### / • SDM S Documen t I D 

### 203705 2

FINA L

METHOD S AND STANDARD S FO REVALUATIN G

THE PERFORMANC E O FTHE LAK E COUNT Y COMMUNIT Y HEALT H PROGRA M (LCCHP )

July , 200 2
Prepare dby : LCCH P Performanc e Standard s Workin g Grou p

# I I I I I I I I I I I I I I I I I I I EXECUTIV E SUMMAR Y

Thi s documen t

identifie s fou r

Performanc e Standard s tha t wil l b e use dt o evaluat e th e performanc e o f

th e Lak e Count y Communit y Healt hProgra m(LCCHP ) a s th e remed y selecte d fo r Operabl e Uni t

9 a t th e Californi aGulc hSuperfun dSite
. Thes e performanc e standard s ar e intende dt o hel p guid e th e activitie s performe dunde r th e LCCH Ps o tha t

th e Remedia l Actio n Objective s identifie dfo r

OU 9 ar e achieved
. Onc e ademonstratio n ha s bee n mad e tha t th e Performanc e Standard s hav e al l bee n achieved , th e OU 9 remed y wil l b e considere dcomplete
. Remedia l Actio n Objective s Th e Remedia l Actio n Objective s (RAOs ) establishe db y EP A fo r OU 9 ar e a s follows : RAO-1
. N o mor e tha n 5 % o f childre n ag e 0-7 2 month s residin g withi n OU9 , eithe r no w o r i n th e future , shoul dhav e bloo dlea dvalue s exceedin g 1 0 ug/d L RAO-2
. N o mor e tha n 1 % o f childre n ag e 0-7 2 month s residin g withi nOU9 , eithe r no w o r i n th e future , shoul dhav e bloo dlea dvalue s exceedin g 1 5 ug/d L Fo r convenience , th e percen t o f childre n wit hbloo dlea dvalue s abov e 1 0 ug/d Li s referre dt o a s "P10" , an dth e percen t

abov e 1 5 ug/d Li s referre dt o a s "PI5"
. Statistica l Unit s Fo r th e purpose s o f

evaluatin g performanc e an dcomplianc e wit hRAOs , Operabl e Uni t 9 i s divide dint o tw o "Statistica l Units"
. Eac hStatistica l Uni t wil l b e evaluate dindependently
. Performanc e Standard s fo rOU 9 Remed y Th e remed y fo r

aStatistica l Uni t

wil l b e considere dcomplet e whe n th e followin g performanc e standard s ar e achieved
. Standar d1 The total number of blood lead program participants from the Statistical Unit over the preceding 3-year period (i.e., the sum of

the number

of participants for

each of three running years) shall be at least 180children (age 6-72 months), and the 3-year

average recruitment

of newly eligible individuals shall

be 50%or

greater.
Th e purpos e o f

thi s standar di s t o hel p ensur e tha t test s fo r Standard s 2 , 3 , an d4 (below ) ar e al l base do n alarg e an drepresentativ e fractio no f th e eligibl e population
. Thi s i s necessary t o hav e confidenc e th e dat agenerate db y th e progra mar e generall y applicable , an dar e no t base do n a smal l (an dun-representative ) par t o f th e community
. ES- lStandar d2

Based on the consolidated

blood lead data set for the three year

period, the calculated

P10value shall be 5%or less, and the calculatedPJ5value shall be 1%or less, with no individual

PJO value in any of

the three years exceeding a value of 8%. Th e purpos e o f

thi s standar di s t o ensur e tha t th e incidenc e o f

childre n wit helevate dbloo dlea d value s (greate r

tha n 10-1 5 ug/dL ) i s no t

greate r tha n specifie di nth e RAO s fo r th e site. Standar d3 Based on the consolidated

blood lead data set for the three year

period, the probability shall be less than 5%that

the true P10value exceeds 7%, and the probability shall

be less than 5%that the true PI5value exceeds 2%. Th e purpos e o f

thi s standar di s t o ensur e tha t i f aTyp e I decisio n erro r

occur s fo r

Standar d2 a s a resul t o f statistica l variabilit y i nth e data , th e magnitud e o f th e erro r wil l b e small
. Standar d4 Based on the set

of soil lead data for blood lead program participants during the preceding three year period, the proportion of

soil lead values above the 70'

percentile of

the Statistical

Unit as a whole will

not be significantly lower

than 30%, unless the reason for the difference is unavoidable. Th e purpos e o f

thi s requiremen t

i s t o demonstrat e tha t

th e distributio n o f

soi l lea dvalue s fo r participant s i n th e bloo dlea dprogra mdoe s no t under-represen t

th e hig hen d(70 t hpercentil e an d above ) o f th e soi l lea ddistributio n fro mth e Statistica l Unit
. I n th e cas e tha t thi s demonstratio n i s no t achieved , th e LCCH Pwil l investigat e t o determin e i f i t i s reasonabl e an dpractica l t o achiev e th e standard , eithe r b y increase drecruitin g o f childre n wh o resid e i n area s wher e soi l lead s ten dt o b e high , and/o r b y increasin g th e tota l numbe r o f observation s (an dhenc e th e power)
. I f

so , th e LCCH Pwil l tak e al l reasonabl e an dpractica l step s t o seek complianc e wit h Performanc e Standar d4
. I f th e reaso n fo r

th e failur e i s foun db y th e LCCH Pt o b e unavoidable , Performanc e Standar d4 wil l b e waived
. Decisio n Rul e I f aStatistica l Uni t

achieve s complianc e wit hth e performanc e standard s detaile dabove , ongoin g demonstratio n o f

complianc e wit hth e RAO s wil l no t b e require dfo r

tha t Statistica l Unit
. Th e LCCH Pwil l b e considere dcomplet e fo r th e Operabl e Uni t

whe n bot hStatistica l Unit s hav e achieve dth e standards
.

ES- 2

### METHOD S AND STANDARD S FO REVALUATIN G THE PERFORMANC E O F THE LCCHP
1. 0 Purpos e o f

thi s Documen t Thi s documen t

describe s th e approac htha t th e Lak e Count y Communit y Healt hPla n(LCCHP ) Work Grou p shal l utiliz e t o evaluat e th e on-goin g performanc e o f th e program , an didentifie s performanc e standard s tha t mus t b e satisfie dt o demonstrat e tha t th e remed y fo r

Operabl e Uni t

9 (OU9 ) i s complete
. 2. 0 Remedia l Actio nObjective s (RAO- 1 an dRAO-2 ) Th e Remedia l Actio nObjective s establishe db y EP A fo r OU 9 ar e a s follows : RAO-1
. N o mor e tha n5 % o f childre nag e 0-7 2 month s residin g withi nOU9 , eithe r no w o r i nth e future , shoul dhav e bloo dlea dvalue s exceedin g 1 0 ug/d L RAO-2
. N o mor e tha n1 % o f childre nag e 0-7 2 month s residin g withi nOU9 , eithe r no w o r i nth e future , shoul dhav e bloo dlea dvalue s exceedin g 1 5 ug/d L Fo r convenience , th e percen t

o f childre nwit hbloo dlea dvalue s abov e 1 0 ug/d Li s referre dt o a s "P10" , an dth e percen t

abov e 1 5 ug/d Li s referre dt o a s "PI5"
. Becaus e childre nag e 0- 6 month s usuall y hav e lo w exposur e t o lea dfro msoi l o r dust , an dbecaus e collectio no f bloo dfro minfant s i nthi s ag e rang e i s generall y no t desirable , thi s progra mfocuse s o n childre nag e 6-7 2 month s o f ag e rathe r tha nchildre nag e 0-7 2 month s o f age . 3. 0 Statistica l Unit s Fo r th e purpose s o f

evaluatin g complianc e wit hRAO- 1 an dRAO-2 , th e sit e (Operabl e Uni t 9 ) wil l b e divide dint o tw o "Statistica l Units"
. Statistica l Uni t 1 wil l contai nSub-area s A , B , D , an dE , whil e Statistica l Uni t 2 wil l contai nSub-area s C , Fan dG
. Thi s groupin g i s base do nth e know nsimilaritie s i n th e characteristic s o f housin g an dsource s o f

environmenta l lea dexposur e withi nth e combine dSub-areas
. A mor e detaile drational e fo r thi s grouping , includin g th e dat a evaluate dt o identify an dcombin e simila r Sub-areas , i s provide da s Attachmen t 1
. Eac hStatistica l Uni t

wil l b e evaluate dindependently
. I f aStatistica l Uni t

achieve s complianc e wit hth e RAOs , a s define db y th e assessmen t method s an dperformanc e standard s detaile d below , ongoin g demonstratio no f complianc e wit hth e RAO s wil l no t b e require dfo r

tha t Statistica l Unit
. However , th e LCCH Pwil l continu e t o mak e bloo dlea dtestin g an d environmenta l testin g an dremediatio nservice s availabl e t o al l eligibl e resident s i nth e Statistica l Uni t unti l completio no f

th e LCCH Pprogra mwhe nth e othe r Statistica l Uni t

als o achieve s complianc e wit hth e RAOs
.4. 0 Performanc e Standard s fo r OU 9 Remed y Th e remed y fo r

aStatistica l Uni t

wil l b e considere dcomplet e whe nth e followin g performanc e standard s ar e achieved : 1 ) Th e tota l numbe r

