Draft

235  Partial Verification Blurg (incomplete)

235.1 Summary

  • Propensity Score Intuition
  • Partial Verification
  • ‘Data/Methods’ Limitations:
  • Partial Verification Bias
  • Omniscient View
  • Only some tested
  • Complete Case
  • Correctly modeled propensity score
  • Inverse Propensity Weights
  • Weighted (pseudo)population restores prevalence and sex balance of the whole population

235.2 Slide outline

235.2.1 Slide 1

  • Propensity Score Intuition
  • Needs to be finished. ### Slide 2
  • Partial Verification
  • Omniscient View
  • 10 of 24 have hypercapnia
  • 5 of 12 men
  • 5 of 12 women
  • P(Test | Man) 50%
  • P(Test | Woman) 25%
  • Clinicians can’t perfect predict who needs the test
  • ORtest|hypercap: 2.8 (M or W) ### Slide 3
  • Partial Verification ### Slide 4
  • ‘Data/Methods’ Limitations:
  • ‘Partial Verification’: hypercapnia status is only ascertained in patients who get an ABG.
  • Analysis: Among patients who have ABGs checked
  • Target: Among all patients who may have hypercapnia
  • The probability of getting an ABG is variable and idiosyncratic
  • Inverse probability of blood-gas weighting?
  • Missing data is tricky
  • P(ABG) 0.5
  • P(ABG) 0.25
  • Observed w/ Hypercapnia
  • Weighted by Inverse of Prob
  • True Status (unobserved)
  • The Missing Indicator Method.
  • CMAJ 2012 ### Slide 5
  • Partial Verification Bias ### Slide 6
  • Omniscient View
  • 50% prevalence; both sexes
  • Our goal is to predict who has the condition in the entire sample ### Slide 7
  • Only some tested ### Slide 8
  • Complete Case
  • 66% prevalence; mostly women
  • If you train the model on this, it’ll learn that sex predicts the condition.
  • True! among people who get the test ### Slide 9
  • Only some tested
  • But we are particularly interested in predicting for people who didn’t get the test ### Slide 10
  • Correctly modeled propensity score
  • 33%
  • 100%
  • 33%% ### Slide 11
  • Inverse Propensity Weights
  • 1/.33
  • 3
  • 1/1
  • 1 ### Slide 12
  • Weighted (pseudo)population restores prevalence and sex balance of the whole population
  • Intuition:
  • If someone who was unlikely to get the test but did and they have the condition → there are likely many similar patients with the condition that didn’t get the test.

235.3 Learning objectives

  • Propensity Score Intuition
  • Partial Verification
  • ‘Data/Methods’ Limitations:
  • Partial Verification Bias
  • Omniscient View

235.4 Bottom line / summary

  • Propensity Score Intuition
  • Partial Verification
  • ‘Data/Methods’ Limitations:
  • Partial Verification Bias
  • Omniscient View

235.5 Approach

  1. TODO: Outline the initial assessment or decision point.
  2. TODO: Outline the next diagnostic or management step.
  3. TODO: Outline follow-up or escalation criteria.

235.6 Red flags / when to escalate

  • TODO: List red flags that require urgent escalation.

235.7 Common pitfalls

  • TODO: Capture common errors or missed steps.

235.8 References

TODO: Add landmark references or guideline citations.

235.9 Slides and assets

235.10 Source materials