|
Size: 562
Comment:
|
Size: 914
Comment:
|
| Deletions are marked like this. | Additions are marked like this. |
| Line 3: | Line 3: |
| ||<tablewidth="42%">rows||columns|| ||a||b|| ||c||d|| |
||||||<33% style="TEXT-ALIGN: center"> ||<33% style="TEXT-ALIGN: center"> '''Col 1''' ||<34% style="TEXT-ALIGN: center"> '''Col 2'''|| ||||||<33% style="VERTICAL-ALIGN: top"> '''Row 1''' ||<33% style="VERTICAL-ALIGN: top"> a ||<34% style="VERTICAL-ALIGN: top"> b || ||||||<33% style="VERTICAL-ALIGN: top"> '''Row 2''' ||<33% style="VERTICAL-ALIGN: top"> c ||<34% style="VERTICAL-ALIGN: top"> d || |
| Line 13: | Line 9: |
| It turns out that ln(OR) has a variance of (1/a) + (1/b) + (1/c) + (1/d) | It turns out that {{{ Variance{ln(OR)} = (1/a) + (1/b) + (1/c) + (1/d) }}} |
| Line 17: | Line 16: |
| (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.
