Propensity Scores are useful if there are no hidden biases

Propensity Scores for medicines essentially matches each patient to a control patient by 70+ characteristics
such as: age, sex, initial weight, BMI, latitude, medical history, current comorbidities, drugs being taken, etc.

__There can, however, be hidden biases such as: selection bias and placebo affect

Propensity Score Analysis cannot compensate for selection/election bias
A person elects to participate in an experiment because he believes it might help
He believes that his actions might influence his health ( what he eats, supplements, exercise, etc)
Propensity Score Analysis cannot compensate for the placebo effect

Even taking a known sugar pill makes a person feel better
Placebo (witch doctor, white cost) effects are stronger for the more important halth problems
Especially for those for which a person may feel they otherwise have little control
Very difficult to match a person with another who has the same degree of placebo reasction
A very large trial would tend to minimize differences in placebos, but not differences in selection bias
  ( they decided to take XX because felt it might help)
doctors often have a strong bias that no supplement can possibly help -supplements just turn into expensive urine
Different mindset in those who electr to try a supplement, or elect to particiate in a trial

expectation bias
Wonder if less bias in RCT if pay the participants - thenlose fewer dropouts due to low expectatins of benefit
.

Some people under-report the amount of vitamin D that they are taking - to not upset their doctors.

They may tend to say that they are taking 2000 IU when actually they are taking 10,000 IU
This possible under-reporting needs to be addressed

Since vitamin D seems to exert epigenetic effects [30], data on the adherence to rickets prevention could also be used to assess CVD risk in later life.

A prerequisite would, however, be a reliable assessment of relevant covariates and cardiovascular events.

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See also Web on PSA/PSM

• WikipediaJan 2022
  • "One disadvantage of Propensity Score Matching is that it only accounts for observed (and observable) covariates and not latent characteristics. Factors that affect assignment to treatment and outcome but that cannot be observed cannot be accounted for in the matching procedure."
  • Example of unobservables: belief that the person has some control over their health - e.g. taking a pill, eating a food, exercising, etc. will help
  • Some people elected to not participate in a trial because they had no expectation of being helped by it.
  • Judea Pearl argues about hidden biases that invalidate PSA
• Propensity Score Analysis: Recent Debate and Discussion - 2020 PDF
  • "a recent study suggested that propensity score matching may accomplish the opposite of its intended goal—increasing imbalance, inefficiency, model dependence, and bias"
  • important:: sources of selection bias
• PubMed "propensity score analysis" 2293 papers as of Jan 2022
• A Tutorial and Case Study in Propensity Score Analysis:
  An Application to Estimating the Effect of In-Hospital Smoking Cessation Counseling on Mortality 2011 PSA 2011 is attached at bottom of this page
• How To Use Propensity Score Analysis 2008 PDF is attached at bottom of this page
• Google Scholar search for "propensity score" "vitamin d" 4060 items as of Jan 2022
• Confounding and Control of Confounding in Nonexperimental Studies of Medications in Patients With CKD Jan 2012
• An Introduction to Propensity Score Methods for Reducing the Effects of Confounding in Observational Studies June 2011 PDF is attached
• Peter C Austin website huge number of PDF papers on PSA and other analysis techniques
• The Validity of "Identical Matching Placebos" -1974 PDF
  • Placebos must match in color, taste, size, etc. AND side effects. otherwise particiants soon learn if they are in the placebo group

See also Vitamin D Life

• Overview Vitamin D Intervention perhaps not have to be limited to RCT
• Not enough women willing to stop taking vitamin D to permit breast cancer clinical trial – June 2012
  Which is another reason to avoid the use of RCT
• Cataract surgery resulted in 30 percent fewer hip fractures – July 2012 used PSA
• Statin use increased probability of diabetes by 48 percent – perhaps via vitamin D Jan 2012 used PSA

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