Data, Methods, Debate

Sara Goldrick-Rab of UW-Madison started an interesting late night tweaching (thanks to @akilbello for term) session on methodological rigor. It continued with an interesting tete-a-tete with Stuart Buck. I'm refraining from drawing parallels between tools of oppression and quantitative analysis

  1. @AmyAlex63 Seriously, if you guys are covering this study, I do hope you've asked someone to review it. Many issues.
  2. Looks like @BrookingsEd plans to release that study this morning. I like Matt Chingos a lot, but the statements are overblown.
  3. Here's a paper explaining issues w this type of subgroup analysis. 1.usa.gov/R5GMRN Also note sizable crossovers, baseline non-equiv
  4. Larger tx effects on college among blacks, where T group had more BA-educated parents than C's (p=.09). Not random. bit.ly/PBgqul
  5. See Table 1, by subgroup, then notice the teeny-tiny attention 2 those serious issues on next page. bit.ly/PBgqul
  6. Note major inconsistency btw paragraph 2 on p. 12 & first full paragraph on p. 17. Effects AREN'T proven different by racial grp, and net 0
  7. Seems like @EdWeek only interviewed researchers w an agenda aimed at supporting vouchers... bit.ly/PBj4Ao
  8. @saragoldrickrab I am slower than you! It takes me a minute. But I was wondering about home effects. That's growth. :D
  9. .@tressiemcphd would need to be driven by differences between T and C at baseline. Always keep in mind when reading RCTS
  10. .@chingos @rweingarten Matt have u read Howard Bloom's piece on effect heterogeneity? These subgroup diffs are shaky at best.
  11. .@chingos @paul_e_peterson You are really stretching beyond ur results w statements like that. One subgroup, unbalanced, no avg effects...
  12. .@chingos @paul_e_peterson discussing small point estimates like these in percentages usually leads to overblown conclusions too
  13. .@chingos @stuartbuck1 Disparity btw table 1 results & text on following pg is stunning.Gliding past key treatment disparities at baseline?
  14. .@shankerblog @nealmccluskey @stuartbuck1 @chingos I'd like 2 see this study try to be submitted as an NBER paper. Attempt it?
  15. @DianeRavitch No serious statistician would publish that report. It's grasping at straws to find something nice to say about vouchers.
  16. @saragoldrickrab grad students don't get this kind of clear breakdown of methods in current research often. this is seriously awesome.
  17. Here's the deal: if u want 2 suggest effect heterogeneity, you'd best (1) specific a theory as 2 why it would occur B4 the analysis.
  18. (2) spell out groups w pre-Tx measures & establish equivalence pre-T in every group. U only check some observables so get worried if not =
  19. (3) don't just suggest group diffs in size of impacts- test 4 them and display results (these authors don't)
  20. (4) you better have a good explanation why they occurred and even better why average effects are NULL
  21. @saragoldrickrab The main conclusion of the study was that vouchers made no difference, but they teased out a way to spin "success" for WSJ
  22. .@saragoldrickrab But father absent is in opposite direction (p=.08) and comfortably pass joint sig test (see notes to Table 1).
  23. @saragoldrickrab Perhaps we should discuss this a bit more in paper, but I'm not that worried about it given joint sig test.
  24. .@saragoldrickrab @rweingarten Will take a look at Bloom piece tomm, but Af-Am effects robust across outcomes, consistent w/ test scores.

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tressie mc

Sociologist. PhD student. I stan for organizational lit. Professional hell-raiser. I tried to shut up once & it ended badly for all. #EmoryUniversity

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