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<span style="font-size:24px"><strong>The 2020 ICPSR Summer Program starts May 13</strong></span><br>
<br>
The feeling we get when the first group of courses start is hard to describe. Equal parts excited, nervous, hopeful. A lot like the first day of kindergarten, when we stop and think about it. So we have our favorite outfits picked out and a brand new pencil box ready for the start of our 2020 schedule, led by these four courses!<br>
<br>
<a href="https://umich.us3.list-manage.com/track/click?u=4de0acf23f8cd9a943b256ebd&id=29351ceb59&e=17afda8ecf" style="color:#007c89;font-weight:normal;text-decoration:underline" target="_blank">Quantitative Methods to Advance Diversity, Equity, and Inclusion</a> (May 13-15)<br>
<em>Instructor: Matthew Diemer, University of Michigan</em><br>
<br>
This three-day workshop centers latent variable modeling as a strategy to address and advance diversity, equity, and inclusion (DEI). This workshop actively interweaves social identities (e.g., race/ethnicity, gender, and social class) and equity with quantitative concepts, instead of distancing methods from the lived experiences of students and larger societal issues. A second emphasis in this workshop is learning to "speak the language" of quantitative methods, because methodological expertise is one way to communicate and advance diversity, equity, and inclusion in spaces where facility with highly technical quantitative concepts and techniques is privileged.<br>
<br>
<a href="https://umich.us3.list-manage.com/track/click?u=4de0acf23f8cd9a943b256ebd&id=173fea304a&e=17afda8ecf" style="color:#007c89;font-weight:normal;text-decoration:underline" target="_blank">Usage and Application of Meta-Analysis Techniques</a> (May 13-15)<br>
<em>Instructor: Mariola Christine Moeyaert, State University of New York at Albany</em><br>
<br>
This workshop provides hands-on exposure to the process involved in conducting a meta-analysis from the planning stage, through the selection of appropriate statistical techniques, through the issues involved in analyzing data, to the interpretation of results. During the workshop, participants will learn how to calculate various kinds of effect sizes and to use them to conduct and make appropriate inferences from meta-analyses. Examples and case studies from the social sciences will be integrated into the discussions and lectures.
<p style="margin:10px 0;padding:0;color:#202020;font-family:Helvetica;font-size:16px;line-height:150%;text-align:left"><br>
<a href="https://umich.us3.list-manage.com/track/click?u=4de0acf23f8cd9a943b256ebd&id=7be1766e92&e=17afda8ecf" style="color:#007c89;font-weight:normal;text-decoration:underline" target="_blank">I</a><a href="https://umich.us3.list-manage.com/track/click?u=4de0acf23f8cd9a943b256ebd&id=2baf19043b&e=17afda8ecf" style="color:#007c89;font-weight:normal;text-decoration:underline" target="_blank">ntroduction to R</a> (May 13-15)<br>
<em>Instructor: Ryan Kennedy, University of Houston</em><br>
<br>
Most students learn to use R piecemeal, by performing tasks similar to what they have already learned in another program like Stata or SPSS. The result is often frustration on the part of both students and professors. This course takes a different approach. Utilizing the "tidyverse" tools, this course shows how writing code in R can be both easy and intuitive. We will cover graphics, data management and modeling, automated updating of tables, replication using markdown, functional programming, and, time permitting, application design. This course is not about repeating in R what students have already learned elsewhere, but to instead become R programmers capable of approaching any new challenge.<br>
<br>
<a href="https://umich.us3.list-manage.com/track/click?u=4de0acf23f8cd9a943b256ebd&id=cf6cd48e14&e=17afda8ecf" style="color:#007c89;font-weight:normal;text-decoration:underline" target="_blank">Multilevel Analysis</a> (May 13-15)<br>
<em>Instructor: Ling Zhu, University of Houston</em><br>
<br>
Multilevel analysis is a widely used approach to deal with nested data, which allow researchers to consider both social contexts and micro-level characteristics in their statistical models. Multilevel analysis also provides advantages and flexibility for modeling longitudinal data. This course will focus on teaching participants the full roadmap of multilevel analysis: setting up and managing multilevel data, identifying data structures, choosing the appropriate model specification, evaluating fixed and random effects, interpreting and visualizing statistical results. We will start with applications in the context of hierarchical linear regression models, and then discuss several extensions suitable for time-serious-cross-section data and categorical dependent variables. </p>
<br>
<strong>REMINDER: </strong>All 2020 Summer Program courses are being offered virtually!
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<a class="m_-8037999114611706352mcnButton" title="View all 2020 courses" href="https://umich.us3.list-manage.com/track/click?u=4de0acf23f8cd9a943b256ebd&id=90d5fc2e4a&e=17afda8ecf" style="font-weight:bold;letter-spacing:normal;line-height:100%;text-align:center;text-decoration:none;color:#ffffff;display:block" target="_blank">View all 2020 courses</a>
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<div style="text-align:center"><strong>Registration now open!</strong></div>
<div>To register for these or any of our courses visit our <a href="https://umich.us3.list-manage.com/track/click?u=4de0acf23f8cd9a943b256ebd&id=401d27a238&e=17afda8ecf" style="color:#007c89;font-weight:normal;text-decoration:underline" target="_blank">Registration page</a> to get started.</div>
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<em>Copyright © 2020 ICPSR Summer Program in Quantitative Methods of Social Research, All rights reserved.</em>
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You are receiving this email because you are a participant, TA, instructor, or friend of the Summer Program.
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<strong>Our mailing address is:</strong>
<br>
<div><span>ICPSR Summer Program in Quantitative Methods of Social Research</span><div><div>P.O. Box 1248</div><span>Ann Arbor</span>, <span>MI</span> <span>48106-1248</span></div></div><br>
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