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DEFINING CHARACTERISTICS OF EPIDEMIOLOGY & EPIDEMIOLGISTS


1.       Epidemiologists... are variable lovers.

2.       Epidemiology is more than skin deep.

3.       Epidemiologists... prefer close associations.

4.       Nobody outmatches an epidemiologist!

5.       EXCITE AN EPIDEMIOLOGIST… cause an effect.

6.       Epidemiologists... prefer causal relationships.

7.       If you have the TIME and PLACE, I'm the PERSON.

8.       It takes on significance... with an epidemiologist.

9.       Epidemiologists... make better cohorts.

10.   Epidemiologists do it... all the TIME EVERYWHERE with EVERYBODY.

11.   WHOWHATWHENWHEREWHYHOW spells Epidemiology!

12.   Cancer Causes Epidemiology

13.   Epidemiologists...rate!

14.   Epidemiologists... know all the methods

15.   Epidemiologists... avoid spurious relationships.

16.   Epidemiologists... are well-adjusted.

17.   Epidemiologists... do it without bias.

18.   Epidemiologists... always need analysis.

19.   Respond... to an Epidemiologist.

20.   Epidemiologists... do it with informed consent (confidentiality guaranteed).

21.   Nobody outmatches my dad the epidemiologist!

22.   No one counts like my wife the epidemiologist!

23.   Tell me your attributes and I'll tell you your chances.

24.   Get your case under control with an epidemiologist.

25.   Epidemiologists... make a significant difference.

26.   Epidemiologists...Count!

27.   Epidemiologists... do it with reliability.

28.   Epidemiologists… do it with populations.

29.   Epidemiologists… do it randomly.

30.   Epidemiologists need infection too!

31.   Epidemiologists... do it with 95% confidence

32.   Epidemiologists... are matchmakers.

33.   Epidemiologists... have nice figures.

34.   Epidemiologists... have the odds.

35.   Epidemiologists... do it for your health.

36.   Epidemiologists... give group rates.

37.   Epidemiologists... look for meaningful relationships.

38.   Epidemiologists... have interesting transmissions.

39.   Epidemiologists... love Snow jobs.

40.   Epidemiology... is a risky business.

41.   Epidemiologists... leave nothing to chance.

42.   Epidemiologists... do it with increased frequency.

43.   No, I am not a skin doctor!

44.   Epidemiologists... do in the field!

45.   Epidemiologists... compare and save.

46.   Ride the downhill slope - with epidemiologists!

47.   Sample an epidemiologist!

48.   Frost follows Snow, in epidemiology.

49.   Co-relate with an epidemiologist!

50.   Dat-a Epidemiologist!

 

Old epidemiologists never die...

Old epidemiologists never die... they just don’t count anymore. (CONTEST WINNER)

Old epidemiologists never die... they just get very retrospective.

Old epidemiologists never die... they just lose their external validity.

Old epidemiologists never die... they just become totally confounded.

Old epidemiologists never die... they just suffer from an age effect.

Old Epidemiologists Never Die... they are just less likely to respond.

Old  Epidemiologists Never Die... they just fulfill their life expectancy.

Old Epidemiologists Never Die... their data just get soft.

Old Epidemiologists Never Die... they just don't count anymore.

Old Epidemiologists Never Die... they just assume new configurations.

Old Epidemiologists Never Die... they just reach infinite significance.

Old Epidemiologists Never Die... they simply cross-over.

Old Epidemiologists Never Die...their thoughts just get morbid

Old Epidemiologists Never Die... they get adjusted

Old Epidemiologists Never Die... they simply cross over

Old Epidemiologists Never Die... they make Type III errors

Old Epidemiologists Never Die... they can’t get their SMR’s up

Old Epidemiologists Never Die... they just lose power

Old Epidemiologists Never Die... they just become less prevalent

Old Epidemiologists Never Die... they just go double-blind

Old Epidemiologists Never Die... they just get age adjusted

Old Epidemiologists Never Die... they just lose their effect

Old Epidemiologists Never Die... but on the average, they regress and get mean

Old Epidemiologists Never Die... there is always a finite probability of surviving another 24 hours

Old Epidemiologists Never Die... they are just lost to followup

Old Epidemiologists Never Die... they are distributed randomly

Old Epidemiologists Never Die... they indirectly adjust their age

Old Epidemiologists Never Die... they just lose controls

Old Epidemiologists Never Die... it's an epidemiologic fallacy.

Old Epidemiologists Never Die... they just redefine their parameters.

Old Epidemiologists Never Die... they just add to the sum of squares.

Old Epidemiologists Never Die... they’re afraid it causes bladder cancer.

Old Epidemiologists Never Die... they can't agree on a cause of death.

Old Epidemiologists Never Die… they have herd immunity.

Old Epidemiologists Never Die… their effect just gets modified

Old Epidemiologists Never Die… they just don't interact as much

Old Epidemiologists Never Die… they just become a discordant pair

Old Epidemiologists Never Die… they’re done in by their agents.

