Research in Social Work
Practice
Salem State University
School of Social Work
Session Six
Jeff Driskell, MSW, PhD
Today’s class
• Check/Announcements
• Lecture▫ Sampling
Follow-up: Article Search
Sampling Design
What Do We Mean by Sampling?
• It is NOT going to Costco on a Saturday
morning and sampling all the free food.
• It is NOT taking a bit out of all the chocolates in
the candy box to see which one tastes the best.
Sampling Defined
“A process of selecting a group of subjects from
a larger population in the hope that studying
this smaller group (the sample) will reveal
important things about the larger group (the
population) from which it is drawn”.
Wedding Cake Scenario
Why is Sampling Important in
Research?
Population vs. Sample
• Population
▫ A set of people or
events in which a
sample is drawn.
• Sample
▫ Infers population
characteristics
from a subset of
the population
 Saves money
 Saves time
 Can be more
accurate – don’t
need whole
population
What is the sampling frame?
Sampling Frame Examples?
Sampling Error
• Not representative
• Non-response error
• Sample error can be reduced:
▫ The larger the sample, the less error
▫ Homogenous samples have less error compared to
heterogeneous samples
Sampling Approaches
Sampling Process
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•
•
•
•
Definition of target population
Selection of a sampling frame (list)
Probability or Non-probability sampling
Inclusion/exclusion criteria
Determine sample size (beyond scope of this
class)
• Execute the sampling process
Types of Sampling
Probability
Sampling
•
•
•
•
Simple Random
Systematic
Stratified
Cluster
Non-Probability
Sampling
•
•
•
•
Convenience
Quota
Purposive
Snowball
Probability Sampling
• Every member of the population has an equal
chance of (non-zero) of being selected.
RANDOM SELECTION
• Allows the researcher to make few observations
and generalize to larger population
• Selection of elements occurs in a way that
portrays the characteristics of the total
population.
Random Selection/Sampling
Vs
Random Assignment
Public Opinion Polls
• What sampling frame was identified in this clip?
• How is random sampling described?
• http://science360.gov/obj/video/dc8e0737ceac-4582-bee9-5f195951a01a/science-behindnews-opinion-polls-random-sampling
Application:
• Study aim: To assess grades and social
adjustment of students in a U.S. 4th grade
public school suburban classroom
• You walk into the classroom to pick a random
sample, you choose the first two rows of
students.
▫ What is the probability that you have a
representative group?
▫ What will this do to your results?
Web Sampling Activity
• http://www.sagepub.com/prsw2/interactives/e
ngines/index.htm
Activity- Applying Research Design
and Sampling
Simple Random Sampling
• Simplest to implement and understand
• By luck of the draw, may not have a good
representation of the population
• Several random methods
Simple Random Sampling
Systematic Random Sampling
• Identical to simple but with a more organized
selection system
• More precise than simple sampling
• Every nth number is selected (i.e. every third or
tenth)
• Begin with simple random number selection
Systematic Random Sampling
Stratified Random Sampling
• Also known as proportional or quota sampling
• Divide population into sub-groups then take a
simple random sample in each group.
• Greater degree of representativeness than simple
random sampling
• Groups are homogenous
Stratified Random Sampling
Cluster Sampling
• Also known as multi-stage
• Often used when your population is dispersed
over a large geographic area
• Drawing a sample in two or more stages
▫ Divide population into clusters
▫ Randomly select clusters
▫ Measure all elements within those clusters
Cluster Example
Non-Probability Sampling
• Does not involve random selection
• May be able to generalize but does not follow
rules of probability theory
• More cost effective for agencies to implement
• Types
▫
▫
▫
▫
Convenience
Purposive
Quota
Snowball
Convenience
• Once of the most common methods
• Obtaining cases based on convenience
• Increase in sampling error due to researcher bias
Purposive
• Selecting a sample based on one’s knowledge of
a population OR based on predetermined
characteristics
• Often used in qualitative research
Quota
• Selecting a stratified non-random sample
• Divide population into categories and select a
certain number (quota) of subjects from each
category
Snowball
• Start with one member of a group and use them
to assist you in gaining access to other members
of the same group
• Think of it as a referral system
• Often used with hard to reach populations
Case Example- M’LANA
• Community based Participatory Research
(CBPR)
Limitations to Non-probability
• Less representative of your study population
compared to using probability sampling
• Common uses of non-probability sampling:
▫ Pilot study
▫ Agency based research
▫ Qualitative design
Strengths and Weaknesses of
Basic Sampling Techniques
Technique
Strengths
Weaknesses
Nonprobability Sampling
Convenience sampling
Least expensive, least
time-consuming, most
convenient
Low cost, convenient,
not time-consuming
Sample can be controlled
for certain characteristics
Can estimate rare
characteristics
Selection bias, sample not
representative, not recommended for
descriptive or causal research
Does not allow generalization,
subjective
Selection bias, no assurance of
representativeness
Time-consuming
Easily understood,
results projectable
Difficult to construct sampling
frame, expensive, lower precision,
no assurance of representativeness.
Can decrease representativeness
Judgmental sampling
Quota sampling
Snowball sampling
Probability sampling
Simple random sampling
(SRS)
Systematic sampling
Stratified sampling
Cluster sampling
Can increase
representativeness,
easier to implement than
SRS, sampling frame not
necessary
Include all important
subpopulations,
precision
Easy to implement, cost
effective
Difficult to select relevant
stratification variables, not feasible to
stratify on many variables, expensive
Imprecise, difficult to compute and
interpret results
Sample Size
Common question
How large does my sample need to be?
Group Discussion
Use the article you selected for class today
and answer the following questions:
• Who is the study population?
• What is the sampling frame?
• Probability or Non-probability?
• Name the sample strategy (i.e. Snowball)
• Strengths/limitations of the design
Determining Your Study Sampling
Method and Procedures
1.
2.
3.
4.
Define the study population
Determine the sampling frame
Determine inclusion criteria
Determine appropriate sampling
method/strategy (random, non-random,
snowball)
5. Determine how you will recruit the study
population
Qualitative Sampling
Qualitative Sampling
• Differs from quantitative sampling methods
• Sample can include schools, agencies, or people.
• Not concerned with representativeness but more
so the depth and quality of the data.
• Non-probability approach (not randomized)
• Typically a purposive sampling strategy is
implemented (eligibility criteria).
• Sample size varies (i.e attempt saturation)
Other Sampling Types/Techniques
(Patton, 2002)
• Extreme or deviant case sampling- “outer
edges” of a phenomena
• Intensity sampling• Maximum variation sampling• Homogeneous sampling- opposite
maximum variation.
• Typical case sampling- recruits average
members of a population