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“erm, but it's OK for you to transpose this risk to 7.5 million people?!?!?”
The 7.5 million match the sample set of JWs in New Zealand. The 10x multiplier is not presented of all patients with anemia. In other words, if we look at the 10x as a “sample set” it does not align (match) with all patients with anemia. It only aligns with patients with conditions that align with the matched comparison groups.
“Anyway, the questions I've asked are easy to find. I thought you'd be able to find them by clicking on the page numbers but obviously not. I know you're trying to bait for insults so you can storm off but I'd like to thrash this out until you see your own error.”
I’ve failed to address several questions and comment in this discussion because they didn’t have any merit worth answering for. I said this already.
“How come your numbers don't change if the rate of deaths does? If there are 1000 JWs instead of just the 103 who refused treatment ... the rate is the same as regular people (1.9%) but your method comes up with 50,000 "extra" deaths. Are you claiming that *no* JW ever accepts blood?”
My numbers are tied to hard data and not rates. The number of preventable deaths is hard. The number of JWs in New Zealand is hard. Various mortality rates will not change these hard numbers. These hard numbers present a fixed ratio.
“Your mistake through all this is to treat "JWs who chose to refuse blood" as synonymous with the entire population of JWs. Any stats to do with deaths from refusal to accept blood is already based on a smaller and more specific sample which is NOT representative of JWs in general. In fact, all JWs who do not refuse to accept blood are in the stats for, well, everyone else.”
The data set from Beliaev includes JWs who accepted blood product forbidden under Watchtower doctrine. Hence the issue you raise is present and accounted for.
Regardless, we still have a hard number of preventable deaths and we still have a hard number of JWs in New Zealand. Also, the data set at issue is specifically about red cells transfusion. Those who died over and above the norm refused red cell transfusion. If there were JWs in New Zealand suffering severe anemia who accepted red blood cell transfusion all that means is those JWs are not in the data set and whether they lived of died does not affect the ratio mentioned above because the ratio is not of JWs who die and those who do not die based on accepting red cells transfusion but, rather, the actual number of preventable deaths versus the JW New Zealand population.
“It's why your numbers don't tally with simple sanity checks and experience / observation.”
The number of 50,000 over a 50-year period is imperceptible unless a person has figures before them to do the math.
“If he'd had more patients in the study but the same mortality rate, then what would the extra deaths do to your numbers? What effect would fewer numbers (but the same rate) have?”
My extrapolation is based on hard numbers and not a rate. However, if more patients died and the rate of mortality remained the same among the JW patients compared with the matched group then nothing would have changed in terms of JWs at risk for premature mortality.
“If your method was based on the rate it wouldn't change ... but it does. Almost as though it has nothing to do with the mortality rate.”
Again, look at the hard numbers. The mortality rate in the Beliaev study is not stated in a way to apply it to a larger sample that does not align with the matched group. But the hard numbers are stated in a way to apply it to a larger group.
Marvin Shilmer