andrew_gelman_stats andrew_gelman_stats-2011 andrew_gelman_stats-2011-708 knowledge-graph by maker-knowledge-mining

708 andrew gelman stats-2011-05-12-Improvement of 5 MPG: how many more auto deaths?


meta infos for this blog

Source: html

Introduction: This entry was posted by Phil Price. A colleague is looking at data on car (and SUV and light truck) collisions and casualties. He’s interested in causal relationships. For instance, suppose car manufacturers try to improve gas mileage without decreasing acceleration. The most likely way they will do that is to make cars lighter. But perhaps lighter cars are more dangerous; how many more people will die for each mpg increase in gas mileage? There are a few different data sources, all of them seriously deficient from the standpoint of answering this question. Deaths are very well reported, so if someone dies in an auto accident you can find out what kind of car they were in, what other kinds of cars (if any) were involved in the accident, whether the person was a driver or passenger, and so on. But it’s hard to normalize: OK, I know that N people who were passengers in a particular model of car died in car accidents last year, but I don’t know how many passenger-miles that


Summary: the most important sentenses genereted by tfidf model

sentIndex sentText sentNum sentScore

1 A colleague is looking at data on car (and SUV and light truck) collisions and casualties. [sent-2, score-0.685]

2 For instance, suppose car manufacturers try to improve gas mileage without decreasing acceleration. [sent-4, score-0.781]

3 The most likely way they will do that is to make cars lighter. [sent-5, score-0.468]

4 But perhaps lighter cars are more dangerous; how many more people will die for each mpg increase in gas mileage? [sent-6, score-0.761]

5 Deaths are very well reported, so if someone dies in an auto accident you can find out what kind of car they were in, what other kinds of cars (if any) were involved in the accident, whether the person was a driver or passenger, and so on. [sent-8, score-1.349]

6 But it’s hard to normalize: OK, I know that N people who were passengers in a particular model of car died in car accidents last year, but I don’t know how many passenger-miles that kind of car was driven, so how do I convert this to a risk? [sent-9, score-1.893]

7 I can find out how many cars of that type were sold, and maybe even (through registration records) how many are still on the road, but I don’t know the total number of miles. [sent-10, score-0.383]

8 Some types of cars are driven much farther than others, on average. [sent-11, score-0.544]

9 This lets you look at things like: given that the car is in an accident, how likely is it that someone in the car will die? [sent-13, score-1.182]

10 This sort of analyses makes heavy cars look good (for the passengers in those vehicles; not so good for passengers in other vehicles, which is also a phenomenon of interest! [sent-14, score-0.889]

11 ) but perhaps this is misleading: heavy cars are less maneuverable and have longer stopping distance, so perhaps they’re more likely to be in an accident in the first place. [sent-15, score-0.987]

12 Conceivably, a heavy car might be a lot more likely to be in an accident, but less likely to kill the driver if it’s in one, compared to a lighter car that is better for avoiding accidents but more dangerous if it does get hit. [sent-16, score-1.853]

13 Any car that is driven by a disproportionately large fraction of men in their late teens or early twenties is going to have horrible accident statistics, whereas any car that is selected largely by middle-aged women with young kids is going to look pretty good. [sent-18, score-1.719]

14 If 20-year-old men drove Volvo station wagons, the Volvo station wagon would appear to be one of the most dangerous cars on the road, and if 40-year-old women with 5-year-old kids drove Ferraris, the Ferrari would seem to be one of the safest. [sent-19, score-1.024]

15 Big engines and heavy frames cost money to make, so inexpensive cars tend to be light and to have small engines, in addition to being physically small. [sent-21, score-0.919]

16 If an inexpensive car has a poor safety record, is it because it’s light, because it’s small, or because it’s lacking safety features? [sent-23, score-0.896]

17 And yes, size matters, not just weight: a bigger car can have a bigger “crumple zone” and thus lower average acceleration if it hits a solid object, for example. [sent-24, score-0.784]

18 If large, heavy cars really are safer than small, light cars, how much of the difference is due to size and how much is due to weight? [sent-25, score-0.906]

19 Perhaps a large, light car would be the best, but building a large, light car would require special materials, like titanium or aluminum or carbon fiber, which might make it a lot more expensive…what, if anything, do we want to hold constant if we increase the fleet gas mileage? [sent-26, score-1.539]

