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Abstract
Once the research question and the research design have been finalised, it is important to
select the appropriate sample for the study. The method by which the researcher selects the
sample is the ‘Sampling Method’. There are essentially two types of sampling methods: 1)
probability sampling – based on chance events (such as random numbers, flipping a coin etc.);
and 2) non-probability sampling – based on researcher’s choice, population that accessible &
available. Some of the non-probability sampling methods are: purposive sampling, convenience
sampling, or quota sampling. Random sampling method (such as simple random sample or
stratified random sample) is a form of probability sampling. It is important to understand the
different sampling methods used in clinical studies and mention this method clearly in the
manuscript. The researcher should not misrepresent the sampling method in the manuscript
(such as using the term ‘random sample’ when the researcher has used convenience sample).
The sampling method will depend on the research question. For instance, the researcher may
want to understand an issue in greater detail for one particular population rather than worry
about the ‘generalizability’ of these results. In such a scenario, the researcher may want to
use ‘purposive sampling’ for the study.
Key Words: Non-probability sampling, sampling strategies, probability sampling
Methodology Series Module 5: Sampling Strategies
Maninder Singh Setia
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Website: www.e‑ijd.org
DOI: 10.4103/0019‑5154.190118
Introduction
The purpose of this section is to discuss various sampling
methods used in research. After finalizing the research
question and the research design, it is important to
select the appropriate sample for the study. The method
by which the researcher selects the sample is the
“Sampling Method” [Figure 1].
Why do we need to sample?
Let us answer this research question: What is the
prevalence of HIV in the adult Indian population?
The best response to this question will be obtained
when we test every adult Indian for HIV. However, this
is logistically difficult, time consuming, expensive, and
difficult for a single researcher – do not forget about
ethics of conducting such a study. The government
usually conducts an exercise regularly to measure certain
outcomes in the whole population – “the census.”
However, as researchers, we often have limited time
and resources. Hence, we will have to select a few adult
Indians who will consent to be a part of the study. We
will test them for HIV and present out results (as our
estimates of HIV prevalence). These selected individuals
are called our “sample.” We hope that we have selected
the appropriate sample that is required to answer our
research question.
The researcher should clearly and explicitly mention the
sampling method in the manuscript. The description of
these helps the reviewers and readers assess the validity
and generalizability of the results. Furthermore, the
authors should also acknowledge the limitations of their
sampling method and its effects on estimated obtained
in the study.
Types of Methods
We will try to understand some of these sampling
methods that are commonly used in clinical research.
There are essentially two types of sampling methods:
(1) Probability sampling – based on chance events (such
as random numbers, flipping a coin, etc.) and
Epidemiologist, MGM Institute of
Health Sciences, Navi Mumbai,
Maharashtra, India
Address for correspondence:
Dr. Maninder Singh Setia,
MGM Institute of Health Sciences,
Navi Mumbai, Maharashtra, India.
E-mail: maninder.setia@
karanamconsultancy.in
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How to cite this article: Setia MS. Methodology series module 5:
Sampling strategies. Indian J Dermatol 2016;61:505‑9.
Received: August, 2016. Accepted: August, 2016.
IJD® MODULE ON BIOSTATISTICS AND RESEARCH METHODOLOGY FOR THE DERMATOLOGIST
MODULE EDITOR: SAUMYA PANDA
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Setia: Sampling strategies
506Indian Journal of Dermatology 2016; 61(5)
(2) nonprobability sampling – based on researcher’s
choice, population that accessible and available.
What is a “convenience sample?”
Research question: How many patients with psoriasis
also have high cholesterol levels (according to our
definition)?
We plan to conduct the study in the outpatient
department of our hospital.
This is a common scenario for clinical studies. The
researcher recruits the participants who are easily
accessible in a clinical setting – this type of sample is
called a “convenience sample.” Furthermore, in such a
clinic-based setting, the researcher will approach all the
psoriasis patients that he/she comes across. They are
informed about the study, and all those who consent to
be the study are evaluated for eligibility. If they meet
the inclusion criteria (and need not be excluded as per
the criteria), they are recruited for the study. Thus, this
will be “consecutive consenting sample.”
