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Obama's State of the Union Address

No, I'm arguing that you are asserting your opinion over the expertise of the researchers and I believe they are correct and your assertions are not.

What assertions? The only assertions made in the paper are either vague and unquantified (and thus of no real use), or they're quantified by measurements of things that don't mean much. You can't actually defend the measurements as being meaningful, but have abandoned all efforts to do so beyond your argument from authority. And for what? Does your entire position on healthcare hinge upon the statistics in this paper being accepted as meaningful? Surely not. Surely your position on healthcare is stronger than one paper. So why are you squandering your credibility in the defense of these bad statistics?

I'm not the one with partisan blinders on here, SG.
 
What assertions? The only assertions made in the paper are either vague and unquantified (and thus of no real use), or they're quantified by measurements of things that don't mean much. You can't actually defend the measurements as being meaningful, but have abandoned all efforts to do so beyond your argument from authority. And for what? Does your entire position on healthcare hinge upon the statistics in this paper being accepted as meaningful? Surely not. Surely your position on healthcare is stronger than one paper. So why are you squandering your credibility in the defense of these bad statistics?

I'm not the one with partisan blinders on here, SG.


Well said - even if you had to say it 20 times for the ignorami. :) :cool:
 
Exactly. Argument from authority does not mean you cite an authority on a subject they can speak authoritatively about.

The fallacy comes when you have a disconnect between the expertise of the person cited and the thing being claimed.
Not sure why this is so hard for some to understand.
 
Well said - even if you had to say it 20 times for the ignorami.
Argument by assertion. Argument ad nauseam. The nonsense about "overlap" is pure BS.

Our 2001 study in 5 states found that medical problems contributed to at least 46.2% of all bankruptcies. Since then, health costs and the numbers of un- and underinsured have increased, and bankruptcy laws have tightened.

Methods
We surveyed a random national sample of 2314 bankruptcy filers in 2007, abstracted their court records, and interviewed 1032 of them. We designated bankruptcies as “medical” based on debtors' stated reasons for filing, income loss due to illness, and the magnitude of their medical debts.

Results

Using a conservative definition, 62.1% of all bankruptcies in 2007 were medical; 92% of these medical debtors had medical debts over $5000, or 10% of pretax family income. The rest met criteria for medical bankruptcy because they had lost significant income due to illness or mortgaged a home to pay medical bills. Most medical debtors were well educated, owned homes, and had middle-class occupations. Three quarters had health insurance. Using identical definitions in 2001 and 2007, the share of bankruptcies attributable to medical problems rose by 49.6%. In logistic regression analysis controlling for demographic factors, the odds that a bankruptcy had a medical cause was 2.38-fold higher in 2007 than in 2001.

Conclusions

Illness and medical bills contribute to a large and increasing share of US bankruptcies.
This was published in a peer reviewed journal. The American Journal of Medicine. Contained in the study is a great deal of data that has been ignored by this sophomoric critique. As if the *researchers were clueless.

*David U. Himmelstein, MD; Deborah Thorne, PhD; Elizabeth Warren, JD; Steffie Woolhandler, MD, MPH

In multivariate analysis, being uninsured at filing did not predict a medical cause of bankruptcy, while a gap in coverage did (odds ratio [OR] = 1.35, P = .002). Other predictors included: older age (OR = 1.016/year, P = .0001), married (OR = 1.59, P = .0001), female (OR = 1.34, P = .002), larger household (OR = 1.97/household member, P = .01), and lower income quartile (OR = 1.30, P = .0001).

Medical debtors' court records identified more debt owed directly to doctors and hospitals than did nonmedical debtors', a mean of $4988 vs $256, respectively (P <.0001). Medical debtors with coverage gaps owed providers a mean of $8338, vs $2740 (P <.0001) for medical debtors with continuous coverage. Nonmedical debtors had few medical debts, averaging under $300 regardless of insurance status. (Medical debts financed through credit cards or other borrowing, or owed to collection agencies are not included because they cannot be identified through court records.)
Chi-squared and 2-tailed t tests were used for univariate analyses. We used forward stepwise logistic regression analysis on the 2007 cohort to assess predictors of medical bankruptcy and predictors of home loss or foreclosure among homeowners. Finally, we performed logistic regression using the combined 2001 and 2007 cohorts to examine whether the odds of a bankruptcy being medical were higher in 2007 than in 2001, after controlling for demographics, income, and insurance status. SAS Version 9.1 (SAS Institute Inc., Cary, NC) was used for all analyses.
What is more likely, that some nobody on a forum is right or the peer reviewers (referees)? That is as asinine as the folks who attack science on GMOs or AGW with their silly nit picking without even understanding the math or protocols.

