Optimum allocation for a dual-frame telephone survey 3. Screening protocol

In the screening protocol, one conducts survey interviews for all units in the landline sample s A . MathType@MTEF@5@5@+= feaagKart1ev2aqatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr 4rNCHbGeaGqiFu0Je9sqqrpepC0xbbL8F4rqqrpipeea0xe9Lq=Je9 vqaqFeFr0xbbG8FaYPYRWFb9fi0FXxbbf9=e0dfrpm0dXdHqVu0=vr 0=vr0=fdbaqaaeGacaGaaiaabeqaamaabaabaaGcbaGaam4CamaaBa aaleaacaWGbbaabeaakiaac6caaaa@39B2@ One conducts screening interviews (for telephone status) for all units in the cell-phone sample s B MathType@MTEF@5@5@+= feaagKart1ev2aqatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr 4rNCHbGeaGqiFu0Je9sqqrpepC0xbbL8F4rqqrpipeea0xe9Lq=Je9 vqaqFeFr0xbbG8FaYPYRWFb9fi0FXxbbf9=e0dfrpm0dXdHqVu0=vr 0=vr0=fdbaqaaeGacaGaaiaabeqaamaabaabaaGcbaGaam4CamaaBa aaleaacaWGcbaabeaaaaa@38F7@ and then conducts the survey interviews only for the units that screen-in as CPO. Therefore, expected data collection costs arise according to the model

C S C = c A n A + c B β n B + c B ( 1 β ) n B = c A n A + c B n B , ( 3.1 ) MathType@MTEF@5@5@+= feaagKart1ev2aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr 4rNCHbGeaGqiFu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq=Jc9 vqaqpepm0xbba9pwe9Q8fs0=yqaqpepae9pg0FirpepeKkFr0xfr=x fr=xb9adbaqaaeGaciGaaiaabeqaamaabaabaaGcbaaeaaaaaaaaa8 qafaqaaeGacaaabaGaam4qa8aadaWgaaWcbaWdbiaadofacaWGdbaa paqabaaak8qabaGaeyypa0Jaam4ya8aadaWgaaWcbaWdbiaadgeaa8 aabeaak8qacaWGUbWdamaaBaaaleaapeGaamyqaaWdaeqaaOWdbiab gUcaRiqadogagaqbamaaBaaaleaacaWGcbaabeaakiabek7aIjaad6 gapaWaaSbaaSqaa8qacaWGcbaapaqabaGcpeGaey4kaSIabm4yayaa gaWaaSbaaSqaaiaadkeaaeqaaOWaaeWaa8aabaWdbiaaigdacqGHsi slcqaHYoGyaiaawIcacaGLPaaacaWGUbWdamaaBaaaleaapeGaamOq aaWdaeqaaaGcpeqaaaqaaiabg2da9iaadogapaWaaSbaaSqaa8qaca WGbbaapaqabaGcpeGaamOBa8aadaWgaaWcbaWdbiaadgeaa8aabeaa k8qacqGHRaWkceWGJbGbaibadaWgaaWcbaGaamOqaaqabaGccaWGUb WdamaaBaaaleaapeGaamOqaaWdaeqaaOWdbiaacYcaaaWdaiaaywW7 caaMf8UaaGzbVlaaywW7caaMf8UaaiikaiaaiodacaGGUaGaaGymai aacMcaaaa@6546@

