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June 2017

Logistic regression: Analyzing binary outcomes

June 8 @ 12:00 pm - 4:00 pm

A 4-hour workshop taught by Stephen R. Porter, Ph.D. Register Overview Many outcomes in education are binary in nature: accept or decline an offer of admission, pass or fail a course, persist to another year or stop out. Logistic regression, rather than multiple regression, is the standard approach to analyzing discrete outcomes. This workshop will train participants in applying logistic regression to their research, focusing on 1) the parallels with multiple regression, and 2) how…

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Factor analysis using SPSS

June 12 @ 12:00 pm - 4:00 pm

Register A 4-hour workshop taught by Mary Ann Coughlin, D.P.E. Overview Factor analysis is a statistical technique commonly used to establish evidence of survey instrument validity. Exploratory factor analysis explores the relationships among variables to discover if those variables can be grouped into a smaller set of underlying factors. Often researchers and applied practitioners are faced with the difficult task of summarizing numerous variables from a survey and want to reduce the data into a smaller…

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Handling missing data: Multiple imputation for the applied researcher

June 14 @ 12:00 pm - 4:00 pm

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…

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Introduction to matching and propensity score analysis

June 15 @ 10:00 am - 4:00 pm

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 workshop provides a…

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Basics of multilevel modeling: Handing grouped data in research and evaluation

June 20 @ 10:00 am - 4:00 pm

A 6-hour workshop taught by Paul D. Umbach, Ph.D. Register Overview This workshop provides the basics multilevel modeling, focusing on practical applications rather than statistical theory. Researchers and evaluators from a range 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 not statistically independent, thus violating a basic assumption of standard…

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