o f bloo dlea dprogra mparticipant s fro mth e Statistica l Uni t ove r th e precedin g 3-year

perio d(i.e. , th e su mo f

th e numbe r

o f participant s fo r

eac ho f thre e runnin g years ) shal l b e a t

leas t 18 0 childre n(ag e 6-7 2 months) , an dth e 3-year averag e recruitmen t

o f newl y eligibl e individual s shal l b e 50 % o r greater
. 2 ) Base do n th e consolidate dbloo dlea ddat ase t fo r th e thre e yea r

period , th e calculate d P1 0 valu e shal l b e 5 % o r

less , an dth e calculate dPI 5 valu e shal l b e 1 % o r less 1 , wit hn o individua l P1 0 valu e i nan y o f th e thre e year s exceedin g avalu e o f 8%
. 3 ) Base do n th e consolidate dbloo dlea ddat ase t fo r th e thre e yea r

period , th e probabilit y shal l b e les s tha n5 % tha t

th e tru e P1 0 valu e exceed s 7% , an dth e probabilit y shal l b e les s tha n5 % tha t

th e tru e PI 5 valu e exceed s 2%
. 4 ) Base do n th e se t

o f soi l lea ddat afo r

bloo dlea dprogra mparticipant s durin g th e precedin g thre e yea r

period , th e proportio no f

soi l lea dvalue s abov e th e 70 thpercentil e o f th e Statistica l Uni t

a s awhol e wil l no t

b e significantl y lowe r

tha n30% , unles s th e reaso n fo r th e differenc e i s unavoidable
. Th e purpos e o f thi s requiremen t

i s t o determin e i f

bloo d lea dprogra mparticipant s ar e fro mresidence s tha t under-represen t

th e hig hen d(70 th percentil e an dabove ) o f

th e soi l lea ddistributio nfro mth e Statistica l Unit
. Th e LCCH Pwil l b e considere dcomplet e fo r th e Operabl e Uni t

whe nbot hStatistica l Unit s hav e achieve dth e standard s above , a s wel l a s al l othe r responsibilitie s o f

th e progra ma s specifie di n th e LCCH PWorkplan
. Becaus e th e existin g sit e condition s wer e use da s th e basi s fo r th e desig no f

certai nelement s o f thes e performanc e standards , th e standard s wil l b e subjec t t o revie w an dmodificatio ni f futur e sit e condition s ar e substantiall y differen t tha nthos e tha t

exis t a t presen t (2002)
. Fo r

example , a futur e dro p o r

ris e i nth e chil dpopulatio nma y warran t modificatio no f

performanc e standar d numbe r 1 t o reflec t

th e ne w populatio nnumbers
. An y modification s recommende db y th e LCCH PWorkgrou p wil l b e consisten t wit hth e rational e presente di nthi s documen t an dsubjec t t o fina l revie w an dapprova l b y th e U.S
. EPA
. 5. 0 Statistica l Procedure s 5.1 Data Reduction Th e individua l bloo dlea ddat avalue s fo r eac hyea r wil l b e evaluate di naccor dwit hpreviousl y

1 Al l calculate dP1 0 an dPI 5 value s wil l b e rounde dt o th e neares t 1%
.

# I I I I I I I I I I I I I I I I I I I establishe dprocedure s (Attachmen t 8)
. Individual s wh o hav e elevate dbloo dlea dvalue s tha t ar e attributabl e t o source s beyon dth e contro l o f th e progra mwil l no t

b e include di n th e dat ase t use d t o evaluat e progra mperformance
. Thi s determinatio nwil l b e mad e b y th e LCCH Pworkgrou p o nacase-by-cas e basis
. 5.2 Calculation of

PI 0and PI 5Values Th e value s o f

P1 0 an dP1 5 ca n b e estimate ddirectl y fro madat ase t (e.g. , 5 childre nou t

o f 10 0 wit hbloo dlea dvalue s abov e 1 0 ug/d Lcorrespond s t o a n observe dP1 0 valu e o f 5%)
. However , th e value s o f

P1 0 an dPI 5 calculate di nthi s wa y ten dt o b e statisticall y unstabl e whe nth e numbe r o f childre ni s no t

large , an dsmal l difference s i n th e numbe r o f childre nabov e th e RA O value s ca nhav e alarg e effec t o nth e P1 0 an dP1 5 values
. Therefore , fo r th e purpose s o f

trackin g th e performanc e o f

th e LCCHP , th e valu e o f

P1 0 an dP I 5 wil l b e calculate dbase do n astatistica l curve-fittin g approac htha t utilize s th e entir e bloo dlea ddat ase t fo r aStatistica l Unit
. I nbrief , th e bloo dlea ddat afo r childre n( 6 t o 7 2 month s o f age ) residin g i neac hStatistica l Uni t wil l b e fi t t o a n appropriat e continuou s parametri c distribution , an dbase do n th e bes t fi t mode l t o th e data , th e percen t

o f th e sample s exceedin g 1 0 ug/d Lan d1 5 ug/d Lwil l b e calculate dfro mth e mode l parameters
. Attachmen t

2 provide s tw o alternativ e Exce l spreadsheet s tha t automaticall y perform s th e calculatio no f

th e P1 0 an dP I 5 valu e base do nth e assumptio ntha t th e bloo dlea dvalue s ar e likel y t o b e distribute dapproximatel y lognormally
. Th e firs t shee t shoul db e use di f

th e dat ase t contain s n o non-detec t

values , whil e th e secon dspreadshee t shoul db e use di f

th e dat ase t contain s on e o r

mor e non-detects
. I n eithe r case , th e fi t

base do n th e assumptio no f lognormalit y shoul db e accepte di f

th e goodnes s o f

fi t statisti c i s les s tha nth e critica l value
. I f th e lognorma l fi t i s rejected , the nalternativ e model s (e.g. , gamma , Weibull , beta , Johnso nSb , etc. ) shoul db e teste dt o se e i f

asignificantl y improve dfi t ca n b e achieved
. 5.3 Uncertainty in the PI 0and PI 5Values Th e P1 0 an dP I 5 value s calculate da s describe dabov e represen t th e bes t estimat e o f

th e tru e P1 0 an dP I 5 valu e fo r

th e populatio no f

childre nresidin g i n th e Statistica l Subunit , base do n th e measure dbloo dlea dvalue s i nth e participatin g population
. However , th e calculate dvalue s ar e uncertai nbecaus e th e calculation s ar e base do n arando msampl e o f childre nrathe r

tha nth e entir e population
. Attachmen t 6 provide s a n Excel-Crysta l Bal l spreadshee t tha t estimate s th e uncertaint y i n th e calculate dP1 0 an dPI 5 values
. Th e require dinput s ar e th e observe d geometri c mea nan dgeometri c standar ddeviatio n o f th e bloo dleaddat ase t

an dth e numbe r

o f dat apoint s i nth e dat ase t

fo r th e precedin g thre e yea r

period
. Th e outpu t

i s th e uncertaint y distributio naroun dth e bes t estimat e o f

P I 0 o r P I 5
. Th e probabilit y tha t th e tru e P1 0 valu e exceed s 7% , o r

tha t th e tru e P1 5 valu e excee d2% , ma y b e determine ddirectl y fro mth e outputs
.5.4 Representativeness of Soil Lead Values for

Program Participants Th e representativenes s o f th e soi l lea dlevel s fo r

th e bloo dlea dprogra mparticipant s i na Statistica l Uni t

wil l b e evaluate db y comparin g th e distributio no f soi l lea dvalue s fro mth e residence s o f

bloo dlea dprogra mparticipant s t o th e distributio no f soi l lea dvalue s fo r

th e statistica l uni t

a s awhol e a t

agive npoin t

i ntime
. Th e statistica l metho dfo r thi s compariso nwil l b e ates t o f proportion s (Canavo s 1984)
. I nbrief , thi s tes t categorize s eac hsoi l lea dvalu e i n adat ase t int o on e o f

tw o bins : abov e some specifie d concentratio nlevel , o r

belo w tha t

level
. Becaus e th e purpos e o f th e tes t i s t o determin e i f

th e bloo dlea dprogra mparticipant s ar e fro mresidence s tha t under-represen t

th e hig hen do f

th e soi l lea ddistribution , th e valu e selecte dfo r th e categorizatio nwil l b e th e 70 thpercentil e o f th e "reference " dat ase t

(al l soi l value s fro mth e statistica l unit)
. Thus , b y definition , th e proportio n o f al l sample s i nth e referenc e dat ase t abov e thi s valu e wil l b e 30%
. Th e percen t o f al l sample s abov e tha t

sam e concentratio nvalu e i s the ncompute dfo r th e "test " dat ase t

(th e soi l lead s fo r propertie s wher e bloo dlea dstud y participant s reside)
. Th e probabilit y tha t th e tru e proportio n o f sample s i nth e tes t

dat ase t i s lowe r tha nth e proportio ni nth e referenc e dat ase t i s evaluate d usin g th e tes t

o f proportion s (se e Attachmen t 7)
. I f th e p valu e o f

th e tes t i s lowe r tha n0.05 , ther e i s a95 % probabilit y tha t th e bloo dlea dprogra mparticipant s ar e fro mpropertie s tha t under-represen t

th e hig hen do f

th e soi l lea ddistributio ni nth e Statistica l Unit
. I f th e p valu e i s greate r tha n0.05 , th e tes t

dat ase t wil l no t b e declare ddifferen t

tha nth e referenc e dat aset , unles s th e powe r

o f th e tes t t o detec t adifferenc e o f

10 % i s to o low
. Thi s i s accomplishe db y articulatin g th e decisio nrul e a s follows : Performanc e Standar d4 i s satisfie di f p > a , wher e a= 0.0 5 /

