Google Analytics is a powerful tool that tracks and analyzes website traffic for informed marketing decisions.
Service URL: policies.google.com (opens in a new window)
__utmz
Contains information about the traffic source or campaign that directed user to the website. The cookie is set when the GA.js javascript is loaded and updated when data is sent to the Google Anaytics server
6 months after last activity
__utmv
Contains custom information set by the web developer via the _setCustomVar method in Google Analytics. This cookie is updated every time new data is sent to the Google Analytics server.
2 years after last activity
__utmx
Used to determine whether a user is included in an A / B or Multivariate test.
18 months
_ga
ID used to identify users
2 years
_gali
Used by Google Analytics to determine which links on a page are being clicked
30 seconds
_ga_
ID used to identify users
2 years
_gid
ID used to identify users for 24 hours after last activity
24 hours
_gat
Used to monitor number of Google Analytics server requests when using Google Tag Manager
1 minute
_gac_
Contains information related to marketing campaigns of the user. These are shared with Google AdWords / Google Ads when the Google Ads and Google Analytics accounts are linked together.
90 days
__utma
ID used to identify users and sessions
2 years after last activity
__utmt
Used to monitor number of Google Analytics server requests
10 minutes
__utmb
Used to distinguish new sessions and visits. This cookie is set when the GA.js javascript library is loaded and there is no existing __utmb cookie. The cookie is updated every time data is sent to the Google Analytics server.
30 minutes after last activity
__utmc
Used only with old Urchin versions of Google Analytics and not with GA.js. Was used to distinguish between new sessions and visits at the end of a session.
End of session (browser)
One of my goals is promoting evidence-based medicine and science-based medicine that is in the best interest of the community including patients.
No person is going to argue against medicine being evidence-based. Difficulties may arise as to what is acceptable evidence?
One part of the issue is, and always has been, whether evidence-based medicine is to be given a narrow definition that: favours (1) particular types of scientific research, (2) favours particular cliques of researchers, (3) favours economic models that are convenient for particular types of companies, (4) favours a particular type of scientific methodology that is often not appropriate or practicable for scientific study of a particular matter — thereby retarding (even preventing) the treatment of some types of disease.
The second part of the issue is the role that regulation plays in “evidence-based medicine”. This becomes particularly troubling when “evidence-based” is conflated with “regulatory-authority”. At a fundamental level all these things are NOT compatible.
I offer you this blinded thought experiment. Randomly select a cohort of 150 stem-cell scientists from all those that have published in the last 10 years. (Additional experiments with other types of scientist might also be undertaken.) Randomly divide the cohort into three groups of 50. Throughout the duration of the experiment, all 150 scientists are not allowed any contact with any of the others and NONE of the subject scientists are to know the experimental design. Each member of Group A is asked to independently define “evidence-based medicine”. Each member of Group B is assigned one of the definitions of “evidence-based medicine” from Group A. Members of Group B are then asked to evaluate existing medical treatments strictly according to the definition they have been assigned — as though they were a regulatory authority — and classify those treatments as either “evidence-based medicine” or “not evidence-based medicine”. The same would be done for Group C as for Group B. The resulting data set would then be analysed for internal consistency and any overall trends (if such exists). And in 50 years time we’d come back to the data set and see if it was in any way predictive of future developments in medicine.
My bet is that we would find a bunch of definitions that just weren’t up to assessing exisiting medical practices. Even with the highly selective nature of the cohort, I’d bet that there would be many logical inconsistencies within the definitions. I’d bet that the members in Group B would not be able to use the definitions to unambiguously separate treatments into one category or the other — and their assignments would differ from Group C. Finally, I predict that most existing medical practice would be classified as “NOT evidence-based”. As for 50 years on, I doubt that anyone can predict…
I took a look at some of the websites in your list of links. I was dismayed at the attitude taken by some of these bloggers — yes they found significant errors in the (published) work of others but they also made pretty bad mistakes themselves, and they were derogatory whereas the work that they criticized was not. I couldn’t help but think that they would have better proved their scientific credentials by submitting their comments or reanalyses for peer review and (possible) publication by the journal that published the work that they criticize.
Finally, I observe that evidence is never complete. The medical practitioner and patient are often in the difficult position of finding a way forward amidst uncertainty. Circumstances are often such that doing something may cause harm whereas doing nothing would definitely be bad news. The null-space option caused by dogmatic adherence to this or that version of “evidence-based medicine” can also do harm.
I’ve seen some advocates for “evidence-based medicine” adopt a very bloody minded view that would preclude anything for which there had not been double-blinded, randomized, placebo-controlled experiments and wot-not. I take it that such advocates would prefer that doctors not set broken bones… Or perhaps, such advocates would not use a parachute to escape a falling plane.
http://www.bmj.com/content/327/7429/1459