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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.


See also Web on PSA/PSM

See also VitaminDWiki

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Created by admin. Last Modification: Tuesday January 11, 2022 22:40:18 GMT-0000 by admin. (Version 42)

Attached files

ID Name Comment Uploaded Size Downloads
16869 PSA increase inbalance.pdf PDF 2020 admin 11 Jan, 2022 01:55 1.36 Mb 8
16868 blumenthal1974.pdf admin 11 Jan, 2022 00:24 288.56 Kb 8
1377 Ensemble-Based Methods Feb 2012.pdf admin 08 Jun, 2012 12:33 153.35 Kb 391
1376 Propensity score 2011 to reduce confounding.pdf admin 05 Jun, 2012 03:07 211.29 Kb 416
1374 How to Use PSA 2008.pdf PDF admin 03 Jun, 2012 20:09 161.02 Kb 970
1373 PSA 2011.pdf PDF admin 03 Jun, 2012 20:08 1.21 Mb 403
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