Optimum allocation for a dual-frame telephone survey
3. Screening protocolOptimum 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 , o p t
=
L
R
A
/
c
A
n
B , o p t
=
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
)
Editorial policy
Survey Methodology publishes articles dealing with various aspects of statistical development relevant to a statistical agency, such as design issues in the context of practical constraints, use of different data sources and collection techniques, total survey error, survey evaluation, research in survey methodology, time series analysis, seasonal adjustment, demographic studies, data integration, estimation and data analysis methods, and general survey systems development. The emphasis is placed on the development and evaluation of specific methodologies as applied to data collection or the data themselves. All papers will be refereed. However, the authors retain full responsibility for the contents of their papers and opinions expressed are not necessarily those of the Editorial Board or of Statistics Canada.
Submission of Manuscripts
Survey Methodology is published twice a year in electronic format. Authors are invited to submit their articles in English or French in electronic form, preferably in Word to the Editor, (statcan.smj-rte.statcan@canada.ca , Statistics Canada, 150 Tunney’s Pasture Driveway, Ottawa, Ontario, Canada, K1A 0T6). For formatting instructions, please see the guidelines provided in the journal and on the web site (www.statcan.gc.ca/SurveyMethodology).
Note of appreciation
Canada owes the success of its statistical system to a long-standing partnership between Statistics Canada, the citizens of Canada, its businesses, governments and other institutions. Accurate and timely statistical information could not be produced without their continued co-operation and goodwill.
Standards of service to the public
Statistics Canada is committed to serving its clients in a prompt, reliable and courteous manner. To this end, the Agency has developed standards of service which its employees observe in serving its clients.
Copyright
Published by authority of the Minister responsible for Statistics Canada.
© Minister of Industry, 2015
Catalogue no. 12-001-X
Frequency: semi-annual
Ottawa
Date modified:
2017-09-20