Marvin said-
Beliaev does not document how many 16-18-year olds died in the JW group.
That's a problem, since that would be VERY IMPORTANT data to know, in order tighten up unknowns to obtain statistically-valid conclusions. Since it wasn't recorded/reported, we can only guess (similar to how the JWs don't track and report the # of deaths Worldwide). The problem is NZ's dangerously-low age of consent (16; in the rest of the World, it's generally 18).
Now tell everyone why this could vastly inflate the number of my extrapolation. Can you please do that?
Sure.
Let's suppose ONLY ONE of those patients in Beliaev's study WAS aged 16-18 yrs, and hence would be allowed under NZ law to die, which wouldn't be the case if they had lived virtually anywhere else in the rest of the World (say, AU or US, where age of consent is 18). If they HAD, the State would step in and FORCE life-saving blood against their parent's or their wishes. In the U.S., we don't let 16 yr olds die, like they MUST do in NZ.
(Here's a recent thread about a 17 y.o. in AU who's life was protected by the AU Court system, a safety net which wouldn't under him had the teen lived in NZ (since he'd be allowed to reject blood and die at 17 in NZ and no one could say boo). Here's a recent thread about one such boy who made the media outlets:)
http://www.jehovahs-witness.net/watchtower/medical/262354/1/Jehovahs-Witness-boy-fights-court-for-right-to-die#.Ummm9SQhZLc
So suppose only ONE participant was aged 16-18 in Beliaev's study. What would that do to your Worldwide extrapolation figure?
Let's find out what happens if ONE pt wasn't allowed to die (like they would in NZ).
From your website:
This study found 103 Witness patients who suffered severe anemia and 20.4% 19.4% of these died (i.e., 21 20 of these patients died).
During this period the death rate among patients who suffered severe anemia but accepted ARBC transfusion was 1.9%. The net difference in mortality rate is 17.5% 18.45%. Of the Witnesses who died, the number who died over and beyond the group that accepted ARBC transfusion (the non-Witness group) is 18 19, or 17.5% 18.45% of the 103.
● Over a 10 year period there were 18 19 Witnesses who died that shouldn’t have. That’s 1.8 1.9 per year.
● Over the same 10 year period the number of Witnesses in New Zealand averaged 12,700. 1.8 1.9 deaths per year is 0.014% .015% of the Witness population.
● During year 2011 the Watchtower organization presents the number of Jehovah’s Witnesses at 7,400,000.[3] 0.014% 0.015% of this number is 1,049 1109.
● During year 2011 there were 1,049 1109 premature deaths among Jehovah's Witnesses due to Watchtower's blood doctrine.
I'll leave you to do the rest of the math (noting that only ONE pt less in the JW death count results in an over-estimattion for 2011 by over 5%; a similiar error overall would drop your 50k figure to 45k, if applying the same difference found in 2011 numbers; not a valid assumption, but I'm not taking the time to do it for EVERY YEAR and then add up the results).
That demonstrates the importance of what Simon has repeatedly stated about the so-called "butterfly effect" in statistics, where small changes in the input side of the calculator can have a dramatic impact on the final results (especially when you multiply those seemingly minor changes by 7.4 x 10 6 )!
But again, the actual number of such teen patients who participated in the study is unknown, and hence that's a MAJOR OVERSIGHT in the study for the purposes of extrapolation to the various legal climates around the World which don't let teens die. It would've been nice for the study authors to have reported the ages of the 21 JWs who died, so as to support a campaign of RAISING NZ's relatively-low age of consent, or to support extrapolation Worldwide as you'd like to do in a responsible manner manner supported by valid accepted methodology of statistical analysis.
BTW, you said this earlier to LisaRose:
Don’t forget that the Beliaev study was a matched comparison. This means patient profiles and comorbidities were accounted for. So, for instance, in the 103 JW patient pool there were 8 with cancer and in the non-JW pool there were 15 patients with cancer. But regardless of condition, if treatment options were exhausted so a patient was in palliative care they were not included in the study because inclusion would skew the result.
I suspect that factor alone would skew the results, but not in the way you're suggesting, since excluding those end-of-life palliative care patients from BOTH groups would actually INCREASE the effect of the more easily-treatable young patients who died, hence amplifying the effects of those in this otherwise-protected group who live in other Countries (the exclusion would tend to bias the data set away from the older patients, and skewing towards the younger, more-easily saved, thus skewing the results to over-exaggerate those deaths).
Marvin said-
There has been much bantered around in this discussion about whether New Zealanders have a higher rate of anemia (in this case Hb =/< 8 grams dL). This criticism boils down to: If New Zealanders have a higher rate of anemia compared to the rest of the world on average, this could mean my extrapolation at issue is inflated.
Here’s what wrong with that notion: There is a difference between rate of anemia and rate of mortality due to anemia, and there is a gargantuan difference between rate of anemia and rate of mortality due to refusing blood with anemia.
Because anemia is a largely treatable condition then rate of anemia is not so much a determinant of mortality due to anemia. What counts in my extrapolation is not rate of anemia (or severe anemia) but, rather, known deaths attributed solely to lack of red cell transfusion in patients suffering severe anemia. Rate of anemia does not change this mortality statistic against the population.
And that's what you're missing:
Not only does the sample population have a higher rate of anemia, but you admit that in the sub-population it has a higher mortality rate if left untreated, and those two factors explain WHY the study is unfit for extrapolation purposes: it's not truly a representative sample of the entire population Worldwide. Hence, the results would likely VASTLY AMPLIFY the mortality due to REFUSING BT, and hence the results wouldn't extrapolate to OTHER groups. Why? The subjects of the study weren't an accurate sampling of the population you're trying to extrapolate to!
Take the incidence of diabetes amongst the Navajo Nation: four times higher than the national average, diabetes is also more fatal if left untreated (the life expectancy of a male Navajo is shocking low, like in the low 50's). Hence it's more important for Navajo pts with diabetes to take their meds regularly, good nutrition, exercise, don't drink/smoke, etc, since diabetes will cause vastly-more problems, and at a younger age
(As part of my clinical rotations in my last year of training, I spent a quarter at Shiprock Indian Health Service Hospital, NM,dealing with the management of pts with dbb. I remember a few pts in their 30's who were on dialysis, losing limbs in wheelchairs, etc but they continued to not take their condition seriously, with a fatalistic "Oh, well" attitude. Sad, but people will do what they will do, and you can only advise, since you cannot force anyone to care if they don't.)
Now, given that we know the Navajo tribe is not representative of the U.S. population (300 mil), it would be ENTIRELY INAPPROPRIATE to try to extrapolate a figure on the prevalence and mortality from diabetes in the US based on a study conducted on the Navajo reservation, since we KNOW it isn't representative! Sampling a population to make sure it truly is representative of what you're trying to sample is a subject with many courses dedicated to the task.
Invalid sampling makes extrapolation unstable and unreliable, as attempts to draw conclusions become unreliable when the sample actually isn't representative of the larger group you're trying to draw conclusions about. That's why ALL studies can only reliably tell us anything for the environment they were designed to sample (and YES, some study results MAY lend themselves to extrapolation, AS LONG AS the population is fairly similar in characteristics to that used in the study; you refer to this in matched groups, but you cannot be sure the groups used in the study are similar to other populations, and you cannot just assume they are similar).
In this case, Beliaev's study was looking at the clinical outcomes and cost comparisons within NZ for refusing blood, and anything beyond that causes the confidence interval (margin of error) to get unacceptably large.
Adam