20 And of course the parameters I’ve listed above — size, weight, safety features, and driver characteristics — don’t begin to cover all of the relevant factors. [sent-29, score-0.288]


similar blogs computed by tfidf model

tfidf for this blog:

wordName wordTfidf (topN-words)

[('car', 0.521), ('cars', 0.383), ('accident', 0.238), ('heavy', 0.173), ('light', 0.164), ('driver', 0.147), ('mileage', 0.144), ('safety', 0.141), ('passengers', 0.139), ('accidents', 0.131), ('volvo', 0.117), ('gas', 0.116), ('engines', 0.106), ('driven', 0.105), ('dangerous', 0.102), ('vehicles', 0.1), ('inexpensive', 0.093), ('lighter', 0.088), ('weight', 0.087), ('size', 0.086), ('causal', 0.085), ('likely', 0.085), ('station', 0.084), ('features', 0.082), ('explanatory', 0.078), ('drove', 0.078), ('road', 0.076), ('die', 0.067), ('large', 0.064), ('bigger', 0.062), ('kind', 0.06), ('types', 0.056), ('look', 0.055), ('kids', 0.055), ('men', 0.055), ('perhaps', 0.054), ('wagon', 0.053), ('acceleration', 0.053), ('deficient', 0.053), ('fleet', 0.053), ('mpg', 0.053), ('normalize', 0.053), ('teens', 0.053), ('wagons', 0.053), ('women', 0.052), ('question', 0.05), ('confounders', 0.05), ('suv', 0.05), ('untangle', 0.05), ('due', 0.05)]

similar blogs list:

simIndex simValue blogId blogTitle

same-blog 1 0.99999982 708 andrew gelman stats-2011-05-12-Improvement of 5 MPG: how many more auto deaths?

Introduction: This entry was posted by Phil Price. A colleague is looking at data on car (and SUV and light truck) collisions and casualties. He’s interested in causal relationships. For instance, suppose car manufacturers try to improve gas mileage without decreasing acceleration. The most likely way they will do that is to make cars lighter. But perhaps lighter cars are more dangerous; how many more people will die for each mpg increase in gas mileage? There are a few different data sources, all of them seriously deficient from the standpoint of answering this question. Deaths are very well reported, so if someone dies in an auto accident you can find out what kind of car they were in, what other kinds of cars (if any) were involved in the accident, whether the person was a driver or passenger, and so on. But it’s hard to normalize: OK, I know that N people who were passengers in a particular model of car died in car accidents last year, but I don’t know how many passenger-miles that

2 0.25059697 720 andrew gelman stats-2011-05-20-Baby name wizards

Introduction: The other day I noticed a car with the improbable name of Nissan Rogue, from Darien, Connecticut (at least that’s what the license plate frame said). And, after all, what could be more “rogue”-like than a suburban SUV? I can’t blame the driver of the car for this one; I’m just amused that the marketers and Nissan thought this was an appropriate name for the car.

3 0.23394606 1417 andrew gelman stats-2012-07-15-Some decision analysis problems are pretty easy, no?

Introduction: Cassie Murdoch reports : A 47-year-old woman in Uxbridge, Massachusetts, got behind the wheel of her car after having a bit too much to drink, but instead of wreaking havoc on the road, she ended up lodged in a sand trap at a local golf course. Why? Because her GPS made her do it—obviously! She said the GPS told her to turn left, and she did, right into a cornfield. That didn’t faze her, and she just kept on going until she ended up on the golf course and got stuck in the sand. There were people on the course at the time, but thankfully nobody was injured. Police found a cup full of alcohol in her car and arrested her for driving drunk. Here’s the punchline: This is the fourth time she’s been arrested for a DUI. Assuming this story is accurate, I guess they don’t have one of those “three strikes” laws in Massachusetts? Personally, I’m a lot more afraid of a dangerous driver than of some drug dealer. I’d think a simple cost-benefit calculation would recommend taking away

4 0.22811723 527 andrew gelman stats-2011-01-20-Cars vs. trucks

Introduction: Anupam Agrawal writes: I am an Assistant Professor of Operations Management at the University of Illinois. . . . My main work is in supply chain area, and empirical in nature. . . . I am working with a firm that has two separate divisions – one making cars, and the other makes trucks. Four years back, the firm made an interesting organizational change. They created a separate group of ~25 engineers, in their car division (from within their quality and production engineers). This group was focused on improving supplier quality and reported to car plant head . The truck division did not (and still does not) have such an independent “supplier improvement group”. Other than this unit in car, the organizational arrangements in the two divisions mimic each other. There are many common suppliers to the car and truck division. Data on quality of components coming from suppliers has been collected (for the last four years). The organizational change happened in January 2007. My focus is

5 0.16786177 2123 andrew gelman stats-2013-12-04-Tesla fires!