where c B MathType@MTEF@5@5@+= feaagKart1ev2aqatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr 4rNCHbGeaGqiFu0Je9sqqrpepC0xbbL8F4rqqrpipeea0xe9Lq=Je9 vqaqFeFr0xbbG8FaYPYRWFb9fi0FXxbbf9=e0dfrpm0dXdHqVu0=vr 0=vr0=fdbaqaaeGacaGaaiaabeqaamaabaabaaGcbaaeaaaaaaaaa8 qaceWGJbGbauaadaWgaaWcbaGaamOqaaqabaaaaa@3913@ is the cost per completed screener (to ascertain telephone status) in sample s B , MathType@MTEF@5@5@+= feaagKart1ev2aqatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr 4rNCHbGeaGqiFu0Je9sqqrpepC0xbbL8F4rqqrpipeea0xe9Lq=Je9 vqaqFeFr0xbbG8FaYPYRWFb9fi0FXxbbf9=e0dfrpm0dXdHqVu0=vr 0=vr0=fdbaqaaeGacaGaaiaabeqaamaabaabaaGcbaGaam4CamaaBa aaleaacaWGcbaabeaakiaacYcaaaa@39B1@ c B MathType@MTEF@5@5@+= feaagKart1ev2aqatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr 4rNCHbGeaGqiFu0Je9sqqrpepC0xbbL8F4rqqrpipeea0xe9Lq=Je9 vqaqFeFr0xbbG8FaYPYRWFb9fi0FXxbbf9=e0dfrpm0dXdHqVu0=vr 0=vr0=fdbaqaaeGacaGaaiaabeqaamaabaabaaGcbaGabm4yayaaga WaaSbaaSqaaiaadkeaaeqaaaaa@38F4@ is the cost per completed screener and interview in sample s B , MathType@MTEF@5@5@+= feaagKart1ev2aqatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr 4rNCHbGeaGqiFu0Je9sqqrpepC0xbbL8F4rqqrpipeea0xe9Lq=Je9 vqaqFeFr0xbbG8FaYPYRWFb9fi0FXxbbf9=e0dfrpm0dXdHqVu0=vr 0=vr0=fdbaqaaeGacaGaaiaabeqaamaabaabaaGcbaGaam4CamaaBa aaleaacaWGcbaabeaakiaacYcaaaa@39B1@ and c B = c B β + c B ( 1 β ) . MathType@MTEF@5@5@+= feaagKart1ev2aqatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr 4rNCHbGeaGqiFu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq=Jc9 vqaqpepm0xbba9pwe9Q8fs0=yqaqpepae9pg0FirpepeKkFr0xfr=x fr=xb9adbaqaaeGaciGaaiaabeqaamaabaabaaGcbaaeaaaaaaaaa8 qaceWGJbGbaibadaWgaaWcbaGaamOqaaqabaGccqGH9aqpceWGJbGb auaadaWgaaWcbaGaamOqaaqabaGccqaHYoGycqGHRaWkceWGJbGbay aadaWgaaWcbaGaamOqaaqabaGcdaqadaWdaeaapeGaaGymaiabgkHi Tiabek7aIbGaayjkaiaawMcaaiaac6caaaa@4514@ In this notation, n A MathType@MTEF@5@5@+= feaagKart1ev2aqatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr 4rNCHbGeaGqiFu0Je9sqqrpepC0xbbL8F4rqqrpipeea0xe9Lq=Je9 vqaqFeFr0xbbG8FaYPYRWFb9fi0FXxbbf9=e0dfrpm0dXdHqVu0=vr 0=vr0=fdbaqaaeGacaGaaiaabeqaamaabaabaaGcbaaeaaaaaaaaa8 qacaWGUbWdamaaBaaaleaapeGaamyqaaWdaeqaaaaa@393F@ is the number of survey interviews completed amongst landline respondents and n B MathType@MTEF@5@5@+= feaagKart1ev2aqatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr 4rNCHbGeaGqiFu0Je9sqqrpepC0xbbL8F4rqqrpipeea0xe9Lq=Je9 vqaqFeFr0xbbG8FaYPYRWFb9fi0FXxbbf9=e0dfrpm0dXdHqVu0=vr 0=vr0=fdbaqaaeGacaGaaiaabeqaamaabaabaaGcbaaeaaaaaaaaa8 qacaWGUbWdamaaBaaaleaapeGaamOqaaWdaeqaaaaa@3940@ is the number of completed interviews (telephone screener only for non-CPO respondents, and screener plus survey interview for CPO respondents) amongst cell-phone respondents. That is, the expected total number of completed survey interviews is n A + ( 1 β ) n B . MathType@MTEF@5@5@+= feaagKart1ev2aqatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr 4rNCHbGeaGqiFu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq=Jc9 vqaqpepm0xbba9pwe9Q8fs0=yqaqpepae9pg0FirpepeKkFr0xfr=x fr=xb9adbaqaaeGaciGaaiaabeqaamaabaabaaGcbaaeaaaaaaaaa8 qacaWGUbWdamaaBaaaleaapeGaamyqaaWdaeqaaOWdbiabgUcaRmaa bmaapaqaa8qacaaIXaGaeyOeI0IaeqOSdigacaGLOaGaayzkaaGaam OBa8aadaWgaaWcbaWdbiaadkeaa8aabeaakiaac6caaaa@40D7@