Old Epidemiologists Never Die… they just end up in analysis

Old Epidemiologists Never Die… they’re just under-reported

Old Epidemiologists Never Die…they just reach their confidence limits.

Old Epidemiologists Never Die… but they do get tired of hearing AIDS.

Old Epidemiologists Never Die… they just plot new peaks.

Old Epidemiologists Never Die… they just ride off into the subset.

Old Epidemiologists Never Die… they just risk being relatively odd.

Old Epidemiologists Never Die… it's too risky.

Old Epidemiologists Never Die…they just reinterpret temporal relationships.

Old Epidemiologists Never Die… until their names appear in 80 column obituaries.

Old Epidemiologists Never Die… they just exceed the highest age stratum.

Old Epidemiologists Never Die… they just get ring around the cholera.

Old Epidemiologists Never Die… but their responses are variable.

Old Epidemiologists Never Die… they are just distributed randomly.

Old Epidemiologists Never Die… they just become lost to follow-up.

Old Epidemiologists Never Die… they just count less.

Old Epidemiologists Never Die… their data just get soft.

Old Epidemiologists Never Die… they just can't be traced.

Old Epidemiologists Never Die… their lives just get tabled.

Old Epidemiologists Never Die… their case just loses control.

Old Epidemiologists Never Die… Anyway, that's how they interpret the data.

Old Epidemiologists Never Die… they're just broken down by age and sex.

Old Epidemiologists Never Die… they just leave their cohorts behind.

Old Epidemiologists Never Die… they just fail their goodness of fit.

Old Epidemiologists Never Die… their samples just get smaller.

Old Epidemiologists Never Die… can't find a job? That's why!

Old Epidemiologists Never Die… they just cause new effects.

Old Epidemiologists Never Die… but they do tend to suffer from doze-response effects.

Old Epidemiologists Never Die… they just put their relatives at risk!

Old Epidemiologists Never Die… anyhow that’s how they interpret the data

Old Epidemiologists Never Die because they’ve learned to control for age.

Old Epidemiologists Never Die… they just correct all their risk factors.

Old Epidemiologists Never Die… they just retire and go fishing for salmonellosis and farm for tuberculosis.

Old Epidemiologists Never Die… their life just gets tabled

Old Epidemiologists Never Die

Old Epidemiologists Never Die

Old Epidemiologists Never Die… they just don't factor in the analysis.

Old Epidemiologists Never Die… they become step-wise.

Old Epidemiologists Never Die… they are just no longer prevalent.

Old Epidemiologists Never Die… they just become insignificant.

Old Epidemiologists Never Die… their effects just get modified.

Old Epidemiologists Never Die… they just drop out.

Old Epidemiologists Never Die… they just get lost in the field.

Old Epidemiologists Never Die…they just cause a new effect

Old Epidemiologists Never Die…they just can't quite manage the logistics of life.

Old Epidemiologists Never Die…they just rate lower.

Old Epidemiologists Never Die… they just do less than expected.

The Intro

Dear Sir,

I enclose a semantic exercise on chemists which, applied to the community of epidemiologists, might consitute the basis for one of your entertaining and instructive competitions.

Old Organic Chemists Never Die...

“they just get substituted”

“they just slowly decompose”

“but they become unstable”                  

“but they seldom exceed the activation

 energy for coupling”

“but they grow more and more aromatic”

“they just lose control of their apparatus”

New Scientist, September 22, 1983

To set the ball rolling, here goes:

Old Epidemiologists Never Die...

“they just become less and less probable”

Old Epidemiologists Never Die...

“they just join the trohoc”

(with apologies to Alvan Feinstein)

The first applies more to statisticians than to epidemiologists and the second is probably too much of an “in” joke to gain wide currency. I have no doubt other members of the herd can do better.

Michel Thuriaux

 

Old Epidemiologists Never Die

                Old Epidemiologists Never Die…

                but perpetuate the title

                for tho they do no longer shed

                we study bout the life they led

                which keeps the butter on our bread

                and our statistics vital    

 

A Lesson in Epidemiology from CasanovaSurgeon: I have made a good deal of money, and it is to you, Captain-God bless you!- That I am indebted for my personal comforts. Captain: How so?   Surgeon: In this way, Captain. You had a connection with Don Jerome's housekeeper, and he left her. When you went away with a certain souvenir which she communicated to a certain friend of hers, who, in perfect good faith, made a present to his wife. This lady did not wish, I suppose to be selfish and she gave her souvenir to a libertine, who in turn was so generous with it, that within less than a month, I had about fifty clients.”  Reproduced with permission of McGraw-Hill Inc. from The Illustrated Treasury of Medical Curiosa by Art Newman, Copyright 1988

Mench’s Laws:

·         The data you have are not the data you want

·         The data you want are not the data you need

               The data you need are not the data you can get

 

   
 

 

 

 
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