# HSCI 307 Lecture Notes - Lecture 9: Stratified Sampling, Cluster Sampling, Sampling Probability

56 views2 pages Non-probability sampling
Probability sampling
…depends on primarily on whether reliable inferences are to be made about the population
Sampling is a means of selecting a subset of units from a population for the purpose of collecting
information from those units to draw inferences about the population as a whole
Uses a subjective method of selecting individuals or units from a population
Fast, easy, and inexpensive
Non-probability sampling
Reliable estimates can be produced along with estimates of the sampling error, and
More complex, time-consuming, and usually more costly than non-probability sampling
Probability sampling
Non-probability sampling - Non-random samples
Unclear whether sample is generalizable
Sample participants selected based on their relevance to the research topic rather than
their representativeness
The selection of individuals from the population for a non-probability sample can result in
large bias
Selection bias - an individual's inclusion probability cannot be calculated for non-
probability samples, so there is no way of producing reliable estimates of their precision
(sampling error)
It is unclear whether or not it is possible to generalize the results from the sample to the
population
It can be used to generate ideas
As a preliminary step toward the development of a probability sample survey
As a follow-up step to help understand the results of a probability sample survey
It is often used to select individuals for focus groups and in-depth interviews: Census of
Population questionnaires
Too costly
Participants cooperation difficult with stigmatized behaviours
Difficult to obtain large sample of rare groups (e.g. heroin users)
Difficult to capture "hard-to-reach" populations
Not methodologically viable方法上可行
Often probability methods are
Why use it?
Individuals are selected in an aimless, arbitrary manner with little or no planning
involved
Assumes that the population is homogeneous
Haphazard sampling - "convenience sampling"
Based on previous ideas of population composition and behaviours
An expert with knowledge of the population decides which individuals in the
population should be sampled - the expert purposely selected what is considered to
be a representative sample
Perhaps more bias than haphazard sampling
Can be useful in exploratory studies, e.g. in selecting members for focus groups or
in-depth interviews to test specific aspects of a questionnaire
Judgement sampling
Volunteer smokers, diabetics, people with sleep disorders…
Can be subject to large selection bias, but is sometimes necessary
Volunteer sampling
One of the most common forms of non-probability sampling
Sampling is done until a specific number of units for various subpopulations (the
quotas) has been selected (20 males and 20 females)
Is considered preferable to other non-probability sampling because it forces the
inclusion of members of different subpopulations
Similar to stratified sampling but differs in how the individuals are selected -
relatively inexpensive and easy to administer
Quota sampling
Probability sampling
i.
Non-probability sample, usually a quota sample
ii.
Improve quota sampling by using a combination of probability and non-probability
sampling.
Modified probability sampling
6 types of non-probability sampling schemes
Probability sampling
Random refers to a selection process that gives each
element/unit in a population an equal probability of being
selected
Individuals must be randomly selected
1.
Not that all units have the same inclusion probability but
that all units have a known non-zero inclusion probability
SRS and SYS are both equal probability sample
Individuals must have a non-zero chance of being selected
2.
2 main criteria for probability sampling (QUIZ)
Since each individual is randomly selected and each individual's
inclusion probability can be calculated
Reliable estimates of interest can be produced (e.g. prevalence,
incidence or association, and an estimate of the sampling error of
each estimate)
It is more difficult, takes longer, and is usually more expensive
than non-p sampling
Types of probability sample designs
every possible sample of size nhas an equal chance of
being selected
Each individual in the sample has the same inclusion
probability - π = n/N, N is the number of units in the
population, (e.g. lottery 6/49)
The most basic
If the objective of the survey is simply to provide overall
population estimates - this should be sufficient
Can be expensive
Requires list prior to sampling
Simple random sampling (SRS)
A gap, or interval between each selection (e.g. every 5th
house in a street)
Tells how many elements to skip in the sampling from
before you pick of your sample
The sample size n
1)
Population size N
2)
To calculate N/nd
Sampling interval
Systematic sampling
Individual
If the cost of survey collection is high and the resources are
available…less statistically efficient sampling strategy than
SRS
The entire population is divided into clusters or groups and
a random sample of these clusters is selected 分组后随机选
Typically used when the researcher cannot get a complete
Cluster sampling
Groups/clusters
Less focus on representativeness
Greater focus on how the
relevance of the sample to the
research topic
Interest in cases that will enhance
the processes of social life in a
specific context
Non-probability samples
Qualitative perspective
Representativeness
Produce accurate generalizations
Saves time and \$\$
Measurement more accurate (e.g.
more effort on high-quality
measurements)
Probability samples
Quantitative perspective
Terminology
The concretely specified large group of many cases
from which a researcher draws a sample and to
which results from a sample are generalized
The population of interest about which inferences
are desired
Target population (source population?)
A selected subset of the target population
Sample (sample?)
A member of the target population (e.g. a person,
a health facility)
Sampling unit/element
A list of all available sampling units in the target
population (e.g. telephone list, electoral list, list of
Sampling frame (study population?)
The ratio of the size of the sample to the size of the
target population
Sampling ratio
Chapter 8 Sampling
Friday, March 24, 2017
15:35
week 9 Chapter 8 Sampling Page 1
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