Introduction: Paul Kedrosky writes: Curious if you’ve looked at the current debate about Tesla fires, statistically speaking. Lots of arm-waving about true/sample proportions, sample sizes, normal approximations, etc. Would love to see a blog post if it intrigues you at all. I hadn’t heard about this at all! I mean, sure, I’d heard of Tesla, this is an electric car being built by some eccentric billionaire . But I didn’t know they were catching on fire! At this point I was curious so I followed the link. It was an interesting discussion to read, partly because some of the commenters were so open about their financial interests; for example , i felt like now is a good time to share some of my insights, specifically regarding the tesla fires. i know many people won’t like to hear what i have to say. and i don’t have a longer term holding in tesla any more, although sometimes i day-trade tesla from the long or short side. tesla has been kind to me, both as an investor and model s

6 0.16139354 307 andrew gelman stats-2010-09-29-“Texting bans don’t reduce crashes; effects are slight crash increases”

7 0.14529586 1693 andrew gelman stats-2013-01-25-Subsidized driving

8 0.12250514 1789 andrew gelman stats-2013-04-05-Elites have alcohol problems too!

9 0.1189769 1491 andrew gelman stats-2012-09-10-Update on Levitt paper on child car seats

10 0.11174048 1053 andrew gelman stats-2011-12-11-This one is so dumb it makes me want to barf

11 0.11146943 1621 andrew gelman stats-2012-12-13-Puzzles of criminal justice

12 0.10494176 1453 andrew gelman stats-2012-08-10-Quotes from me!

13 0.10267247 1776 andrew gelman stats-2013-03-25-The harm done by tests of significance

14 0.097757943 1541 andrew gelman stats-2012-10-19-Statistical discrimination again

15 0.09704005 2341 andrew gelman stats-2014-05-20-plus ça change, plus c’est la même chose

16 0.095189296 970 andrew gelman stats-2011-10-24-Bell Labs

17 0.092906967 814 andrew gelman stats-2011-07-21-The powerful consumer?

18 0.091663837 1646 andrew gelman stats-2013-01-01-Back when fifty years was a long time ago

19 0.089220904 2299 andrew gelman stats-2014-04-21-Stan Model of the Week: Hierarchical Modeling of Supernovas

20 0.084067434 2280 andrew gelman stats-2014-04-03-As the boldest experiment in journalism history, you admit you made a mistake


similar blogs computed by lsi model

lsi for this blog:

topicId topicWeight

[(0, 0.146), (1, -0.028), (2, 0.04), (3, -0.026), (4, 0.028), (5, 0.01), (6, 0.023), (7, 0.003), (8, 0.024), (9, 0.013), (10, -0.051), (11, -0.01), (12, 0.022), (13, 0.001), (14, 0.02), (15, 0.02), (16, 0.05), (17, -0.015), (18, 0.024), (19, 0.027), (20, -0.003), (21, -0.005), (22, -0.0), (23, 0.009), (24, 0.015), (25, 0.058), (26, -0.034), (27, -0.064), (28, 0.026), (29, 0.024), (30, 0.025), (31, 0.002), (32, -0.015), (33, -0.014), (34, -0.017), (35, -0.007), (36, 0.024), (37, 0.031), (38, -0.022), (39, 0.039), (40, -0.045), (41, -0.068), (42, -0.028), (43, -0.0), (44, 0.0), (45, 0.014), (46, 0.021), (47, 0.03), (48, 0.048), (49, 0.035)]

similar blogs list:

simIndex simValue blogId blogTitle

same-blog 1 0.94167352 708 andrew gelman stats-2011-05-12-Improvement of 5 MPG: how many more auto deaths?