This method is relatively easy and is one of the
common types of sampling methods used (particularly in
postgraduate dissertations).
Since this is clinic-based sample, the estimates from
such a study may not necessarily be generalizable to the
larger population. To begin with, the patients who access
healthcare potentially have a different “health-seeking
behavior” compared with those who do not access health
in these settings. Furthermore, many of the clinical cases
in tertiary care centers may be severe, complicated, or
recalcitrant. Thus, the estimates of biological parameters
or outcomes may be different in these compared
with the general population. The researcher should
clearly discuss in the manuscript/report as to how the
convenience sample may have biased the estimates (for
example: Overestimated or underestimated the outcome
in the population studied).
What is a “random sample?”
A “random sample” is a probability sample where every
individual has an equal and independent probability of
being selected in the sample.
Please note that “random sample” does not mean
arbitrary sample. For example, if the researcher selects
10–12 individuals from the waiting area (without any
structure), it is not a random sample. Randomization is
a specific process, and only samples that are recruited
using this process is a “random sample.”
What is a “simple random sample?”
Let us recruit a “simple random sample” in the above
example. The center only allows a fixed number of patients
every day. All the patients have to confirm the appointment
a day in advance and should present in the clinic between 9
and 9:30 a.m. for the appointment. Thus, by 9:30 a.m., you
will all have all the individuals who will be examined day.
We wish to select 50% of these patients for posttreatment
survey.
Steps:
1. Make a list of all the patients present at 9:30 a.m.
2. Give a number to each individual
3. Use a “randomization method” to select five of
these numbers. Although “random tables” have been
used as a method of randomization, currently, many
researchers use “computer-generated lists for random
selection” of participants. Most of the statistical
packages have programs for random selection of
population. Please state the method that you have
used for random selection in the manuscript
4. Recruit the individuals whose numbers have been
selected by the randomization method.
The process is described in Figure 2.
What is a major issue with this recruitment
process?
As you may notice, “only males” have been recruited for
the study. This scenario is possible in a simple random
sample selection.
This is a limitation of this type of sampling
method – population units which are smaller in number in
the sampling frame may be underrepresented in this sample.
What is “stratied sample?”
In a stratified sample, the population is divided into
two or more similar groups (based on demographic or
clinical characteristics). The sample is recruited from
each stratum. The researcher may use a simple random
sample procedure within each stratum.
Let us address the limitation in the above example
(selection of 50% of the participants for postprocedure
survey).
Figure 1: Flowchart from “Universe” to “Sampling Method”
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Setia: Sampling strategies
507 Indian Journal of Dermatology 2016; 61(5)
Steps:
1. Make a list of all the patients present at 9:30 a.m.
2. Divide the list into two strata: Males and females
3. Use a “randomization method” to select three
numbers among males and two numbers among
females. As discussed earlier, the researcher may
use random tables or computer generated random
selection. Please state the method that you have
used for random selection in the manuscript
4. Recruit the individuals whose numbers have been
selected by the randomization method.
The process is described in Figure 3.
Thus, with this sampling method, we ensure that people
from both sexes are included in the sample. This type
of sampling method is used for sampling when we want
to ensure that minority populations (in number) are
adequately represented in the sample.
Kindly note that in this example, we sampled 50% of the
population in each stratum. However, the researcher may
oversample in one particular stratum and under-sample
in the other. For instance, in this example, we may
have taken three females and three males (if want to
ensure equal representation of both). All this should be
discussed explicitly in methods.
What is a “systematic sample?”
