{smcl}
{hline}
help for {hi:ggipower} {right:(SJ3-1: st0032)}
{hline}

{title:Syntax}

{p 8 14 2}{cmd:ggipower} {cmd:using} {it:filename}


{title:Input file}

{p 4 4 2}The input file must contain the following variables; there is no
limit on the number of observations. Each observation should contain
one set of parameters for which power, and sample sizes are required.

{col 5}Variable name{col 22}Details

{col 5}{cmd:pg1}{col 22}The population frequency of susceptibility genotype1
		     (permitted range 0 < {cmd:pg1} < 1)

{col 5}{cmd:pg2}{col 22}The population frequency of susceptibility genotype2
		     (permitted range 0 < {cmd:pg2} < 1)

{col 5}{cmd:inh1}{col 22}The mode of inheritance for susceptibility genotype1
		     (permitted values D or R, D=Dominant, R=Recessive)

{col 5}{cmd:inh2}{col 22}The mode of inheritance for susceptibility genotype2
		     (permitted values D or R, D=Dominant, R=Recessive)

{col 5}{cmd:rrg1}{col 22}The relative risk of disease in people exposed to
		     susceptibility genotype1 but not to susceptibility 
		     genotype2, compared with those people exposed to neither 
		     factor (permitted range 0 < {cmd:rrg1})

{col 5}{cmd:rrg2}{col 22}The relative risk of disease in people exposed to
		     susceptibility genotype2 but not to susceptibility
		     genotype1, compared with those people exposed to
		     neither factor (permitted range 0 < {cmd:rrg2})

{col 5}{cmd:rrint}{col 22}The interaction relative risk (such that the risk of
		     disease in people exposed to both risk factors
		     = {cmd:rrg1} * {cmd:rrg2} * {cmd:rrint}; permitted range 0 < {cmd:rrint})

{col 5}{cmd:pd}{col 22}The population disease frequency (permitted range 0 < pd < 1)

{col 5}{cmd:rrsibm}{col 22}The multiplication in risk of disease to sibs of cases 
                     due to unmeasured risk factors (permitted range 0 < {cmd:rrsibm})

{col 5}{cmd:alpha_1}{col 22}The required significance level for the interaction
		     test (permitted range 0 < {cmd:alpha_1} < 1) 

{col 5}{cmd:ssize}{col 22}The sample size (number of cases) for which power
		     calculations are required (number of cases equals
		     number of controls; permitted range {cmd:ssize} < 0)

{col 5}{cmd:power}{col 22}The power for which sample size calculations are required (%)
		     (permitted range {cmd:alpha_1} (x 100%) <= {cmd:power} < 100)


{title:Description}

{p 4 4 2}{cmd:ggipower} calculates power, sample size, and expected odds
ratios for departure from multiplicative joint effects (gene-gene interaction)
for the following study designs for a given set(s) of population parameters.

{col 5}{ul:Case}{col 28}{ul:Control}{col 51}{ul:Analysis}
{col 5}Population based{col 28}Population based{col 51}Unmatched
{col 5}Population based{col 28}Has affected sibling{col 51}Matched
{col 5}Population based{col 28}Has affected sibling{col 51}Unmatched
{col 5}Has affected sibling{col 28}Population based{col 51}Unmatched
{col 5}Has affected sibling{col 28}Has affected sibling{col 51}Unmatched


{title:Method}

{p 4 4 2}Power calculations for case-control studies is carried out using a
large sample likelihood-ratio approximation method.  The method assumes that
the distribution of the likelihood ratio is approximately a central chi2
distribution under the null hypothesis and a non-central chi2 distribution
under the alternative hypothesis. An approximation to the non-centrality
parameter can be calculated as the likelihood-ratio statistic from the
analysis of an exemplary dataset.  In addition, sample size can also be
calculated as it is directly proportional to the non-centrality parameter.
These methods are detailed in Brown et al. (1999) and the exemplary data
method, with examples, is outlined by Longmate (2001).


{title:Example}

{p 4 8 2}{cmd:. ggipower using ggi_parameters}


{title:Results}

{p 4 4 2}Results are saved in the dataset that conatins the original sets of
parameters.  When only one set of parameters is considered (initial
dataset only has one observation), results are also written in the
results window.

{p 4 4 2}Note:  There is often little difference in power between recessive
and dominant modes of inheritance for the same design.  This is
because susceptibility genotype frequency, rather than allele frequency
is specified.


{title:References}

{p 4 8 2}Brown, B. W., J. Lovato, and K. Russell. 1999. Asymptotic power
calculations: description, examples, computer code. {it:Statistics in}
{it:Medicine} 18: 3137-3151.

{p 4 8 2}Longmate, J. A. 2001. Complexity and power in case-control
association studies. {it:American Journal of Human Genetics} 68: 1229--1237.

{p 4 8 2}Self, S. G., R. H. Mauritsen, and J. Ohara. 1992. Power calculations
for likelihood ratio tests in generalized linear models. {it:Biometrics} 48:
31--39.


{title:Author}

        Catherine Saunders
        Genetic Epidemiology Divison
        Cancer Research UK Clinical Centre in Leeds
        Cancer Genetics Building
        St James's University Hospital
        Beckett Street
        Leeds, LS9 7TF
        UK
        Email: catherine.saunders@cancer.org.uk