The unbiased estimator of the overall population total is

Y ^ = Y ^ A + Y ^ b   , ( 3.2 ) MathType@MTEF@5@5@+= feaagKart1ev2aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr 4rNCHbGeaGqiFu0Je9sqqrpepC0xbbL8F4rqqrpipeea0xe9Lq=Je9 vqaqFeFr0xbbG8FaYPYRWFb9fi0FXxbbf9=e0dfrpm0dXdHqVu0=vr 0=vr0=fdbaqaaeGacaGaaiaabeqaamaabaabaaGcbaGabmywayaaja aeaaaaaaaaa8qacqGH9aqppaGabmywayaajaWaaSbaaSqaa8qacaWG bbaapaqabaGcpeGaey4kaSYdaiqadMfagaqcamaaBaaaleaapeGaam OyaaWdaeqaaOWdbiaabckacaGGSaGaaGzbVlaaywW7caaMf8UaaGzb VlaaywW7caGGOaGaaG4maiaac6cacaaIYaGaaiykaaaa@4B8F@

where Y ^ A = ( N A / n A ) y A , MathType@MTEF@5@5@+= feaagKart1ev2aqatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr 4rNCHbGeaGqiFu0Je9sqqrpepC0xbbL8F4rqqrpipeea0xe9Lq=Je9 vqaqFeFr0xbbG8FaYPYRWFb9fi0FXxbbf9=e0dfrpm0dXdHqVu0=vr 0=vr0=fdbaqaaeGacaGaaiaabeqaamaabaabaaGcbaGabmywayaaja WaaSbaaSqaaabaaaaaaaaapeGaamyqaaWdaeqaaOWdbiabg2da9maa bmaapaqaa8qadaWcgaqaaiaad6eapaWaaSbaaSqaa8qacaWGbbaapa qabaaak8qabaGaamOBa8aadaWgaaWcbaWdbiaadgeaa8aabeaaaaaa k8qacaGLOaGaayzkaaGaamyEa8aadaWgaaWcbaWdbiaadgeaa8aabe aakiaacYcaaaa@430B@ Y ^ b = ( N B / n B ) y b , MathType@MTEF@5@5@+= feaagKart1ev2aqatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr 4rNCHbGeaGqiFu0Je9sqqrpepC0xbbL8F4rqqrpipeea0xe9Lq=Je9 vqaqFeFr0xbbG8FaYPYRWFb9fi0FXxbbf9=e0dfrpm0dXdHqVu0=vr 0=vr0=fdbaqaaeGacaGaaiaabeqaamaabaabaaGcbaGabmywayaaja WaaSbaaSqaaabaaaaaaaaapeGaamOyaaWdaeqaaOWdbiabg2da9maa bmaapaqaa8qadaWcgaqaaiaad6eapaWaaSbaaSqaa8qacaWGcbaapa qabaaak8qabaGaamOBa8aadaWgaaWcbaWdbiaadkeaa8aabeaaaaaa k8qacaGLOaGaayzkaaGaamyEa8aadaWgaaWcbaWdbiaadkgaa8aabe aakiaacYcaaaa@434F@ and y A = y a + y a b . MathType@MTEF@5@5@+= feaagKart1ev2aqatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr 4rNCHbGeaGqiFu0Je9sqqrpepC0xbbL8F4rqqrpipeea0xe9Lq=Je9 vqaqFeFr0xbbG8FaYPYRWFb9fi0FXxbbf9=e0dfrpm0dXdHqVu0=vr 0=vr0=fdbaqaaeGacaGaaiaabeqaamaabaabaaGcbaaeaaaaaaaaa8 qacaWG5bWdamaaBaaaleaapeGaamyqaaWdaeqaaOWdbiabg2da9iaa dMhapaWaaSbaaSqaa8qacaWGHbaapaqabaGcpeGaey4kaSIaamyEa8 aadaWgaaWcbaWdbiaadggacaWGIbaapaqabaGccaGGUaaaaa@4185@ The variance of the estimator is

