*****************************************;
** SAS Scoring Code for PROC Logistic;
*****************************************;

length I_top10 $ 12;
label I_top10 = 'Into: top10' ;
label U_top10 = 'Unnormalized Into: top10' ;

label P_top101 = 'Predicted: top10=1' ;
label P_top100 = 'Predicted: top10=0' ;

drop _LMR_BAD;
_LMR_BAD=0;

* LABEL STATEMENTS TO DESCRIBE PREDICTORS;

label
  prob_days_100 ='100+ days of probation this or last year'
  adj_react     ='Adjustment reaction ICD-9 309 this or last year'
  chron_r       ='Diagnosed with chronic medical condition'
  cjic_arr      ='Arrested this or last year'
  cjic_arr_1    ='Number of arrests this year'
  cjic_arr_SEC_1='Jail security level=3 or 4 in current year'
  cjic_arr_bk_1 ='Booking code 849A  or 849B in current year'
  cjic_cite     ='Jail booking this or last year'
  cjic_days_1   ='Number of days in jail this year'
  cta_chr_hmls  ='HMIS chronic homeless flag'
  ems_1         ='Emergency Medical service record this year'
  ems_2         ='Emergency Medical service record last year'
  ems_gt2       ='Number of EMS encounters > 2 this or last year'
  icd_HC        ='Diagnosis of high-cost ICD-9 this or last year' 
  fs_gt1        ='More than 1 month in food stamp payment this or last year'
  heart         ='Diagnosis of heart disease ICD-9 402-429 this or last year'
  inp_c_1       ='Number of inpatient admissions this year'
  inp_days      ='Total # of inpatient days this & last year'
  inp_em        ='Inpatient via ER or from psych. fac. this or last year'
  mh_outp_d     ='Number of MH outpatient days this & last year'
  mh_outp_gt1   ='Mental Health outpatient visits > 1 last 2 years'
  mh_inp_c_1    ='Number of Mental Health inpatient admissions this year'
  organs_cnt    ='Count of ICD-9 (Organ Failures) 569-573, 576-578, 585-594, or 596 this & last year'
  oth_mort      ='other ill-defined/unknown causes of morbidity and mortality with ICD-9 799 this or last year'
  outp_1        ='VMC non-inpatient health system encounters this year'
  outp_c_1      ='Number of non-inpatient health system encounterss this year'
  outp_em_1     ='if outpatient ER, psych serv or amb.surgery - current year'
  outp_gt10_1   ='Non-inpatient health system encounterss this year > 10'
  schiz         ='Diagnosis of schizophrenia ICD-9 295 this or last year'
  ssa_1         ='Public assistance benefits in current year'
  Sub_Abuse     ='Substance abuse indicated by medical diagnosis or justice system charge'
  dads_cnt      ='Total # of DADS encounters this & last year'
  mh_inp_gt1_1  ='Mental Health inpatient admissions > 1 this or last year'
  neoplas_cnt   ='Count of diagnosis of neoplasm (ICD-9 140-239) this & last year'
;


*** Check interval variables for missing values;
if nmiss(prob_days_100,adj_react,chron_r,cjic_arr,cjic_arr_1,cjic_arr_SEC_1,
        cjic_arr_bk_1,cjic_cite,cjic_days_1,cta_chr_hmls,ems_1,ems_2,ems_gt2,
        icd_HC,fs_gt1,heart,inp_c_1,inp_days,inp_em,mh_outp_d,mh_outp_gt1,
        mh_inp_c_1,organs_cnt,oth_mort,outp_1,outp_c_1,outp_em_1,outp_gt10_1,
        schiz,ssa_1,Sub_Abuse,dads_cnt,mh_inp_gt1_1,neoplas_cnt) then do;
   _LMR_BAD=1;
   goto _SKIP_000;
end;

*** Generate design variables for sex;
drop _0_0 ;
length _st1 $ 1; drop _st1;
_st1 = left(trim(put (sex, $1.)));
_0_0= 0; 
if _st1 = 'F'  then do;
   _0_0 = 1;
end;
else if _st1 = 'M'  then do;
   _0_0= -1; 
end;
else do;
   _0_0 = .;
   _LMR_BAD=1;
   goto _SKIP_000;
end;

*** Generate design variables for age_gr;
drop _1_0 _1_1 _1_2 ;
length _st9 $ 9; drop _st9;
_st9 = left(trim(put (age_gr, $9.)));
_1_0= 0; 
_1_1= 0; 
_1_2= 0; 
if _st9 = '18-45'  then do;
   _1_0 = 1;
end;
else if _st9 = '46-65'  then do;
   _1_1 = 1;
end;
else if _st9 = '65+'  then do;
   _1_2 = 1;
end;
else if _st9 = 'lt-18'  then do;
   _1_0= -1; 
   _1_1= -1; 
   _1_2= -1; 
end;
else do;
   _1_0 = .;
   _1_1 = .;
   _1_2 = .;
   _LMR_BAD=1;
   goto _SKIP_000;
end;

