/* LOS_ENTRY_YR_AGE_0-17yr.sas */
/* Purpose: Use Event history analysis to compute median length of stay
 * by AGE group [CW spell=1 only].
 * Original Programmer: Daniel Webster
 * REVSION HISTORY:
 * 9-14-2009-created to provide yearly cohort los estimates by age
 * 4-12-2010-began running data for 2007 entry cohort
 * 10-14-2010-divided infant category into neonates (<1mo) and others (1-11mo)
 * 4-20-2011-added 2008 entry cohorts
 * 2-10-2011-added 2009 entry cohorts
 * 5-22-2012-modified filename to specify 0-17yr old entries to 
 * 2-19-2012-added 2010 entry cohorts
 * 2-14-2014-added 2011 entry cohorts
 * accommodate new AB12 programs & files that will reference 0-20yr old entries
 * Project: CWS/CMS Performance Indicators
 */

options nodate nocenter nonumber ls=90;

data tmp0;
set dwh.ucb_fc_afcars; 

if A34_SPELL = 1 then SP = 1;
else if A34_SPELL ge 2 then SP = 2;

run;

data tmp1;
set tmp0;

where SP = 1;

timein=.;
if pe_e_dt = . then do;
timein=&CUTOFF -pe_s_dt;
end;
if pe_e_dt ne . then do;
timein=pe_e_dt-pe_s_dt;
end;
run;

/*restrict to children in care 8+ days*/
data tmp1;
set tmp1;
where timein ge 8;
run;

/*restrict to one record per child*/
data temp1a;
set tmp1;
by FKCLIENT_T;
if last.FKCLIENT_T;

/* lagdays */
lagdays = .;
if (PE_E_DT = .) then do;
  lagdays = int(&CUTOFF-PE_S_DT);
end;
if (PE_E_DT ge '01jan88'd) then do;
  lagdays = int(PE_E_DT-PE_S_DT);
end;

/* in */
in = .;
if (PE_E_DT = .) then in = 1;
else if (PE_E_DT ne . and PE_E_DT ge '01jan88'd) then in = 0;

first_yr=year(pe_s_dt);

/*updated age calculation*/
age = floor((intck('month',birth_dt,pe_s_dt)-(day(pe_s_dt) lt day(birth_dt)))/12);  
age2 = (pe_s_dt-birth_dt);  

race=ethnic*1;

GENDER=.;
if GENDER_CD='F' then GENDER=1; 
else if GENDER_CD='M' then GENDER=2;
else if GENDER_CD='I' then GENDER=3;

run;

%macro REPORTYEAR(START,STOP) ;
%do ENTYR = &START %to &STOP ;

/*restrict entry cohort years and entries age 0-17 years, ethnic and gender not missing*/
data temp3;
set temp1a;

where (FIRST_YR = &ENTYR)  and age between 0 and 17 AND race in (1,2,3,4,5) and GENDER ne .;

AGEGRP=.;
if age in (0) then AGEGRP=1; else
if age in (1,2) then AGEGRP=2; else
if age in (3,4,5) then AGEGRP=3; else
if age in (6,7,8,9,10) then AGEGRP=4; else
if age in (11,12,13,14,15) then AGEGRP=5; else
if age in (16,17) then AGEGRP=6;

COUNTY=rsp_cnty*1;

AGEGRP2=AGEGRP;
if agegrp in (1) then do;
if age2 lt 29 then AGEGRP2=1; else
AGEGRP2=1.5;
end;

run;


/*remove missing placement type*/
data temp3a;
set temp3;

if AGEGRP2=. then AGEGRP2=99;

if COUNTY in (59,98,99,.) then COUNTY=98;

run;

/* state */
proc sort data = temp3a;
by AGEGRP2;
run;

/*quartiles*/
ods output quartiles=mlos1;
proc lifetest data=temp3a method = km intervals = 1.1 to 85.1 by 85;
time lagdays*in(1);
by AGEGRP2;
run;

data mlos1;
set mlos1;
where AGEGRP2 ne .; 
run;

ods output quartiles=mlos1a;
proc lifetest data=temp3a method = km intervals = 1.1 to 85.1 by 85;
time lagdays*in(1);
run;

data mlos1a;
set mlos1a;
AGEGRP2=100;
run;

data mlosfac1;
set mlos1 mlos1a ;
if percent=50 then do;
pe2=estimate;
end;
if percent=25 then do;
pe1=estimate;
end;
if percent=75 then do;
pe3=estimate;
end;

drop stratum; 
drop estimate;
drop percent;
drop lowerlimit;
drop upperlimit;
run;


proc sort data=temp3a;
by county AGEGRP2;
run;

ods output quartiles=mlos2;
proc lifetest data=temp3a method = km intervals = 1.1 to 85.1 by 85;
time lagdays*in(1);
by county AGEGRP2;
run;

data mlos2;
set mlos2;
where AGEGRP2 ne 7; /*drop missing AGEGRP group*/
drop stratum;
run;

ods output quartiles=mlos2a;
proc lifetest data=temp3a method = km intervals = 1.1 to 85.1 by 85;
time lagdays*in(1);
by county;
run;

data mlos2a;
set mlos2a;
AGEGRP2=100;
run;

data mlosfac2;
set mlos2 mlos2a;
if percent=50 then do;
pe2=estimate;
end;
if percent=25 then do;
pe1=estimate;
end;
if percent=75 then do;
pe3=estimate;
end;

drop stratum;
drop estimate;
drop percent;
drop lowerlimit;
drop upperlimit;

cal=1;
run;

data mlosfac3;
set mlosfac1 
mlosfac2;
if county=. Then county=0;
else if county in (59,98,99,.) then county = 98;
run;

/*change values of missing point estimates such that proc format [sfmt] will
assign a "**" while misstext in tabulate will assign a blank -- to differentiate
between a non-calculable estimate and one where there is no underlying data*/

data mlos&ENTYR;
set mlosfac3;
if pe1=. then pe1=0;
if pe2=. then pe2=0;
if pe3=. then pe3=0;

PERIOD_DT = &ENTYR;
TYPE = 1;  /* AGE 0-17 */
GROUP = 2; /* AGE */

rename
AGEGRP2 = AGE17A
GENDER = GENDER_CD
race = ETHNIC;

run;

proc append base = local.mlos_AGE17 data = mlos&ENTYR;

run;


%end;
%mend REPORTYEAR ;
%REPORTYEAR(2004,2023);
/* LOS_ENTRY_YR_AGE_0-20yr.sas */
/* Purpose: Use Event history analysis to compute median length of stay
 * by AGE group [CW spell=1 only].
 * Original Programmer: Daniel Webster
 * REVSION HISTORY:
 * 9-14-2009-created to provide yearly cohort los estimates by age
 * 4-12-2010-began running data for 2007 entry cohort
 * 10-14-2010-divided infant category into neonates (<1mo) and others (1-11mo)
 * 4-20-2011-added 2008 entry cohorts
 * 2-10-2011-added 2009 entry cohorts
 * 5-22-2012-modified filename to specify 0-20yr old entries to 
 * accommodate new AB12 programs & files that will reference 0-20yr old entries
 * 2-19-2013-added 2010 entry cohorts
 * 2-14-2014-added 2011 entry cohorts
 * Project: CWS/CMS Performance Indicators
 */

data tmp0;
set dwh.ucb_fc_afcars;

if A34_SPELL = 1 then SP = 1;
else if A34_SPELL ge 2 then SP = 2;

run;

data tmp1;
set tmp0;

where SP = 1;

timein=.;
if pe_e_dt = . then do;
timein=&CUTOFF -pe_s_dt;
end;
if pe_e_dt ne . then do;
timein=pe_e_dt-pe_s_dt;
end;
run;

/*restrict to children in care 8+ days*/
data tmp1;
set tmp1;
where timein ge 8;
run;


/*restrict to one record per child*/
data temp1a;
set tmp1;
by FKCLIENT_T;
if last.FKCLIENT_T;

/* lagdays */
lagdays = .;
if (PE_E_DT = .) then do;
  lagdays = int(&CUTOFF-PE_S_DT);
end;
if (PE_E_DT ge '01jan88'd) then do;
  lagdays = int(PE_E_DT-PE_S_DT);
end;

/* in */
in = .;
if (PE_E_DT = .) then in = 1;
else if (PE_E_DT ne . and PE_E_DT ge '01jan88'd) then in = 0;

first_yr=year(pe_s_dt);

/*updated age calculation*/
age = floor((intck('month',birth_dt,pe_s_dt)-(day(pe_s_dt) lt day(birth_dt)))/12);  
age2 = (pe_s_dt-birth_dt);  

race=ethnic*1;

GENDER=.;
if GENDER_CD='F' then GENDER=1; 
else if GENDER_CD='M' then GENDER=2;
else if GENDER_CD='I' then GENDER=3;

run;


%macro REPORTYEAR(START,STOP) ;
%do ENTYR = &START %to &STOP ;

/*restrict entry cohort years and entries age 0-20 years, ethnic and gender not missing*/
data temp3;
set temp1a;

where (FIRST_YR = &ENTYR)  and age between 0 and 20 AND race in (1,2,3,4,5) and GENDER ne .;

AGEGRP=.;
if age in (0) then AGEGRP=1; else
if age in (1,2) then AGEGRP=2; else
if age in (3,4,5) then AGEGRP=3; else
if age in (6,7,8,9,10) then AGEGRP=4; else
if age in (11,12,13,14,15) then AGEGRP=5; else
if age in (16,17) then AGEGRP=6; else
if age in (18,19,20) then AGEGRP=7;


COUNTY=rsp_cnty*1;

AGEGRP2=AGEGRP;
if agegrp in (1) then do;
if age2 lt 29 then AGEGRP2=1; else
AGEGRP2=1.5;
end;

run;


/*remove missing placement type*/
data temp3a;
set temp3;

if AGEGRP2=. then AGEGRP2=99;

if COUNTY in (59,98,99,.) then COUNTY=98;

run;

