thsi isuonteq sekam me tnaw to aet na e ilco oioekc adn phoe i lebed uot
iDd on neo tcinoe htat het ddsO riota on teh top etfl si onw?gr Am I imigsns ?ehontigms If oyu utlecaalc it, t'is 6 sjut ekli het otp ghrti ..one..
RO ;tg&1 necdsaiti riseadecn ueorccencr of nve.et The lony RO rteegar nhat 1 wsa ni hte tbael atth itnacdeid hatt hte jcsuteb ate eoskcio tbu dti'nd kindr lmi.k uTs,h ahtt is the yonl eon itwh a ifnaiicgnts noercceruc
For a more systematic approach. First look at cookies p-val is sig when not stratified, the top table is stratified the OR > 1 => sig => cookies have association.
Then look at milk p-val is sig when not stratified, the bottom table stratified the OR = 1 => loss of significance => milk have no association.
Uworld ID 1173 has a good explanation for how to look at stratified analysis.
The afct ttah eth dsdo aiotr ni the top flet is ciertorcn aesmk ihst sotnuiqe yrve ifudcilf.t It ksame ti paerpa sa fi the ocsekio rea sevucaita btu the lkmi hda eoms tipceeovtr atc.orf So .nooxsibou
liItlinya mkil irnknidg saw dsaeaitcso hitw .ioclE otkubrae twhi =OR39. nad P1l0;t&0.0 f.n..it)gi(nacSi rAfet inactriastofti ntio eta icokose adn did not aet eookcsi RO eacmeb 1 adetnsi of 3.9 gnaimen het onassoitica seeapi.adrdp erhferT,eo gaeitn oecokis asw a ufenrdonoc nda rhete is on rlea itsicasonao weeetbn drigiknn iklm adn iEinol.sae.d.tc.,. sklim' te(h uofn)rdneco uinttobiocrn wsa ilssroenebp rof eth OR of 39. in het fsrit pa.lec This wsa ftrduheer tdemraednsto iwth OR of 6 ni eth oosecki anleo pg.our
For people who generally had trouble reading the two charts:
First chart: We separated the entire population into two smaller populations to test for the cookies affect. In Population A (drank milk) there was an odds ratio of 6 (typo in the actual chart). In Population B (did not drink milk) there was an odds ratio of 6. Since the odds ratios are not 1, we can conclude that the cookies have an effect regardless of the population (ie drank milk people versus didn't drink milk people).
Second chart: New set of populations to test for the effect of milk. In Population C (ate cookies) there was an odds ratio of 1. In Population D (did not eat cookies) there was also an odds ratio of 1. This means that milk did not have an effect ever and didn't contribute to the disease.
"Only cookies are independently associated with E. coli cases" means that only the cookies cause the disease without the effects of something else.
isTh one heter erwe rofu ddso i,otars one reiovdpd nrude ahec ba.tel The ylon one ahtt ahd na dods iatro grtraee hnta 10. was the ltbea ni teh top hitgr (
dsdO atoiR = 6, I ivee,l)eb iwhch hwne uyo kooled ta het alle,bs dle to het hrgit awenr.s
n"A dods aorti of 1 etsndciia htat eth dctioonni or eentv dnreu udtsy is leqyaul kilyel ot ocurc ni tbho og.spur An sdod itoar aegetrr tanh 1 cienidast tath the idniconot or envet si eomr lileky to ocrcu ni eht frtis roug"p. (kihrsit.pgdwkip/nitdoe:/sora_iiaew.t/dO/)
The OR in the upper left 22 table is incorrect, which should be 6 (726/36*2 =6), not 1. This means the OR of "ate cookies" does not change after stratification by "drank milk", so "drank milk" is not a confounder, and "ate cookies" is independently asso w/ EHEC outbreak.
On the other hand, OR for "drank milk" changed a lot (from 3.9 to 1.0), which indicates "drank milk" might be a confounder and, therefore, is not independently asso w/ EHEc outbreak.
we can make things simple like this way: if we want to know whether X1,or X2 correlates Y, we just separately test X1 and Y, and X2 and Y accordingly. When test X1 with Y, we require no X2 exposure; When test X2 with Y, we require no X1 exposure;
We test cookie with diarrhea, when milk was not drunk (top right): positive We test milk with diarrhea, when no cookie was eaten (lower right): negative
conclusion: only cookie correlates to the diarrhea
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