Powe r I nth e cas e tha t

thi s decisio nrul e i s no t

satisfied , th e LCCH Pwil l investigat e t o determin e i f i t i s reasonabl e an dpractica l t o improv e th e representativenes s o f th e bloo dlea dstud y populatio nb y increase drecruitin g o f

childre nresidin g i n area s tha t ten dt o hav e hig hsoi l lea dlevels , and/o r t o increas e th e powe r

o f th e tes t b y increasin g th e tota l numbe r o f dat apoint s i n th e dat aset
. I f so , th e LCCH Pwil l tak e al l reasonabl e an dpractica l step s t o see k complianc e wit hPerformanc e Standar d4
. Th e progra mshal l no t b e declare dcomplet e unti l Performanc e Standar d4 ha s bee n achieved , unles s th e reaso nfo r th e non-complianc e i s impractica l t o correc t du e t o a nabsenc e o f eligibl e children , especiall y thos e residin g a t propertie s wit helevate dsoi l lea dlevels
. I f th e reaso nfo r th e failur e i s foun db y th e LCCH Pt o b e unavoidable , Performanc e Standar d4 wil l b e waived
. 5.5Estimation of

Recruitment

Rate for Newly Eligible Individuals Estimatio no f

th e annua l recruitmen t

rat e o f previousl y unteste dchildre ni s difficul t becaus e detaile dstatistic s o n th e numbe r o f unteste dchildre nar e no t

available , an dbecaus e th e precis e identit y o f

th e unteste dpopulatio nchange s eac hyea r a s childre nar e bo mi n th e are ao r a s the y mov e int o o r

ou t o f th e area . However , ascreening-leve l populatio nmode l (se e Attachmen t 4 ) reveal s tha t

th e annua l steady-stat e recruitmen t rat e ma y b e estimate do n asite-wid e basi s a s th erati o o f th e numbe r

o f first-tim e teste dchildre n (ag e 6-7 2 months ) divide db y th e estimate d numbe r o f newl y eligibl e childre n i n th e site
. Newl y eligibl e childre n ar e define da s childre n wh o ar e bor n i n th e sit e are ao r childre n les s tha n 6 year s o f ag e wh o mov e int o th e sit e area . Th e estimat e o f

newl y eligibl e childre n eac hyear wil l b e derive dfro mavailabl e informatio n a ) th e percentag e o f

Lak e Count y childre n wh o liv e i n OU9 , a s indicate db y th e yea r 200 0 census , b ) a n estimat e o f

th e numbe r

o f childre n bor n i n Lak e Count y eac hyear , an dc ) a n estimat e o f th e numbe r

o f ne w childre n eligibl e t o enrol l i n publi c schoo l eac hyear . Th e numbe r o f birth s an dnumbe r

o f ne w school-ag e childre n withi n th e sit e (OU9 ) wil l b e compute dfro mth e Lak e Count y estimate s base do n th e percentag e o f Lak e Count y childre n livin g withi n th e site' s (OU9 ) boundarie s a t

th e tim e o f

th e 200 0 census . Th e 200 0 censu s data , example s o f th e supportin g birt hcoun t

an dschoo l enrollmen t

dat at o b e used , an dexampl e calculation s ar e presente di n Attachmen t

5
. 6. 0 Discussion : Basi s o f th e Performanc e Standard s 6.1 Use of

a Three- Year

Averaging Period Th e us e o f

athree-yea r

averagin g perio di s selecte dt o ensur e tha t achievemen t

o f th e performanc e standar di s stabl e ove r time , an dt o minimiz e th e ris k o f Typ e I an dTyp e I I error s du e t o short-ter mrando mfluctuation s i n th e calculate dvalue s o f P1 0 an dPI5
. Base do n dat a obtaine dt o date , typica l annua l sample s size s ar e aroun d160-20 0 childre n total , distribute d approximatel y evenl y betwee n th e tw o Statistica l Units
. Thus , th e expecte dnumbe r o f participant s fo r

eac hStatistica l Uni t

i s abou t 80-100
. Mos t

GS D value s rang e fro m1. 4 t o 1.9 , wit havalu e o f

abou t 1. 7 bein g typical
. Assumin g aGS D o f 1. 7 an dassumin g aminimu m sampl e siz e o f

60/year , th e Typ e I an dTyp e I I erro r rate s base do n athree-yea r runnin g averag e P1 0 valu e (calculate dusin g Mont e Carl o simulation , a s detaile di n Attachmen t 3 ) ar e a s follows : Tru e P1 0 Valu e 3 % 4 % 5 % 6 % 7 % 8 % Erro r

Typ e Typ e I I

Typ e I Erro r

Rat e 2 % 19 % 51 % 20 % 6 % 2 % Typ e I erro r

= declar e P1 0 t o b e 5 % o r les s whe ni t

i s actuall y highe r

tha n5 % Typ e I I erro r

= declar e P1 0 t o b e highe r tha n5 % whe ni t

i s actuall y 5 % o r

lowe r A s seen , i f

th e tru e P1 0 valu e i s onl y slightl y highe r tha n RAO- 1 (e.g. , 6%) , ther e i s abou t a20 % chanc e tha t

th e measure dthree-yea r runnin g averag e P1 0 valu e woul db e 5 % o r less , leadin g t o a Typ e I erro r

(decidin g th e sit e wa s i n complianc e whe n i t reall y wa s not)
. However , i f th e differenc e betwee n th e tru e P1 0 valu e an dRAO- 1 i s larger (e.g. , 7 % o r

higher) , the n th e probabilit y o f

aTyp e I erro r

become s quit e smal l (abou t 6%)
. Similarly , i f

th e tru e P1 0 valu e i sonl y slightl y belo w RAO- 1 (e.g
. 4%) , the n th e probabilit y o f aTyp e I I erro r

(declarin g th e dat a t o b e highe r

tha n 5 % whe n i t

reall y i s not ) i s abou t

19% , an dthi s valu e decrease s rapidl y a s th e tru e P1 0 valu e become s smaller
. Thes e erro r rate s ar e no t

sensitiv e t o th e assume dGS D value , bu t d o ten dt o decreas e i f

th e numbe r

o f bloo dlea dprogra mparticipant s eac hyear i s highe r tha n th e assume dparticipatio n rat e o f 60/year (se e below)
. A simila r patter n i s obtaine dfo r

error s i n th e PI 5 value , a s show n below : TruePlSValu e 0.50 % 0.75 % 1.00 % 1.25 % 1.50 % 2.00 % Erro r

Typ e Typ e I I

Typ e I Erro r

Rat e 7 % 29 % 56 % 24 % 14 % 4 % Typ e I erro r

= declar e P1 5 t o b e 1 % o r les s whe n i t

i s actuall y highe r

tha n 1 % Typ e I I erro r

= declar e PI 5 t o b e highe r tha n 1 % whe n i t

i s actuall y 1 % o r

lowe r A s above , th e chance s o f

makin g adecisio n erro r

ar e highes t

whe n th e tru e P I 5 valu e i s ver y clos e t o th e decisio n valu e (1%) , an dth e erro r rate s decreas e rapidl y a s th e tru e valu e become s eithe r smalle r o r large r tha n th e decisio n value
. 6.2 Requirements

for Participation Rate Confidenc e i n th e calculate dP1 0 an dP1 5 value s i s directl y relate dt o th e numbe r o f individual s wh o participat e i n th e program , wit hlo w participatio n correspondin g t o lo w confidence
. T o hel p ensur e aminimu mleve l o f confidence , tw o type s o f requirement s ar e establishe dregardin g annua l an dcumulativ e participation : a) Total Number of Participants Each Year Th e firs t requiremen t

fo r participatio nrat e i s base do nth e tota l numbe r o f participant s eac hyear , includin g bot hne w an drepea t

participants
. Thi s requiremen t i s neede dt o minimiz e th e statistica l chance s o f aTyp e I o r

aTyp e I I erro r i nth e calculatio n o f

th e P1 0 an dP I 5 values
. A s discusse di nAppendi x 3 , bot hTyp e I an dTyp e I I erro r rate s ar e expecte dt o b e withi nacceptabl e bound s i f th e annua l numbe r

o f participant s i neac hStatistica l Uni t i s 8 0 o r more , bu t ar e likel y t o becom e margina l o r unacceptabl e i f

th e numbe r

o f participant s fall s t o abou t 4 0 pe r year . O n thi s basis , th e minimu mthree-yea r runnin g averag e numbe r

o f participant s (i.e. , individua l childre n tested ) pe r Statistica l Uni t i s 6 0 pe r Statistica l Uni t

pe r yea r (18 0 tota l fo r

athree-yea r

period)
. b) Fraction of

Untested Children Recruited

Each Year Th e secon delemen t

o f th e participatio n rat e requiremen t i s th e numbe r

o f ne w (i.e. , previousl y untested ) participant s recruite dint o th e progra meac hyear . Thi s requiremen t i s neede dt o ensur etha t

ther e i s goo drepresentativenes s acros s ag e strat a(yea r o f birth ) i n th e population , an dt o ensur e ther e i s agoo dprobabilit y tha t eac heligibl e chil dwil l b e teste da t leas t once . Assumin g tha t th e odd s o f

recruitin g apreviousl y unteste dchil dint o th e progra mi s abou t constan t ove r time , the n th e odd s o f

achil dparticipatin g a t

leas t onc e durin g th e 6 yea r

eligibilit y perio d(ag e 6-7 2 months ) i s P=l-(l-p) 6 where : p = probabilit y o f participatin g a t

leas t onc e i n 6 year s P= probabilit y o f

apreviousl y unteste dchil dbein g recruite di n an y on e yea r I f th e valu e o f

p i s 50% , the n th e valu e o f Pi s 98%
. O n thi s basis , a50 % recruitmen t o f previousl y unteste dchildre n i s identifie da s th e minimu mtarge t participatio n rat e fro macros s th e sit e eac hyear . 6.3 Representativeness of the Program Participants A n importan t

goa l o f an y progra mo f

thi s typ e i s t o ensur e tha t th e participant s i n th e progra m ar e representativ e o f

th e communit y a s awhole , an dtha t specifi c sub-population s ar e no t substantiall y over - o r

under-represented
. There ar e man y differen t indice s tha t

ma y b e use dt o evaluat e representativeness , includin g age , gender , race , socioeconomi c status , education , an d environmenta l exposur e level s t o lea di n soil , paint , an dwater
. a) Representativeness of

