{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