Var { Y ^ } = N 2 ( R A 2 n A + R B 2 n B )   , ( 3.3 ) MathType@MTEF@5@5@+= feaagKart1ev2aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr 4rNCHbGeaGqiFu0Je9sqqrpepC0xbbL8F4rqqrpipeea0xe9Lq=Je9 vqaqFeFr0xbbG8FaYPYRWFb9fi0FXxbbf9=e0dfrpm0dXdHqVu0=vr 0=vr0=fdbaqaaeGacaGaaiaabeqaamaabaabaaGcbaaeaaaaaaaaa8 qacaqGwbGaaeyyaiaabkhadaGadaWdaeaaceWGzbGbaKaaa8qacaGL 7bGaayzFaaGaeyypa0JaamOta8aadaahaaWcbeqaa8qacaaIYaaaaO WaaeWaa8aabaWdbmaalaaapaqaa8qacaWGsbWdamaaDaaaleaapeGa amyqaaWdaeaapeGaaGOmaaaaaOWdaeaapeGaamOBa8aadaWgaaWcba Wdbiaadgeaa8aabeaaaaGcpeGaey4kaSYaaSaaa8aabaWdbiaadkfa paWaa0baaSqaa8qacaWGcbaapaqaa8qacaaIYaaaaaGcpaqaa8qaca WGUbWdamaaBaaaleaapeGaamOqaaWdaeqaaaaaaOWdbiaawIcacaGL PaaacaGGGcGaaiilaiaaywW7caaMf8UaaGzbVlaaywW7caaMf8Uaai ikaiaaiodacaGGUaGaaG4maiaacMcaaaa@5A43@

where

R A 2 = W A 2 S A 2 MathType@MTEF@5@5@+= feaagKart1ev2aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr 4rNCHbGeaGqiFu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq=Jc9 vqaqpepm0xbba9pwe9Q8fs0=yqaqpepae9pg0FirpepeKkFr0xfr=x fr=xb9adbaqaaeGaciGaaiaabeqaamaabaabaaGcbaaeaaaaaaaaa8 qacaWGsbWdamaaDaaaleaapeGaamyqaaWdaeaapeGaaGOmaaaakiab g2da9iaadEfapaWaa0baaSqaa8qacaWGbbaapaqaa8qacaaIYaaaaO Gaam4ua8aadaqhaaWcbaWdbiaadgeaa8aabaWdbiaaikdaaaaaaa@3F72@

and

R B 2 = W B 2 S b 2 { 1 β + β ( 1 β ) Y ¯ b 2 S b 2 }   . MathType@MTEF@5@5@+= feaagKart1ev2aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr 4rNCHbGeaGqiFu0Je9sqqrpepC0xbbL8F4rqqrVeFfea0xe9Lq=Je9 vqaqFeFr0xbba9Fa0P0RWFb9fq0FXxbbf9=e0dfrpm0dXdirVu0=vr 0=vr0=fdbaqaaeGaciGaaiaabeqaamaabaabaaGcbaaeaaaaaaaaa8 qacaWGsbWdamaaDaaaleaapeGaamOqaaWdaeaapeGaaGOmaaaakiab g2da9iaadEfapaWaa0baaSqaa8qacaWGcbaapaqaa8qacaaIYaaaaO Gaam4ua8aadaqhaaWcbaWdbiaadkgaa8aabaWdbiaaikdaaaGcdaGa daWdaeaapeGaaGymaiabgkHiTiabek7aIjabgUcaRiabek7aInaabm aapaqaa8qacaaIXaGaeyOeI0IaeqOSdigacaGLOaGaayzkaaWaaSaa a8aabaGabmywayaaraWaa0baaSqaa8qacaWGIbaapaqaa8qacaaIYa aaaaGcpaqaa8qacaWGtbWdamaaDaaaleaapeGaamOyaaWdaeaapeGa aGOmaaaaaaaakiaawUhacaGL9baacaGGGcGaaiOlaaaa@5683@