Soil Lead Levels O f th e numerou s alternativ e metric s o f representativeness , th e on e tha t i s mos t importan t

fo r th e purpose s o f

thi s progra mi s th e leve l o f lea di n soil
. Tha t

is , i t i s considere do f

specia l importanc e t o ensur e tha t th e childre n wh o participat e i n th e progra mar e draw n fro mresidence s wit hsoi l lea dvalue s tha t

d o no t significantl y under-represen t th e hig hen do f

th e soi l lea d distributio n i n th e Statistica l Unit
. I t i s fo r thi s reaso n tha t

Performanc e Standar d4 require s a statistica l tes t

t o demonstrat e tha t

th e soi l lea dvalue s fro mth e yard s o f bloo dlea dprogra m participant s contai n aproportio n o f hig hsoi l lea dvalue s tha t i s simila r

t o th e Statistica l Uni t

a s a whole
. Not e that , becaus e th e on-goin g operatio n o f th e LCCH P i s expecte dt o caus e a downwar dshif

t i n th e distributio n o f

soi l lea dvalue s i n eac hStatistica l Unit , thi s compariso n mus t b e base do n th e most

curren t estimat e o f

th e soi l lea ddistributio n i n th e Statistica l Unit
. b) Other Indices of

Representativeness Ther e ar e n o quantitativ e performanc e standard s linke dt o an y othe r metri c o f representativeness , bu t i t i s considere dimportan t

tha t th e LCCH Pwor k

har dt o ensur e tha t

childre n fro mal l segment s o f

th e communit y ar e effectivel y recruite dint o th e program . Therefore , th e LCCH P workgrou p wil l monito r

dat ao n th e demographi c attribute s o f th e individual s participatin g i n th ebloo dlea dmonitorin g program , an dsee k t o ensur e tha t

th e participatin g populatio ni s representativ e o f

th e communit y a s awhole
. Thi s wil l b e don e b y monitorin g th e followin g indice s o f representativeness :
a ) Spatia l Representativeness
. Spatia l representativenes s wil l b e tracke db y mappin g th e sub-are ao f

th e residenc e o f

eac hchil dparticipatin g i n th e bloo dlea dprogram , an dcalculatin g th e estimate dparticipatio nrat e fo r eac ho f th e tw o Statistica l Unit s an dfo r eac ho f th e Sub-area s (A-G)
. Thes e dat awil l b e monitore dannuall y b y th e LCCH PWork

Group , a s describe di n th e annua l repor t outline , an dindication s o f lo w participatio nrat e fro man y subare awil l b e responde dt o b y increase drecruitin g effort s i ntha t

subarea
. Factor s t o conside r i nplannin g th e increase drecruitin g effor t fo r a n are amay includ e availabl e informatio no n leadlevel s i n potentia l source s i n th e are a(soil , leade dpaint , etc) , th e numbe r an dstatu s o f

childre ni n th e area , th e histori c frequenc y o f

elevate dbloo dlea dvalue s fro mth e area , etc
. b ) Ag e Grou p Representativeness
. Th e preferre dtim e o f firs t bloo dtestin g fo r

a n eligibl e chil di s betwee nag e 1 an d2
. Thi s i s becaus e mos t bloo dlea dsurvey s indicat e tha t

bloo dlea dvalue s ten dt o b e highes t i nthi s ag e group , presumabl y becaus e childre ni n thi s ag e grou p hav e th e highes t tendenc y t o inges t

lea dfro mnon dietar y sources . However , dat acollecte dfro machil da t an y ag e betwee n0 an d6 year s wil l b e considere dacceptable
. Th e workgrou p wil l monito r yearl y statistic s o n th e relativ e numbe r

o f participant s stratifie db y ag e group , an dwil l mak e al l reasonabl e effort s t o maximiz e participatio nb y childre nag e 1-2
. c) Othe r Demographi c Factors
. Ideally , the ethni c andsocioeconomi c statu s (SES ) of childre nparticipatin g i nth e progra mshoul db e representativ e o f th e populatio n residin g i n eac hstatistica l unit
. Thi s i s becaus e mos t bloo dlea dsurvey s revea l tha t ther e ar e statisticall y significan t difference s i ngeometri c mea nbloo dlea dvalu e i n group s o f childre nstratifie db y rac e o r SES
. I n thi s program , dat aar e availabl e o n ethnicit y o f

progra mparticipants , an dth e LCCH Pworkgrou p shal l analyz e thes e dat a annuall y t o asses s whethe r th e progra mparticipant s ar e representativ e o f th e communit y makeu p a s awhole
. I f not , th e LCCH Pshal l increas e effort s t o recrui t participatio no f

an y sub-group s tha t

ma y ten dt o b e under-represented
. 7. 0 Evaluatio no f

"Residua l Risk " I t i s recognize dtha t

acertai ndegre e o f

ris k fro mpotentia l lea dexposure s wil l remai ni nth e communit y onc e aremed y i s completed
. However , agoal o f th e programi s t o ensur e tha t whateve r residua l risk s tha t

remai na t unremediate dan dremediate dproperties , a t completio no f th e LCCHP , wil l b e sufficientl y lo w a s t o no t excee dth e RAOs
. Tha t

is , give ncomplianc e wit h th e performanc e standards , i t i s expecte dtha t

n o mor e tha n5 % o f

ase t o f childre nselecte da t rando mfro mth e communit y (OU9 ) wil l hav e abloo dlea dvalu e abov e 1 0 ug/dL , an dn o mor e tha n1 % wil l hav e abloo dlea dvalu e abov e 1 5 ug/dL
.

# I I I i i i i i i i i i i i i i i i i Usin g th e performanc e standard s a s define dabove , couple dwit hothe r requirement s o f

th e LCCH Pprogra m(includin g a n activ e outreac hprogra mt o ensur e tha t al l are aresident s ar e awar e o f th e progra man dhav e bee ngive nreasonabl e opportunit y t o participat e befor e th e progra mcease s operation) , i t i s expecte dtha t

thi s goal wil l b e achieve db y th e tim e th e LCCH P i s completed
. Thi s conclusio ni s base do nth e fundamenta l assumptio ntha t th e participant s i n th e LCCH Par e generall y representativ e o f th e communit y a s awhole , an dtha t th e statistica l attribute s o f

th e progra mparticipant s als o appl y t o th e propertie s an dindividual s wh o d o no t participate
. 8. 0 Reference s D'Agostin o RB , Stephen s M A (eds)
. 1986
. Goodness-of-Fi t Techniques
. Marcel l Decker , Inc. , Ne w York
. Canavo s GC
. 1984
. Applie dProbabilit y an dStatistica l Methods
. Little , Brow nan dCo
. Boston
.

