Comments on: Math

Math

semmi — Fri, 25 Apr 2003 13:42:54 -0800

Every Unhappy Family Has Its Own Bilinear Influence Function.

By: ZenMasterThis

ZenMasterThis — Fri, 25 Apr 2003 14:03:56 -0800

In longitudinal studies of couples who have passed through the Love Lab, Mr. Gottman and his colleagues have successfully predicted which ones will divorce with greater than 90-percent accuracy. If peer review supports this statement, that's simply amazing.

By: ookamaka

ookamaka — Fri, 25 Apr 2003 14:22:07 -0800

I would definitely be interested in reading more about this. Anyone happen to read the book by any chance? (I'm not even totally sure it's been released yet)

By: m@

m@ — Fri, 25 Apr 2003 14:23:38 -0800

...equations that described a dynamic system in which a snarky comment by one spouse would result in negative emotions in the partner, sometimes resulting in a downward spiral. They call it "Bilinear Influence Function", I call it Metafilter.

By: ZenMasterThis

ZenMasterThis — Fri, 25 Apr 2003 14:31:43 -0800

[insert snarky comment here]

By: yoga

yoga — Fri, 25 Apr 2003 14:36:34 -0800

Interesting link, semmi, thanks. It would be interesting to see some of that data translated into Tufte's lingo.

By: hurkle

hurkle — Fri, 25 Apr 2003 14:37:40 -0800

He has argued, for example, that a crucial predictor of divorce is a husband's inability or unwillingness to be influenced by his wife's suggestions and emotional expressions. So, in essence, if a husband doesn't do what his wife tells him to do, they'll end up getting divorced? Sounds like his research is dead spot on.

By: ZenMasterThis

ZenMasterThis — Fri, 25 Apr 2003 14:40:26 -0800

MarriageFilter. (you knew someone would say it sooner or later)

By: Skot

Skot — Fri, 25 Apr 2003 14:45:56 -0800

Slate had a piece on this a bit ago, if anyone's interested.

By: Outlawyr

Outlawyr — Fri, 25 Apr 2003 14:53:28 -0800

"So, in essence, if a husband doesn't do what his wife tells him to do, they'll end up getting divorced?" I could have told them that without the fancy calculus. As for the "Love Lab", show me the way

By: blue_beetle

blue_beetle — Fri, 25 Apr 2003 14:55:20 -0800

[insert negative emotions here]

By: PigAlien

PigAlien — Fri, 25 Apr 2003 15:07:27 -0800

Fuck you all, you slimy pigs! I'm divorcing the lot of you, contemptuous fools.

By: sonofsamiam

sonofsamiam — Fri, 25 Apr 2003 15:16:00 -0800

Every Unhappy Family Has Its Own Bilinear Influence Function. I guess Tolstoy was wrong. Huh.

By: jfuller

jfuller — Fri, 25 Apr 2003 15:43:02 -0800

Please professor, a mathematical model of this marriage.

By: dilettanti

dilettanti — Fri, 25 Apr 2003 16:06:46 -0800

"In longitudinal studies of couples who have passed through the Love Lab, Mr. Gottman and his colleagues have successfully predicted which ones will divorce with greater than 90-percent accuracy." If peer review supports this statement, that's simply amazing. My guess is that their model had an R^2 of 0.9, or that it "explained" 90% of the variation in the data, and not that there were any out-of-sample predictions actually being made. Sloppy journalism and technical terms never mix very well. "Statistics will just give you the bare facts. If you want to understand why a dynamic system behaves as it does, then you need to use nonlinear tools." This guy claims to understand catastrophe theory, but he thinks that statistics are all linear? Watch the leg, pal...another yank like that and it may just fall right off... I'm all for rating facial expressions on a scale from -4 to 4, and drawing inferences therefrom, but this article was painful on the brain.

By: ParisParamus

ParisParamus — Fri, 25 Apr 2003 17:10:08 -0800

"Unhappy Family" is the name of an entree at the Chinese Restaurant across from the Bronx County Courthouse.

By: ROU_Xenophobe

ROU_Xenophobe — Fri, 25 Apr 2003 17:30:23 -0800

Given that it's a nonlinear model, it probably won't have a R2. I think they meant that they assigned a probability-of-divorce (within the time frame) to every couple, and 90% of the time, couples that divorced had PODs over 0.5, and couples that didn't had PODs under 0.5. I wonder how they dealt with the censoring problems? Some couples that they met surely just aren't divorced *yet*, and there may be cases where the marriage ended with someone's death, etc etc. I'm not really impressed with a 90% success rate. We don't know what kind of success rate you get with a simple null model. I've run probits/gompits with a predictive success of about 85%, where the model was predicting that *everyone* would get a 1, and 85% did. Also, I bet it's really rilly easy to pick out half the divorces or so from other variables (age at marriage, or conversational correlates with that, etc).

By: SpaceCadet

SpaceCadet — Fri, 25 Apr 2003 19:02:34 -0800

He has argued, for example, that a crucial predictor of divorce is a husband's inability or unwillingness to be influenced by his wife's suggestions and emotional expressions. So, in essence, if a husband doesn't do what his wife tells him to do, they'll end up getting divorced? I can vouch for that - happened to me. Men: you are either blessed with luck and the woman of your dreams doesn't go all weird after you marry OR Men: obey your wives or face divorce

By: wobh

wobh — Fri, 25 Apr 2003 21:04:28 -0800

Personal finance teacher at college gave this advice: "Guys, marry a smart woman, and do everything she says." His rationale had a lot to do with divorces wreaking havoc on one's fincancial security, but it tied in with one's own happiness too. A good wife will make you work harder on things you would never do otherwise, but it'll pay off in all sorts of ways. It seemed like good advice to me and ever since then I've been keeping my eye open for a woman who's seems to be going somewhere where I would like to go too. Still looking.

By: dilettanti

dilettanti — Mon, 28 Apr 2003 10:59:05 -0800

Given that it's a nonlinear model, it probably won't have a R2. Actually, an R2 measure is frequently calculated for nonlinear binary dependent variable models (e.g., logit and probit models) [see, for instance, pp. 37-39 of Maddala's Limited-Dependent and Qualitative Variables in Econometrics]. The standard R2 is just the correlation between "predicted" (model) and observed values. My point, though, however obscured it might have been, was that the 90% was likely some sort of "goodness of fit" measure, and not the prediction accuracy of the model on some independent (later) sample. Of course, without reading the book, I can't be sure.