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*To*: "'email @ redacted'" <email @ redacted>*Subject*: RE: [IP] Re: D prevention*From*: "Handsfield, James H." <email @ redacted>*Date*: Wed, 9 Jan 2002 13:42:19 -0500*Reply-To*: email @ redacted

Andrew Aronoff [mailto:email @ redacted] wrote: > I realize this isn't a statistics course, but could you amplify a bit? > > I've never heard of a "random event with an apparent probability". > I've heard of events with unknown causes, but such events are, by > definition, *not* random, since they are distinct from the noise. OK, let's start with a particular set of events. The total number of events is, in statistical terms, the universe of events. In most cases, we cannot record all events. So, we sample the universe of events and infer that what we see in the sample has the same distribution of events as in the universe. This is the random sample. The randomness comes from the sampling protocol in which each event has an equal probability of being selected for study. In a normal distribution (the classic bell curve) events near the center of the distribution will be chosen more frequently than those near the tails simply because there are more of them. When we do a statistical analysis of these data, we are looking for factors that cause the distribution to deviate from the randomness of the sampling protocol. Where we are unable to detect them, we infer that the events are random *WITH RESPECT TO THAT FACTOR*. IOW, there is not a statistically significant association between the factor and the event. In the situation(s) that gave rise to this discussion, to say that multiple cases of type 1 DM in a single family is a random occurrence is simply to say that we cannot detect any association between hereditary factors and the incidence of type 1. Logic would tell us that there certainly *appears* to be an association, but, since multiple research projects have not found it, our current conclusion is that multiple cases in one family falls within the observed random distribution of the universe of type 1 DM. There is probably no completely random event in the universe, that meaning that there is no force or other condition that would cause events to group in some way. In biological systems, and statistically, we look for an ideal of a random normal distribution. There are other distributions as well, and those take different statistical tools to work with. Take age of onset in type 1, for example. There's a reason that it is also known as juvenile onset diabetes. But because there are mature adults who develop type 1 (me, for example - well, I may not be the best one to judge about the maturity!), the upper tail is going to be quite long, with the central measure near 12 years old. > Deirdre wrote: > D> If type 1 diabetes occurs in 1 in 300 people, someone has a .33 of > D> a percent chance of having type 1. However, if someone has a > D> sibling with type 1, their odds of having it rise 15 fold to 5%. > > Again, please expand on your comments. If Type I were truly random and > someone already had a sibling, then the odds of their next sibling > would remain the same at 1 in 300. But it's not the same -- the odds > fall (not rise) to 1 in 20. > > Why isn't this a non-random event in this family? What am I missing? We have no way of knowing if it is random within the family. It's much too small a sample size to detect any associations. But if we select 10000 families at random with at least one diabetic child, what is the probability that more than one will have type 1? Or if we select 10000 families with at least two children (since we're looking at multiple events, single child families wouldn't qualify for the study), what are the probabilities that one child will develop type 1? What are the probabilities that more than one will develop it? Let's make it a little more complicated: select 10000 families with two or more children and a parent who has type 1. Look at the probabilities again. So far, the studies that have been done have not been able to detect a non-random association between the cases. If you're still with me, thanks for your forbearance. I hope I haven't confused the issue any further. Jim Handsfield email @ redacted OR email @ redacted The opinions expressed are mine and may not represent those of my wife who runs our house and makes more important decisions than I do. ---------------------------------------------------------- for HELP or to subscribe/unsubscribe, contact: HELP@insulin-pumpers.org send a DONATION http://www.Insulin-Pumpers.org/donate.shtml

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