# I I I I I I I I I I I I I I I I I I I ATTACHMEN T 1 Rational e fo rStatistica l Uni tDefinition s
Th e tw o Statistica l Unit s represen t combination s o f

th e existin g Subarea s int o group s havin g simila r

environmenta l condition s wit hrespec t t o potentia l source s o f

lea d exposure . Th e environmenta l dat aan dpropert y informatio n collecte db y th e Universit y o f Cincinnat i i n 199 1 an db y th e Kid s Firs t Progra mfro m199 4 throug hMa y o f 200 1 wer e combine dan dthe n use dt o mak e comparison s o f environmenta l condition s i n th e variou s Subareas
. Th e dat ause dfo r thes e inter-are acomparison s ar e th e property
averag e lea dconcentration s i n yar dsoil , interio r paint , exterio r

paint , wate r

an ddust
. Thes e dat aar e presente di n aserie s o f "bo x an dwhisker " plot s tha t displa y th e distributio n o f

lea dconcentration s i n eac hmedi atyp e an dwithi n eac ho f th e Subareas
. Othe r factor s suc ha s percentag e o f home s tha t

ar e owne r

(o r renter ) occupie dan dag e o f housin g wer e als o evaluate dan dconsidere di n compariso n o f th e Subare acharacteristics
. Area s A , B , D an dEar e simila r i n thei r yar dsoil , interio r

paint , exterio r

paint , wate r

an d dus t lea dlevels
. I n addition , Area s A , B an dD hav e approximatel y th e sam e proportio n o f owner-occupie dan drenta l propertie s an dsimila r ag e housing
. Thes e Subarea s mak e u p th e olde r

portion s o f

th e Cit y o f

Leadville
. Are aE , Stringtown , ha s mor e owne r occupie dpropertie s an dslightl y newe r housin g tha n Area s A , B an dD , bu t despit e th e newe r housin g age , pain t

an ddus t lea dconcentration s ar e no t distinc t fro mthos e i n th e olde r portion s o f

Leadville
. Thes e fou r

Subarea s hav e bee n combine dt o establis h Statistical Uni t

1
. Area s C , Fan dGal l hav e newe r housin g tha n th e othe r

areas . Area s C an dGar e simila r i nthei r distribution s o f

lea di n soil , interio r

paint , exterio r

paint , wate r

an ddust , an d excep t fo r th e drinkin g wate r

data , thes e distribution s ar e distinc t fro mthos e observe di n Area s A , B , D an dE
. Are aFsoi l lea dconcentration s hav e typicall y bee n highe r tha n i n eithe r C o r Gan dmor e lik e thos e observe di n Area s A an dD
. However , soi l remediatio n fo r al l propertie s withi n Are aFwa s initiate di n200 1 an di s expecte dt o b e complet e i n 2002
. Fo r thi s reason , w e expec t

tha t th e soi l lea dconcentration s i n Are aFwil l b e mor e lik e thos e i n Area s C an dGafte r 200 2 tha n thos e tha t

remai n i n Area s A , B , D an dE
. Lea dconcentration s i n wate r initiall y appeare dhighe r

i n Are aFtha n i n an y o f

th e othe r areas , bu t thi s differenc e wa s mainl y du e t o relativel y hig hlea dconcentration s i nth e ta p wate r sample s collecte db y th e Universit y o f Cincinnat i i n1991
. Ta p wate r sample s collecte db y th e Kid s Firs t Progra mfro move r

th e las t 5 year s sho w lowe r

lea d concentration s (refe r

t o followin g bo x an dwhiske r plot s fo r Kid s Firs t

Progra mwate r an dBornschei n stud y wate r samples)
. Thi s differenc e i n th e tw o set s o f tap wate r result s wa s no t apparen t i n an y othe r

Subare as o i t

di dno t appea r t o b e a n artifac t

o f sligh t difference s i n th e wate r

samplin g procedure s use db y thos e tw o programs . Al l o f th e residence s withi n Are aF , th e Lak e Fork Traile r Park , obtai n thei r

ta p wate r fro masingl e privat e wel l adjacen t

t o th e traile r

park
. Th e curren t

manage r o f th e traile r

par k reporte d tha t tw o wate r

suppl y well s wer e use di n th e pas t an dbothwer e likel y i n us e durin g th e199 1 samplin g event ; a t present , onl y on e o f

th e well s i s use dfo r

wate r suppl y t o th e traile r park
. Give nthi s information , i t appear s tha t

th e wel l n o longe r

i n us e ma y hav e provide dwate r

wit hhighe r

lea dconcentration s tha nth e remainin g wate r suppl y well
. Th e lea dconcentration s i n wate r sample s collecte dfro mAre aFi n th e las t 5 year s d o no t appea r distinc t fro mthos e i n an y othe r

Subare ao f

th e site
. Give nthes e data , Area s C , F an dGhav e bee ncombine dt o establis hStatistica l Uni t 2
. Combinin g th e existin g Subarea s int o tw o Statistica l Unit s provide s relativel y larg e number s o f

youn g childre neligibl e t o participat e i n bloo dlea dmonitorin g fro meac ho f th e units
. Base do n annua l participatio nnumber s fro mth e las t seve nyears , w e expec t participatio nfro mapproximatel y 9 0 youn g childre nfro mArea s A , B , D an dEcombine d an dapproximatel y 10 0 youn g childre nfro mArea s C , Fan dGcombined
. Explanatio no f

Bo x an dWhiske r

Plots : Th e lea ddistribution s i n variou s environmental-lea dsource s ar e presente di n th e followin g "bo x an dwhisker " plots
. Thes e plot s wer e prepare dfro mth e lead-testin g dat a collecte db y th e Kid s Firs t Progra m(199 5 throug hMa y 2001 ) an dth e Universit y o f Cincinnati , o r

R
. Bornschien , stud y (1991) , an dthe y ca n b e use dt o compar e th e lea d concentration s i n environmenta l medi afro mth e variou s Subareas
. Fo r eac ho f th e environmenta l media , th e lea dconcentration s measure da t asingl e propert y wer e averaged , an dth e property-averag e value s wer e the nuse dt o prepar e th e bo x plots
. Th e bo x an dwhiske r

plot s sho w th e media nvalu e (soli dline) , 25 t han d75 t hpercentil e value s (bo x limits) , 10 than d90 thpercentil e value s (whiske r en dpoints) , an d5 t han d95 th percentil e value s (outsid e circles ) fo r th e lea dconcentratio ndistributio ni n eac hSubare a dat aset
.

# I I I I I I I I I I I I I I I I I I I Averag e Soi l Lea d Concentratio n Participatin g Propertie s

• ^ 1400 0 - ,§

. 1200 0 - i O r o 1000 0 - § c 800 0 - 0 g 600 0 - C O 400 0 - 0 ) D ) 5 oj 200 0 - > 0 - • 

# T +
A • 

# T V B 

# ,

C •

~| ~

4 r D Are a •

I 

# 4 -
E 0

•_ .

-4 - I ^

I F G

# I I I I I I I I I I I I I I I I I I I Averag e Dus t Lea d Concentratio n Participatin g Propertie s

500 0

400 0 -

300 0 -

S 200 0 -

100 0 - 

# T



# - r

D 

### Are a

# I I I I I I I I I I I I I I I I I I I 3 0

2 0 - 

## £ 1J H o 0 J j 1 0 0 D J 

### Averag e Interio rPain t Lea d Concentratio n Participatin g Propertie s



### I
B C D E F G

Are a3 0

2 0 - "

0 )

_ C D Q

.

x 1 0 11 1 d > D )

* c 

## I 5 H 

### Averag e Exterio rPain t Lea d

Participatin g Propertie s



## I 

# T4 , C D Are a

### Averag e Lea d i n Drinkin g Wate r Kid s Firs t Progra m Propertie s

3 0

2 5 -
2 0 - .
O)
TO 0 ) 1 5 -
1 0 -
5 - 

# T

D Are a3 5 

### Lea d i n Drinkin g Wate r Bornschei n Stud y(1991 ) Dat a

3 0 -- -
D > 2 5 - -

0 ) o O 1 5 -- •
1 0

0 - r C D E Are aATTACHMEN T 2 Spreadsheet s fo rP1 0 an d P1 5 Calculatio n Base d o n aLognorma l Bloo d Lea d Distributio n
Tw o alternativ e Exce l spreadsheet s ar e attache dfo r us e i ncalculatio n o f

bloo dlea dstatistics , assumin g th e bloo dlea ddistributio n i s lognormall y distributed
. Th e spreadshee t

entitle d"Pb B L N Fit-N o Censoring.xls " shoul db e use di f non e o f th e dat a point s i n th e dat ase t

ar e belo w th e analytica l detectio n limit
. Thi s shee t derive s th e distributio n parameter s usin g maximu mlikelihoo d(MLE ) methods , an dth e goodnes s o f fi t (GOF ) tes t

i s base do nth e Anderson-Darlin g statistic
. Thi s GO Fmetho di s selecte dbecaus e i t assign s highe r weight s t o observation s i nth e tail s o f th e distribution s tha n othe r goodnes s o f

fi t methods
. Th e spreadshee t

entitle d"Pb B L N Fit-WithCensoring.xls " shoul db e use di f on e o r mor e o f th e dat apoint s i n th e dat ase t

ar e belo w th e analytica l detectio n limit
. Thi s shee t derive s th e distributio nparameter s usin g linear regression , an dth e goodnes s o f fi t tes t i s base do n th e ch i square dstatistic
. Thi s approac hi s somewha t les s robus t

tha t us e o f th e ML Ean dAnderso n Darlin g methods , bu t

technique s fo r

applicatio n o f

thes e method s t o censore ddat aar e no t established
.ATTACHMEN T 3 

# I I I I I I

• 

### Estimatio no f Typ e I an dTyp e I I Erro r Rate s Usin g Mont e Carl o Simulatio n 

# I I I I I I I I I I I I1. 0 INTRODUCTIO N

Th e basi c proces s t o b e use dfo r evaluatio n o f

th e performanc e o f

th e LCCH Pi s summarize d below : 1
. Fi t abloo dlea ddat ase t

fro maStatistica l Uni t

t o acontinuou s parametri c distributio n (e.g. , lognormal ) 2
. Base do n th e bes t

fi t parameters , calculat e th e P1 0 an dPI 5 value s 3
. Compar e th e P1 0 valu e t o RAO- 1 (5% ) an dth e P1 5 valu e t o RAO- 2 (1% ) 4
. Declar e th e remed y successfu l fo r tha t Statistica l Uni t

