{smcl}
{hline}
help for {hi:profhap}
{hline}


{title:Calculates profile likelihood confidence intervals for results using {hi:hapipf}}

{p 8 27}
{cmdab:profhap}
[{cmd:if}{it: exp}] 
 , {cmdab:or}{cmd:(}{it:string}{cmd:)}
 {cmdab::ipf}{cmd:(}{it:string}{cmd:)}
 [{cmdab:}
 {cmdab:by}{cmd:(}{it:string}{cmd:)}
 {cmdab:acc}{cmd:(}{it:real}{cmd:)}
 {cmdab:lev:el}{cmd:(}{it:real}{cmd:)}
 {cmdab:hapacc}{cmd:(}{it:real}{cmd:)}
 {cmdab:savegraph}
] 

{p}

{title:Description}

{p 0 0}
This function calculates the confidence intervals for the odds ratios estimated
by the command {cmd:hapipf}. It uses the profile likelihood by estimating the log-likelihood
of a series of constrained log-linear models.

{p 0 0}
This command will only estimate the confidence interval for a single OR and can be used to estimate
the odds ratio in a stratified analysis.

{p}

{title:Options}

{p 0 4}
{cmdab:or}{cmd:(}{it:string}{cmd:)}
first the case control variable is specified then two haplotypes/alleles. The first
    haplotype/allele indicates the unexposed group and the other haplotype/allele is the exposed group e.g. {hi:or(D 1 2)} specifies that the case control variable is D and that the allele 1 represents the unexposed group and allele 2 the exposed. 

{p 0 4}
{cmdab::ipf}{cmd:(}{it:string}{cmd:)}
specifies the log-linear model in the constrained table.
  It requires special syntax of
   the form {hi:l1*l2+l3}. {hi:l1*l2} allows all the interactions
   between the first two loci and locus 3 is independent of them.
   This syntax is used in most books on Log-linear modelling, "-" terms and brackets are not allowed.

{p 0 4}
{cmdab:by}{cmd:(}{it:string}{cmd:)} 
specifies a stratifying variable.

{p 0 4}
{cmdab:acc}{cmd:(}{it:real}{cmd:)} specifies the accuracy of the estimated upper and lower bounds of the confidence interval.

{p 0 4}
{cmdab:lev:el}{cmd:(}{it:real}{cmd:)}  specifies the significance level of the confidence interval.

{p 0 4}
{cmdab:hapacc}{cmd:(}{it:real}{cmd:)} specifies the convergence threshold of both {inp:hapipf} and {inp:ipf}.

{p 0 4}
{cmdab:savegraph} specifies that the profile graph is saved to file {hi:profile.gph}

{p}

{title:Examples}

{p 0}
{hi:Single-point Odds Ratio (OR)}

{p 0}
The simplest example is where there is one genetic marker (with alleles 1 and 2) and a binary outcome {hi: D}.
The model specified in the {hi:ipf()} option must not include the interaction of interest i.e. whether marker {hi:l1} is associated with {hi:D} because this term is fitting using constraint files. Only one OR confidence interval is calculated using profile likelihood and "reference" and "exposed" alleles are specified as {hi: 1} and {hi:2}, respectively, in the {hi: or()} option.

{inp:. profhap a1 a2, ipf(l1+D) or(D 1 2)}

{p 0}
{hi:Stratified Estimation of an OR}

{p 0}
The parameter of interest is the OR comparing haplotype 2.2 to haplotype 1.1. 
Where the OR is now the pooled estimate over each level of the categorical variable {hi:S}. 
Again the haplotype-outcome interaction {hi:l1*l2*D} is not
included in the {hi:ipf()} model.

{inp:. profhap a1 a2 b1 b2, ipf(S*D+l1*l2*S) or(D 1.1 2.2) by(S) acc(0.0001)}

{p 0}
This can be extended to 3 markers (comparing haplotype 2.2.2 to haplotype 1.1.1). 

{inp:. profhap a1 a2 b1 b2 c1 c2, ipf(S*D+l1*l2*l3*S) or(D 1.1.1 2.2.2) by(S) acc(0.0001)}

{title:Author}

{p}
Adrian Mander, Glaxo Smithkline, Harlow, UK.

Email {browse "mailto:adrian.p.mander@gsk.com":adrian.p.mander@gsk.com}

{title:Also see}

Related commands

HELP FILES 	Installation status	SSC installation links		Description

{help hapipf}		(required)		({stata ssc install hapipf})  	Haplotype Frequency estimation
{help qhapipf}		(if installed)		({stata ssc install qhapipf})   Quantitative Trait
{help swblock}		(if installed)		({stata ssc install swblock})   Haplotype blocks
{help hapblock}		(if installed)		({stata ssc install hapblock})  Haplotype blocks
{help gipf}		(if installed)    	({stata ssc install gipf})	Graphical Log-linear Representation