3.3 KiB
2025
2025-W03
2025-01-18 Saturday
[2025-01-18 Sat 11:54] [[/home/will/research/phd_deliverables/JobMarketPaper/Paper/sections/11_intro_and_lit.tex::45]]
Need to decide whether or not to include this set of sentences.
[2025-01-18 Sat 11:58] [[/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.