/*
  midas_dlg_metareg.dlg — Meta-regression dialog
  Version 2.0  31mar2026
*/

VERSION 16.0
POSITION . . 500 720

DIALOG main, title("MIDAS: Meta-Regression") tabtitle("Main")
BEGIN
    TEXT     tx_vars    10   10  200  ., label("Variables: tp fp fn tn")
    VARLIST  vl_vars    10   30  470  ., label("Variables")
    
    TEXT     tx_id      10   60  100  ., label("Study ID:")
    VARNAME  vn_id     110   60  200  ., label("ID variable")
    
    TEXT     tx_cov     10   90  100  ., label("Covariates:")
    VARLIST  vl_cov    110   90  370  ., label("Covariate(s)") numeric
    
    GROUPBOX gb_target  10  130  250  90, label("Covariate Target")
    RADIO    rb_both    20  150  200  ., first label("Both Se and Sp") default(1)
    RADIO    rb_sen     20  170  200  ., label("Sensitivity only") option(senonly)
    RADIO    rb_spe     20  190  200  ., last  label("Specificity only") option(speonly)
    
    CHECKBOX ck_nogr   280  150  200  ., label("Suppress graph") option(nograph)
    CHECKBOX ck_nois   280  175  200  ., label("Show iterations") option(noisily)
    
    TEXT     tx_save   10   235  100  ., label("Save LaTeX:")
    FILE     fl_save  110   235  370  ., label("Browse...") filter("TeX files|*.tex") save
    
    TEXT     tx_level  10   270  100  ., label("CI Level (%):")
    SPINNER  sp_level 110   270   60  ., min(80) max(99) default(95)
END

DIALOG sroc, tabtitle("Binary SROC")
BEGIN
    TEXT     tx_info    10   10  470  40, ///
        label("For binary covariates, the SROC plot fits separate models per subgroup. Choose the subgroup estimator below.")
    
    TEXT     tx_subest  10   55  150  ., label("Subgroup estimator:")
    COMBOBOX cb_subest 160   55  150  ., dropdownlist         ///
        contents(subest_list) value(subest_val) default(mle)
    
    GROUPBOX gb_inla   10   90  470  60, label("INLA (R-INLA)")
    TEXT     tx_rpath   20  110  120  ., label("Rscript path:")
    FILE     fl_rpath  140  110  330  ., label("Browse...") filter("Executables|*.exe")
    
    GROUPBOX gb_hmc    10  160  470  260, label("HMC (CmdStan)")
    TEXT     tx_stan    20  180  120  ., label("CmdStan dir:")
    FILE     fl_stan   140  180  330  ., label("Browse...") directory
    
    TEXT     tx_model   20  210  120  ., label("Model file:")
    EDIT     ed_model  140  210  200  ., default("midas.stan")
    
    TEXT     tx_output  20  240  120  ., label("Output prefix:")
    EDIT     ed_output 140  240  200  ., default("metareg")
    
    TEXT     tx_subcov  20  270  120  ., label("Covariance:")
    COMBOBOX cb_subcov 140  270  150  ., dropdownlist         ///
        contents(cov_list) value(cov_val) default(cholesky)
    
    TEXT     tx_chains  20  305  60   ., label("Chains:")
    SPINNER  sp_chains  80  305  60   ., min(1) max(16) default(4)
    TEXT     tx_warmup 160  305  60   ., label("Warmup:")
    SPINNER  sp_warmup 220  305  80   ., min(100) max(50000) default(1000)
    
    TEXT     tx_iter    20  335  60   ., label("Iter:")
    SPINNER  sp_iter    80  335  80   ., min(1000) max(100000) default(10000)
    TEXT     tx_thin   160  335  60   ., label("Thin:")
    SPINNER  sp_thin   220  335  60   ., min(1) max(100) default(10)
    
    TEXT     tx_seed    20  365  60   ., label("Seed:")
    SPINNER  sp_seed    80  365  80   ., min(1) max(999999) default(12345)
END

LIST subest_list
BEGIN
    MLE (meglm)
    INLA (R-INLA)
    HMC (CmdStan)
END

LIST subest_val
BEGIN
    mle
    inla
    hmc
END

LIST cov_list
BEGIN
    Cholesky
    Inverse-Wishart
    Spherical
    Huang-Wand
END

LIST cov_val
BEGIN
    cholesky
    iwishart
    spherical
    huangwand
END

OK ok1, label("OK")
CANCEL can1, label("Cancel")
SUBMIT sub1, label("Submit")

PROGRAM command
BEGIN
    put "midas metareg "
    varlist main.vl_vars
    put ", id(" main.vn_id ")"
    put " covariates(" main.vl_cov ")"
    
    optionarg main.rb_sen
    optionarg main.rb_spe
    optionarg main.ck_nogr
    optionarg main.ck_nois
    
    if main.sp_level.isneq(95) {
        put " level(" main.sp_level ")"
    }
    
    if main.fl_save.isneq("") {
        put `" savetable(""'
        put main.fl_save
        put `"")"'
    }
    
    if sroc.cb_subest.isneq("mle") {
        put " subestimator(" sroc.cb_subest ")"
    }
    
    if sroc.fl_rpath.isneq("") {
        put `" rpath(""'
        put sroc.fl_rpath
        put `"")"'
    }
    
    if sroc.fl_stan.isneq("") {
        put `" standir(""'
        put sroc.fl_stan
        put `"")"'
    }
    
    if sroc.ed_model.isneq("") & sroc.cb_subest.iseq("hmc") {
        put `" modelfile(""'
        put sroc.ed_model
        put `"")"'
    }
    
    if sroc.ed_output.isneq("") & sroc.cb_subest.iseq("hmc") {
        put `" outputfile(""'
        put sroc.ed_output
        put `"")"'
    }
    
    if sroc.cb_subest.iseq("hmc") {
        put " chains(" sroc.sp_chains ")"
        put " warmup(" sroc.sp_warmup ")"
        put " iter(" sroc.sp_iter ")"
        put " thin(" sroc.sp_thin ")"
        put " seed(" sroc.sp_seed ")"
        if sroc.cb_subcov.isneq("") {
            put " subcovariance(" sroc.cb_subcov ")"
        }
    }
    
    stata
END