Can You Read My Mind?

Ghosts, ESP, telekinesis, astrology, and other assorted oddities are back in view. One of the "SyFy" channel's most popular series is a show about hunting apparitions. The movie Men Who…

Decision Calculator

This is just a rough prototype meant to be easy to play with inside a post. READ the help and guidebook! Suggestions for new canned examples welcome—the hard part is deriving historical performance data.

Rules

  1. Read the Decision Calculator guidebook below!
  2. Fill in the Performance Table, or click on one of the predefined examples.
  3. Fill in the Cost Comparison Table, or click on one of the predefined examples. You do not need to calculate the total: that’s done automatically.
  4. Click Calculate (or Reset between examples).
  5. Accuracy comparison rates are given between the Expert System and the Naive Guess.
  6. Cost results are found in the Expected Cost Comparison Table.
  7. Finally, a solution saying which option you should choose is given. Skill should be > 0!
  8. Important: Use this software at your own risk. No warranties of any kind are given or implied. Always consult a competent medical professional. .

Preset examples:

See Below HELP HELP HELP

 

1. Fill in the Historical Performance Table.

Present Absent
Test +
Test –

 

2. Fill in the Cost Comparison Table.

False Positive Costs Score False Negative Costs Score
Total: Total:

 

3. Click calculate (or Reset between examples).


 

4. The Optimal Naive Guess is to:

 

5. Accuracy (%) Comparison Table

Test Accuracy
Expert System
Naive Guess

 

6. Expected Costs Comparison Table

Test Expected False Positive Cost Expected False Negative Cost Total
Expert System
Naive Guess

 

7. The skill score is:


It should be greater than 0 for a skillful test!

 

8. The solution:

 

GUIDEBOOK

This article provides you with an introduction and a step-by-step guide of how to make good decisions in particular situations. These techniques are invaluable whether you are an individual or a business.

These results hold for all manner of examples—from deciding whether to have a PSA test or mammography, to get a vaccine, to finding a good stock broker or movie reviewer, to situations that require intense statistical modeling, to financial forecasts, to lie detector usefulness. Any situation that has a dichotomous outcome can use these techniques.

Many people opt for precautionary medical tests—frequently because a television commercial or magazine article scares them into it. What people don’t realize is that these tests have hidden costs. These costs are there because tests are never 100% accurate. So how can you tell when you should take a test?

When is worth it?

Under what circumstances is it best for you to receive a medical test? When you “Just want to be safe”? When you feel, “Why not? What’s the harm?”

In fact, these are not good reasons to undergo a medical test. You should only take a test if you know that it’s going to give you useful information. You want to know the test performs well and that it makes few mistakes, mistakes which could end up costing you emotionally, financially, and even physically.

Let’s illustrate this by taking the example of a healthy woman deciding whether or not to have a mammogram to screen for breast cancer. She read that all women over 40 should have this test “Just to be sure.” She has heard lots of horror stories about breast cancer. Testing almost seems like a duty. She doesn’t have any symptoms of breast cancer and is in good health. What should she do?

What can happen when she takes this (or any) medical test? One of four things:

  1. The test could correctly indicate that no cancer is present. This is good. The patient is assured.
  2. The test could correctly indicate that a true cancer is present. This is good in the sense that treatment options can be investigated immediately.
  3. The test could falsely indicate no cancer is present when it truly is. This error is called a false negative. This is bad because it could lead to false hope and could cause the patient to ignore symptoms because, “The test said I was fine.”
  4. The test could falsely indicate that cancer is present when it truly is not. This error is called a false positive. This is bad because it is distressing and could lead to unnecessary and even harmful treatment. The test itself, because it uses radiation, even increases the risk of true cancer because of the unnecessary exposure to x-rays.

This table shows all the possibilities in a test for the presence of absence of a thing (like breast cancer, prostate cancer, a lie, AIDS, and so on). For mammograms, “Present” means that cancer is actually there, and “Absent” means that no cancer is there. For a PSA test, “Present” means a prostate cancer is actually there, and “Absent” means that it is not. For a Movie Reviewer, “Present” means you liked a movie, and “Absent” means you did not.

Test Table
Present Absent
Test + Good: True Positive Bad: False Positive
Test – Bad: False Negative Good: True Negative

“Test +” says that the test indicates the test said the thing (cancer) is present. “Test -” says that the test indicates the absence of the thing. For the Movie Reviewer example, “Test +” means the reviewer recommended a film.

There are two cells in this graph that are labeled “Good,” meaning the test has performed correctly. The other two cells are labeled “Bad,” meaning the test has erred. Study this table to be sure you understand how to read it because it will be used throughout this article.

 

Error everywhere

The main point is this: all tests and all measurements have some error. There is no such thing as a perfect test or perfect measurement! Mistakes always happen. This is an immutable law of the universe. Some tests are better than others, and tables like this are necessary to understand how to rate how well a particular test performs.