Introduction: This entry was posted by Phil Price. A colleague is looking at data on car (and SUV and light truck) collisions and casualties. He’s interested in causal relationships. For instance, suppose car manufacturers try to improve gas mileage without decreasing acceleration. The most likely way they will do that is to make cars lighter. But perhaps lighter cars are more dangerous; how many more people will die for each mpg increase in gas mileage? There are a few different data sources, all of them seriously deficient from the standpoint of answering this question. Deaths are very well reported, so if someone dies in an auto accident you can find out what kind of car they were in, what other kinds of cars (if any) were involved in the accident, whether the person was a driver or passenger, and so on. But it’s hard to normalize: OK, I know that N people who were passengers in a particular model of car died in car accidents last year, but I don’t know how many passenger-miles that

2 0.75065881 53 andrew gelman stats-2010-05-26-Tumors, on the left, or on the right?

Introduction: In response to the post The bane of many causes in the context of mobile phone use and brain cancer, Robert Erikson wrote: The true control here is the side of the head of the tumor: same side as phone use or opposite side. If that is the test, the data from the study are scary. Clearly tumors are more likely on the “same” side, at whatever astronomical p value you want to use. That cannot be explained away by misremembering, since an auxiliary study showed misremembering was not biased toward cell phone-tumor consistency. A strong signal in the data pointed by Prof. Erikson is that the tumors are overwhelmingly likelier to appear on the same side of the head as where the phone is held. I’ve converted the ratios into percentages, based on an assumption that the risk for tumors would be apriori equal for both sides of the head. There is a group of people with low-to-moderate exposure and high lateral bias, but the bias does increase quite smoothly with increasing

3 0.74758381 1086 andrew gelman stats-2011-12-27-The most dangerous jobs in America

Introduction: Robin Hanson writes: On the criteria of potential to help people avoid death, this would seem to be among the most important news I’ve ever heard. [In his recent Ph.D. thesis , Ken Lee finds that] death rates depend on job details more than on race, gender, marriage status, rural vs. urban, education, and income  combined !  Now for the details. The US Department of Labor has described each of 807 occupations with over 200 detailed features on how jobs are done, skills required, etc.. Lee looked at seven domains of such features, each containing 16 to 57 features, and for each domain Lee did a factor analysis of those features to find the top 2-4 factors. This gave Lee a total of 22 domain factors. Lee also found four overall factors to describe his total set of 225 job and 9 demographic features. (These four factors explain 32%, 15%, 7%, and 4% of total variance.) Lee then tried to use these 26 job factors, along with his other standard predictors (age, race, gender, m

4 0.74265176 791 andrew gelman stats-2011-07-08-Censoring on one end, “outliers” on the other, what can we do with the middle?

Introduction: This post was written by Phil. A medical company is testing a cancer drug. They get a 16 genetically identical (or nearly identical) rats that all have the same kind of tumor, give 8 of them the drug and leave 8 untreated…or maybe they give them a placebo, I don’t know; is there a placebo effect in rats?. Anyway, after a while the rats are killed and examined. If the tumors in the treated rats are smaller than the tumors in the untreated rats, then all of the rats have their blood tested for dozens of different proteins that are known to be associated with tumor growth or suppression. If there is a “significant” difference in one of the protein levels, then the working assumption is that the drug increases or decreases levels of that protein and that may be the mechanism by which the drug affects cancer. All of the above is done on many different cancer types and possibly several different types of rats. It’s just the initial screening: if things look promising, many more tests an

5 0.73769778 1789 andrew gelman stats-2013-04-05-Elites have alcohol problems too!

Introduction: Speaking of Tyler Cowen, I’m puzzled by this paragraph of his: Guns, like alcohol, have many legitimate uses, and they are enjoyed by many people in a responsible manner. In both cases, there is an elite which has absolutely no problems handling the institution in question, but still there is the question of whether the nation really can have such bifurcated social norms, namely one set of standards for the elite and another set for everybody else. I don’t know anything about guns so I’ll set that part aside. My bafflement is with the claim that “there is an elite which has absolutely no problem handling [alcohol].” Is he kidding? Unless Cowen is circularly defining “an elite” as the subset of elites who don’t have an alcohol problem, I don’t buy this claim. And I actually think it’s a serious problem, that various “elites” are so sure that they have “absolutely no problem” that they do dangerous, dangerous things. Consider the notorious incident when Dick Cheney shot a

6 0.71627915 527 andrew gelman stats-2011-01-20-Cars vs. trucks

7 0.715855 2341 andrew gelman stats-2014-05-20-plus ça change, plus c’est la même chose

8 0.71551573 287 andrew gelman stats-2010-09-20-Paul Rosenbaum on those annoying pre-treatment variables that are sort-of instruments and sort-of covariates

9 0.69438881 923 andrew gelman stats-2011-09-24-What is the normal range of values in a medical test?

