1.4. Unit weight models

Among the successful improper linear models, there is one that tends to be

a bit more reliable and easier to use than the others. Unit weight models

assign equal weights to (standardized) predictor cues, so that each cue has

an equal ‘‘say’’ in the final prediction. Our favorite example of a unit weight

model is what we might call the ‘‘F minus F Rule.’’ Howard and Dawes

(1976) found a very reliable, low-cost reasoning strategy for predicting

marital happiness. Take the couple’s rate of lovemaking and subtract from

it their rate of fighting. If the couple makes love more often than they

fight, then they’ll probably report being happy; if they fight more often

than they make love, then they’ll probably report being unhappy. Howard

and Dawes tested their hypothesis on data compiled by Alexander (1971)

in which 42 couples ‘‘monitored when they made love, when they had

fights, when they had social engagements (e.g., with in-laws), and so on.

These subjects also made subjective ratings about how happy they were

in their marital or coupled situation’’ (Dawes 1982, 393). The results were

interesting: ‘‘In the thirty happily married couples (as reported by the

monitoring partner) only two argued more often than they had intercourse.

All twelve of the unhappily married couples argued more often’’

(478). The reliability of the F minus F Rule was confirmed independently

by Edwards and Edwards (1977) and Thornton (1977).

The F minus F Rule exhibits three advantages of unit weight SPRs.

First, it requires attention to only a slim portion of the available evidence.

We can ignore the endless variety of psychological and behavioral quirks

and incompatibilities that married people can exhibit and instead focus on

two relatively simple, straightforward (though personal) cues. Second, the

30 Epistemology and the Psychology of Human Judgment

F minus F Rule is very simple to use. There is no need to try to weigh

different complex cues against each other. For example, there is no need to

guess whether the (presumably) negative sign that the partners have different

approaches to finances is outweighed by the (presumably) positive

sign that both had happily married parents. Third, the F minus F Rule is

known to be quite reliable.

Given the success of unit weight models, Paul Meehl has said, ‘‘In most

practical situations an unweighted sum of a small number of ‘big’ variables

will, on the average, be preferable to regression equations’’ (quoted in

Dawes and Corrigan 1974, 105). Dawes and Corrigan succinctly state the

cash value of these results: To be more reliable than expert humans in the

social arena, ‘‘the whole trick is to know what variables to look at and then

know how to add’’ (1974, 105).

Among the successful improper linear models, there is one that tends to be

a bit more reliable and easier to use than the others. Unit weight models

assign equal weights to (standardized) predictor cues, so that each cue has

an equal ‘‘say’’ in the final prediction. Our favorite example of a unit weight

model is what we might call the ‘‘F minus F Rule.’’ Howard and Dawes

(1976) found a very reliable, low-cost reasoning strategy for predicting

marital happiness. Take the couple’s rate of lovemaking and subtract from

it their rate of fighting. If the couple makes love more often than they

fight, then they’ll probably report being happy; if they fight more often

than they make love, then they’ll probably report being unhappy. Howard

and Dawes tested their hypothesis on data compiled by Alexander (1971)

in which 42 couples ‘‘monitored when they made love, when they had

fights, when they had social engagements (e.g., with in-laws), and so on.

These subjects also made subjective ratings about how happy they were

in their marital or coupled situation’’ (Dawes 1982, 393). The results were

interesting: ‘‘In the thirty happily married couples (as reported by the

monitoring partner) only two argued more often than they had intercourse.

All twelve of the unhappily married couples argued more often’’

(478). The reliability of the F minus F Rule was confirmed independently

by Edwards and Edwards (1977) and Thornton (1977).

The F minus F Rule exhibits three advantages of unit weight SPRs.

First, it requires attention to only a slim portion of the available evidence.

We can ignore the endless variety of psychological and behavioral quirks

and incompatibilities that married people can exhibit and instead focus on

two relatively simple, straightforward (though personal) cues. Second, the

30 Epistemology and the Psychology of Human Judgment

F minus F Rule is very simple to use. There is no need to try to weigh

different complex cues against each other. For example, there is no need to

guess whether the (presumably) negative sign that the partners have different

approaches to finances is outweighed by the (presumably) positive

sign that both had happily married parents. Third, the F minus F Rule is

known to be quite reliable.

Given the success of unit weight models, Paul Meehl has said, ‘‘In most

practical situations an unweighted sum of a small number of ‘big’ variables

will, on the average, be preferable to regression equations’’ (quoted in

Dawes and Corrigan 1974, 105). Dawes and Corrigan succinctly state the

cash value of these results: To be more reliable than expert humans in the

social arena, ‘‘the whole trick is to know what variables to look at and then

know how to add’’ (1974, 105).