/* state */
proc sort data = temp3a;
by AGEGRP2;
run;

/*quartiles*/
ods output quartiles=mlos1;
proc lifetest data=temp3a method = km intervals = 1.1 to 85.1 by 85;
time lagdays*in(1);
by AGEGRP2;
run;

data mlos1;
set mlos1;
where AGEGRP2 ne .; 
run;

ods output quartiles=mlos1a;
proc lifetest data=temp3a method = km intervals = 1.1 to 85.1 by 85;
time lagdays*in(1);
run;

data mlos1a;
set mlos1a;
AGEGRP2=100;
run;

data mlosfac1;
set mlos1 mlos1a ;
if percent=50 then do;
pe2=estimate;
end;
if percent=25 then do;
pe1=estimate;
end;
if percent=75 then do;
pe3=estimate;
end;

drop stratum; 
drop estimate;
drop percent;
drop lowerlimit;
drop upperlimit;
run;


proc sort data=temp3a;
by county AGEGRP2;
run;

ods output quartiles=mlos2;
proc lifetest data=temp3a method = km intervals = 1.1 to 85.1 by 85;
time lagdays*in(1);
by county AGEGRP2;
run;

data mlos2;
set mlos2;
where AGEGRP2 ne 7; /*drop missing AGEGRP group*/
drop stratum;
run;

ods output quartiles=mlos2a;
proc lifetest data=temp3a method = km intervals = 1.1 to 85.1 by 85;
time lagdays*in(1);
by county;
run;

data mlos2a;
set mlos2a;
AGEGRP2=100;
run;

data mlosfac2;
set mlos2 mlos2a;
if percent=50 then do;
pe2=estimate;
end;
if percent=25 then do;
pe1=estimate;
end;
if percent=75 then do;
pe3=estimate;
end;

drop stratum;
drop estimate;
drop percent;
drop lowerlimit;
drop upperlimit;

cal=1;
run;

data mlosfac3;
set mlosfac1 
mlosfac2;
if county=. Then county=0;
else if county in (59,98,99,.) then county = 98;
run;

/*change values of missing point estimates such that proc format [sfmt] will
assign a "**" while misstext in tabulate will assign a blank -- to differentiate
between a non-calculable estimate and one where there is no underlying data*/

data mlos&ENTYR;
set mlosfac3;
if pe1=. then pe1=0;
if pe2=. then pe2=0;
if pe3=. then pe3=0;

PERIOD_DT = &ENTYR;
TYPE = 3;  /* AGE 0-20 */
GROUP = 2; /* AGE */

rename
AGEGRP2 = AGE20A
GENDER = GENDER_CD
race = ETHNIC;

run;

proc append base = local.mlos_AGE20 data = mlos&ENTYR;

%end;
%mend REPORTYEAR ;
%REPORTYEAR(2004,2023);

/* LOS_ENTRY_YR_AGE_ageout.sas */
/* Purpose: Use Event history analysis to compute median length of stay
 * by AGE group [CW spell=1 only].
 * Original Programmer: Daniel Webster
 * REVSION HISTORY:
 * 9-14-2009-created to provide yearly cohort los estimates by age
 * 4-12-2010-began running data for 2007 entry cohort
 * 10-14-2010-divided infant category into neonates (<1mo) and others (1-11mo)
 * 4-20-2011-added 2008 entry cohorts
 * 2-10-2011-added 2009 entry cohorts
 * 5-22-2012-modified filename to specify 0-17yr old entries to 
 * accommodate new AB12 programs & files that will reference 0-20yr old entries
 * 8-29-2012-created new pgm & modified output files to specify 0-17yr old
 * entries with ageout exit created if still in care at 18th birthday [AB12]
 * 2-19-2013-added 2010 entry cohorts
 * 2-14-2014-added 2011 entry cohorts
 * Project: CWS/CMS Performance Indicators
 */


data tmp0;
set dwh.ucb_fc_afcars;

if A34_SPELL = 1 then SP = 1;
else if A34_SPELL ge 2 then SP = 2;

run;

data tmp1;
set tmp0;

where SP = 1;

timein=.;
if pe_e_dt = . then do;
timein=&CUTOFF -pe_s_dt;
end;
if pe_e_dt ne . then do;
timein=pe_e_dt-pe_s_dt;
end;
run;

/*restrict to children in care 8+ days*/
data tmp1;
set tmp1;
where timein ge 8;
run;


/*restrict to one record per child*/
data temp1a;
set tmp1;
by FKCLIENT_T;
if last.FKCLIENT_T;
run;

/*calculate date of 18th birth date*/
data temp1a;
set temp1a;
bdate18=intnx('month',birth_dt,12*18,'same');
format bdate18 mmddyy10.;
run;

/*insert study date where pe end date missing so can*/
/*calculate whether this falls prior to 18th birth date*/
data temp1b;
set temp1a;
if pe_e_dt=. then pe_e_dt2=&cutoff; else
pe_e_dt2=pe_e_dt;
run;

/*where pe end date falls prior to 18th birth date for*/
/*children still in care, change pe end date to 18th birth date*/
data temp1b;
set temp1b;
pe_e_dt3=pe_e_dt2;
if pe_e_dt2 gt bdate18 then do;
pe_e_dt3=bdate18;
end;
format pe_e_dt2 mmddyy.;
format pe_e_dt3 mmddyy.;
run;

/*proc print data=temp1b (obs=1000);
var fkclient_t pe_s_dt pe_e_dt pe_e_dt2 pe_e_dt3 birth_dt bdate18 ;
run;*/

data temp1c;
set temp1b;
drop pe_e_dt pe_e_dt2;
run;
data temp1c;
set temp1c;
rename pe_e_dt3=pe_e_dt;
run;


data temp1a;
set temp1c;

/* lagdays */
lagdays = .;
if (PE_E_DT = .) then do;
  lagdays = int(&CUTOFF-PE_S_DT);
end;
if (PE_E_DT ge '01jan88'd) then do;
  lagdays = int(PE_E_DT-PE_S_DT);
end;

/* in */
in = .;
if (PE_E_DT = .) then in = 1;
else if (PE_E_DT ne . and PE_E_DT ge '01jan88'd) then in = 0;

first_yr=year(pe_s_dt);

/*updated age calculation*/
age = floor((intck('month',birth_dt,pe_s_dt)-(day(pe_s_dt) lt day(birth_dt)))/12);  
age2 = (pe_s_dt-birth_dt);  

race=ethnic*1;

GENDER=.;
if GENDER_CD='F' then GENDER=1; 
else if GENDER_CD='M' then GENDER=2;
else if GENDER_CD='I' then GENDER=3;

run;

%macro REPORTYEAR(START,STOP) ;
%do ENTYR = &START %to &STOP ;

/*restrict entry cohort years and entries age 0-17 years, ethnic and gender not missing*/
data temp3;
set temp1a;

where (FIRST_YR = &ENTYR)  and age between 0 and 17 AND race in (1,2,3,4,5) and GENDER ne .;

AGEGRP=.;
if age in (0) then AGEGRP=1; else
if age in (1,2) then AGEGRP=2; else
if age in (3,4,5) then AGEGRP=3; else
if age in (6,7,8,9,10) then AGEGRP=4; else
if age in (11,12,13,14,15) then AGEGRP=5; else
if age in (16,17) then AGEGRP=6;

COUNTY=rsp_cnty*1;

AGEGRP2=AGEGRP;
if agegrp in (1) then do;
if age2 lt 29 then AGEGRP2=1; else
AGEGRP2=1.5;
end;

run;


/*remove missing placement type*/
data temp3a;
set temp3;


if AGEGRP2=. then AGEGRP2=99;

if COUNTY in (59,98,99,.) then COUNTY=98;

run;

/* state */
proc sort data = temp3a;
by AGEGRP2;
run;

/*quartiles*/
ods output quartiles=mlos1;
proc lifetest data=temp3a method = km intervals = 1.1 to 85.1 by 85;
time lagdays*in(1);
by AGEGRP2;
run;

data mlos1;
set mlos1;
where AGEGRP2 ne .; 
run;

ods output quartiles=mlos1a;
proc lifetest data=temp3a method = km intervals = 1.1 to 85.1 by 85;
time lagdays*in(1);
run;

data mlos1a;
set mlos1a;
AGEGRP2=100;
run;

data mlosfac1;
set mlos1 mlos1a ;
if percent=50 then do;
pe2=estimate;
end;
if percent=25 then do;
pe1=estimate;
end;
if percent=75 then do;
pe3=estimate;
end;

drop stratum; 
drop estimate;
drop percent;
drop lowerlimit;
drop upperlimit;
run;


proc sort data=temp3a;
by county AGEGRP2;
run;

ods output quartiles=mlos2;
proc lifetest data=temp3a method = km intervals = 1.1 to 85.1 by 85;
time lagdays*in(1);
by county AGEGRP2;
run;

data mlos2;
set mlos2;
where AGEGRP2 ne 7; /*drop missing AGEGRP group*/
drop stratum;
run;

ods output quartiles=mlos2a;
proc lifetest data=temp3a method = km intervals = 1.1 to 85.1 by 85;
time lagdays*in(1);
by county;
run;

data mlos2a;
set mlos2a;
AGEGRP2=100;
run;

data mlosfac2;
set mlos2 mlos2a;
if percent=50 then do;
pe2=estimate;
end;
if percent=25 then do;
pe1=estimate;
end;
if percent=75 then do;
pe3=estimate;
end;

drop stratum;
drop estimate;
drop percent;
drop lowerlimit;
drop upperlimit;

cal=1;
run;

data mlosfac3;
set mlosfac1 
mlosfac2;
if county=. Then county=0;
else if county in (59,98,99,.) then county = 98;
run;