i f th e runnin g 3-year

averag e valu e fo r P1 0 i s 5 % o r

les s an dth e runnin g 3-yea r averag e valu e fo r

PI 5 i s 1 % o r less , give n complianc e wit hothe r requirement s fo r

participatio n rat e an d representativeness
. Becaus e th e value s o f

P1 0 an dP1 5 ar e base do n bloo dlea ddat aset s tha t ar e subjec t

t o variabilit y ove r

tim e an dspace , rando mvariation s i n th e bloo dlea dvalue s o f th e progra m participant s coul dlea dt o th e chanc e o f makin g a n incorrec t

decision
. Thes e error s ar e o f tw o types : Typ e I Error : Decidin g tha t

th e RAO s hav e bee n satisfie dfo r aStatistica l Uni t

whe n actua l bloo dlea d value s d o no t

satisf y th e RAO s Typ e I I Error : Decidin g tha t

th e RAO s hav e no t

bee n satisfie dfo r

aStatistica l Uni t

whe n actua l bloo d lea dvalue s d o satisf

y th e RAO s I norde r t o evaluat e th e chance s o f makin g aTyp e I o r

aTyp e I I erro r

fo r aStatistica l Uni t

unde r th e propose dprocess , Mont e Carl o simulatio n wa s employed , a s describe dbelow
. 2. 0 MONT E CARL O SIMULATIO N Al l Mont e Carl o simulation s wer e performe dusin g acommerciall y availabl e softwar e packag e (Crysta l Ball , availabl e fro mDecisioneering
. Inc ) a s a n add-o n t o Microsof t Excel
. Th e basi c procedur e use dt o asses s th e chanc e o f Typ e I an dTyp e I I error s wa s a s follows : 1
. A "true " distributio n o f bloo dlea dvalue s wa s define db y specifyin g th e tru e P1 0 valu e an dth e tru e geometri c standar ddeviatio n (GSD)
. 2
. Fro mthi s specifie ddistribution , arando msampl e o f n bloo dlea dvalue s wa s drawn
. 3
. Fro mthi s rando mse t

o f bloo dlea dvalues , th e bes t fi t parameter s o f

alognorma l distributio n wer e calculated , an dth e sample-specifi c P1 0 valu e wa s calculate d 4
. Step s 2 an d3 wer e repeate dman y time s (10,000 ) 5
. I f th e tru e P1 0 valu e wa s abov e 5% , th e fractio no f al l trail s tha t

yielde dacalculate dP1 0 valu e o f 5 % o r les s wa s calculated
. Thi s i s th e Typ e I erro r rate
.

# I I I I I I I I I I I I I I I I I I I 6
. I f

th e tru e P1 0 valu e wa s abov e 5 % o r below , th e fractio no f

al l trail s tha t

yielde da calculate dP1 0 valu e abov e 5 % wa s calculated
. Thi s i s th e Typ e I I erro r rate
. Thi s proces s wa s repeate dfo r aserie s o f

alternativ e valu e o f

P1 0 an dGSD , testin g i n eac hcas e ho w th e Typ e I an dTyp e I I erro r rate s depen do n a ) th e numbe r o f year s acros s whic harunnin g averag e i s calculated , an db ) th e numbe r o f participant s eac hyear . 3. 0 RESULT S 3. 1 Averagin g Tim e Th e firs t issu e investigate dwa s ho w erro r rate s depende do n th e numbe r o f year s use dt o calculat e th e runnin g average . Base do n bloo dlea ddat acollecte dt o date , atypica l valu e fo r GS D i s abou t

1.7 , an dth e typica l numbe r o f participant s pe r

Statistica l Uni t

i s 8 0 o r mor e pe r year . T o b e conservative , avalu e o f 60/year wa s assumed
. Th e valu e o f P1 0 wa s se t

t o aserie s o f value s rangin g fro m3 % t o 8% , an dfiv e separat e rando mdat aset s (correspondin g t o 5 consecutiv e year s o f

data ) wer e drawn
. The nth e runnin g averag e P1 0 valu e wa s calculate dfo r averagin g time s o f

1 , 2 , 3 , 4 , an d5 years . Th e result s ar e show nbelow , an dar e presente dgraphicall y i n Figur e A3-1
. Tru e P1 0 3 % 4 % 5 % 6 % 7 % 8 % Erro rRat e (% )

1 Y r 10. 6 28. 7 48. 5 34. 6 21. 3 11. 6 2Y r

4. 5 23. 5 50. 2 26. 3 11. 0 4. 0 3Y r

2. 5 19. 6 51. 2 21. 2 6. 4 1. 7 4Y r

1. 3 16. 4 52. 9 17. 2 3. 8 0. 7 5Y r

1. 2 14. 2 53. 9 14. 1 2. 3 0. 2 Tru e P1 5 0.50 % 0.75 % 1.00 % 1.25 % 1.50 % 2.00 % Erro rRat e {% )

1 Y r 15. 6 32. 7 48. 6 38. 0 28. 4 14. 5 2Y r

9. 6 31. 4 53. 9 29. 0 16. 5 5. 4 3Y r

6. 2 29. 4 56. 1 22. 4 11. 1 2. 2 4Y r

4. 3 27. 2 58. 9 18. 7 7. 0 1. 0 5Y r

3. 1 25. 1 60. 6 16. 0 4. 8 0. 4
A s see ni n th e uppe r

panel , i f th e tru e P1 0 valu e i s onl y slightl y highe r tha nRAO- 1 (e.g. , 6%) , ther e i s abou t

a21 % chanc e tha t

th e measure dthree-year

runnin g averag e P1 0 valu e woul db e 5 % o r less , leadin g t o aTyp e I erro r (decidin g th e sit e wa s i n complianc e whe ni t reall y wa s not)
. However , i f

th e differenc e betwee nth e tru e P1 0 valu e an dRAO- 1 i s large r (e.g. , 7 % o r

higher) , the nth e probabilit y o f

aTyp e I erro r

become s quit e smal l (abou t 6 % base do n a3-year averagin g period)
. Similarly , i f th e tru e P1 0 valu e i s onl y slightl y belo w RAO- 1 (e.g
. 4%) , the n th e probabilit y o f

aTyp e I I erro r

(declarin g th e dat at o b e highe r tha n5 % whe ni t

reall y i s not ) i sabou t

20 % base do n a3-yea r

averagin g period , an dthi s valu e decrease s a t th e tru e P1 0 valu e become s smaller
. A simila r patter n exist s fo r

error s i nth e PI 5 valu e (lowe r panel)
. Thes e erro r rate s ar e no t

sensitiv e t o th e assume dGS D value , bu t d o ten dt o decreas e i f

th e numbe r

o f bloo d lea dprogra mparticipant s eac hyear i s highe r tha n th e minimu mvalu e o f 60/year tha t wa s assume d(se e below)
. 3. 2 Numbe ro f

Participant s pe rStatistica l Uni t Th e secon dissu e investigate dwa s ho w erro r rate s depende do n th e tota l numbe r o f participant s i neac hyea r

an dfo r th e three-year

averagin g time
. Thes e calculation s wer e al l base do na n assume drunnin g 3-year

averagin g tim e fo r

participatio n number s an daGS D o f 1. 7 fo r eac ho f th e thre e annua l dat asets
. Th e result s ar e show n belo w an dar e presente dgraphicall y i nFigur e A3-2 : Tru e P1 0

3 % 4 % 5 % 6 % 7 % 8 % Erro rRat e (% )

20/y r 13. 8 32. 6 53. 3 30. 1 17. 7 10. 5 40/y r

5. 5 23. 9 52. 7 24. 6 10. 4 4. 1 60/y r

2. 4 18. 6 51. 2 20. 4 6. 1 1. 7 80/y r

1. 1 14. 8 51. 6 16. 6 3. 9 0. 7 100/y r

0. 7 11. 5 51. 9 14. 2 2. 5 0. 3 TrueP1 5 0.50 % 0.75 % 1.00 % 1.25 % 1.50 % 2.00 % Erro rRat e (% )

20/y r 25. 1 44. 3 59. 1 28. 4 19. 7 9. 6 40/y r

13. 3 35. 6 57. 4 25. 8 14. 4 4. 5 60/y r

7. 0 29. 3 56. 2 23. 5 10. 6 2. 0 80/y r

3. 8 24. 9 55. 4 20. 6 8. 3 0. 9 100/y r

2. 1 21. 4 55. 1 19. 2 6. 5 0. 5 A s show n i nth e uppe r

panel , estimate dTyp e I erro r rate s fo r P1 0 value s decreas e a s th e numbe r o f participant s increases
. I f th e numbe r

o f participant s i s abou t

8 0 pe r yea r (abou t wha t i s expected) , th e Typ e I erro r rat e i s abou t

17 % i f th e tru e P1 0 valu e i s 6% , an dabou t 4 % i f th e tru e P1 0 valu e i s 7%
. I f

th e numbe r

o f participant s decrease s t o abou t 4 0 pe r year , Typ e I erro r

rate s ar e higher , reachin g 25 % fo r atru e P I 0 o f

6 % an d10 % fo r

atru e P1 0 o f

7%
. Likewise , i f

th e tru e P1 0 i s 4% , Typ e I I erro r rate s ar e generall y acceptabl e (15% ) whe n ther e ar e 8 0 participant s pe r year , bu t becom e margina l (24% ) whe n ther e ar e onl y 4 0 participant s pe r year . A similar patter n exist s fo r