So yeah, A.) I call B.S. B.) Stop being a cheerleader and step up to the plate and tell us why a peer viewed study in a major journal has a glaring error that only some nobody could spot? I'll bet you or anyone else in this thread criticizing the study can't even run the math or even know what the hell SAS is much less make claims.

I've written statistical analysis software for UCLA and I know something about it. Please stop acting like you know something about statistics when you obviously don't.
 
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What is more likely, that some nobody on a forum found an error that is right or the peer reviewers (referees)?

And we're back to argument from authority.

This isn't about an error. Actually, there probably is an error in the paper (see if you can spot it, I'll tell you if you give up), but that's not the real problem. The problem is their choice of metric. I've explained why that choice of metric is problematic. What's been the response? A demand to defer to the experts. No one is even trying to defend the actual metric that they used.

So yeah, A.) I call B.S. B.) Stop being a cheerleader and step up to the plate and tell us why a peer viewed study in a major journal has a glaring error that only some nobody could spot?

Anybody could spot the problem with this paper, if they wanted to. Peer review doesn't guarantee that anybody will. If you and SG are any indications, plenty of people don't want to see the problem. And your own response is BS. You refuse to engage in the actual debate here, but only post second-hand. Stop being a cheerleader and step up to the plate and tell us why their metric is the relevant metric.
 
He's using the same type of specious arguments as Creationists do against Evolution.
Yep, at least Ian Juby is a member of Mensa so when he weekly identifies the "errors" of evolution he has some basis, right? I mean, why the hell should anyone appeal to the authority of the biological evolutionists? What the hell good is peer reviewed published studies? It's just science, right?
 

Obviously not, since I've never made any claims about myself at all here. My claims have always been about the contents of the article, a topic you have long since abandoned, and never really addressed in the first place. I explained why the definitons they used were not useful here. You have never even attempted to explain why those definitions are useful. All you can do is whine about "peer review", as if that were a magic talisman which should ward off any investigation.

And you call yourself a skeptic.
 
Obviously not, since I've never made any claims about myself at all here. My claims have always been about the contents of the article, a topic you have long since abandoned, and never really addressed in the first place. I explained why the definitons they used were not useful here. You have never even attempted to explain why those definitions are useful. All you can do is whine about "peer review", as if that were a magic talisman which should ward off any investigation.

And you call yourself a skeptic.
And yet you cannot seem to believe it is possible you have not presented a convincing critique. All you are able to conclude is all the "experts" are wrong, we are all duped, and you have presented a convincing case. When I tell you your case was not convincing and why, your answer it to switch to ad homs.
 
What an excellent question! What bracket is the study talking about?

$50,000 or more. For less than that, they use 10% of annual income. Keep in mind also that the expenses are totaled over two years, not one year.
 
You refuse to engage in the actual debate here, but only post second-hand. Stop being a cheerleader and step up to the plate and tell us why their metric is the relevant metric.

LOL, you bad mouthed OWS, didn't you?
 
Overlapping data.

To understand how specious this silly claim is, imagine a homeroom in some school (English). Lets run statistics for height on that class. Now, imagine next period, a different class (math). Some of the kids from first period are in this class with other students (they overlap). We again run the study again. Now, we average the two studies together.

Question, if we know A.) the average overlap and B.) the standard deviation for the overlap can we average the two different studies accurately?
 
And yet you cannot seem to believe it is possible you have not presented a convincing critique.

By that, you mean I haven't convinced you. But given your persistent refusal to engage or even understand what I've actually said, that failure isn't really something I'm worried about.

All you are able to conclude is all the "experts" are wrong

No. I didn't say they were wrong. I said that their numbers were meaningless. This is a perfect example of your inability to understand the basics of my position. They measured something that isn't useful. It doesn't matter how correct they are about a measurement which isn't useful. Nor does their expertise make it useful. Yet you insist it MUST be, solely because they're experts, because you can't defend the relevance of their definitions on the actual merits.
 
To understand how specious this silly claim is, imagine a homeroom in some school (English). Lets run statistics for height on that class. Now, imagine next period, a different class (math). Some of the kids from first period are in this class with other students (they overlap). We again run the study again. Now, we average the two studies together.

Question, if we know A.) the average overlap and B.) the standard deviation for the overlap can we average the two different studies accurately?

Yeah, um... no. That's got absolutely nothing to do with what I was talking about. This isn't about overlapping samples, it's about overlapping categories. Like measuring height AND weight for the same sample. Furthermore, there is no averaging or standard deviation involved here, it's binary categorizations. But with more than just two categories, and with some of those categories being pretty meaningless.

Really, RandFan, you're just embarrassing yourself when you try to jump into a debate where you've ignored half the posts.
 

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