Sampling Techniques
By
Dr.S.Shaffi Ahamed
Why should we take sample?, Can’t we study the whole ?
It is possible
depends on objective
-to know how many live in a country
--age and sex categories
--changing pattern of age structure
--when plan for country
-Census
--death in a hospital
--record all the death
It is not possible
-to test the life of bulbs – burn bulbs till it lost its life
-count of RBW in blood – draw all the blood & count
-Count the stars in the sky
It is not necessary
- estimate Hb% in blood – a drop of blood is enough –
blood in any part of the body will provide same
Study subjects
(i) May be people
-healthy or sick
-census of a certain disease
- clients of a clinic
-workers in a certain occupation
-recipients of a specified Rx
-people exposed to certain stimuli
(ii)May not be people
-in the case of vital events (births, deaths)
-records (vital, medical or civil)
-population may consist of health centers
-village units or hospital units
(iii) Time
- a Wednesday clinic/February births
Sampling in Epidemiology
• Why?
• Unable to study all members of a
population
• Reduce bias
• Save time and money
• Measurements may be better in
sample than in entire population
• Feasibility
Value of careful sampling - Presidential elections
Early 20th century – opinion was sampled haphazardly by asking
passers-by on a street corner or selected group through mailed
questionnaire.
Then improved system – use of telephone directories or automobile
registration list or magazine subscription lists.
Literary Digest Magazine in USA in 1920, 1930 to predict election–
correct in 1920,1924,1928 and 1934 elections
but failed in 1936 used 2 million responses. They ignored lower
social classes who had neither telephone/automobiles.
Lessons were learned is the
The power of prediction is not necessarily a function of sample size;
and
(i) Sample should be representative of the population surveyed
When and Where sampling technique is
appropriate
• Vast data
– No. of units is very large-S economizes money,
time &effort
• When utmost accuracy is not required
– suitable in those situations where 100%
accuracy is not required
• Where census is impossible
-- not enumerating all individuals
• Homogeneity
– if all the units are alike. S is very easy to use
Sampling
Sampling is the process or technique of
selecting a sample of appropriate
characteristics and adequate size.
Sampling in Epidemiology
• Definitions
• Sampling unit – the basic unit around which a
sampling procedure is planned
• Person
• Group – household, school, district, etc.
• Component – eye, physiological response
• Sampling frame – list of all of the sampling
units in a population
• Sample – collection of sampling units from the
eligible population
Sampling in Epidemiology
•
• Random Sample
• Simple random sample
• Stratified random sample
• Cluster sample
• Adaptive cluster sample
• Multistage sample
Non-random Sample
• Convenience sample
• Systematic sample
• Consecutive sample
• Quota sample
• Volunteer sample
• Capture-recapture
Sampling in Epidemiology
• Probability (random) sampling
• Sampling in which each sampling unit has a
known and nonzero probability of being
included in the sample
• Replacement
• With replacement – sampling unit returned to
population before next sampling event
• Without replacement – sampling unit not
returned to population before next sampling
event

Simple Random Sampling Without Replacement A simple
random sample is one in which each of the possible samples of
elements taken from a population of elements has the same
probability of selection. In a simple random sample without
replacement, any element selected in a sample CANNOT be
selected again for the same sample.

EXAMPLE A school with 500 students is randomly giving away
five (5) prizes to its students during its year-end picnic. Each
student's name is entered on a slip of paper and placed in a
container. Names are to be drawn randomly from the container
by the principal of the school. After the name of the winner of
a prize is drawn and the prize awarded, the winner's name is
left out of the container (not replaced). Therefore, once a
student has been selected to win a prize, he or she cannot be
selected again.
Sampling in Epidemiology
• Simple random sampling
• Each sampling unit has an equal chance
of being included in the is sample
• In epidemiology, sampling generally
done without replacement as this
approach allows for a wider coverage of
sampling units, and as a result smaller
standard errors
Sampling in Epidemiology
• Simple random sampling
• Advantages
• Simple process and easy to understand
• Easy calculation of means and variance
• Disadvantages
• Not most efficient method, that is, not the
most precise estimate for the cost
• Requires knowledge of the complete
sampling frame
• Cannot always be certain that there is an
equal chance of selection
• Non respondents or refusals
Sampling in Epidemiology
•
Simple random sampling
•
Estimate hemoglobin levels in patients with sickle cell
anemia
1. Determine sample size
2. Obtain a list of all patients with sickle cell anemia
in a hospital or clinic
3. Patient is the sampling unit
4. Use Lottery method/ a table of random numbers to
select units from the sampling frame
5. Measure hemoglobin in all patients
6. Calculate mean and standard deviation of sample
SRS Methods
• Lottery Method
• Random Number Table method
Tables of random numbers
are used after numbers have been
assigned to numbers of the study
population. Use random number table
to select subject. Start anywhere.
