Title



     ivlsmm -- (double) Logistic structural mean model



Syntax



        ivlsmm depvar [varlist1] (varlist2 = varlist_iv) [if] [in] [weight] [, options]



    varlist1 is the list of exogenous variables.



    varlist2 is the list of endogenous variables.



    varlist_iv is the list of exogenous variables used with varlist1 as instruments for varlist2.



    options               Description
    ----------------------------------------------------------------------------------------------
      amxb(lc:varlist)    The linear predictor for the association model, by default the
                            instruments and exogenous variables are included
      from(matrix)        initial values for the parameter estimates for both association and
                            causal models
      level(#)            set confidence level; default is level(95)
      gmm_options         Options passed to gmm



Description



    ivlsmm implements the double logistic structural mean model (LSMM) of Vansteelandt and
    Goetghebeur (2003) which is a generalisation of the LSMM of Robins (1989).



    ivlsmm is implemented using a call to gmm.



Options



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



Examples



    Read in binary outcome data; y outcome, x exposure, w covariate, z* instrumental variables
    (genotypes).



        . use https://raw.github.com/remlapmot/ivonesamplemr/main/data/ivbinoutdata, clear



    Fit the model with a single instrumental variable.



        . ivlsmm y (x = z1)



    Fit the model with multiple instruments.



        . ivlsmm y (x = z1 z2 z3)



    Fit the model with multiple exposures, and instruments, and adjusting for w.



        . ivlsmm y w (x1 x2 = z1 z2 z3)



Stored results



    To see the results ivlsmm stores in e() issue ereturn list after running the command.



    ivlsmm stores the following in r():



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



References



    Clarke PS, Palmer TM, Windmeijer F.  Estimating structural mean models with multiple
        instrumental variables using the Generalised Method of Moments.  Statistical Science,
        2015, 30, 1, 96-117.  DOI



    Palmer TM, Sterne JAC, Harbord RM, Lawlor DA, Sheehan NA, Meng S, Granell R, Davey Smith G,
        Didelez V.  Instrumental variable estimation of causal risk ratios and causal odds ratios
        in Mendelian randomization analyses.  American Journal of Epidemiology, 2011, 173, 12,
        1392-1403.  DOI



    Robins JM.  The analysis of randomised and nonrandomised AIDS treatment trials using a new
        approach to causal inference in longitudinal studies.  In Health Service Research
        Methodology: A Focus on AIDS (L. Sechrest, H. Freeman and A. Mulley, eds.).  1989.
        113–159. US Public Health Service, National Center for Health Services Research,
        Washington, DC.



    Vansteelandt S, Goetghebeur E.  Causal inference with generalized structural mean models.
        Journal of the Royal Statistical Society (Series B).  2003, 65, 4, 817-835.  DOI



Author



INCLUDE help ivonesamplemr-author