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It turns out that ln(OR) has a variance of (1/a) + (1/b) + (1/c) + (1/d) It turns out that
{{{
V
ariance {ln(OR)} = (1/a) + (1/b) + (1/c) + (1/d)
}}}
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(ln OR)* ln(OR) ) / variance ( ln(OR) )           __ln (OR)^2__   variance ( ln(OR) )

Suppose we have a 2 x 2 table of frequencies

Col 1

Col 2

Row 1

a

b

Row 2

c

d

The Odds Ratio is defined as ad/bc

It turns out that

Variance {ln(OR)} = (1/a) + (1/b) + (1/c) + (1/d)

so it follows

ln (OR)^2 variance ( ln(OR) )

is chi-square on 1 degree of freedom.

If you have a zero cell then adding one half to all the frequencies enables an estimate of the odds ratio to be made.

Reference:

Everitt BS (1996) Making Sense of Statistics in Psychology A Second Level Course. OUP:Oxford.

None: FAQ/oddsr (last edited 2015-11-12 15:36:24 by PeterWatson)