/*change values of missing point estimates such that proc format [sfmt] will
assign a "**" while misstext in tabulate will assign a blank -- to differentiate
between a non-calculable estimate and one where there is no underlying data*/

data mlos&ENTYR;
set mlosfac3;
if pe1=. then pe1=0;
if pe2=. then pe2=0;
if pe3=. then pe3=0;

PERIOD_DT = &ENTYR;
TYPE = 2;  /* AGE 0-17 Aged Out */
GROUP = 2; /* AGE */

rename
AGEGRP2 = AGE17OUT
GENDER = GENDER_CD
race = ETHNIC;

run;

proc append base = local.mlos_AGE17OUT data = mlos&ENTYR;

run;

%end;
%mend REPORTYEAR ;
%REPORTYEAR(2004,2023);
/* LOS_ENTRY_YR_ETH_0-17yr.sas */
/* Purpose: Use Event history analysis to compute median length of stay
 * by ETHNIC group [CW spell=1 only].
 * Original Programmer: Daniel Webster
 * REVSION HISTORY:
 * 9-14-2009-created to provide yearly cohort los estimates by ethnicity
 * 4-12-2010-added 2007 entry cohorts
 * 4-20-2011-added 2008 entry cohorts
 * 2-10-2011-added 2009 entry cohorts
 * 5-22-2012-modified filename to specify 0-17yr old entries to 
 * accommodate new AB12 programs & files that will reference 0-20yr old entries
 * 2-19-2013-added 2010 entry cohorts
 * 2-14-2014-added 2011 entry cohorts
 * Project: CWS/CMS Performance Indicators
 */


data tmp0;
set dwh.ucb_fc_afcars;

if A34_SPELL = 1 then SP = 1;
else if A34_SPELL ge 2 then SP = 2;

run;

data tmp1;
set tmp0;

where SP = 1;

timein=.;
if pe_e_dt = . then do;
timein=&CUTOFF-pe_s_dt;
end;
if pe_e_dt ne . then do;
timein=pe_e_dt-pe_s_dt;
end;
run;

/*restrict to children in care 8+ days*/
data tmp1;
set tmp1;
where timein ge 8;
run;

/*restrict to one record per child*/
data temp1a;
set tmp1;
by FKCLIENT_T;
if last.FKCLIENT_T;

/* lagdays */
lagdays = .;
if (PE_E_DT = .) then do;
  lagdays = int("&CUTOFF"d-PE_S_DT);
end;
if (PE_E_DT ge '01jan88'd) then do;
  lagdays = int(PE_E_DT-PE_S_DT);
end;

/* in */
in = .;
if (PE_E_DT = .) then in = 1;
else if (PE_E_DT ne . and PE_E_DT ge '01jan88'd) then in = 0;

first_yr=year(pe_s_dt);

/*updated age calculation*/
age = floor((intck('month',birth_dt,pe_s_dt)-(day(pe_s_dt) lt day(birth_dt)))/12);  

race=ethnic*1;

GENDER=.;
if GENDER_CD='F' then GENDER=1; 
else if GENDER_CD='M' then GENDER=2;
else if GENDER_CD='I' then GENDER=3;

run;

%macro REPORTYEAR(START,STOP) ;
%do ENTYR = &START %to &STOP ;

/*restrict entry cohort years and entries age 0-17 years, ethnic and gender not missing*/
data temp3;
set temp1a;

where (FIRST_YR = &ENTYR) and age between 0 and 17 AND race in (1,2,3,4,5) and GENDER ne .;

COUNTY=rsp_cnty*1;

run;


/*remove missing placement type*/
data temp3a;
set temp3;


if COUNTY in (59,98,99,.) then COUNTY=98;

run;

/* state */
proc sort data = temp3a;
by RACE;
run;

/*quartiles*/
ods output quartiles=mlos1;
proc lifetest data=temp3a method = km intervals = 1.1 to 85.1 by 85;
time lagdays*in(1);
by RACE;
run;

data mlos1;
set mlos1;
where RACE ne .; 
run;

ods output quartiles=mlos1a;
proc lifetest data=temp3a method = km intervals = 1.1 to 85.1 by 85;
time lagdays*in(1);
run;

data mlos1a;
set mlos1a;
RACE=100;
run;

data mlosfac1;
set mlos1 mlos1a ;
if percent=50 then do;
pe2=estimate;
end;
if percent=25 then do;
pe1=estimate;
end;
if percent=75 then do;
pe3=estimate;
end;

drop stratum; 
drop estimate;
drop percent;
drop lowerlimit;
drop upperlimit;
run;


proc sort data=temp3a;
by county RACE;
run;

ods output quartiles=mlos2;
proc lifetest data=temp3a method = km intervals = 1.1 to 85.1 by 85;
time lagdays*in(1);
by county RACE;
run;

data mlos2;
set mlos2;
where RACE ne .; /*drop missing RACE group*/
drop stratum;
run;

ods output quartiles=mlos2a;
proc lifetest data=temp3a method = km intervals = 1.1 to 85.1 by 85;
time lagdays*in(1);
by county;
run;

data mlos2a;
set mlos2a;
RACE=100;
run;

data mlosfac2;
set mlos2 mlos2a;
if percent=50 then do;
pe2=estimate;
end;
if percent=25 then do;
pe1=estimate;
end;
if percent=75 then do;
pe3=estimate;
end;

drop stratum;
drop estimate;
drop percent;
drop lowerlimit;
drop upperlimit;

cal=1;
run;

data mlosfac3;
set mlosfac1 
mlosfac2;
if county=. Then county=0;
else if county in (59,98,99,.) then county = 98;
run;

/*change values of missing point estimates such that proc format [sfmt] will
assign a "**" while misstext in tabulate will assign a blank -- to differentiate
between a non-calculable estimate and one where there is no underlying data*/
data mlos&ENTYR;
set mlosfac3;
if pe1=. then pe1=0;
if pe2=. then pe2=0;
if pe3=. then pe3=0;

PERIOD_DT = &ENTYR;
TYPE = 1;  /* AGE 0-17 */
GROUP = 3; /* Ethnicity */

rename
GENDER = GENDER_CD
race = ETHNIC;

run;

proc append base = local.mlos_ETH17 data = mlos&ENTYR;
run;


%end;
%mend REPORTYEAR ;
%REPORTYEAR(2004,2023);
/* LOS_ENTRY_YR_ETH_0-20yr.sas */
/* Purpose: Use Event history analysis to compute median length of stay
 * by ETHNIC group [CW spell=1 only].
 * Original Programmer: Daniel Webster
 * REVSION HISTORY:
 * 9-14-2009-created to provide yearly cohort los estimates by ethnicity
 * 4-12-2010-added 2007 entry cohorts
 * 4-20-2011-added 2008 entry cohorts
 * 2-10-2011-added 2009 entry cohorts
 * 5-22-2012-modified filename to specify 0-20yr old entries to 
 * accommodate new AB12 programs & files that will reference 0-20yr old entries
 * 2-19-2013-added 2010 entry cohorts
 * 2-14-2014-added 2011 entry cohorts
 * Project: CWS/CMS Performance Indicators
 */

data tmp0;
set dwh.ucb_fc_afcars;

if A34_SPELL = 1 then SP = 1;
else if A34_SPELL ge 2 then SP = 2;

run;

data tmp1;
set tmp0;

where SP = 1;

timein=.;
if pe_e_dt = . then do;
timein=&CUTOFF-pe_s_dt;
end;
if pe_e_dt ne . then do;
timein=pe_e_dt-pe_s_dt;
end;
run;

/*restrict to children in care 8+ days*/
data tmp1;
set tmp1;
where timein ge 8;
run;


/*restrict to one record per child*/
data temp1a;
set tmp1;
by FKCLIENT_T;
if last.FKCLIENT_T;

/* lagdays */
lagdays = .;
if (PE_E_DT = .) then do;
  lagdays = int("&CUTOFF"d-PE_S_DT);
end;
if (PE_E_DT ge '01jan88'd) then do;
  lagdays = int(PE_E_DT-PE_S_DT);
end;

/* in */
in = .;
if (PE_E_DT = .) then in = 1;
else if (PE_E_DT ne . and PE_E_DT ge '01jan88'd) then in = 0;

first_yr=year(pe_s_dt);

/*updated age calculation*/
age = floor((intck('month',birth_dt,pe_s_dt)-(day(pe_s_dt) lt day(birth_dt)))/12);  

race=ethnic*1;

GENDER=.;
if GENDER_CD='F' then GENDER=1; 
else if GENDER_CD='M' then GENDER=2;
else if GENDER_CD='I' then GENDER=3;

run;

%macro REPORTYEAR(START,STOP) ;
%do ENTYR = &START %to &STOP ;

/*restrict entry cohort years and entries age 0-20 years, ethnic and gender not missing*/
data temp3;
set temp1a;

where (FIRST_YR = &ENTYR) and age between 0 and 20 AND race in (1,2,3,4,5) and GENDER ne .;

COUNTY=rsp_cnty*1;

run;


/*remove missing placement type*/
data temp3a;
set temp3;


if COUNTY in (59,98,99,.) then COUNTY=98;

run;

/* state */
proc sort data = temp3a;
by RACE;
run;

