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Survey Sampling Techniques course is one of important courses in Statisitics. Major poiuts of this course are: probability sampling, confidence intervals, Two-stage cluster sampling, Two-stage cluster sampling, estimation for mean, choosing strata, allocation across strata, ratio estimation, domain estimation, Two-stage cluster sampling. Keywords in these slides are: Nonresponse, Design Phase, Weighting Adjustments, Imputation of Missing Values, Eligibility Known, Unit Nonresponse, Item Nonresp
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-^
-^
-^
Design
phase
After
data
collection
-^ Second
survey
to
collect
data
on
nonrespondents
(double
sampling) • Weighting
adjustments
-^ Imputation
of
missing
values
-^
-^
-^
-^
-^
n^ R
n
-^
Proportion
-^
Percentage
-^
R M^
nn n^
nR^ n nR^ n^100
nM n
Nonresponse
population
framework
Whole Population
elements with pop mean
1
^
Ui
i
U^
y N y
Nonresponse
framework
and
population
parameters
Nonresponse
population
framework
-^
Relationship
between
population
mean
and
means
for
responding
and
nonresponding
subpopulations
RU
RU
MU M
RU M
MU M
RU R
MU M
U
y
y
y N N
y N N
y N N
y N N
y N N y
)
(
)
(^1) (
RU R MU M
Ui R
i R
Ui M
i M
Ui
Ui
i
i
Ui
i
U^
y N N y N N
N
y N
N
y N N y y N y N
y^
R
M
M^
R
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)
1 ( )
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1
Derivation
Nonrespondents
Respondents
Sample
elements
mean ent
nonrespond
onn
informatio no
???
respond not will
units
sample^ M nM y
s
respondent
of
mean
(^1) sample
respond will SUs^
i
R R R
y
n n y
-^
the
population
mean
of
y^
for
the
nonresponding
subpopulation
and
the
population
mean
of
y^
for
the
responding
subpopulation
-^
Difference
between
population
means,
Nonesponse
rate,
n^ M
n^
n^ R
n
y^ MU yRU
RU
MU
y
y^
-^
Consider
likely
mechanisms
for
NR
when
designing
survey
-^
Reduce
respondent
burden
to
extent
possible
-^
Main
areas
-^
Survey
setting
and
timing
-^
Data
collection
methodology
-^ Burden
for
individual
-^
Sample
design
-^ Burden
for
population
-^
Remedies
for
avoiding
NR
also
tend
to
improve
data
quality
-^
Read
more
in
Chapter
8
of^
Lohr.
Strategy
2:
Use
data
from
call
‐backs
of
NR
cases
to
adjust
for
bias
-^
Select
a^
sample
from
the
nonrepsondents
to
the
survey
Collect
data
from
contacted
nonrespondents
Use
these
data
to
estimate
population
mean
for
nonrespondents
-^
Estimate
population
mean
for
whole
pop
with
a^
weighted
combination
of
respondent
sample
mean
and
nonrespondent
sample
mean
This
sample
design
is
an
example
of
“double”
or
‐phase”
sampling
(we
won’t
cover
this
in
y^ MU
y^ U
Sample
mean
from
responding
population
-^
Sample
mean
from
“call
‐back”
subset
of
nonresponding
population
(assume
response)
-^
Unbiased
estimator
for
population
mean
weighted
mean
of
two
sample
means
n^ R i
i R R
y n y^
1 1
n^ MCB i
i
MCB M
y
n y^
1 1
M M R R CB^
y n n y n n y^
ˆ
-^
^
^
2
2
2
2
) ˆ ( ) ˆ (
1 1
(^11)
(^11)
) ˆ( ˆ^ V
CB M M
CB R R M M R R
CB^
y y n n
y y n n
n s n
n n s n
n n
y
docsity.com
Basic
problem
for
unit
nonresponse
-^
In
general,
sample
may
not
reflect
composition
of
population
-^
-^
With
nonresponse,
even
if
we
start
with
a
“representative”
sample,
we
can
get
a
set
of
respondents
sample
that
do
not
reflect
the
composition
of
the
population
Basic
problem
for
unit
nonresponse
We
will
get
nonresponse
bias
from
an
unadjusted
sample
mean
of
respondents
if^
our
analysis
variable
is
related
to
the
nonresponse
mechanism
-^
Suppose
we
are
studying
a^ disease
that
is^
more
likely
to
occur
in
males
-^
y = j^
1 if
person
j^ has
the
disease,
0 otherwise
-^
Suppose
females
tend
to
respond
at
a^ higher
rate,
but
they
get
the
disease
less
often
-^
Using
a^ simple
mean
estimator
is^
likely
to
underestimate
the
true
disease
prevalence
in
the
population
-^
Remedy
(gender
as
groups,
or
post
‐strata):
make
an
estimate
for
males
and
an
estimate
for
females
and
pool
using
the
known
proportion
of
males
and
females
in^
the
target
population