P1 0 erro r rate s (lowe r

panel)
.FIGUR E A3-1 . DEPENDENC E O F ERRO RRAT E O N AVERAGIN G TIM E

P1 0 ERRO R RAT E A S A FUNCTIO N O F AVERAGIN G TIM E (N=60/yr ) 6 0

5 0

4 0
S & 3 0 

## i
UJ 2 0

1 0 - Typ e I I Erro r

(Declar e P1 0 unacceptabl e whe n I t I s acceptable )

3 % 4 % Typ e I Erro r (Declare P1 0 acceptabl e whe n i t I s no

t acceptable )

5 % 6 % TrueP10(ug/dL ) 7 % Yea n
Yea r 2

7 0 -
6 0

s o

s fl] o : 4 0

3 0

2 0

1 0

0 P1 5 ERRO R RAT E A S AFUNCTIO N O F AVERAGIN G TIM E ( N = 60/yr )

Typ e I I Erro r (Declare P1 5 unacceptabl e whe n i t i s acceptable ) Typ e I Erro r (Declare P1 5 acceptabl e whe n i t i s not acceptable )

0.50 % 0.75 % 1.00 % 1.25 % TrueP15(ug/dL ) 1.50 % 2.00 %FIGUR E A3-2
. DEPENDENC EO FERRO RRAT E O N NUMBE RO FPARTICIPANT S

6 0

5 0

4 0

3 0

2 0

1 0 P1 0 ERRO R RAT E A S A FUNCTIO N O F PARTICIPATIO N RAT E (3-Y R PROGRAM )

Typ e I I Erro r (Declar e P1 0 unacceptabl e whe n i t i s acceptable )

3 % 4 % Typ e I Erro r (Declare P1 0 acceptabl e whe n i t i s not acceptable )

5% 6% Tru e P I 0 (ug/dL ) 7 % 8 %

P1 5 ERRO R RAT E A S A FUNCTIO N O F PARTICIPATIO N RAT E (3-Y R PROGRAM ) 7 0 -i
6 0

5 0

o I4 0

3 0

2 0

1 0 Typ e I I Erro r

(Declar e P1 5 unacceptabl e whe n i t I s acceptable )

0.50 % Typ e I Erro r (Declar e P1 5 acceptabl e whe n i t I s no t acceptable )

80/y r

0.75 % 1.00 % 1.25 % Tru e P 1 5 (ug/dL ) 1.50 % 2.00 %ATTACHMEN T 4 Estimatio n o f

Recruitmen tRat e
A s discusse dabove , achievin g a nadequat e participatio nrat e i s a nimportan t performanc e goa l o f th e LCCHP , an don e elemen t o f tha t goa l i s achievin g a nadequat e recruitmen t o f ne w (previousl y untested ) participant s i n t o th e progra meac hyear . However , measuremen t o f th e recruitmen t

rat e i s no t

simple , sinc e achil di s counte da s havin g participate di f he/sh e i s teste d anytim e durin g a6-year

period , rathe r

tha ndurin g som e specifie dnarro w tim e window
. I n addition , th e populatio no f childre nchange s eac hyear , a s ne w childre nar e bor no r mov e int o th e site , andas childre nmov e awa y or "graduate " (i.e. , reac han age of 73 month s or

more)
. I norde r t o evaluat e th e relativ e merit s o f severa l alternativ e metric s tha t migh t b e use dt o quantify recruitmen t

rate , ascreening-leve l populatio nmode l wa s constructed
. Fo r th e purpose s o f thi s model , th e followin g definition s an dterm s ar e employed : "recruitment " i s define da s th e first-tim e donatio no f abloo dsampl e b y a n eligibl e chil d "eligibl e child " i s define da s achil dlivin g i nth e sit e betwee n6 month s an d7 2 month s o f ag e wh o ha s no t

previousl y participate di n th e LCCH Pbloo dlea dprogra m "newl y eligible " mean s achil dwh o i s bo mt o afamil y residin g i n th e sit e o r achil dag e 6 t o 7 2 month s wh o move s int o th e sit e Fo r simplicity , th e mode l assume da"stationary " population
. Tha t is , th e tota l numbe r

o f childre nag e 6-7 2 month s wh o ente r th e populatio neac hyea r

i s equa l t o th e numbe r

wh o mov e awa y o r "graduate"
. Base do n thi s assumption , th e mode l wa s constructe da s follows : Le t N equa l th e tota l numbe r o f childre nag e 6-7 2 month s o f ag e wh o liv e i n th e site
. Becaus e o f

th e assumptio ntha t

th e populatio ni s stationary , Ni s constan t an ddoe s no t chang e ove r

tim e Le t Ne(t ) equal th e numbe r

o f eligibl e childre n i n yea

r t Le t p(t ) equa l th e numbe r

o f eligibl e childre nwh o ar e teste di nyea r t Le t qequa l th e numbe r

o f childre nwh o ente r

th e populatio neac hyear . Becaus e o f th e assumptio ntha t

th e populatio ni s stationary , thi s i s als o th e numbe r o f childre nwh o leav e th e populatio neac hyear . Base do nthes e definitions , th e recruitmen t rat e (RR ) i nyea r

t i s give nby :

### RR(t ) = p(t)/Ne(t )

Th e numbe r

o f eligibl e childre ni nyea r

t i s equa l t o th e numbe r

o f eligibl e childre ni nyea r

t-1 , plu s th e numbe r

o f newl y eligibl e childre nwh o joi nth e population , minu s th e numbe r o f eligibl e childre nwh o wer e teste dan dth e numbe r wh o leav e th e populatio nwithou t havin g bee ntested : Ne(t ) = Ne(t-l ) + q- p(t ) - q*( l - p(t)/Ne(t-1) ) Thus : PR(t ) = p(t ) /

[Ne(t-l ) + q- p(t ) - q*(l-p(t)/Ne(t-l) ] I norde r t o implemen t

th e model , th e valu e o f

Nwa s assume dt o b e 500 , an dth e valu e o f qwa s assume dt o b e 80
. A t

t = 0 , th e valu e o f

Ne(t ) = N= 500
. Fo r

simplicit y i t

wa s assume dtha t

p(t ) i s approximatel y constan t

ove r time , an dha s avalu e o f

50
. Thes e value s ar e arbitrary , bu t ar e fairl y realisti c base do nth e bes t informatio navailabl e fo r

th e community
. Base do nthes e assumptions , th e valu e o f R Ra s afunctio no f

tim e i s a s show ni nFigur e A4-1
. A s seen , th e initia l valu e o f R Ri s 50/50 0 = 10% , bu t

thi s valu e increas e ove r

tim e a s eligibl e childre nar e teste di nsubsequen t years . Ultimately , th e recruitmen t rat e plateau s a t

avalu e o f 62.5% , whic hi s equa l t o th e numbe r o f newl y teste dchildre neac hyear divide db y th e numbe r

o f newl y eligibl e childre nenterin g th e populatio neac hyear : Platea u valu e o f

R R= p/ q Th e platea u valu e i s alway s give nb y th e rati o p/q , regardles s o f th e assume dnumeri c value s o f N , qan dp . Th e tim e t o reac hth e platea u decrease s a s th e valu e o f p/ qincreases
. Eve nthoug hthi s mode l i s highl y simplified , i t reveal s tha t

th e rati o o f

p t o qi s ausefu l indicato r o f th e recruitmen t

rate , an dthi s rati o wa s selecte da s th e metri c fo r us e b y th e LCCHP
.FIGUR E A4-1 . POPULATIO N MODE L RESULT S

70 % 60 % - g 2 50 % - | 40 % 1 o > 30 % -

O

. Q

. 20 %
10 %
0 % - Yearl yRat e -Tested/Ne w

1 0 1 5 2 0

Yea ro f Progra m 2 5 3 0 3 5ATTACHMEN T 5 Dat aan d Exampl e Calculatio n o f Annua l Recruitmen tRat eLak e Count y Yea r 200 0 Censu s Dat a Compilatio n fo r Youn g Childre n ( 0 t o 7 2 months )

Percentag e o f Lake County' s Youn g Childre n Wh o Resid e withi n OU 9 Censu s Are a Trac t 96 1 6 Trac t 96 1 7 Trac t 96 1 8 Lake Count y Bloc k 20 1 2 , Trac t 96 1 8 Trac t 961 7 an d Bloc k 201 2 Descriptio n

Count yare a nort h o f Leadvill e Leadvill e an d outlyin g area s t o sout h Countyare a approximatel ysouthwes t o f Cal

. Gulc h Entire count y are a Include s al l o f Lak e For k Traile rPar k Al l area s withi n OU 9 Withi n OU9 ? n o ye s partiall y ye s ye s Numbe ro f Childre n 0 t o

7 2 Month s Ol d 21 0 42 8 9 0 72 8 5 8 48 6 Percentag e o f Youn g

Childre n Count

yWid e 0.2 9 0.5 9 0.1 2 1.00

- 0.6 7

Recruitmen t Rat e i n LCCH P Bloo d Lea d Monitorin g Progra m (withi n OU 9 boundaries )

Yea r 199 3 199 4 199 5 199 6 199 7 199 8 199 9 200 0 200 1 Live-birth s Coun t

9 2 9 6 11 2 11 4 100 12 9 13 3 139 NA Kindergarte n Coun t

11 3 12 4 11 7 10 2 9 8 11 5 10 6 Ne wChildre n

Move d I n

1 0 2 3

- 8 Ne wEligibl e Childre n

Lake County

11 0 13 1 13 6 13 1 OU 9

7 4 8 8 9 1 8 8 First-tim e Teste d

OU 9 152(1994+1995 ) 14 9 14 5 8 8 7 7 8 7 61 Recruitmen t Rat e Inde x OU 9

119 % 88 % 95 % 69 % Notes: Live-births

Count from Lake County Health Department. Kindergarten

Count from The Center based on number of children 5 years and older on October 1 of calendar year. New Children Moved In is the kindergarten

count this year minus the live births 5 years previous. New Eligible Children/Lake

County is the sum of # of live births from previous year and # of children moved into site. New Eligible Chi/dren/OU9

represents

67 percent of Lake County value. Participation

Rate is the first-time tested count divided by the estimate of new eligible children in OU9. Italics indicates estimated

values. NA=

Not Available.