/*quartiles*/
ods output quartiles=mlos1;
proc lifetest data=temp3a method = km intervals = 1.1 to 85.1 by 85;
time lagdays*in(1);
by RACE;
run;

data mlos1;
set mlos1;
where RACE ne .; 
run;

ods output quartiles=mlos1a;
proc lifetest data=temp3a method = km intervals = 1.1 to 85.1 by 85;
time lagdays*in(1);
run;

data mlos1a;
set mlos1a;
RACE=100;
run;

data mlosfac1;
set mlos1 mlos1a ;
if percent=50 then do;
pe2=estimate;
end;
if percent=25 then do;
pe1=estimate;
end;
if percent=75 then do;
pe3=estimate;
end;

drop stratum; 
drop estimate;
drop percent;
drop lowerlimit;
drop upperlimit;
run;


proc sort data=temp3a;
by county RACE;
run;

ods output quartiles=mlos2;
proc lifetest data=temp3a method = km intervals = 1.1 to 85.1 by 85;
time lagdays*in(1);
by county RACE;
run;

data mlos2;
set mlos2;
where RACE ne .; /*drop missing RACE group*/
drop stratum;
run;

ods output quartiles=mlos2a;
proc lifetest data=temp3a method = km intervals = 1.1 to 85.1 by 85;
time lagdays*in(1);
by county;
run;

data mlos2a;
set mlos2a;
RACE=100;
run;

data mlosfac2;
set mlos2 mlos2a;
if percent=50 then do;
pe2=estimate;
end;
if percent=25 then do;
pe1=estimate;
end;
if percent=75 then do;
pe3=estimate;
end;

drop stratum;
drop estimate;
drop percent;
drop lowerlimit;
drop upperlimit;

cal=1;
run;

data mlosfac3;
set mlosfac1 
mlosfac2;
if county=. Then county=0;
else if county in (59,98,99,.) then county = 98;
run;

/*change values of missing point estimates such that proc format [sfmt] will
assign a "**" while misstext in tabulate will assign a blank -- to differentiate
between a non-calculable estimate and one where there is no underlying data*/

data mlos&ENTYR;
set mlosfac3;
if pe1=. then pe1=0;
if pe2=. then pe2=0;
if pe3=. then pe3=0;

PERIOD_DT = &ENTYR;
TYPE = 3;  /* AGE 0-20 */
GROUP = 3; /* Ethnicity */

rename
GENDER = GENDER_CD
race = ETHNIC;

run;

proc append base = local.mlos_ETHNIC20 data = mlos&ENTYR;


%end;
%mend REPORTYEAR ;
%REPORTYEAR(2004,2023);
/* LOS_ENTRY_YR_ETHNIC_ageout.sas */
/* Purpose: Use Event history analysis to compute median length of stay
 * by ETHNIC group [CW spell=1 only].
 * Original Programmer: Daniel Webster
 * REVSION HISTORY:
 * 9-14-2009-created to provide yearly cohort los estimates by ethnicity
 * 4-12-2010-added 2007 entry cohorts
 * 4-20-2011-added 2008 entry cohorts
 * 2-10-2011-added 2009 entry cohorts
 * 5-22-2012-modified filename to specify 0-17yr old entries to 
 * accommodate new AB12 programs & files that will reference 0-20yr old entries
 * 8-29-2012-created new pgm & modified output files to specify 0-17yr old
 * entries with ageout exit created if still in care at 18th birthday [AB12]
 * 2-19-2013-added 2010 entry cohorts
 * 2-14-2014-added 2011 entry cohorts
 * Project: CWS/CMS Performance Indicators
 */



data tmp0;
set dwh.ucb_fc_afcars;

if A34_SPELL = 1 then SP = 1;
else if A34_SPELL ge 2 then SP = 2;

run;

data tmp1;
set tmp0;

where SP = 1;

timein=.;
if pe_e_dt = . then do;
timein=&CUTOFF-pe_s_dt;
end;
if pe_e_dt ne . then do;
timein=pe_e_dt-pe_s_dt;
end;
run;

/*restrict to children in care 8+ days*/
data tmp1;
set tmp1;
where timein ge 8;
run;


/*restrict to one record per child*/
data temp1a;
set tmp1;
by FKCLIENT_T;
if last.FKCLIENT_T;

run;

/*calculate date of 18th birth date*/
data temp1a;
set temp1a;
bdate18=intnx('month',birth_dt,12*18,'same');
format bdate18 mmddyy10.;
run;

/*insert study date where pe end date missing so can*/
/*calculate whether this falls prior to 18th birth date*/
data temp1b;
set temp1a;
if pe_e_dt=. then pe_e_dt2=&cutoff; else
pe_e_dt2=pe_e_dt;
run;

/*where pe end date falls prior to 18th birth date for*/
/*children still in care, change pe end date to 18th birth date*/
data temp1b;
set temp1b;
pe_e_dt3=pe_e_dt2;
if pe_e_dt2 gt bdate18 then do;
pe_e_dt3=bdate18;
end;
format pe_e_dt2 mmddyy.;
format pe_e_dt3 mmddyy.;
run;

/*proc print data=temp1b (obs=1000);
var fkclient_t pe_s_dt pe_e_dt pe_e_dt2 pe_e_dt3 birth_dt bdate18 ;
run;*/

data temp1c;
set temp1b;
drop pe_e_dt pe_e_dt2;
run;
data temp1c;
set temp1c;
rename pe_e_dt3=pe_e_dt;
run;


data temp1a;
set temp1c;

/* lagdays */
lagdays = .;
if (PE_E_DT = .) then do;
  lagdays = int("&CUTOFF"d-PE_S_DT);
end;
if (PE_E_DT ge '01jan88'd) then do;
  lagdays = int(PE_E_DT-PE_S_DT);
end;

/* in */
in = .;
if (PE_E_DT = .) then in = 1;
else if (PE_E_DT ne . and PE_E_DT ge '01jan88'd) then in = 0;

first_yr=year(pe_s_dt);

/*updated age calculation*/
age = floor((intck('month',birth_dt,pe_s_dt)-(day(pe_s_dt) lt day(birth_dt)))/12);  

race=ethnic*1;

GENDER=.;
if GENDER_CD='F' then GENDER=1; 
else if GENDER_CD='M' then GENDER=2;
else if GENDER_CD='I' then GENDER=3;

run;

%macro REPORTYEAR(START,STOP) ;
%do ENTYR = &START %to &STOP ;

/*restrict entry cohort years and entries age 0-17 years, ethnic and gender not missing*/
data temp3;
set temp1a;

where (FIRST_YR = &ENTYR) and age between 0 and 17 AND race in (1,2,3,4,5) and GENDER ne .;

COUNTY=rsp_cnty*1;

run;


/*remove missing placement type*/
data temp3a;
set temp3;


if COUNTY in (59,98,99,.) then COUNTY=98;

run;

/* state */
proc sort data = temp3a;
by RACE;
run;

/*quartiles*/
ods output quartiles=mlos1;
proc lifetest data=temp3a method = km intervals = 1.1 to 85.1 by 85;
time lagdays*in(1);
by RACE;
run;

data mlos1;
set mlos1;
where RACE ne .; 
run;

ods output quartiles=mlos1a;
proc lifetest data=temp3a method = km intervals = 1.1 to 85.1 by 85;
time lagdays*in(1);
run;

data mlos1a;
set mlos1a;
RACE=100;
run;

data mlosfac1;
set mlos1 mlos1a ;
if percent=50 then do;
pe2=estimate;
end;
if percent=25 then do;
pe1=estimate;
end;
if percent=75 then do;
pe3=estimate;
end;

drop stratum; 
drop estimate;
drop percent;
drop lowerlimit;
drop upperlimit;
run;


proc sort data=temp3a;
by county RACE;
run;

ods output quartiles=mlos2;
proc lifetest data=temp3a method = km intervals = 1.1 to 85.1 by 85;
time lagdays*in(1);
by county RACE;
run;

data mlos2;
set mlos2;
where RACE ne .; /*drop missing RACE group*/
drop stratum;
run;

ods output quartiles=mlos2a;
proc lifetest data=temp3a method = km intervals = 1.1 to 85.1 by 85;
time lagdays*in(1);
by county;
run;

data mlos2a;
set mlos2a;
RACE=100;
run;

data mlosfac2;
set mlos2 mlos2a;
if percent=50 then do;
pe2=estimate;
end;
if percent=25 then do;
pe1=estimate;
end;
if percent=75 then do;
pe3=estimate;
end;

drop stratum;
drop estimate;
drop percent;
drop lowerlimit;
drop upperlimit;

cal=1;
run;

data mlosfac3;
set mlosfac1 
mlosfac2;
if county=. Then county=0;
else if county in (59,98,99,.) then county = 98;
run;

/*change values of missing point estimates such that proc format [sfmt] will
assign a "**" while misstext in tabulate will assign a blank -- to differentiate
between a non-calculable estimate and one where there is no underlying data*/

data mlos&ENTYR;
set mlosfac3;
if pe1=. then pe1=0;
if pe2=. then pe2=0;
if pe3=. then pe3=0;

PERIOD_DT = &ENTYR;
TYPE = 2;  /* AGE 0-17 Aged Out */
GROUP = 3; /* Ethnicity */

rename
GENDER = GENDER_CD
race = ETHNIC;

run;

proc append base = local.mlos_ETH17OUT data = mlos&ENTYR;

run;

%end;
%mend REPORTYEAR ;
%REPORTYEAR(2004,2023);
/* LOS_ENTRY_YR_GENDER_0-17yr.sas */
/* Purpose: Use Event history analysis to compute median length of stay
 * by GENDER group [CW spell=1 only].
 * Original Programmer: Daniel Webster
 * REVSION HISTORY:
 * 9-14-2009-created to provide yearly cohort los estimates by GENDER
 * 4-12-2010-added 2007 entry cohorts
 * 4-20-2011-added 2008 entry cohorts
 * 2-10-2011-added 2009 entry cohorts
 * 5-22-2012-modified filename to specify 0-17yr old entries to 
 * accommodate new AB12 programs & files that will reference 0-20yr old entries
 * 2-19-2013-added 2010 entry cohorts
 * 2-14-2014-added 2011 entry cohorts
 * Project: CWS/CMS Performance Indicators
 */

data tmp0;
set dwh.ucb_fc_afcars;

if A34_SPELL = 1 then SP = 1;
else if A34_SPELL ge 2 then SP = 2;

run;

data tmp1;
set tmp0;

where SP = 1;

timein=.;
if pe_e_dt = . then do;
timein=&CUTOFF-pe_s_dt;
end;
if pe_e_dt ne . then do;
timein=pe_e_dt-pe_s_dt;
end;
run;

/*restrict to children in care 8+ days*/
data tmp1;
set tmp1;
where timein ge 8;
run;


