical foundation in how to write good survey questions. The purpose of this workshop is to arm you with the knowledge to develop valid and reliable questionnaires by looking at approaches for developing survey questions and methods for evaluating them. As survey researchers, it is difficult to be certain that respondents interpret your questions exactly as you…
Find out more »December 2019
Introduction to matching and propensity score analysis
THIS WORKSHOP HAS BEEN CANCELLED. Please sign up for the Introduction to Matching and Propensity Score workshop on January 30 or April 17. A 6-hour workshop taught by Steve Porter, Ph.D. You may also be interested in our introduction to binary logistic regression class. Register Overview Propensity score analysis (also known as “matching”) is a popular way to estimate the effects of programs and policies on outcomes. Yet researchers face a dizzying array of choices, in terms of particular matching techniques to…
Find out more »January 2020
Introduction to matching and propensity score analysis
A 6-hour workshop taught by Steve Porter, Ph.D. You may also be interested in our introduction to binary logistic regression class. Register Overview Propensity score analysis (also known as “matching”) is a popular way to estimate the effects of programs and policies on outcomes. Yet researchers face a dizzying array of choices, in terms of particular matching techniques to use, as well as many different options for implementing a specific technique. This workshop provides a concise introduction to matching for the applied…
Find out more »February 2020
Increasing web survey response rates: What works?
A 4-hour workshop taught by Paul D. Umbach, Ph.D. Register Overview Are you getting low response rates when you conduct web surveys? This workshop provides valuable information about how to increase web survey response rates. The purpose of this class is to arm you with the knowledge and range of techniques researchers suggest increase web survey response rates. We examine the heuristics people use when deciding to participate in a survey and answer survey questions and explore ways to increase the likelihood…
Find out more »Exploring the power of predictive analytics: A step-by-step introduction to building a student-at-risk prediction model
A 5-hour workshop taught by Serge Herzog, Ph.D. Register Overview The purpose of this workshop is to teach institutional research, assessment, and evaluation professionals how to effectively build and implement a predictive model to identify students at risk of dropping out using standard regression methods with SPSS. Instruction will be delivered in a hands-on format, offering an interactive step-by-step model-building process that allows participants to develop their own prediction model, using preloaded data that mimics information available with the typical college enrollment…
Find out more »Student success prediction at your fingertips: Developing online dashboards with Microsoft Power BI©
A 5-hour workshop taught by Serge Herzog, Ph.D. Participants of this workshop will benefit from also taking our Predictive Analytics workshop. Register Overview The purpose of this workshop is to teach education professionals how to build online dashboards to predict student outcomes literally with ‘the push of a button’. Participants learn how to use common data files (Excel, CSV etc) with Power BI©, and how to create dashboards with interactive data visualization and drill-down tools that display predicted student outcomes (e.g. admission…
Find out more »March 2020
Introduction to the R Statistical Computing Environment
A 6-hour workshop taught by Mariola Moeyaert, Ph.D. Register Overview The R statistical programming language and computing environment is a free, open-source package for statistical analysis. R has become the de-facto standard in statistics (see Muenchen, 2018; Suda, 2017) and is widely used in the social, health, physical, and computational sciences. Researchers transition to R because it is powerful, flexible, makes routine data analysis easy and has a large and rapidly growing community of users. This workshop is designed to introduce…
Find out more »Basics of multilevel modeling: handling grouped data in research and evaluation
A 6-hour workshop taught by Paul D. Umbach, Ph.D. Register Overview This workshop provides the basics of multilevel modeling, focusing on practical applications rather than statistical theory. Researchers and evaluators from a range of disciplines often collect data that have a hierarchical structure. Students are nested within schools (and/or classrooms), employees are nested within firms, and multiple test scores are nested within students. One consequence of this nested structure is that observations are not statistically independent, thus violating a basic assumption of standard analytical…
Find out more »April 2020
Exploring the power of predictive analytics: A step-by-step introduction to building a student-at-risk prediction model
A 5-hour workshop taught by Serge Herzog, Ph.D. Register Overview The purpose of this workshop is to teach institutional research, assessment, and evaluation professionals how to effectively build and implement a predictive model to identify students at risk of dropping out using standard regression methods with SPSS. Instruction will be delivered in a hands-on format, offering an interactive step-by-step model-building process that allows participants to develop their own prediction model, using preloaded data that mimics information available with the typical college enrollment…
Find out more »Introduction to matching and propensity score analysis
A 6-hour workshop taught by Steve Porter, Ph.D. You may also be interested in our introduction to binary logistic regression class. Register Overview Propensity score analysis (also known as “matching”) is a popular way to estimate the effects of programs and policies on outcomes. Yet researchers face a dizzying array of choices, in terms of particular matching techniques to use, as well as many different options for implementing a specific technique. This workshop provides a concise introduction to matching for the applied…
Find out more »Student success prediction at your fingertips: Developing online dashboards with Microsoft Power BI©
A 5-hour workshop taught by Serge Herzog, Ph.D. Participants of this workshop will benefit from also taking our Predictive Analytics workshop. Register Overview The purpose of this workshop is to teach education professionals how to build online dashboards to predict student outcomes literally with ‘the push of a button’. Participants learn how to use common data files (Excel, CSV etc) with Power BI©, and how to create dashboards with interactive data visualization and drill-down tools that display predicted student outcomes (e.g. admission…
Find out more »May 2020
Handling missing data: Multiple imputation for the applied researcher
A 4-hour workshop taught by Ryan S. Wells, Ph.D. You may also be interested in our increasing web survey response rates workshop. Register Overview Item-missing data is a serious concern for any quantitative researcher. Survey participants regularly skip questions, and administrative data is often incomplete. But what do to about this issue is not always straightforward. Researchers often analyze only complete cases (listwise deletion) or they impute missing information using means or regression analysis. These approaches can lead to biased estimates and artificially small standard…
Find out more »