Sometimes, the researcher may decide to include study
participants using a fixed pattern. For example, the
researcher may recruit every second patient, or every
patient whose registration ends with an even number
or those who are admitted in certain days of the
week (Tuesday/Thursday/Saturday). This type of sample
is generally easy to implement. However, a lot of the
recruitments are based on the researcher and may lead
to selection bias. Furthermore, patients who come to the
Figure 3: Representation of Stratified Random Sample
Figure 2: Representation of Simple Random Sample
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Setia: Sampling strategies
508Indian Journal of Dermatology 2016; 61(5)
hospital may differ on different days of the week. For
example, a higher proportion of working individuals may
access the hospital on Saturdays.
This is not a “random sample.” Please do not write that
“we selected the participants using a random sample
method” if you have selected the sample systematically.
Another type of sampling discussed by some authors is
“systematic random sample.” The steps for this method
are:
1. Make a list of all the potential recruits
2. Using a random method (described earlier) to select a
starting point (example number 4)
3. Select this number and every fifth number from
this starting point. Thus, the researcher will select
number 9, 14, and so on.
Please note that the “skip” depends on the total number
of potential participants and the total sample size. For
instance, you have a total of fifty potential participants
and you wish to recruit ten participants, do not skip to
every 10th patient.
Aday (1996) states that the skip depends on the
total number of participants and the total sample size
required.
• Fraction = total number of participants/total sample
size
• In the above example, it will be 50/10 = 5
• Thus, using a random table or computer-generated
random number selection, the researcher will select a
random number from 1 to 5
• Thenumber selectedintwo
• Theresearcherselectsthesecondpatient
• The next patient will be the fth patient after
patient number two – patient number 7
• The next patient will be patient number 12 and so
on.
What is a “cluster sample?”
For some studies, the sample is selected from larger
units or “clusters.” This type of method is generally used
for “community-based studies.”
Research question: What is the prevalence of
dermatological conditions in school children in city
XXXXX?
In this study, we will select students from multiple
schools. Thus, each school becomes one cluster. Each
individual child in the school has much in common
with other children in the same school compared with
children from other schools (for example, they are more
likely to have the same socioeconomic background).
Thus, these children are recruited from the same
cluster.
If the researcher uses “cluster sample,” he/she also
performs “cluster analysis.” The statistical methods for
these are different compared with nonclustered analysis
(the methods we use commonly).
What is a “multistage sample?”
In many studies, we have to combine multiple methods
for the appropriate and required sample.
Let us use a multistage sample to answer this research
question.
Research question: What is the prevalence of
dermatological conditions in school children in city
XXXXX? (Assumption: The city is divided into four zones).
We have a list of all the schools in the city. How do we
sample them?
Method 1: Select 10% of the schools using “simple
random sample” method.
Question: What is the problem with this type of method?
Answer: As discussed earlier, it is possible that we may
miss most of the schools from one particular zone.
However, we are interested to ensure that all zones are
adequately represented in the sample.
Method 2:
• Stage1: Listallthe schoolsin all zones
• Stage 2: Select 10% ofschools from each zone using
“random selection method” (first stratum)
• Stage3: Listallthe studentsinGradeVIII,IX, andX
(population of interest) in each school (second
stratum)
• Stage 4: Create a separatelist for males and females
in each grade in each school (third stratum)
• Stage 5: Select 10% of males and females in each
grade in each school.
Please note that this is just an example. You may have
to change the proportion selected from each stratum
based on the sample size and the total number of
individuals in each stratum.
What are other types of sampling methods?
Although these are the common types of sampling
methods that we use in clinical studies, we have also
listed some other sampling methods in Table 1.
Conclusion
• It is important to understand the different
sampling methods used in clinical studies. As stated
earlier, please mention this method clearly in the
manuscript
• Do not misrepresent the sampling method. For
example, if you have not used “random method” for
selection, do not state it in the manuscript
• Sometimes, the researcher may want to
understand an issue in greater detail for one
particular population rather than worry about
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Setia: Sampling strategies
509 Indian Journal of Dermatology 2016; 61(5)
Conflicts of interest
There are no conflicts of interest.
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the “generalizability” of these results. In such a
scenario, the researcher may want to use 'purposive
sampling'.
Financial support and sponsorship
Nil.
Table 1: Some other types of sampling methods
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