/*restrict to one record per child*/
data temp1a;
set tmp1;
by FKCLIENT_T;
if last.FKCLIENT_T;

/* lagdays */
lagdays = .;
if (PE_E_DT = .) then do;
  lagdays = int("&CUTOFF"d-PE_S_DT);
end;
if (PE_E_DT ge '01jan88'd) then do;
  lagdays = int(PE_E_DT-PE_S_DT);
end;

/* in */
in = .;
if (PE_E_DT = .) then in = 1;
else if (PE_E_DT ne . and PE_E_DT ge '01jan88'd) then in = 0;

first_yr=year(pe_s_dt);

/*updated age calculation*/
age = floor((intck('month',birth_dt,pe_s_dt)-(day(pe_s_dt) lt day(birth_dt)))/12);  

race=ethnic*1;

GENDER=.;
if GENDER_CD='F' then GENDER=1; 
else if GENDER_CD='M' then GENDER=2;
else if GENDER_CD='I' then GENDER=3;

run;

%macro REPORTYEAR(START,STOP) ;
%do ENTYR = &START %to &STOP ;

/*restrict entry cohort years and entries age 0-17 years, ethnic and gender not missing*/
data temp3;
set temp1a;

where (FIRST_YR = &ENTYR) and age between 0 and 17 AND race in (1,2,3,4,5) and GENDER ne .;

COUNTY=rsp_cnty*1;

run;


/*remove missing placement type*/
data temp3a;
set temp3;


if COUNTY in (59,98,99,.) then COUNTY=98;

run;

/* state */
proc sort data = temp3a;
by GENDER;
run;

/*quartiles*/
ods output quartiles=mlos1;
proc lifetest data=temp3a method = km intervals = 1.1 to 85.1 by 85;
time lagdays*in(1);
by GENDER;
run;

data mlos1;
set mlos1;
where GENDER ne .; 
run;

ods output quartiles=mlos1a;
proc lifetest data=temp3a method = km intervals = 1.1 to 85.1 by 85;
time lagdays*in(1);
run;

data mlos1a;
set mlos1a;
GENDER=100;
run;

data mlosfac1;
set mlos1 mlos1a ;
if percent=50 then do;
pe2=estimate;
end;
if percent=25 then do;
pe1=estimate;
end;
if percent=75 then do;
pe3=estimate;
end;

drop stratum; 
drop estimate;
drop percent;
drop lowerlimit;
drop upperlimit;
run;


proc sort data=temp3a;
by county GENDER;
run;

ods output quartiles=mlos2;
proc lifetest data=temp3a method = km intervals = 1.1 to 85.1 by 85;
time lagdays*in(1);
by county GENDER;
run;

data mlos2;
set mlos2;
where GENDER ne .; /*drop missing GENDER group*/
drop stratum;
run;

ods output quartiles=mlos2a;
proc lifetest data=temp3a method = km intervals = 1.1 to 85.1 by 85;
time lagdays*in(1);
by county;
run;

data mlos2a;
set mlos2a;
GENDER=100;
run;

data mlosfac2;
set mlos2 mlos2a;
if percent=50 then do;
pe2=estimate;
end;
if percent=25 then do;
pe1=estimate;
end;
if percent=75 then do;
pe3=estimate;
end;

drop stratum;
drop estimate;
drop percent;
drop lowerlimit;
drop upperlimit;

cal=1;
run;

data mlosfac3;
set mlosfac1 
mlosfac2;
if county=. Then county=0;
else if county in (59,98,99,.) then county = 98;
run;

/*change values of missing point estimates such that proc format [sfmt] will
assign a "**" while misstext in tabulate will assign a blank -- to differentiate
between a non-calculable estimate and one where there is no underlying data*/

data mlos&ENTYR;
set mlosfac3;
if pe1=. then pe1=0;
if pe2=. then pe2=0;
if pe3=. then pe3=0;

PERIOD_DT = &ENTYR;
TYPE = 1;  /* AGE 0-17 */
GROUP = 4; /* Gender */

rename
GENDER = GENDER_CD
race = ETHNIC;

run;

proc append base = local.mlos_GEN17 data = mlos&ENTYR;

run;


%end;
%mend REPORTYEAR ;
%REPORTYEAR(2004,2023);
/* LOS_ENTRY_YR_GENDER_0-20yr.sas */
/* Purpose: Use Event history analysis to compute median length of stay
 * by GENDER group [CW spell=1 only].
 * Original Programmer: Daniel Webster
 * REVSION HISTORY:
 * 9-14-2009-created to provide yearly cohort los estimates by GENDER
 * 4-12-2010-added 2007 entry cohorts
 * 4-20-2011-added 2008 entry cohorts
 * 2-10-2011-added 2009 entry cohorts
 * 5-22-2012-modified filename to specify 0-20yr old entries to 
 * accommodate new AB12 programs & files that will reference 0-20yr old entries
 * 2-19-2013-added 2010 entry cohorts
 * 2-14-2014-added 2011 entry cohorts
 * Project: CWS/CMS Performance Indicators
 */


data tmp0;
set dwh.ucb_fc_afcars;

if A34_SPELL = 1 then SP = 1;
else if A34_SPELL ge 2 then SP = 2;

run;

data tmp1;
set tmp0;

where SP = 1;

timein=.;
if pe_e_dt = . then do;
timein=&CUTOFF-pe_s_dt;
end;
if pe_e_dt ne . then do;
timein=pe_e_dt-pe_s_dt;
end;
run;

/*restrict to children in care 8+ days*/
data tmp1;
set tmp1;
where timein ge 8;
run;


/*restrict to one record per child*/
data temp1a;
set tmp1;
by FKCLIENT_T;
if last.FKCLIENT_T;

/* lagdays */
lagdays = .;
if (PE_E_DT = .) then do;
  lagdays = int("&CUTOFF"d-PE_S_DT);
end;
if (PE_E_DT ge '01jan88'd) then do;
  lagdays = int(PE_E_DT-PE_S_DT);
end;

/* in */
in = .;
if (PE_E_DT = .) then in = 1;
else if (PE_E_DT ne . and PE_E_DT ge '01jan88'd) then in = 0;

first_yr=year(pe_s_dt);

/*updated age calculation*/
age = floor((intck('month',birth_dt,pe_s_dt)-(day(pe_s_dt) lt day(birth_dt)))/12);  

race=ethnic*1;

GENDER=.;
if GENDER_CD='F' then GENDER=1; 
else if GENDER_CD='M' then GENDER=2;
else if GENDER_CD='I' then GENDER=3;

run;


%macro REPORTYEAR(START,STOP) ;
%do ENTYR = &START %to &STOP ;

/*restrict entry cohort years and entries age 0-20 years, ethnic and gender not missing*/
data temp3;
set temp1a;

where (FIRST_YR = &ENTYR) and age between 0 and 20 AND race in (1,2,3,4,5) and GENDER ne .;

COUNTY=rsp_cnty*1;

run;


/*remove missing placement type*/
data temp3a;
set temp3;


if COUNTY in (59,98,99,.) then COUNTY=98;

run;

/* state */
proc sort data = temp3a;
by GENDER;
run;

/*quartiles*/
ods output quartiles=mlos1;
proc lifetest data=temp3a method = km intervals = 1.1 to 85.1 by 85;
time lagdays*in(1);
by GENDER;
run;

data mlos1;
set mlos1;
where GENDER ne .; 
run;

ods output quartiles=mlos1a;
proc lifetest data=temp3a method = km intervals = 1.1 to 85.1 by 85;
time lagdays*in(1);
run;

data mlos1a;
set mlos1a;
GENDER=100;
run;

data mlosfac1;
set mlos1 mlos1a ;
if percent=50 then do;
pe2=estimate;
end;
if percent=25 then do;
pe1=estimate;
end;
if percent=75 then do;
pe3=estimate;
end;

drop stratum; 
drop estimate;
drop percent;
drop lowerlimit;
drop upperlimit;
run;


proc sort data=temp3a;
by county GENDER;
run;

ods output quartiles=mlos2;
proc lifetest data=temp3a method = km intervals = 1.1 to 85.1 by 85;
time lagdays*in(1);
by county GENDER;
run;

data mlos2;
set mlos2;
where GENDER ne .; /*drop missing GENDER group*/
drop stratum;
run;

ods output quartiles=mlos2a;
proc lifetest data=temp3a method = km intervals = 1.1 to 85.1 by 85;
time lagdays*in(1);
by county;
run;

data mlos2a;
set mlos2a;
GENDER=100;
run;

data mlosfac2;
set mlos2 mlos2a;
if percent=50 then do;
pe2=estimate;
end;
if percent=25 then do;
pe1=estimate;
end;
if percent=75 then do;
pe3=estimate;
end;

drop stratum;
drop estimate;
drop percent;
drop lowerlimit;
drop upperlimit;

cal=1;
run;

data mlosfac3;
set mlosfac1 
mlosfac2;
if county=. Then county=0;
else if county in (59,98,99,.) then county = 98;
run;

/*change values of missing point estimates such that proc format [sfmt] will
assign a "**" while misstext in tabulate will assign a blank -- to differentiate
between a non-calculable estimate and one where there is no underlying data*/

data mlos&ENTYR;
set mlosfac3;
if pe1=. then pe1=0;
if pe2=. then pe2=0;
if pe3=. then pe3=0;

PERIOD_DT = &ENTYR;
TYPE = 3;  /* AGE 0-20 */
GROUP = 4; /* Gender */

rename
GENDER = GENDER_CD
race = ETHNIC;

run;

proc append base = local.mlos_GEN20 data = mlos&ENTYR;