*** Compute Linear Predictors;
drop _LP0;
_LP0 = 0;

*** Effect: age_gr;
_TEMP = 1;
_LP0 = _LP0 + (0.34059495520084) * _TEMP * _1_0;
_LP0 = _LP0 + (0.13968494844892) * _TEMP * _1_1;
_LP0 = _LP0 + (0.11614431391268) * _TEMP * _1_2;
*** Effect: sex;
_TEMP = 1;
_LP0 = _LP0 + (0.04411146937694) * _TEMP * _0_0;
_LP0 = _LP0 + (0.18484873388559) * prob_days_100;
_LP0 = _LP0 + (0.13609975612453) * adj_react;
_LP0 = _LP0 + (0.04895489134286) * chron_r;
_LP0 = _LP0 + (0.44197817895601) * cjic_arr;
_LP0 = _LP0 + (0.20954675975009) * cjic_arr_1;
_LP0 = _LP0 + (0.43934935918945) * cjic_arr_SEC_1;
_LP0 = _LP0 + (0.64042215407843) * cjic_arr_bk_1;
_LP0 = _LP0 + (0.1223452276631) * cjic_cite;
_LP0 = _LP0 + (0.00718644662783) * cjic_days_1;
_LP0 = _LP0 + (0.28192769237099) * cta_chr_hmls;
_LP0 = _LP0 + (0.14118749801468) * ems_1;
_LP0 = _LP0 + (0.23787129999965) * ems_2;
_LP0 = _LP0 + (0.26092985606152) * ems_gt2;
_LP0 = _LP0 + (0.08995915450506) * icd_HC;
_LP0 = _LP0 + (-0.36301570180134) * fs_gt1;
_LP0 = _LP0 + (0.43527492340347) * heart;
_LP0 = _LP0 + (0.13817180102488) * inp_c_1;
_LP0 = _LP0 + (0.01224402559881) * inp_days;
_LP0 = _LP0 + (0.39288101039943) * inp_em;
_LP0 = _LP0 + (0.01064304679293) * mh_outp_d;
_LP0 = _LP0 + (0.3695261529729) * mh_outp_gt1;
_LP0 = _LP0 + (0.00274229911225) * mh_inp_c_1;
_LP0 = _LP0 + (0.0791883039101) * organs_cnt;
_LP0 = _LP0 + (0.11354946277033) * oth_mort;
_LP0 = _LP0 + (0.20908987688703) * outp_1;
_LP0 = _LP0 + (0.02395296933262) * outp_c_1;
_LP0 = _LP0 + (0.02342904649225) * outp_em_1;
_LP0 = _LP0 + (0.23901190368433) * outp_gt10_1;
_LP0 = _LP0 + (0.37949788208024) * schiz;
_LP0 = _LP0 + (0.29913637684586) * ssa_1;
_LP0 = _LP0 + (0.47455302603067) * Sub_Abuse;
_LP0 = _LP0 + (0.00213648221448) * dads_cnt;
_LP0 = _LP0 + (0.39265637130671) * mh_inp_gt1_1;
_LP0 = _LP0 + (0.05005306320528) * neoplas_cnt;
*** Effect: mh_outp_gt10*age_gr;
_TEMP = mh_outp_gt10;
_LP0 = _LP0 + (-0.17700846963535) * _TEMP * _1_0;
_LP0 = _LP0 + (-0.22611857103319) * _TEMP * _1_1;
_LP0 = _LP0 + (-1.3812527522529) * _TEMP * _1_2;
_LP0 = _LP0 + (-0.84303105007885) * heart * mh_outp_gt1;
_LP0 = _LP0 + (-0.39378196335407) * inp_em * mh_inp_gt1_1;
_LP0 = _LP0 + (-0.0008838015018) * cjic_arr_1 * cjic_days_1;
_LP0 = _LP0 + (-0.39309066580315) * adj_react * cta_chr_hmls;
_LP0 = _LP0 + (0.23496365450024) * chron_r * ems_1;
_LP0 = _LP0 + (0.26671621212913) * chron_r * outp_em_1;
_LP0 = _LP0 + (-0.5514524972113) * cjic_arr_bk_1 * ems_1;
_LP0 = _LP0 + (-0.30705085640449) * prob_days_100 * cjic_arr_bk_1;

*** Predicted values;
drop _MAXP _IY _P0 _P1;
_TEMP = -3.81182860403159  + _LP0;
if (_TEMP < 0) then do;
   _TEMP = exp(_TEMP);
   _P0 = _TEMP / (1 + _TEMP);
end;
else _P0 = 1 / (1 + exp(-_TEMP));
_P1 = 1.0 - _P0;
P_top101 = _P0;
_MAXP = _P0;
_IY = 1;
P_top100 = _P1;
if (_P1 >  _MAXP + 1E-8) then do;
   _MAXP = _P1;
   _IY = 2;
end;
select( _IY );
   when (1) do;
      I_top10 = '1' ;
      U_top10 = 1;
   end;
   when (2) do;
      I_top10 = '0' ;
      U_top10 = 0;
   end;
   otherwise do;
      I_top10 = '';
      U_top10 = .;
   end;
end;
_SKIP_000:
if _LMR_BAD = 1 then do;
I_top10 = '';
U_top10 = .;
P_top101 = .;
P_top100 = .;
end;
drop _TEMP;