USMLE Biostats 3: Research Bias

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/ lymed Welcome to LY Med, where I go over everything you need to know for the USMLE STEP 1, with new videos every day.
Follow along with First Aid, or with my notes which can be found here:
www.dropbox.com/sh/an1j9swvjx...
This video will be on research biases. A research bias decreases the objectivity of a study and skews results. Let's talk about some:
Selection bias: the bias introduced by the selection of individuals, groups or data for analysis in such a way that proper randomization is not achieved, thereby ensuring that the sample obtained is not representative of the population intended to be analyzed. Subcategories of this includes the Berksen Effect (selecting unhealthy participants from a hospital), healthy worker effect (selecting a group that is healthier than the population), and non-response bias (where responders differ from nonresponders).
Procedural bias: this is a blanket statement in where different groups are not treated the same.
Measurement bias: results from poorly measuring the outcome you are measuring. A subtype of this is the Hawthorne Effect: the alteration of behavior by the subjects of a study due to their awareness of being observed.
Recall bias: caused by differences in the accuracy or completeness of the recollections or memories by study participants regarding events or experiences from the past.
Attrition bias: attrition means the action or process of gradually reducing the strength. Thus Attrition bias refers to systematic differences between groups in withdrawals from a study. Withdrawals from the study lead to incomplete outcome data.
Observer bias: occurs when the researcher studies a certain group, with prior knowledge and subjective feelings about the group being studied.
Observer expectancy bias: is a form of reactivity in which a researcher's cognitive bias causes them to subconsciously influence the participants of an experiment.
Susceptibility bias: when sicker patients receive differing treatment which may skew the data
Lead time bias: Lead time is the length of time between the detection of a disease and its usual diagnosis. Early diagnosis by screening may not prolong the life of someone. Lead time bias can affect interpretation of the five-year survival rate.
Late look bias: Late-look bias occurs when patients with severe disease are less likely to be studied because they are more likely to succumb to their disease before being studied.
Confounding bias: confounding means to mix variables up so they are difficult to discern. So confounding bias is the interference by a third variable so as to distort the association being studied between two other variables.
Our last topic will be on non-biases that look like biases. This includes generalization, which means extrapolating data to a larger population. Effect modification is another one: Effect modification occurs when the magnitude of the effect of the primary exposure on an outcome (i.e., the association) differs depending on the level of a third variable.

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Much love, -Mike

[@livefromNorCal]

This guy is an excellent teacher. I passed a certification by watching his video.

[@okaformay5241]

Currently watching all the stats videos…Very simplified and easy to understand…thanks you for all the videos.

[@docjw8914]

Thank you so much man. This was the best simplification of bias I have ever seen.

[@wire4me]

This is the best simplified clarification between confounding bias and effect modification. Thanks for clearing that up

[@xaviermathias8929]

Thanks a lot bro! I’m just doing my dissertation now and am doing my results section and this has made everything nice and simple 🙌🏽

[@reregad590]

From Egypt : thank you very much I am a student and you helped me a lot by this video

[@maentarawneh7727]

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[@swasthikadahal6251]

Awesome videos thank you so much . It really helped me .

[@marzgunz1004]

There is a problem, because you are separating susceptibility bias from the rest of the selection bias. There is a UW question, where susceptibility bias is the problem, and the answer is "Selection bias" instead of "Measurment bias". And UW states: . "When the treatment regimen selected for a patient depends on the severity of the patient's condition, a form of selection bias known as susceptibility bias (confounding by indication) can result".
Also I believe that attrition is another type of selection bias, because after the patients abandon, the groups don't match the general population. There is another UW question I rembember from step1 where this happened.
I think you tried to organized it chronologically so it makes more sense, and its good, is just that there are some exceptions. Selection bias is horrible, there are a lot of subtypes and I haven't found the resource that groups this in the right way and includes them all

[@ronroger6962]

top top work!, great job, thank you!

[@MrKarzan80]

Thank you.

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Thank you so much , very helpful

[@kulshinidealwis9521]

Thank you!!!

[@Aisha2178]

Bro thank you!

[@joserosa1107]

GOLD!

[@swasthikadahal6251]

Is attrition bias a selection bias?

[@aasmine]

awesome !! :)

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