%end;
%mend REPORTYEAR ;
%REPORTYEAR(2004,2023);
/* LOS_ENTRY_YR_GENDER_ageout.sas */
/* Purpose: Use Event history analysis to compute median length of stay
 * by GENDER group [CW spell=1 only].
 * Original Programmer: Daniel Webster
 * REVSION HISTORY:
 * 9-14-2009-created to provide yearly cohort los estimates by GENDER
 * 4-12-2010-added 2007 entry cohorts
 * 4-20-2011-added 2008 entry cohorts
 * 2-10-2011-added 2009 entry cohorts
 * 5-22-2012-modified filename to specify 0-17yr old entries to 
 * accommodate new AB12 programs & files that will reference 0-20yr old entries
 * 8-29-2012-created new pgm & modified output files to specify 0-17yr old
 * entries with ageout exit created if still in care at 18th birthday [AB12]
 * 2-19-2013-added 2010 entry cohorts
 * 2-14-2014-added 2011 entry cohorts
 * Project: CWS/CMS Performance Indicators
 */


data tmp0;
set dwh.ucb_fc_afcars;

if A34_SPELL = 1 then SP = 1;
else if A34_SPELL ge 2 then SP = 2;

run;

data tmp1;
set tmp0;

where SP = 1;

timein=.;
if pe_e_dt = . then do;
timein=&CUTOFF-pe_s_dt;
end;
if pe_e_dt ne . then do;
timein=pe_e_dt-pe_s_dt;
end;
run;

/*restrict to children in care 8+ days*/
data tmp1;
set tmp1;
where timein ge 8;
run;


/*restrict to one record per child*/
data temp1a;
set tmp1;
by FKCLIENT_T;
if last.FKCLIENT_T;
run;

/*calculate date of 18th birth date*/
data temp1a;
set temp1a;
bdate18=intnx('month',birth_dt,12*18,'same');
format bdate18 mmddyy10.;
run;

/*insert study date where pe end date missing so can*/
/*calculate whether this falls prior to 18th birth date*/
data temp1b;
set temp1a;
if pe_e_dt=. then pe_e_dt2=&cutoff; else
pe_e_dt2=pe_e_dt;
run;

/*where pe end date falls prior to 18th birth date for*/
/*children still in care, change pe end date to 18th birth date*/
data temp1b;
set temp1b;
pe_e_dt3=pe_e_dt2;
if pe_e_dt2 gt bdate18 then do;
pe_e_dt3=bdate18;
end;
format pe_e_dt2 mmddyy.;
format pe_e_dt3 mmddyy.;
run;

/*proc print data=temp1b (obs=1000);
var fkclient_t pe_s_dt pe_e_dt pe_e_dt2 pe_e_dt3 birth_dt bdate18 ;
run;*/

data temp1c;
set temp1b;
drop pe_e_dt pe_e_dt2;
run;
data temp1c;
set temp1c;
rename pe_e_dt3=pe_e_dt;
run;


data temp1a;
set temp1c;

/* lagdays */
lagdays = .;
if (PE_E_DT = .) then do;
  lagdays = int("&CUTOFF"d-PE_S_DT);
end;
if (PE_E_DT ge '01jan88'd) then do;
  lagdays = int(PE_E_DT-PE_S_DT);
end;

/* in */
in = .;
if (PE_E_DT = .) then in = 1;
else if (PE_E_DT ne . and PE_E_DT ge '01jan88'd) then in = 0;

first_yr=year(pe_s_dt);

/*updated age calculation*/
age = floor((intck('month',birth_dt,pe_s_dt)-(day(pe_s_dt) lt day(birth_dt)))/12);  

race=ethnic*1;

GENDER=.;
if GENDER_CD='F' then GENDER=1; 
else if GENDER_CD='M' then GENDER=2;
else if GENDER_CD='I' then GENDER=3;

run;


%macro REPORTYEAR(START,STOP) ;
%do ENTYR = &START %to &STOP ;

/*restrict entry cohort years and entries age 0-17 years, ethnic and gender not missing*/
data temp3;
set temp1a;

where (FIRST_YR = &ENTYR) and age between 0 and 17 AND race in (1,2,3,4,5) and GENDER ne .;

COUNTY=rsp_cnty*1;

run;


/*remove missing placement type*/
data temp3a;
set temp3;


if COUNTY in (59,98,99,.) then COUNTY=98;

run;

/* state */
proc sort data = temp3a;
by GENDER;
run;

/*quartiles*/
ods output quartiles=mlos1;
proc lifetest data=temp3a method = km intervals = 1.1 to 85.1 by 85;
time lagdays*in(1);
by GENDER;
run;

data mlos1;
set mlos1;
where GENDER ne .; 
run;

ods output quartiles=mlos1a;
proc lifetest data=temp3a method = km intervals = 1.1 to 85.1 by 85;
time lagdays*in(1);
run;

data mlos1a;
set mlos1a;
GENDER=100;
run;

data mlosfac1;
set mlos1 mlos1a ;
if percent=50 then do;
pe2=estimate;
end;
if percent=25 then do;
pe1=estimate;
end;
if percent=75 then do;
pe3=estimate;
end;

drop stratum; 
drop estimate;
drop percent;
drop lowerlimit;
drop upperlimit;
run;


proc sort data=temp3a;
by county GENDER;
run;

ods output quartiles=mlos2;
proc lifetest data=temp3a method = km intervals = 1.1 to 85.1 by 85;
time lagdays*in(1);
by county GENDER;
run;

data mlos2;
set mlos2;
where GENDER ne .; /*drop missing GENDER group*/
drop stratum;
run;

ods output quartiles=mlos2a;
proc lifetest data=temp3a method = km intervals = 1.1 to 85.1 by 85;
time lagdays*in(1);
by county;
run;

data mlos2a;
set mlos2a;
GENDER=100;
run;

data mlosfac2;
set mlos2 mlos2a;
if percent=50 then do;
pe2=estimate;
end;
if percent=25 then do;
pe1=estimate;
end;
if percent=75 then do;
pe3=estimate;
end;

drop stratum;
drop estimate;
drop percent;
drop lowerlimit;
drop upperlimit;

cal=1;
run;

data mlosfac3;
set mlosfac1 
mlosfac2;
if county=. Then county=0;
else if county in (59,98,99,.) then county = 59;
run;

/*change values of missing point estimates such that proc format [sfmt] will
assign a "**" while misstext in tabulate will assign a blank -- to differentiate
between a non-calculable estimate and one where there is no underlying data*/

data mlos&ENTYR;
set mlosfac3;
if pe1=. then pe1=0;
if pe2=. then pe2=0;
if pe3=. then pe3=0;

PERIOD_DT = &ENTYR;
TYPE = 2;  /* AGE 0-17 Aged Out */
GROUP = 4; /* Gender */

rename
GENDER = GENDER_CD
race = ETHNIC;

run;

proc append base = local.mlos_GEN17OUT data = mlos&ENTYR;
run;


%end;
%mend REPORTYEAR ;
%REPORTYEAR(2004,2023);
/* LOS_ENTRY_YR_PPT_0-17yr.sas */
/* Purpose: Use Event history analysis to compute median length of stay
 * by entry cohort year [CW spell=1 only]
 * Programmer: D. Webster
 * Project: CWS/CMS Performance Indicators
 * 8-18-2008-change program to call on UCB_AFCARS; examine spells only 8+ days
 * 8-18-2008-categorize last placement using scp_rltc into only kin & non-kin,
 * after frequencies on temp3 below showed that, of those with last placement
 * in congregate care, lt 1% were placed with kin
 * 1-27-2009-change age calculation
 * 5-21-2009-added classdata steps to force in rows for all ctys & strata
 * 4-12-2010-added 2007 entry cohorts
 * 4-20-2011-added 2008 entry cohorts
 * 2-10-2011-added 2009 entry cohorts
 * 5-22-2012-modified filename to specify 0-17yr old entries to 
 * accommodate new AB12 programs & files that will reference 0-20yr old entries
 * 2-19-2013-added 2010 entry cohorts
 * 2-14-2014-added 2011 entry cohorts
 * 12-2-2016-chnage kin & non-kin to predominant placement facility type
 * Project: CWS/CMS Performance Indicators
*  9-27-2021 - mofified for new UCB_FC and to allow missing county j magruder
 */

libname userstor "/opt/sas8.2/ud_templates" ;
ods path userstor.templat(read) sashelp.tmplmst(read) ;

data tmp0;
set dwh.ucb_fc_afcars;

if A34_SPELL = 1 then SP = 1;
else if A34_SPELL ge 2 then SP = 2;

if PREDOM_FT = 99 then PREDOM_FT = 98;

run;

data tmp1;
set tmp0;

where SP = 1;

timein=.;
if pe_e_dt = . then do;
timein=&CUTOFF-pe_s_dt;
end;
if pe_e_dt ne . then do;
timein=pe_e_dt-pe_s_dt;
end;
run;

/*restrict to children in care 8+ days*/
data tmp1;
set tmp1;
where timein ge 8;
run;

/*PROC PRINT DATA=TMP1 (obs=200);
var fkclient_t spell a34_spell plcmnt plc_last;
run;*/

/*get last placement type in spell*/
proc sort data=tmp1; by fkclient_t spell oh_s_dt;

data temp1;
set tmp1;
by fkclient_t; if last.fkclient_t;
plc_last=plc_fclc;
scp_last=scp_rltc;
if plc_last=. then plc_last=0;
run;

/*set missing placement type to 0*/
/*
data temp1;
set tmp2;

faclast2=.;
if faclast in (0) then faclast2=0; 
else faclast2 = faclast;

run;

*/

/*construct age, ethnic vars*/
data temp1a;
set temp1;

/* lagdays */
lagdays = .;
if (PE_E_DT = .) then do;
  lagdays = int("&CUTOFF"d-PE_S_DT);
end;
if (PE_E_DT ge '01jan1988'd) then do;
  lagdays = int(PE_E_DT-PE_S_DT);
end;

/* in */
in = .;
if (PE_E_DT = .) then in = 1;
else if (PE_E_DT ne . and PE_E_DT ge '01jan1988'd) then in = 0;

first_yr=year(pe_s_dt);