10 0.69359869 549 andrew gelman stats-2011-02-01-“Roughly 90% of the increase in . . .” Hey, wait a minute!

11 0.6862151 720 andrew gelman stats-2011-05-20-Baby name wizards

12 0.68265373 2204 andrew gelman stats-2014-02-09-Keli Liu and Xiao-Li Meng on Simpson’s paradox

13 0.67963976 526 andrew gelman stats-2011-01-19-“If it saves the life of a single child…” and other nonsense

14 0.67675287 2030 andrew gelman stats-2013-09-19-Is coffee a killer? I don’t think the effect is as high as was estimated from the highest number that came out of a noisy study

15 0.67635548 1793 andrew gelman stats-2013-04-08-The Supreme Court meets the fallacy of the one-sided bet

16 0.67098951 489 andrew gelman stats-2010-12-28-Brow inflation

17 0.66940135 553 andrew gelman stats-2011-02-03-is it possible to “overstratify” when assigning a treatment in a randomized control trial?

18 0.66820437 1996 andrew gelman stats-2013-08-24-All inference is about generalizing from sample to population

19 0.66667002 86 andrew gelman stats-2010-06-14-“Too much data”?

20 0.66638774 1397 andrew gelman stats-2012-06-27-Stand Your Ground laws and homicides


similar blogs computed by lda model

lda for this blog:

topicId topicWeight

[(9, 0.017), (15, 0.016), (16, 0.049), (21, 0.023), (24, 0.131), (27, 0.225), (40, 0.013), (45, 0.03), (53, 0.023), (72, 0.029), (84, 0.022), (86, 0.026), (95, 0.016), (99, 0.236)]

similar blogs list:

simIndex simValue blogId blogTitle

1 0.9703362 802 andrew gelman stats-2011-07-13-Super Sam Fuld Needs Your Help (with Foul Ball stats)

Introduction: I was pleasantly surprised to have my recreational reading about baseball in the New Yorker interrupted by a digression on statistics. Sam Fuld of the Tampa Bay Rays, was the subjet of a Ben McGrath profile in the 4 July 2011 issue of the New Yorker , in an article titled Super Sam . After quoting a minor-league trainer who described Fuld as “a bit of a geek” (who isn’t these days?), McGrath gets into that lovely New Yorker detail: One could have pointed out the more persuasive and telling examples, such as the fact that in 2005, after his first pro season, with the Class-A Peoria Chiefs, Fuld applied for a fall internship with Stats, Inc., the research firm that supplies broadcasters with much of the data anad analysis that you hear in sports telecasts. After a description of what they had him doing, reviewing footage of games and cataloguing, he said “I thought, They have a stat for everything, but they don’t have any stats regarding foul balls.” Fuld’s

2 0.94139218 347 andrew gelman stats-2010-10-17-Getting arm and lme4 running on the Mac

Introduction: Our “arm” package in R requires Doug Bates’s “lme4″ which fits multilevel models. lme4 is currently having some problems on the Mac. But installation on the Mac can be done; it just takes a bit of work. I have two sets of instructions below. From Yu-Sung: If you have MAC OS DVD, you should install developer X code packages from it. Otherwise, install them from here . After this, do the following in R: install.packages(“lme4″, type = “source”) Then you will have lme4 in R and you can install arm without a problem. And, from David Ozonoff: I installed the lme4 package via the Package Installer but this didn’t work, of course. I then installed, via this link , gfortran which seemed to put the libraries in the right place (I had earlier installed via Fink the gcc42 compiler, so I’m not sure if this is required or not). I then ran, in R, this: install.packages(c(“Matrix”,”lme4″), repos=”http://R-Forge.R-project.org”) This does not appear to work since it wi

3 0.93633294 930 andrew gelman stats-2011-09-28-Wiley Wegman chutzpah update: Now you too can buy a selection of garbled Wikipedia articles, for a mere $1400-$2800 per year!