The optimal allocation of the total sample is

n A, opt = L R A / c A n B, opt = L R B / c B , MathType@MTEF@5@5@+= feaagKart1ev2aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr 4rNCHbGeaGqiFu0Je9sqqrpepC0xbbL8F4rqqrpipeea0xe9Lq=Je9 vqaqFeFr0xbbG8FaYPYRWFb9fi0FXxbbf9=e0dfrpm0dXdHqVu0=vr 0=vr0=fdbaqaaeGacaGaaiaabeqaamaabaabaaGcbaqbaeaabiWaaa qaaabaaaaaaaaapeGaamOBa8aadaWgaaWcbaWdbiaadgeacaGGSaGa aeiOaiaad+gacaWGWbGaamiDaaWdaeqaaaGcbaGaeyypa0dabaWdbm aalyaabaGaamitaiaadkfapaWaaSbaaSqaa8qacaWGbbaapaqabaaa k8qabaWaaOaaa8aabaWdbiaadogapaWaaSbaaSqaa8qacaWGbbaapa qabaaapeqabaaaaaGcpaqaa8qacaWGUbWdamaaBaaaleaapeGaamOq aiaacYcacaqGGcGaam4BaiaadchacaWG0baapaqabaaakeaacqGH9a qpaeaapeWaaSGbaeaacaWGmbGaamOua8aadaWgaaWcbaWdbiaadkea a8aabeaaaOWdbeaadaGcaaWdaeaapeGabm4yayaasaWaaSbaaSqaai aadkeaaeqaaaqabaaaaOGaaiilaaaaaaa@524C@

where L   MathType@MTEF@5@5@+= feaagKart1ev2aqatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr 4rNCHbGeaGqiFu0Je9sqqrpepC0xbbL8F4rqqrpipeea0xe9Lq=Je9 vqaqFeFr0xbbG8FaYPYRWFb9fi0FXxbbf9=e0dfrpm0dXdHqVu0=vr 0=vr0=fdbaqaaeGacaGaaiaabeqaamaabaabaaGcbaaeaaaaaaaaa8 qacaWGmbGaaiiOaaaa@3921@ is a constant that depends on the fixed constraint: cost or variance. The minimum variance subject to fixed cost is given by

min [ Var { Y ^ } ] = ( c A R A + c B R B ) 2 C S C   , ( 3.4 ) MathType@MTEF@5@5@+= feaagKart1ev2aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr 4rNCHbGeaGqiFu0Je9sqqrpepC0xbbL8F4rqqrpipeea0xe9Lq=Je9 vqaqFeFr0xbbG8FaYPYRWFb9fi0FXxbbf9=e0dfrpm0dXdHqVu0=vr 0=vr0=fdbaqaaeGacaGaaiaabeqaamaabaabaaGcbaaeaaaaaaaaa8 qaciGGTbGaaiyAaiaac6gadaWadaWdaeaapeGaciOvaiaacggacaGG YbWaaiWaa8aabaGabmywayaajaaapeGaay5Eaiaaw2haaaGaay5wai aaw2faaiabg2da9maalaaapaqaa8qadaqadaWdaeaapeWaaOaaa8aa baWdbiaadogapaWaaSbaaSqaa8qacaWGbbaapaqabaaapeqabaGcca WGsbWdamaaBaaaleaapeGaamyqaaWdaeqaaOWdbiabgUcaRmaakaaa paqaa8qaceWGJbGbaibadaWgaaWcbaGaamOqaaqabaaabeaakiaadk fapaWaaSbaaSqaa8qacaWGcbaapaqabaaak8qacaGLOaGaayzkaaWd amaaCaaaleqabaWdbiaaikdaaaaak8aabaWdbiaadoeapaWaaSbaaS qaa8qacaWGtbGaam4qaaWdaeqaaaaakmaaBaaaleaapeGaaeiOaaWd aeqaaOGaaiilaiaaywW7caaMf8UaaGzbVlaaywW7caaMf8Uaaiikai aaiodacaGGUaGaaGinaiaacMcaaaa@5FD4@

and the minimum cost subject to fixed variance is

min [ C S C ] = ( c A R A + c B R B ) 2 V 0   . ( 3.5 )

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