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3 Commits
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1672210931 | 12 months ago |
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4bf321b475 | 1 year ago |
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88be4b7a38 | 1 year ago |
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Key points
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This is an attempt at measuring the effect of extending the enrollment period.
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The main issue is that the interaction between enrollment levels, enrollment status, and timing is confounded due to endogeneity.
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This can be addressed
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The other concerns are:
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- endogeneity between market and population.
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I this isn't a caual issue because it is contained between the two, can be treated as a single RV and controlled for together.
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- ommitted variable bias. Did I forget or miss anything?
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- The DAG is based on the details outlined based on FDA rules. I NEED TO LOOK THOSE UP AGAIN. The Assumptions that allow this to work are:
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1. timeliness/accuracy in reporting open and close
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2. updating certain details (open/close recruitment) is helpful because this is part of your marketing. (Concerns about measurement error)
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3.
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- Where did the DAG come from?
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In spite of the endogeneity issue, I chose to continue modelling as if it were causal, because:
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1. If we assume an intervetion that is handles the joint timing/enrollment status together, then it is causally identified (but hard to interpret)
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- Walking away from identification is an issue in that you lose the use of this analysis
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- Interpretation is as follows: changing enrollment status but breaking out of the standard timing of these things. Need a better way to say that.
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2.
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This is the only attempt I've found that tries to address this in a causal way, everything else is just descriptive.
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It also differs in being the first econ literature on measuring the impact of an operational concern.
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Plan
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get list of things that Tom says I'm Missing
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- Needs more citations
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- Standard econometric concerns: Endogenetiy, Simultineatiy, etc.
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- Needs to justify why I am doing what I am doing. What do I add?
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Marketwide attempt to measure the impact of enrollment, an operational concern.
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-
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Integrate additional literature I've worked with.
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- How big of a concern is operational results (about 22% of failures)
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- Topics of how to address issues and what issues arise are common (give a couple of examples)
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- Efforts to reduce failures include better pharmokinetics, attempts at improving enrollment, better enrollment prediction (huge lit).
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Then look at my outline:
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- How can I adjust it to address those missing bits?
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- How can I simplify the structure?
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Maybe a discussion of concerns about simultineity/endogeneity/other confounds/etc is where I
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bring up the confounding parameters and then build a list of how things interact.
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I then use this to flesh out the DAG, and introduce the backdoor criterion.
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I think I'll put this together as a bullet point draft, using the * and -
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notation for paragraphs and sentences respectively. Try to get the main points
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of each sentence/paragraph out.
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