/*updated age calculation*/
age = floor((intck('month',birth_dt,pe_s_dt)-(day(pe_s_dt) lt day(birth_dt)))/12);  

race=ethnic*1;

GENDER=.;
if GENDER_CD='F' then GENDER=1;
else if GENDER_CD='M' then GENDER=2;
else if GENDER_CD='I' then GENDER=3;

run;

%macro REPORTYEAR(START,STOP) ;
%do ENTYR = &START %to &STOP ;

/*restrict to entry cohort and entries age 0-17 years*/
data temp3;
set temp1a;

where (FIRST_YR = &ENTYR) and age between 0 and 17 AND race in (1,2,3,4,5) and GENDER ne .;

run;

/*run freqs to see what % of last plcmnt=congregate are with kin*/
/*if low % then just code as kin/non-kin with no separate category for congregate--turns out it is lt 1% w. kin*/
/*
proc freq data=temp3;
tables kincong*kinbin;
run;
*/

/*remove missing placement type*/
data tmp&ENTYR;
set temp3;

*where PREDOM_FT ne 98; 
county=rsp_cnty*1; /*modified 2021.09.27*/

run;

data tmp&ENTYR;
set tmp&ENTYR;
if county in (59,98,99,.) then county=98;  /*modified to include missing county 2021.09.27*/
run;

/* state */
proc sort data = tmp&ENTYR;
by PREDOM_FT;
run;

/*quartiles*/
ods output quartiles=mlos1;
proc lifetest data=tmp&ENTYR method = km intervals = 1.1 to 85.1 by 85;
time lagdays*in(1);
by PREDOM_FT;
run;

ods output quartiles=mlos1a;
proc lifetest data=tmp&ENTYR method = km intervals = 1.1 to 85.1 by 85;
time lagdays*in(1);
run;

data mlos1a;
set mlos1a;
PREDOM_FT=100;
run;

data mlosfac1;
set mlos1 mlos1a ;
if percent=50 then do;
pe2=estimate;
end;
if percent=25 then do;
pe1=estimate;
end;
if percent=75 then do;
pe3=estimate;
end;

drop stratum;
drop estimate;
drop percent;
drop lowerlimit;
drop upperlimit;
run;

proc sort data=tmp&ENTYR;
by county PREDOM_FT;
run;

ods output quartiles=mlos2;
proc lifetest data=tmp&ENTYR method = km intervals = 1.1 to 85.1 by 85;
time lagdays*in(1);
by county PREDOM_FT;
run;

ods output quartiles=mlos2a;
proc lifetest data=tmp&ENTYR method = km intervals = 1.1 to 85.1 by 85;
time lagdays*in(1);
by county;
run;

data mlos2a;
set mlos2a;
PREDOM_FT=100;
run;

data mlosfac2;
set mlos2 mlos2a;
if percent=50 then do;
pe2=estimate;
end;
if percent=25 then do;
pe1=estimate;
end;
if percent=75 then do;
pe3=estimate;
end;

drop stratum;
drop estimate;
drop percent;
drop lowerlimit;
drop upperlimit;
cal=1;
run;

data mlosfac3;
set mlosfac1 
mlosfac2;
if county=. Then county=0;
run;

/*change values of missing point estimates such that proc format [sfmt] will
assign a "**" while misstext in tabulate will assign a blank -- to differentiate
between a non-calculable estimate and one where there is no underlying data*/

data mlos&ENTYR;
set mlosfac3;
if pe1=. then pe1=0;
if pe2=. then pe2=0;
if pe3=. then pe3=0;

PERIOD_DT = &ENTYR;
TYPE = 1;  /* AGE 0-17 */
GROUP = 1; /* Predominant Placement Type */

rename
GENDER = GENDER_CD
race = ETHNIC;

run;

proc append base = local.mlos_PPT17 data = mlos&ENTYR;
run;

%end;
%mend REPORTYEAR ;
%REPORTYEAR(2004,2023);
/* LOS_ENTRY_YR_PPT_0-20yr.sas */
/* Purpose: Use Event history analysis to compute median length of stay
 * by entry cohort year [CW spell=1 only]
 * Programmer: D. Webster
 * Project: CWS/CMS Performance Indicators
 * 8-18-2008-change program to call on UCB_AFCARS; examine spells only 8+ days
 * 8-18-2008-categorize last placement using scp_rltc into only kin & non-kin,
 * after frequencies on temp3 below showed that, of those with last placement
 * in congregate care, lt 1% were placed with kin
 * 1-27-2009-change age calculation
 * 5-21-2009-added classdata steps to force in rows for all ctys & strata
 * 4-12-2010-added 2007 entry cohorts
 * 4-20-2011-added 2008 entry cohorts
 * 2-10-2011-added 2009 entry cohorts
 * 5-22-2012-modified filename to specify 0-20yr old entries to 
 * accommodate new AB12 programs & files that will reference 0-20yr old entries
 * 2-19-2013-added 2010 entry cohorts
 * 2-14-2014-added 2011 entry cohorts
 * 12-2-2016-chnage kin & non-kin to predominant placement facility type
 * Project: CWS/CMS Performance Indicators
 * 9-27-2021 - mofified for new UCB_FC and to allow missing county j magruder
 */

libname userstor "/opt/sas8.2/ud_templates" ;
ods path userstor.templat(read) sashelp.tmplmst(read) ;

data tmp0;
set dwh.ucb_fc_afcars;

if A34_SPELL = 1 then SP = 1;
else if A34_SPELL ge 2 then SP = 2;

if PREDOM_FT = 99 then PREDOM_FT = 98;

run;

data tmp1;
set tmp0;

where SP = 1;

timein=.;
if pe_e_dt = . then do;
timein=&CUTOFF-pe_s_dt;
end;
if pe_e_dt ne . then do;
timein=pe_e_dt-pe_s_dt;
end;
run;

/*restrict to children in care 8+ days*/
data tmp1;
set tmp1;
where timein ge 8;
run;

/*PROC PRINT DATA=TMP1 (obs=200);
var fkclient_t spell a34_spell plcmnt plc_last;
run;*/

/*get last placement type in spell*/
proc sort data=tmp1; by fkclient_t spell oh_s_dt;

data temp1;
set tmp1;
by fkclient_t; if last.fkclient_t;
plc_last=plc_fclc;
scp_last=scp_rltc;
if plc_last=. then plc_last=0;
run;

/*set missing placement type to 0*/
/*
data temp1;
set tmp2;

faclast2=.;
if faclast in (0) then faclast2=0; 
else faclast2 = faclast;

run;

*/

/*construct age, ethnic vars*/
data temp1a;
set temp1;

/* lagdays */
lagdays = .;
if (PE_E_DT = .) then do;
  lagdays = int("&CUTOFF"d-PE_S_DT);
end;
if (PE_E_DT ge '01jan1988'd) then do;
  lagdays = int(PE_E_DT-PE_S_DT);
end;

/* in */
in = .;
if (PE_E_DT = .) then in = 1;
else if (PE_E_DT ne . and PE_E_DT ge '01jan1988'd) then in = 0;

first_yr=year(pe_s_dt);

/*updated age calculation*/
age = floor((intck('month',birth_dt,pe_s_dt)-(day(pe_s_dt) lt day(birth_dt)))/12);  

race=ethnic*1;

GENDER=.;
if GENDER_CD='F' then GENDER=1;
else if GENDER_CD='M' then GENDER=2;
else if GENDER_CD='I' then GENDER=3;

run;

%macro REPORTYEAR(START,STOP) ;
%do ENTYR = &START %to &STOP ;

/*restrict to entry cohort and entries age 0-20 years*/
data temp3;
set temp1a;

where (FIRST_YR = &ENTYR) and age between 0 and 20 AND race in (1,2,3,4,5) and GENDER ne .;

run;

/*run freqs to see what % of last plcmnt=congregate are with kin*/
/*if low % then just code as kin/non-kin with no separate category for congregate--turns out it is lt 1% w. kin*/
/*
proc freq data=temp3;
tables kincong*kinbin;
run;
*/

/*remove missing placement type*/
data tmp&ENTYR;
set temp3;

*where PREDOM_FT ne 98; 
county=rsp_cnty*1; /*modified 2021.09.27*/

run;

data tmp&ENTYR;
set tmp&ENTYR;
if county in (59,98,99,.) then county=98;  /*modified to include missing county 2021.09.27*/
run;

/* state */
proc sort data = tmp&ENTYR;
by PREDOM_FT;
run;

/*quartiles*/
ods output quartiles=mlos1;
proc lifetest data=tmp&ENTYR method = km intervals = 1.1 to 85.1 by 85;
time lagdays*in(1);
by PREDOM_FT;
run;

ods output quartiles=mlos1a;
proc lifetest data=tmp&ENTYR method = km intervals = 1.1 to 85.1 by 85;
time lagdays*in(1);
run;

data mlos1a;
set mlos1a;
PREDOM_FT=100;
run;

data mlosfac1;
set mlos1 mlos1a ;
if percent=50 then do;
pe2=estimate;
end;
if percent=25 then do;
pe1=estimate;
end;
if percent=75 then do;
pe3=estimate;
end;

drop stratum;
drop estimate;
drop percent;
drop lowerlimit;
drop upperlimit;
run;

proc sort data=tmp&ENTYR;
by county PREDOM_FT;
run;

ods output quartiles=mlos2;
proc lifetest data=tmp&ENTYR method = km intervals = 1.1 to 85.1 by 85;
time lagdays*in(1);
by county PREDOM_FT;
run;

ods output quartiles=mlos2a;
proc lifetest data=tmp&ENTYR method = km intervals = 1.1 to 85.1 by 85;
time lagdays*in(1);
by county;
run;

data mlos2a;
set mlos2a;
PREDOM_FT=100;
run;

data mlosfac2;
set mlos2 mlos2a;
if percent=50 then do;
pe2=estimate;
end;
if percent=25 then do;
pe1=estimate;
end;
if percent=75 then do;
pe3=estimate;
end;

drop stratum;
drop estimate;
drop percent;
drop lowerlimit;
drop upperlimit;
cal=1;
run;

data mlosfac3;
set mlosfac1 
mlosfac2;
if county=. Then county=0;
run;

