The GAILSIMON option in the TABLES statement provides the Gail-Simon test for qualitative interaction for stratified
tables. For more information, see Gail and Simon (1985); Silvapulle (2001); Dmitrienko et al. (2005).
The Gail-Simon test is based on the risk differences in stratified
tables, where the risk difference is defined as the row 1 risk (proportion in column 1) minus the row 2 risk. For more information,
see the section Risks and Risk Differences. By default, PROC FREQ uses column 1 risks to compute the Gail-Simon test. If you specify the GAILSIMON(COLUMN=2) option,
PROC FREQ uses column 2 risks.
PROC FREQ computes the Gail-Simon test statistics as described in Gail and Simon (1985),
![\begin{eqnarray*} Q- & =& \sum _ h ~ (d_ h / s_ h)^2 ~ I(d_ h > 0 ) \\[0.10in] Q+ & =& \sum _ h ~ (d_ h / s_ h)^2 ~ I( d_ h < 0 ) \\[0.10in] Q & =& \min ~ (Q-, ~ Q+) \end{eqnarray*}](images/statug_freq0659.png)
where
is the risk difference in table h,
is the standard error of the risk difference, and
equals 1 if
and 0 otherwise. Similarly,
equals 1 if
and 0 otherwise. The q
tables (strata) are indexed by
.
The p-values for the Gail-Simon statistics are computed as
![\begin{eqnarray*} p(Q-) & =& \sum _ h ~ (1 - F_ h(Q-)) ~ B(h; n=q, p=0.5) \\[0.10in] p(Q+) & =& \sum _ h ~ (1 - F_ h(Q+)) ~ B(h; n=q, p=0.5) \\[0.10in] p(Q) & =& \sum _{h=1}^{q-1} ~ (1-F_ h(Q)) ~ B(h; n=(q-1), p=0.5) \end{eqnarray*}](images/statug_freq0666.png)
where
is the cumulative chi-square distribution function with h degrees of freedom and
is the binomial probability function with parameters n and p. The statistic Q tests the null hypothesis of no qualitative interaction. The statistic
tests the null hypothesis of positive risk differences. A small p-value for
indicates negative differences; similarly, a small p-value for
indicates positive risk differences.