Notes and plans for writing

master
Will King 12 months ago
parent 88be4b7a38
commit 4bf321b475

@ -5,3 +5,64 @@
Need to decide whether or not to include this set of sentences.
**** [2025-01-18 Sat 11:58] [[[[file:/home/will/research/phd_deliverables/JobMarketPaper/Paper/sections/11_intro_and_lit.tex::45]]]]
decide whether to include these details here
** 2025-W17
*** 2025-04-21 Monday
**** [2025-04-21 Mon 11:17] Plan based on last weeks thinking things through
get list of things that Tom says I'm Missing
- Needs more citations
- Standard econometric concerns: Endogenetiy, Simultineatiy, etc.
- Needs to justify why I am doing what I am doing. What do I add?
Marketwide attempt to measure the impact of enrollment, an operational concern.
-
Integrate additional literature I've worked with.
- How big of a concern is operational results (about 22% of failures)
- Topics of how to address issues and what issues arise are common (give a couple of examples)
- Efforts to reduce failures include better pharmokinetics, attempts at improving enrollment, better enrollment prediction (huge lit).
Then look at my outline:
- How can I adjust it to address those missing bits?
- How can I simplify the structure?
Maybe a discussion of concerns about simultineity/endogeneity/other confounds/etc is where I
bring up the confounding parameters and then build a list of how things interact.
I then use this to flesh out the DAG, and introduce the backdoor criterion.
I think I'll put this together as a bullet point draft, using the * and -
notation for paragraphs and sentences respectively. Try to get the main points
of each sentence/paragraph out.
***** List of issues identified by Tom:
Reference style (Author year)
Reference better and more often.
Introduction needs to motivate the problem & what I am trying to do. (could use the sources I have on reasons for failures)
Various issues with tense etc. Use Claude.ai as editor for those.
Reorder sections or outline better
Causal inference vs DAG approach
- standard concens in causal inference
- DAG isn't causal inference in Toms view. He is right, DAG isn't but backdoor criterion is.
- Will need to discuss standard concerns and how they may be related and then incorporate that into the DAG
- Then will need to discuss backdoor criterion, the backdoor paths that exist, and choosing adjustment sets
- Replace bullet points with paragraphs (page 12) maybe use claude to convert that?
- Page 18 comment: Refer to Robins What IF book to get citation
Thoughts:
Chapter 10: Lists 3 sources of bias in preceeding chapters (7,8,9)
- Selection
- Measurement
- Confounders
As I understand it, setting up the graph allows you to note where you
might have issues with all 3. Do-calc gives you the adjustment set to
handle confounding and selection, while measurement is handled either
through modelling uncertanty or improving you measurement approach.
***** Reading to complete before rewriting:
I think I should start by rereading (and taking notes on) What If and
the Causal Mixtape.

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