 

Worst Science Fiction of All Time

Shoot to kill

July 1995

(I wrote this about six or seven years ago and had it posted to my website where I was a graduate student. I thought that it was lost forever, and I only managed to find it because several people archived it. Truly, nothing ever dies on the web. I thank these kind people. It’s a little worn by time and could stand some editing, but I’ll leave it as it originally was.)

Of course, with a title such as this, I had better be able to prove it. After all, hundreds of books are written in the genre each year. Thousands exist to pick from. And who’s to say another, more awful book than the one I’m about to describe, will appear and usurp the uncoveted title of Worst Science Fiction Novel Ever?

These caveats notwithstanding, however, my faith is strong. In fact, I am so absolutely sure that I’m correct in my choice, that I’m willing to risk the title “worst ever”. More on this later.

Many aficionados of science-fiction were weaned, not with short stories and books, but with TV. So it was with me. I started with the original Star Trek, others perhaps with Space 1999. The youth of today will have to make due with Deep Space Nine or Submarine Show (whatever the name is). These shows eased us into the classics, such as Foundation or Stranger in a Strange Land. If you were lucky. Unlucky neophytes wandered into a L. Ron Hubbard treatise or some pulp boiler, complete with front cover fanged monsters menacing beautiful large-breasted women.

Once these innocents, these hapless souls, enter the morass of disagreeable pages they are lost forever to science fiction. Nothing will ever convince them to reenter the fold. Perhaps it is our duty, then, to purge the field of ill-conceived and poorly executed works?

This supposes that one is able to judge the intrinsic merit of the text. Modern critics claim that it cannot be done. They may be right. But this is academic to our subject: what does watching TV have to do with learning to read science fiction? In this case, everything.

Walter Koening played the lovable and overly proud Russian navigator of the Starship Enterprise in the original Star Trek. He appeared in the Star Trek movies. He also wrote a book. Perhaps he felt an inward pull, a conviction that led him to convey a profound message. Or, like William Shatner, it may be that he was trying to cash in on the series and his personal success and make a buck. You be the judge.

Can having a mammogram kill you? How to make decisions under uncertainty.

The answer to the headline is, unfortunately, yes. The Sunday, 10 February 2008 New York Post reported this sad case of a woman at Mercy Medical Center in New York City. The young woman went to the hospital and had a mammogram, which came back positive, indicating the presence of breast cancer (she also had follow-up tests). Since other members of her family had experienced this awful disease, the young woman opted to have a double mastectomy and to have have implants inserted after this. All of which happened. She died a day after the surgery.

That’s not the worst part. It turns out she didn’t have cancer after all. Her test results had been mixed up with some other poor woman’s. So if she never had the mammogram in the first place, and made a radical decision based on incorrect test results, the woman would not have died. So, yes, having a mammogram can lead to your death. It is no good arguing that this is a rare event—adverse outcomes are not so rare, anyway—because all I was asking was can a mammogram kill you. One case is enough to prove that it can.

But aren’t medical tests, and mammograms in particular, supposed to be error free? What about prostate exams? Or screenings for other cancers? How do you make a decision whether to have these tests? How do you account for the possible error and potential harm resulting from this error?

I hope to answer all these questions in the following article, and to show you how deciding whether to take a medical exam is really no different than deciding which stock broker to pick. Some of what follows is difficult, and there is even some math. My friends, do not be dissuaded from reading. I have tried to make it as easy to follow as possible. These are important, serious decisions you will someday have to make: you should not treat them lightly.

Decision Calculator

You can download a (non-updated) pdf version of this paper here.

This article will provide you with an introduction and a step-by-step guide of how to make good decisions in particular situations. These techniques are invaluable whether you are an individual or a business.

The results that you’ll read about hold for all manner of examples—from lie detector usefulness, to finding a good stock broker or movie reviewer, to intense statistical modeling, to financial forecasts. But a particularly large area is medical testing, and it is these kinds of tests that I’ll use as examples.

Many people opt for precautionary medical tests—frequently because a television commercial or magazine article scares them into it. What people don’t realize is that these tests have hidden costs. These costs are there because tests are never 100% accurate. So how can you tell when you should take a test?

When is worth it?

Under what circumstances is it best for you to receive a medical test? When you “Just want to be safe”? When you feel, “Why not? What’s the harm?”

In fact, none of these are good reasons to undergo a medical test. You should only take a test if you know that it’s going to give accurate results. You want to know that it performs well, that is, that it makes few mistakes, mistakes which could end up costing you emotionally, financially, and even physically.

Let’s illustrate this by taking the example of a healthy woman deciding whether or not to have a mammogram to screen for breast cancer. She read in a magazine that all women over 40 should have this test “Just to be sure.” She has heard lots of stories about breast cancer lately. Testing almost seems like a duty. She doesn’t have any symptoms of breast cancer and is in good health. What should she do?

What can happen when she takes this (or any) medical test? One of four things: