Title



     mrmvegger -- Multivariable MR-Egger regression (MVMR-Egger)



Syntax



        mrmvegger varname_gd varname_gp1 [varname_gp2 ...] [aweight] [if] [in] [, options]



    options               Description
    ----------------------------------------------------------------------------------------------
      orient(#)           orient the data wrt to the phenotype which corresponds with the #th
                            genotype-phenotype (SNP-exposure) association variable in the varlist
                            (default is 1)
      level(#)            set confidence level; default is level(95)
      tdist               use t-distribution for Wald test and CI limits



Description



    mrmvegger performs multivariable MR-Egger regression.  For further information see Rees et al.
    (2017).



    By default multiplicative random effect standard errors are reported.  However, if the
    residual variance is found to be less than 1 the model is refitted with this constrained to 1.



    varname_gd variable containing the genotype-disease (SNP-outcome) association estimates.



    varname_gp# variable containing the #th genotype-phenotype (SNP-exposure) association
    estimates.



    For the analytic weights you need to specify the inverse of the genotype-disease (SNP-outcome)
    standard errors squared, i.e. aw=1/(gdse^2).



Options



    orient(#) specifies which phenotype to orient the data to. The default is 1, i.e. the
        phenotype in the first genotype-phenotype (SNP-exposure) variable in the varlist.



    level(#); see [R] estimation options.



    tdist specifies using the t-distribution, instead of the normal distribution, for calculating
        the Wald test and the confidence interval limits.



Examples



    Using the data provided by Do et al. (2013).



    Setup
        . use https://raw.github.com/remlapmot/mrrobust/master/dodata, clear



    Select observations (p-value with LDL-C < 10^-8)
        . gen byte sel1 = (ldlcp2 < 1e-8)



    MVMR-Egger regression
        . mrmvegger chdbeta ldlcbeta hdlcbeta tgbeta [aw=1/(chdse^2)] if sel1==1



    Orient wrt HDL-C instead of LDL-C
        . mrmvegger chdbeta ldlcbeta hdlcbeta tgbeta [aw=1/(chdse^2)] if sel1==1, orient(2)



    Orient wrt triglycerides instead of LDL-C
        . mrmvegger chdbeta ldlcbeta hdlcbeta tgbeta [aw=1/(chdse^2)] if sel1==1, orient(3)



Stored results



    mrmvegger stores the following in e():



    Scalars        
      e(df_r)             residual degrees of freedom (with tdist option)
      e(N)                Number of genotypes
      e(Np)               Number of phenotypes
      e(phi)              Scale parameter (root mean squared error)



    Macros         
      e(cmd)              Command name
      e(cmdline)          Command issued
      e(orientvar)        Genotype-phenotype (SNP-exposure) association variable the model is
                            oriented wrt



    Matrices       
      e(b)                coefficient vector
      e(V)                variance-covariance matrix of the estimates



    mrmvegger stores the following in r():



    Matrices       
      r(table)            Coefficient table with rownames: b, se, z, pvalue, ll, ul, df, crit,
                            eform



References



    Do et al., 2013. Common variants associated with plasma triglycerides and risk for coronary
        artery disease. Nature Genetics. 45, 1345-1352.  DOI



    Rees J, Wood A, Burgess S. Extending the MR-Egger method for multivariable Mendelian
        randomization to correct for both measured and unmeasured pleiotropy.  Statistics in
        Medicine, 2017, 36, 29, 4705-4718.  DOI



Author



INCLUDE help mrrobust-author