Events

ISSR Summer Methodology Workshops | Analyzing Categorical Data | Caroline Andrews & Brian Dillon

Thursday, June 7, 2018 - 9:00am to 4:00pm
Friday, June 8, 2018 - 9:00am to 4:00pm
University of Massachusetts, Amherst | E20 Machmer Hall
Recent modeling evidence shows that analyzing categorical data using non-categorical models produces a range of important analytic errors. This course is designed to provide practical experience and theoretical background for statistical methods for categorical data.

ISSR Summer Methodology Workshops | Analyzing Categorical Data | Caroline Andrews & Brian Dillon

Thursday, June 7, 2018 - 9:00am to 4:00pm
Friday, June 8, 2018 - 9:00am to 4:00pm
University of Massachusetts, Amherst | E20 Machmer Hall
Recent modeling evidence shows that analyzing categorical data using non-categorical models produces a range of important analytic errors. This course is designed to provide practical experience and theoretical background for statistical methods for categorical data.

ISSR Summer Methodology Workshops | Text-as-Data in R | Douglas Rice

Monday, June 11, 2018 - 9:00am to 4:00pm
Tuesday, June 12, 2018 - 9:00am to 4:00pm
University of Massachusetts, Amherst | E20 Machmer Hall
With the recent explosion in availability of digitized text, social scientists increasingly are turning to computational tools for the analysis of text as data. In this two-day course, participants will first learn how to convert text to formats suitable for analysis. From there, the course will introduce and proceed through tutorials on a variety of approaches to the treatment of text-as-data.

ISSR Summer Methodology Workshops | Text-as-Data in R | Douglas Rice

Monday, June 11, 2018 - 9:00am to 4:00pm
Tuesday, June 12, 2018 - 9:00am to 4:00pm
University of Massachusetts, Amherst | E20 Machmer Hall
With the recent explosion in availability of digitized text, social scientists increasingly are turning to computational tools for the analysis of text as data. In this two-day course, participants will first learn how to convert text to formats suitable for analysis. From there, the course will introduce and proceed through tutorials on a variety of approaches to the treatment of text-as-data.

ISSR Summer Methodology Workshops | Introduction to Qualitative Interviewing | Chrystal G. Mwangi & Ezekiel Kimball

Thursday, June 14, 2018 - 9:00am to 2:00pm
Friday, June 15, 2018 - 9:00am to 2:00pm
University of Massachusetts, Amherst | E20 Machmer Hall
This two-day workshop provides a comprehensive introduction to the art and science of qualitative interviewing, addressing questions of design and sampling as well as interview technique. Participants will have the opportunity to develop or refine their own interview protocols as well as to gain hands-on experience interviewing.

ISSR Summer Methodology Workshops | Introduction to Qualitative Interviewing | Chrystal G. Mwangi & Ezekiel Kimball

Thursday, June 14, 2018 - 9:00am to 2:00pm
Friday, June 15, 2018 - 9:00am to 2:00pm
University of Massachusetts, Amherst | E20 Machmer Hall
This two-day workshop provides a comprehensive introduction to the art and science of qualitative interviewing, addressing questions of design and sampling as well as interview technique. Participants will have the opportunity to develop or refine their own interview protocols as well as to gain hands-on experience interviewing.

ISSR Summer Methodology Workshops | Causal Inference with Graphical Models | David Jensen

Monday, June 18, 2018 - 9:00am to 4:00pm
Tuesday, June 19, 2018 - 9:00am to 4:00pm
University of Massachusetts, Amherst | E20 Machmer Hall
A large number of analytical methods have been developed to infer causal dependence from observational data, including propensity score matching, instrumental variable designs, interrupted time-series designs, and many others. Unfortunately, the assumptions and limitations of these methods can be difficult to explain and reason about. This tutorial introduces participants to causal graphical models, a powerful formalism developed within computer science and statistics. This tutorial assumes only a basic understanding of probability and statistics and no knowledge of programming.

ISSR Summer Methodology Workshops | Causal Inference with Graphical Models | David Jensen

Monday, June 18, 2018 - 9:00am to 4:00pm
Tuesday, June 19, 2018 - 9:00am to 4:00pm
University of Massachusetts, Amherst | E20 Machmer Hall
A large number of analytical methods have been developed to infer causal dependence from observational data, including propensity score matching, instrumental variable designs, interrupted time-series designs, and many others. Unfortunately, the assumptions and limitations of these methods can be difficult to explain and reason about. This tutorial introduces participants to causal graphical models, a powerful formalism developed within computer science and statistics. This tutorial assumes only a basic understanding of probability and statistics and no knowledge of programming.

ISSR Summer Methodology Workshops | Organizing and Analyzing Qualitative Data with NVivo 11 for Windows | Eric Griffith and Ashley Carpenter

Monday, July 9, 2018 - 9:00am to 1:00pm
Tuesday, July 10, 2018 - 9:00am to 1:00pm
Wednesday, July 11, 2018 - 9:00am to 1:00pm
University of Massachusetts, Amherst | E20 Machmer Hall
This three-morning workshop will get you up and running with coding and analyzing your qualitative data in NVivo 11. Each day, instructors will also offer optional open lab times when they are available to help you apply the techniques you learned in the morning to your own data.

ISSR Summer Methodology Workshops | Organizing and Analyzing Qualitative Data with NVivo 11 for Windows | Eric Griffith and Ashley Carpenter

Monday, July 9, 2018 - 9:00am to 1:00pm
Tuesday, July 10, 2018 - 9:00am to 1:00pm
Wednesday, July 11, 2018 - 9:00am to 1:00pm
University of Massachusetts, Amherst | E20 Machmer Hall
This three-morning workshop will get you up and running with coding and analyzing your qualitative data in NVivo 11. Each day, instructors will also offer optional open lab times when they are available to help you apply the techniques you learned in the morning to your own data.

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