Introduction: Someone passed on to a message from his university library announcing that the journal “Wiley Interdisciplinary Reviews: Computational Statistics” is no longer free. Librarians have to decide what to do, so I thought I’d offer the following consumer guide: Wiley Computational Statistics journal Wikipedia Frequency 6 issues per year Continuously updated Includes articles from Wikipedia? Yes Yes Cites the Wikipedia sources it uses? No Yes Edited by recipient of ASA Founders Award? Yes No Articles are subject to rigorous review? No Yes Errors, when discovered, get fixed? No Yes Number of vertices in n-dimensional hypercube? 2n 2 n Easy access to Brady Bunch trivia? No Yes Cost (North America) $1400-$2800 $0 Cost (UK) £986-£1972 £0 Cost (Europe) €1213-€2426 €0 The choice seems pretty clear to me! It’s funny for the Wiley journal to start charging now

4 0.92240381 134 andrew gelman stats-2010-07-08-“What do you think about curved lines connecting discrete data-points?”

Introduction: John Keltz writes: What do you think about curved lines connecting discrete data-points? (For example, here .) The problem with the smoothed graph is it seems to imply that something is going on in between the discrete data points, which is false. However, the straight-line version isn’t representing actual events either- it is just helping the eye connect each point. So maybe the curved version is also just helping the eye connect each point, and looks better doing it. In my own work (value-added modeling of achievement test scores) I use straight lines, but I guess I am not too bothered when people use smoothing. I’d appreciate your input. Regular readers will be unsurprised that, yes, I have an opinion on this one, and that this opinion is connected to some more general ideas about statistical graphics. In general I’m not a fan of the curved lines. They’re ok, but I don’t really see the point. I can connect the dots just fine without the curves. The more general id

5 0.91023272 1472 andrew gelman stats-2012-08-28-Migrating from dot to underscore

Introduction: My C-oriented Stan collaborators have convinced me to use underscore (_) rather than dot (.) as much as possible in expressions in R. For example, I can name a variable n_years rather than n.years. This is fine. But I’m getting annoyed because I need to press the shift key every time I type the underscore. What do people do about this? I know that it’s easy enough to reassign keys (I could, for example, assign underscore to backslash, which I never use). I’m just wondering what C programmers actually do. Do they reassign the key or do they just get used to pressing Shift? P.S. In comments, Ben Hyde points to Google’s R style guide, which recommends that variable names use dots, not underscore or camel case, for variable names (for example, “avg.clicks” rather than “avg_Clicks” or “avgClicks”). I think they’re recommending this to be consistent with R coding conventions . I am switching to underscores in R variable names to be consistent with C. Otherwise we were run

6 0.90718192 465 andrew gelman stats-2010-12-13-$3M health care prediction challenge

7 0.90590864 343 andrew gelman stats-2010-10-15-?

same-blog 8 0.90477568 708 andrew gelman stats-2011-05-12-Improvement of 5 MPG: how many more auto deaths?

9 0.89560211 1490 andrew gelman stats-2012-09-09-I’m still wondering . . .

10 0.89555341 173 andrew gelman stats-2010-07-31-Editing and clutch hitting

11 0.87242723 1238 andrew gelman stats-2012-03-31-Dispute about ethics of data sharing

12 0.86944449 1113 andrew gelman stats-2012-01-11-Toshiro Kageyama on professionalism

13 0.86759353 652 andrew gelman stats-2011-04-07-Minor-league Stats Predict Major-league Performance, Sarah Palin, and Some Differences Between Baseball and Politics

14 0.86534411 1727 andrew gelman stats-2013-02-19-Beef with data

15 0.86202729 804 andrew gelman stats-2011-07-15-Static sensitivity analysis

16 0.86040294 1869 andrew gelman stats-2013-05-24-In which I side with Neyman over Fisher

17 0.85505557 1255 andrew gelman stats-2012-04-10-Amtrak sucks

18 0.85330999 341 andrew gelman stats-2010-10-14-Confusion about continuous probability densities

19 0.852669 1982 andrew gelman stats-2013-08-15-Blaming scientific fraud on the Kuhnians

20 0.84673387 66 andrew gelman stats-2010-06-03-How can news reporters avoid making mistakes when reporting on technical issues? Or, Data used to justify “Data Used to Justify Health Savings Can Be Shaky” can be shaky