This free course consists of a series of lectures on each of the major threats to internal validity. Each lecture focuses on but a single threat, e.g., history, and walks you through the gamut of design options that can help to account for that threat empirically. For example, the lecture on the history threat addresses non-equivalent comparison groups, non-equivalent dependent variables, cohort designs, removed and repeated treatment designs, and regression discontinuity design. Each of the lectures also suggest compound designs using two or more of these elements (save regression discontinuity design, which stands alone). Each lecture begins with a review of what the focal threat to internal validity means in lay terms and provides real-world examples of said threat using extant academic and think-tank literature. Each lecture is standalone, meaning each contains all of the requisite information for comprehensive understanding, which also means there is some redundancy across lectures.
***Oh, there's no lecture on design options for accounting for the testing threat because (a) seldom is testing an issue in policy analysis and program evaluation and (b) a lecture is not necessary (if you are worried about testing, change the test in a way that doesn't introduce instrumentation and/or allow more time to elapse between tests). Done. Bam.***
The course is free because its content is redundant with core undergraduate and graduate coursework for public policy, public management, and health policy programs in US universities and universities abroad -- the fact that the course is organized by threat to internal validity, rather than by quasi-experimental evaluation/research design, notwithstanding. The mission of the Applied Public Policy & Management Knowledge Base is only to charge a fee for courses that complement (versus substitute for) core curricula. This free course surveys knowledge and skills you'll need familiarity with for the following, for-fee course offerings from Applied Public Policy & Management Knowledge Base:
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In the 10+ years since earning my doctorate in public policy from Georgia Tech, I've shepherded more than a thousand undergrad and grad students through their public policy and management coursework and exit requirements. I'm quite good at, and really enjoy, helping students to make those critical yet implicit connections between evaluation/research design, dataset development, analytic methods, and model specification. I'm also quite good at, and also really enjoy, helping students to see the forest for the trees and, in doing so, to dominate their coursework, comprehensive exams, exit requirements, and budding careers. I am a prolific academic writer, with more than 30 peer-reviewed journal articles in top journals as well as 2 books and tens of book chapters, and numerous technical reports for government agencies, who has successfully and quickly and many times over turned bad paper (and thesis and article) writers into very good paper (and thesis and article) writers.
Currently, in addition to tutoring clients via this medium, I am funded by a research grant from the US National Science Foundation. In 2013 I received tenure from one of the largest research universities in the US and before that I was a consultant in Washington, DC. My past clients include individuals and groups working at the White House, the US National Science Foundation, the US National Institutes of Health, the National Research Council, and, internationally, the OECD.
For course correspondence requiring attachments, e.g., paper drafts, please use [email protected]
StartPrimer on research/evaluation design terminology (11:22)
StartPrimer on research/evaluation design notation (5:49)
StartHow to Account for SELECTION with Research/Evaluation Design (25:59)
StartHow to Account for PROGRAM-INDUCED MORTALITY with Research/Evaluation Design (22:19)
StartHow to Eliminate REGRESSION TO THE MEAN with Research/Evaluation Design (26:07)
StartHow to Account for INSTRUMENTATION with Research/Evaluation Design (31:15)
StartHow to Account for MATURATION with Research/Evaluation Design (37:31)
StartHow to Account for HISTORY with Research/Evaluation Design (38:57)