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10-Year Cell Phone / Cancer Study Is Inconclusive
crimeandpunishment writes "A major international (retrospective) study into cell phones and cancer, which took 10 years and surveyed almost 13,000 people, is finally complete — and it's inconclusive. The lead researcher said, 'There are indications of a possible increase. We're not sure that it is correct. It could be due to bias, but the indications are sufficiently strong ... to be concerned.' The study, conducted by the World Health Organization and partially funded by the cellphone industry, looked at the possible link between cell phone use and two types of brain cancer. It will be published this week."
To get statistical significance, you don't need to sample the entire population. Beyond a certain number for a certain confidence level, you don't get very much more.
I'm a minority race. Save your vitriol for white people.
The principle is correct, but you're failing to take into account the probability of an the respective events. Given that winning 60% of the vote is considered a landslide, you can think of asking someone whether they're voting Republican or Democrat as a coin flip with a small bias in one way or the other. Because the race is so close, a few extra republicans or democrats in your sample won't produce a huge error in your estimate.
On the other hand, a brain tumor can be thought of as a rare event. If the true incidence rate of brain cancer is five occurrences per thousand people over ten years, and your sample of 1,000 people has six incidences, you have a sample error of 20%. It's because of this that a small variation in the numbers can produce a large error. Therefore if you want to accurately assess the rate of cancer, you need a much bigger sample size.
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Perhaps you could come up with an example where there is no correlation, but there is causation?
I always wonder when I get these "challenges" whether someone really doesn't understand how statistics work, so they are wandering around in a constant state of confusion (or worse, confident ignorance). Or whether they are all pedantic asses who are too lazy and/or stupid to have an independent thought.
I can think of trillions of examples of a causation without correlation. I'll stick to something related to this topic. People who use cell phones have different habits than those without. Perhaps, because people aren't tethered to the desk phone, when they take calls at a desk, they push away or are more likely to walk around. If the CRT radiation has a greater effect than the cell phone radiation, then you'll find a result that correlates cell phone usage with lowered cancer, even though cell phones cause cancer.
The short answer is "confounds." They are everywhere, and you eliminate as many as possible in a study, but you never know what you missed, and you find what you can, publish what you find, and if anyone else identified a confound that wasn't accounted for, they can re-run the study with that in mind to see if it had any effect.
But, that you can't think of even one possible solution to the question you asked means you are too narrow minded or too stupid to worry about. I'm just posting this for those that have reasoning skills left. It's like all the people here, especially when I see people talking about voting and balloting systems, where if they can't think of a solution to a problem, then it's somehow proof that the solution doesn't exist.
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