# I I I I I I I I I I I I I I I I I I I ATTACHMEN T 6 CRYSTA L BAL L SPREADSHEE T FO RESTIMATIN G UNCERTAINT Y I N P1 0 ESTIMATE S

# I I I I I I I I I I I I I I I I I I I ATTACHMEN T 7 EXCE L SPREADSHEE T FO REVALUATIO N O F SOI L LEA D DISTRIBUTION S

# I I I I I I I I I I I I I I I I I I I TES T O F SOI L LEA D REPRESENTATIVENES S

A statistica l tes t

wil l b e performe dt o determin e i f th e populatio no f

childre nwh o participat e i n th e bloo dlea dprogra mar e fro mresidence s tha t d o no t adequatel y represen t

th e uppe r en do f th e soi l lea ddistributio ni nth e statistica l unit
. Le t F l an dF 2 represen t

th e tru e (bu t

unknown ) fractio no f eac hpopulatio ntha t

i s abov e some specifie dsoi l lea dlevel
. Th e inpu t parameter s o f th e tes t ar e th e following : Dat aSe t Soi l lea dvalue s fro mbloo d lea dprogra mparticipant s Al l soi l lea dvalue s fro mth e Statistica l Uni t Numbe r

n l

n 2 

### Observe dproportio ngreate r

tha nth e selecte dvalu e P I P 2



### Fo r larg e n l an dn2 , th e probabilit y tha t F l i s lowe r

tha nF 2 i s estimate dby : p = 1 - NORMSDIST(z ) wher e z = (P1-P2 ) / sqrt (P 1 * ( 1 -P 1 )/n1 + P2 ( 1 -P2)/n2 ) Th e powe r

o f thi s tes t t o detec t adifferenc e o f

siz e delt abetwee nF l an dF 2 a t th e 5 % confidenc e limi t

i s estimate dby : Powe r = NORMSDIST(Zb ) wher e Z b = delta/sqrt((Pl*(l-Pl)/n l + P2(l-P2)/n2 ) - 1.64 5 Th e usua l decisio nrul e fo r declarin g tha t

F l i s lowe r

tha nF 2 i s tha t

p < 0.05
. However , i f powe r o f th e tes t i s lo w (thi s i s mainl y afunctio no f n l an dn2) , the nther e i s decrease d confidenc e i ndecision s wher e p > 0.05
. I norde r t o addres s this , th e decisio nrul e use di nthi s progra mis : Declar e F l t o b e lowe r

tha nF 2 i f p < a , wher e a= 0.0 5 /

power . I nthi s case , Performanc e Standar d4 wil l no t b e satisfie dunles s i t

i s no t possibl e t o addres s th e proble mi napractica l way .

# I I I I I I I I I I I I I I I I I I I ATTACHMEN T 8 DAT A REDUCTIO N

APPROAC H

# 1 1 1 1

• 

# 1

• 

# 1

• 

# • 

# 1 1 MEM O

To : Rebecc aThoma s From : Bil l Bratti n Date : 12/17/9 7 Subject : Dat aReductio n Approac h Rebecca : I n accor dwit hth e agreement s reache ddurin g th e conferenc e cal l today , th e followin g i s th e fo r calculatio n o f

summar y statistic s fo r

bloo dlea ddat areporte db y th e Lak e Count y Healt h Department
. Questio n 1 : Wha t ag e grou p shoul db e evaluated ? Plan : pla n

Childre n ag e 6-7 2 month s (inclusive ) wil l b e include di n calculatio n o f summary statistics
. Th e ag e a t tim e o f bloo dsamplin g wil l b e calculate db y subtractin g Dat e o f Birthfro mSampl e Date , 

# 1 1 1

1
1 1 1 an dth e resul t wil l b e expresse di n month s (rounde dt o th e neares t whol e month)
. Questio n 2 : Wha t restriction s shoul db e place do n lengt ho f tim e a t curren t residenc e and/o r

lengt ho f tim e i n Leadville ? Plan : Bloo dlea ddat afo r

childre n wh o hav e reside di n Leadvill e fo r les s tha n 3 month s shoul db e exclude di n th e calculatio n o f summary statistics
. Questio n 3 : Wha t area s shoul db e include di n statistica l summaries ? Plan : Overal l summar y statistic s presente di n th e Propose dPla n wil l includ e Area s A- Gonly
. Statistic s fo r

Are aH ma y b e helpfu l later
.

# I I I I I I I I I I I I I I I I I I I Questio n4 :

Wha t ar e th e approximat e quantitatio nlimit s fo r capillar y bloo dan dvenou s blood ? Ho w shoul d sample s wit hvalue s a t

o r belo w th e quantitatio nlimit s b e handled ? Plan : Base do navailabl e information , i t appear s tha t

th e detectio nlimi t

fo r bot hvenou s an dcapillar y sample s wa s abou t

2 ug/d Li n199 6 an dearlier , an di s abou t 1 ug/d Lfo r

dat areporte di n1997
. (Thi s i s du e t o achang e i n laboratories)
. Unles s dat abecom e availabl e t o th e contrary , al l value s o f 2 ug/d Lreporte di n199 6 an dearlie r an dal l value s o f

1 ug/d Lreporte di n199 7 an dlate r wil l b e assume dt o b e non-detect s an dwil l b e evaluate db y assignin g avalu e equa l t o 1/ 2 th e detectio n limit
. Questio n5 : Ho w shoul dmultipl e bloo dlea ddat afro maspecifi c chil db e evaluated ? Plan :
a ) Dat afo r

achil dshoul db e average dwithi nayear , bu t no t acros s years . b ) I f al l o f th e sample s withi nayea r ar e th e sam e typ e (eithe r

capillar y o r

venous) , simpl y averag e al l value s fo r

th e year . I f

bot htype s o f

value s ar e presen t

withi nayear , averag e onl y th e venou s data
. c ) Th e ag e tha t

i s assigne dt o th e averag e bloo dlea dshoul db e th e averag e fo r th e actua l age s a t th e tim e o f

eac hsampl e used
. d ) I f achil dmove s withi nayea r s o tha t som e bloo dlea ddat awithi nth e yea r appl y t o on e are aan dothe r

dat aappl y t o adifferen t

area , assig nth e mea nbloo dlea dvalu e t o th e are a wher e th e chil dreside dwhe nth e firs t bloo dsampl e wa s taken
. e ) Becaus e o f

th e potentia l bia s introduce db y th e tendenc y fo r childre nwit helevate dbloo d lead s t o underg o repea t

testin g acros s multipl e years , tw o type s o f analysi s ar e appropriate :

« Al l childre n(whethe r

o r no t the y hav e bee nteste di npreviou s years ) Onl y childre nwh o hav e no t bee nteste di n previou s year s Thes e tw o type s o f

analysi s shoul db e clearl y labele ds o the y ar e no t confuse dwit h eac hother
.

# I I

I Questio n6 :

Wha t i s th e meanin g o f

zer o entere dunde r

bloo dlea di nth e database ? Doe s thi s mea ntha t a • reliabl e analysi s wa s no t achieved ? Plan :

• A zer o mean s tha t ther e wa s insufficien t

bloo dvolum e t o perfor ma n analysis
. Al l "missing " value s wil l b e remove dfro mth e dat aset
. I Questio n7 :

• Shoul dth e reporte dstatisti c o f centra l tendenc y b e th e arithmeti c mea no r th e geometri c mean ? Proposal : | Th e geometri c mea nwil l b e reported
. 

# I I I I I I I I I I I

# TARGE T SHEE T EP AREGIO N VII I SUPERFUN D DOCUMEN TMANAGEMEN TSYSTE M DOCUMEN TNUMBER : 203705 2 SIT E NAME : CALIFORNI A GULC H DOCUMEN TDATE : 07/01/200 2



## DOCUMEN T NO T SCANNE D Du e t o on e o f th e followin g reasons : D PHOTOGRAPH S D 3-DIMENSIONA L D OVERSIZE D 0 AUDIO/VISUA L D PERMANENTL Y BOUN D DOCUMENT S D POO R LEGIBILIT

Y D OTHE R D NO T AVAILABL E D TYPE S O F DOCUMENT S NO T T O B E SCANNE D 

### (Dat a Packages , Dat a Validation , Samplin g Data , CBI , Chai n o f Custody ) DOCUMEN T DESCRIPTION : C D - LCCH P ATTACHMENT S 2

. 6

. & 7 (MA Y 2002 )

Contac t th e Superfun d Record s Cente rt o vie wavailabl e document

. (303)312-647 3