Continue selecting until the desired
sample is reached
Random Number table
1
2
3
4
5
49486
93775
88744
80091
92732
94860
36746
04571
13150
65383
10169
95685
47585
53247
60900
12018
45351
15671
23026
55344
45611
71585
61487
87434
07498
89137
30984
18842
69619
53872
94541
12057
30771
19598
96069
89920
28843
87599
30181
26839
32472
32796
15255
39636
90819
Sampling in Epidemiology
• Systematic sampling
• The sampling units are spaced regularly
throughout the sampling frame, e.g., every 3rd
unit would be selected
• May be used as either probability sample or not
• Not a probability sample unless the starting point is
randomly selected
• Non-random sample if the starting point is
determined by some other mechanism than chance
Sampling in Epidemiology
• Systematic sample
• Advantages
• Sampling frame does not need to be defined in
advance
• Easier to implement in the field
• If there are unrecognized trends in the sample frame,
systematic sample ensure coverage of the spectrum
of units
• Disadvantages
• Variance cannot be estimated unless assumptions are
made
Sampling in Epidemiology
• Systematic sampling
• Estimate HIV prevalence in children born
during a specified period at a hospital
1. Impossible to construct sampling frame in
advance
2. Select a random number between some prespecified bounds
3. Beginning with the random number chosen, take
every 5th birth and measure for HIV infection
Sampling in Epidemiology
• Stratified random sample
• The sampling frame comprises
groups, or strata, with certain
characteristics
• A sample of units are selected
from each group or stratum
Stratified Random selection for drug trail in hypertension
Mild
Moderate
Severe
Sampling in Epidemiology
• Stratified random sample
• Advantages
• Assures that certain subgroups are represented in
a sample
• Allows investigator to estimate parameters in
different strata
• More precise estimates of the parameters
because strata are more homogeneous, e.g.,
smaller variance within strata
• Strata of interest can be sampled most
intensively, e.g., groups with greatest variance
• Administrative advantages
• Disadvantages
• Loss of precision if small number of units is
sampled from strata
Sampling in Epidemiology
• Stratified random sample
1.
2.
3.
4.
5.
• Assess dietary intake in adolescents
Define three age groups: 11-13, 14-16, 17-19
Stratify age groups by sex
Obtain list of children in this age range from
schools
Randomly select children from each of the 6
strata until sample size is obtained
Measure dietary intake
Sampling in Epidemiology
• Cluster sampling
• Clusters of sampling units are first
selected randomly
• Individual sampling units are then
selected from within each cluster
Sampling in Epidemiology
• Cluster sampling
• Advantages
• The entire sampling frame need not be enumerated
in advance, just the clusters once identified
• More economical in terms of resources than simple
random sampling
• Disadvantages
• Loss of precision, i.e., wider variance, but can be
accounted for with larger number of clusters
Sampling in Epidemiology
• Cluster sampling
1.
2.
3.
4.
• Estimate the prevalence of dental caries in
school children
Among the schools in the catchments area, list
all of the classrooms in each school
Take a simple random sample of classrooms, or
cluster of children
Examine all children in a cluster for dental caries
Estimate prevalence of caries within clusters
than combine in overall estimate, with variance
Sampling in Epidemiology
• Multistage sampling
• Similar to cluster sampling except
that there are two sampling events,
instead of one
• Primary units are randomly selected
• Individual units within primary units
randomly selected for measurement
Sampling in Epidemiology
• Multistage sampling
• Estimate the prevalence of dental caries in school
children
1. Among the schools in the catchment area, list all of the
classrooms in each school
2. Take a simple random sample of classrooms, or cluster
of children
3. Enumerate the children in each classroom
4. Take a simple random sample of children within the
classroom
5. Examine all children in a cluster for dental caries
6. Estimate prevalence of caries within clusters than
combine in overall estimate, with variance
QUOTA
SAMPLING
QUOTA SAMPLING
Sampling in Epidemiology
• Convenience sample
• A non-random collection of sampling
units from an undefined sampling frame
• Advantages
• Convenient and easy to perform
• Disadvantages
• Not statistical justification for sample
Sampling in Epidemiology
• Convenience sample
• Case series of patients with a particular
condition at a certain hospital
• “Normal” graduate students walking down
the hall are asked to donate blood for a study
• Children with febrile seizures reporting to an
emergency room
Investigator decides who is enrolled in a
study
Sampling in Epidemiology
• Consecutive sample
• A case series of consecutive patients with a condition of
interest
• Consecutive series means ALL patients with the condition
within hospital or clinic, not just the patients the
investigators happen to know about
• Advantages
• Removes investigator from deciding who enters a study
• Requires protocol with definitions of condition of interest
• Straightforward way to enroll subjects
• Disadvantage
• Non-random
Sampling in Epidemiology
• Consecutive sample
• Outcome of 1000 consecutive patients presenting
to the emergency room with chest pain
• Natural history of all 125 patients with HIVassociated TB during 5 year period
Explicit efforts must be made to identify and
recruit ALL persons with the condition of
interest
Availability sampling:
selecting on the basis of
convenience.