/*change values of missing point estimates such that proc format [sfmt] will
assign a "**" while misstext in tabulate will assign a blank -- to differentiate
between a non-calculable estimate and one where there is no underlying data*/

data mlos&ENTYR;
set mlosfac3;
if pe1=. then pe1=0;
if pe2=. then pe2=0;
if pe3=. then pe3=0;

PERIOD_DT = &ENTYR;
TYPE = 3;  /* AGE 0-20 */
GROUP = 1; /* Predominant Placement Type */

rename
GENDER = GENDER_CD
race = ETHNIC;

run;

proc append base = local.mlos_PPT20 data = mlos&ENTYR;
run;

%end;
%mend REPORTYEAR ;
%REPORTYEAR(2004,2023);
/* LOS_ENTRY_YR_KNK_ageout.sas */
/* Purpose: Use Event history analysis to compute median length of stay
 * by entry cohort year [CW spell=1 only]
 * Programmer: D. Webster
 * Project: CWS/CMS Performance Indicators
 * 8-18-2008-change program to call on UCB_AFCARS; examine spells only 8+ days
 * 8-18-2008-categorize last placement using scp_rltc into only kin & non-kin,
 * after frequencies on temp3 below showed that, of those with last placement
 * in congregate care, lt 1% were placed with kin
 * 1-27-2009-change age calculation
 * 5-21-2009-added classdata steps to force in rows for all ctys & strata
 * 4-12-2010-added 2007 entry cohorts
 * 4-20-2011-added 2008 entry cohorts
 * 2-10-2011-added 2009 entry cohorts
 * 5-22-2012-modified filename to specify 0-17yr old entries to 
 * accommodate new AB12 programs & files that will reference 0-20yr old entries
 * 8-29-2012-created new pgm & modified output files to specify 0-17yr old
 * entries with ageout exit created if still in care at 18th birthday [AB12]
 * 2-19-2013-added 2010 entry cohorts
 * 2-14-2014-added 2011 entry cohorts
 * 12-2-2016-chnage kin & non-kin to predominant placement facility type
 * Project: CWS/CMS Performance Indicators
 * 9-27-2021 - mofified for new UCB_FC and to allow missing county j magruder
 */

libname userstor "/opt/sas8.2/ud_templates" ;
ods path userstor.templat(read) sashelp.tmplmst(read) ;

data tmp0;
set dwh.ucb_fc_afcars;

if A34_SPELL = 1 then SP = 1;
else if A34_SPELL ge 2 then SP = 2;

if PREDOM_FT = 99 then PREDOM_FT = 98;

run;

data tmp1;
set tmp0;

where SP = 1;

timein=.;
if pe_e_dt = . then do;
timein=&CUTOFF-pe_s_dt;
end;
if pe_e_dt ne . then do;
timein=pe_e_dt-pe_s_dt;
end;
run;

/*restrict to children in care 8+ days*/
data tmp1;
set tmp1;
where timein ge 8;
run;

/*PROC PRINT DATA=TMP1 (obs=200);
var fkclient_t spell a34_spell plcmnt plc_last;
run;*/

/*get last placement type in spell*/
proc sort data=tmp1; by fkclient_t spell oh_s_dt;

data temp1;
set tmp1;
by fkclient_t; if last.fkclient_t;
plc_last=plc_fclc;
scp_last=scp_rltc;
if plc_last=. then plc_last=0;
run;


/*calculate date of 18th birth date*/
data temp1a;
set temp1;
bdate18=intnx('month',birth_dt,12*18,'same');
format bdate18 mmddyy10.;
run;

/*insert study date where pe end date missing so can*/
/*calculate whether this falls prior to 18th birth date*/
data temp1b;
set temp1a;
if pe_e_dt=. then pe_e_dt2=&cutoff; else
pe_e_dt2=pe_e_dt;
run;

/*where pe end date falls prior to 18th birth date for*/
/*children still in care, change pe end date to 18th birth date*/
data temp1b;
set temp1b;
pe_e_dt3=pe_e_dt2;
if pe_e_dt2 gt bdate18 then do;
pe_e_dt3=bdate18;
end;
format pe_e_dt2 mmddyy.;
format pe_e_dt3 mmddyy.;
run;

data temp1c;
set temp1b;
drop pe_e_dt pe_e_dt2;
run;

data temp2;
set temp1c;
rename pe_e_dt3=pe_e_dt;
run;


/*construct age, ethnic vars*/
data temp2a;
set temp2;

/* lagdays */
lagdays = .;
if (PE_E_DT = .) then do;
  lagdays = int("&CUTOFF"d-PE_S_DT);
end;
if (PE_E_DT ge '01jan1988'd) then do;
  lagdays = int(PE_E_DT-PE_S_DT);
end;

/* in */
in = .;
if (PE_E_DT = .) then in = 1;
else if (PE_E_DT ne . and PE_E_DT ge '01jan1988'd) then in = 0;

first_yr=year(pe_s_dt);

/*updated age calculation*/
age = floor((intck('month',birth_dt,pe_s_dt)-(day(pe_s_dt) lt day(birth_dt)))/12);  

race=ethnic*1;

GENDER=.;
if GENDER_CD='F' then GENDER=1;
else if GENDER_CD='M' then GENDER=2;
else if GENDER_CD='I' then GENDER=3;

run;

%macro REPORTYEAR(START,STOP) ;
%do ENTYR = &START %to &STOP ;

/*restrict to entry cohort and entries age 0-17 years*/
data temp3;
set temp2a;

where (FIRST_YR = &ENTYR) and age between 0 and 17 AND race in (1,2,3,4,5) and GENDER ne .;

run;

/*run freqs to see what % of last plcmnt=congregate are with kin*/
/*if low % then just code as kin/non-kin with no separate category for congregate--turns out it is lt 1% w. kin*/
/*
proc freq data=temp3;
tables kincong*kinbin;
run;
*/

/*remove missing placement type*/
data tmp&ENTYR;
set temp3;

*where PREDOM_FT ne 98; 
county=rsp_cnty*1; /*modified 2021.09.27*/

run;

data tmp&ENTYR;
set tmp&ENTYR;
if county in (59,98,99,.) then county=98;  /*modified to include missing county 2021.09.27*/
run;

/* state */
proc sort data = tmp&ENTYR;
by PREDOM_FT;
run;

/*quartiles*/
ods output quartiles=mlos1;
proc lifetest data=tmp&ENTYR method = km intervals = 1.1 to 85.1 by 85;
time lagdays*in(1);
by PREDOM_FT;
run;

ods output quartiles=mlos1a;
proc lifetest data=tmp&ENTYR method = km intervals = 1.1 to 85.1 by 85;
time lagdays*in(1);
run;

data mlos1a;
set mlos1a;
PREDOM_FT=100;
run;

data mlosfac1;
set mlos1 mlos1a ;
if percent=50 then do;
pe2=estimate;
end;
if percent=25 then do;
pe1=estimate;
end;
if percent=75 then do;
pe3=estimate;
end;

drop stratum;
drop estimate;
drop percent;
drop lowerlimit;
drop upperlimit;
run;

proc sort data=tmp&ENTYR;
by county PREDOM_FT;
run;

ods output quartiles=mlos2;
proc lifetest data=tmp&ENTYR method = km intervals = 1.1 to 85.1 by 85;
time lagdays*in(1);
by county PREDOM_FT;
run;

ods output quartiles=mlos2a;
proc lifetest data=tmp&ENTYR method = km intervals = 1.1 to 85.1 by 85;
time lagdays*in(1);
by county;
run;

data mlos2a;
set mlos2a;
PREDOM_FT=100;
run;

data mlosfac2;
set mlos2 mlos2a;
if percent=50 then do;
pe2=estimate;
end;
if percent=25 then do;
pe1=estimate;
end;
if percent=75 then do;
pe3=estimate;
end;

drop stratum;
drop estimate;
drop percent;
drop lowerlimit;
drop upperlimit;
cal=1;
run;

data mlosfac3;
set mlosfac1 
mlosfac2;
if county=. Then county=0;
run;

/*change values of missing point estimates such that proc format [sfmt] will
assign a "**" while misstext in tabulate will assign a blank -- to differentiate
between a non-calculable estimate and one where there is no underlying data*/

data mlos&ENTYR;
set mlosfac3;
if pe1=. then pe1=0;
if pe2=. then pe2=0;
if pe3=. then pe3=0;

PERIOD_DT = &ENTYR;
TYPE = 2;  /* AGE 0-17 Aged Out*/
GROUP = 1; /* Predominant Placement Type */

rename
GENDER = GENDER_CD
race = ETHNIC;

run;

proc append base = local.mlos_PPT17OUT data = mlos&ENTYR;
run;

%end;
%mend REPORTYEAR ;
%REPORTYEAR(2004,2023);
data dvlp.mlos;
set local.mlos_age17 local.mlos_ppt17 local.mlos_eth17 local.mlos_gen17
    local.mlos_age17out local.mlos_ppt17out local.mlos_eth17out local.mlos_gen17out
    local.mlos_age20 local.mlos_ppt20 local.mlos_ethnic20 local.mlos_gen20;

run;

proc sql;

drop table local.mlos_age17;
drop table local.mlos_ppt17;
drop table local.mlos_eth17;
drop table local.mlos_gen17;
drop table local.mlos_age17out;
drop table local.mlos_ppt17out;
drop table local.mlos_eth17out;
drop table local.mlos_gen17out;
drop table local.mlos_age20;
drop table local.mlos_ppt20;
drop table local.mlos_ethnic20;
drop table local.mlos_gen20;

quit;

data test.mlos;
set dvlp.mlos;
run;