Random sampling:
every combination of a given
size has an equal chance of
being chosen.
Cluster sampling:
dividing the population into
clusters, typically on the basis
of geography, and taking a
sample of the clusters.
Snowball sampling:
asking individuals studied to
provide references to others.
Multi-stage sampling:
sampling subunits within
sampled units.
Stratified sampling:
dividing the population into
groups on the basis of some
characteristic and then
sampling each group.
Quota sampling:
selecting fixed numbers of
units in each of a number of
categories.
Systematic sampling:
choosing every nth item from a
list, beginning at a random
point.
Suniti Solomon et al
Prevalence and risk factors of HIV 1 and HIV 2 infection in Urban
and rural areas in TN. Int. J. of STD & AIDS 1998;9:98-103
Objective: Find prevalence and risk factors. Setting: Centres in
metropolitancity & municipality. Subjects: Individuals in Tamil nadu.
Sampling Porcedure:
“ Health camps were organised in 5 urban and 5 rural
centres to cover entire state graphically”
“ Every third person screened, in the active reproductive
age group, were recruited as a subject. At each camp the
inclusion of subjects continued until 200 persons were
recruited”
Mary Sexton et al.
Sex differences in the use of asthma drugs: Cross-sectional study.
BMJ 1998; 317: 1434-7
Objective : To assess the use of asthma drugs. Design : Crosssectional study. Setting: Six general practices in East Anglia.
Subjects : Adults aged 20-54 with Asthma
Sampling method
“identify cases with asthma received drugs one year before –
through database from each participating practices. The sample
was stratified into three categories of severity corresponding the
prescribed drugs
Bronchodilator alone (mild)
38%
Steroids (moderate)
57%
Nebulizer treatment (severe)
5%
Use SRS to select subject in each practice based on proportion of
use of each type of drug within the practice
S. Anuradha
Genital ulcer disease and acquisition of HIV infection.
Indian J Med Microbiol 1992; 10(4):265-269
Objective : To find out the association of HIV infection with
genital ulcer disease . Setting : Dept. of STD, GGH, Chennai.
Subjects : Individials attending the STD dept.
Sampling procedure
‘ Blood samples from first 20 patients were taken for
analysis once a week for 40 weeks’.
Statistical analysis : Data were analysed by using SPSS/PC +
ver 4.0. The strength of association between the variables and
HIV serological status was estimated using odds ratio (OR) and
their 95% Confidence Intervals(CI)
Reidy A et al.
Prevalence of series eye disease and visual
impairement in a north London population:
Population based, cross sectional study.
BMJ 1998; 316:1643Objective: To estimate eye disorders and of
visual impairement
Design: Cross-sectional survey.
Setting : General Practices in metropolitan in
England.
Subjects: aged 65 or older & registered
Sampling Procedure
17 general practice group
Random sampling
7 were selected
People age 65 or older were registered with the
general practices. Total 750-850 in each Gen Pract
Use SRS to select eligible people in each practice
One third in each practices were selected to form survey sample
A die is rolled to decide which
one of the six volunteers will get
a new , experimental vaccine
A. Simple Random sampling
B. Stratified random sampling
C. Cluster sampling
D. Systematic random sampling
A sample of students in a school is
chosen as follows: Two students are
selected from each batch by picking
roll number at random from the
attendance registers
A. Simple Random sampling
B. Stratified random sampling
C. Cluster sampling
D. Systematic random sampling
4. A target population for a telephonic
survey is picked by selecting 10 pages from
a total of 100 pages from a telephone
directory by using a table of random
numbers. In each of the selected pages, all
listed persons are called for Interview
A. Simple Random sampling
B. Stratified random sampling
C. Cluster sampling
D. Systematic random sampling
The number 35 is a two-digit random
number generated by a calculator. A sample
of two wheelers in a state is selected by
picking all those vehicles have registration
numbers ending with 35
A. Simple Random sampling
B. Stratified random sampling
C. Cluster sampling
D. Systematic random sampling