Convenience samples are nonprobability samples where the element selection is based on ease of accessibility. They are the least reliable but cheapest and easiest to conduct. Examples include informal pools of friends and neighbors, people responding to an advertised invitation, and “on the street” interviews. Judgment sampling is purposive sampling where the researcher arbitrarily selects sample units to conform to some criterion. This is appropriate for the early stages of an exploratory study. Quota sampling is also a type of purposive sampling. In this type, relevant characteristics are used to stratify the sample which should improve its representativeness. The logic behind quota sampling is that certain relevant characteristics describe the dimensions of the population. In most quota samples, researchers specify more than one control dimension. Each dimension should have a distribution in the population that can be estimated and be pertinent to the topic studied. Snowball sampling means that subsequent participants are referred by the current sample elements. This is useful when respondents are difficult to identify and best located through referral networks. It is also used frequently in qualitative studies.
Convenience samples are nonprobability samples where the element selection is based on ease of accessibility. They are the least reliable but cheapest and easiest to conduct. Examples include informal pools of friends and neighbors, people responding to an advertised invitation, and “on the street” interviews. Judgment sampling is purposive sampling where the researcher arbitrarily selects sample units to conform to some criterion. This is appropriate for the early stages of an exploratory study. Quota sampling is also a type of purposive sampling. In this type, relevant characteristics are used to stratify the sample which should improve its representativeness. The logic behind quota sampling is that certain relevant characteristics describe the dimensions of the population. In most quota samples, researchers specify more than one control dimension. Each dimension should have a distribution in the population that can be estimated and be pertinent to the topic studied. Snowball sampling means that subsequent participants are referred by the current sample elements. This is useful when respondents are difficult to identify and best located through referral networks. It is also used frequently in qualitative studies.
Sampling by dr najeeb memon
1.
LIAQUAT
MEDICAL
UNIVERSITY
By:
Assist: Prof:
Faculty of Community Medicine & Public Health Sciences
Liaquat University of Medical & Health Sciences (LUMHS)
Jamshoro, Sind, Pakistan
e mail mnajeeb80@gmail.com
2.
POPULATION
The
whole group of the individuals
on which the results of the study are
to be generalized is known as
Population. A of people of interest from whom
The entire group
the researcher needs to obtain information.
SAMPLE
small group of individuals chosen for the
study is known as Sample.
The selection of a subset of the population
3.
Listing
Sampling Frame
of all the members of the universe
from which the sample is to be taken , is
known as Sampling Frame.
Listing of population from which a sample is chosen
Sampling frame should be carefully
developed as it affects the results drawn.
4.
WHY SAMPLING IS
NECESSARY?
Convenient.
Economic.
Time saving.
Less resources are required.
Easy to interpret the data.
5.
TYPES OF SAMPLING
• A. Probability Sampling Methods
• B. Non Probability Sampling Methods
6.
SAMPLES TECHNIQUES
A. Probability Sampling Methods
Simple Random
Simple Random
systemic sampling
systemic sampling
Stratified
Stratified
Cluster
Cluster
Multistage
Multistage
14-11
7.
B. Non probability
Sampling Methods
Convenience
Convenience
Judgment
Judgment
Quota
Quota
Snowball
Snowball
14-12
8.
1. Simple Random sampling
1. Simple Random sampling
OR Lottery Method
Each element in the population will have
an equal chance of being included in the
sample.
No: is given to each of units (Persons/ houses)
Table of random Nos: is used
Samples selected haphazardly
(Each has equal chance of being selected)
N = 100 population size, n = 8 sample size
E.g:- In Electro roll / Census
1 - 13
12.
3. Stratified
3. Stratified
It involves division of
population in to smaller
groups (homogenous subgroups)
known as “Strata”
•Then Simple random
sampling OR systematic
sampling is applied with
each stratum.
Example 2
Population is
divided on the basis of
characteristic of interest in the
population E.g. male & female
may have different
consumption patterns.
14.
4. Cluster
4. Cluster
Here we select a simple random sample of
groups such as a certain number of city
blocks & then select a person each from
each block.
This technique is more economical than the random selection of
persons through out the city.
16.
5. Multistage
5. Multistage
•
•
•
•
Sampling at different stages/ Levels
1. National level
A sample selected in stages, beginning with the most
unspecific level (such as regions) and ending with the
2. Provincial level
most specific (such as houses on selected city blocks).
3. District level
18.
NON PROBABILITY
SAMPLING
• Convenient
• Economic
BUT
RESULTS CAN NOT BE GENERALIZED
THEREFORE
Some probability factor is needed to be
imposed to ensure a degree of
representation in the sample.
19.
1. Convenience /Accidental/Incidental sampling
1. Convenience /Accidental/Incidental sampling
Involves the use of the most convenient &
readily available subjects for sample.
A convenience sample is a sample where the
patients are selected, in part or in whole,
at the convenience of the researcher .
Example:
Male on street interviews
Teacher uses students
20.
2. Judgment /Purposive
2. Judgment /Purposive
The researcher chooses the sample based on
who they think would be appropriate for the study.
21.
3. Quota
3. Quota
Researcher selects people according to some fixed quota.
OR
Keep going until the sample size is reached
if you are a researcher conducting a national quota sample, you
might need to know what proportion of the population is
male(40) and what proportion is female (60) as well as what
proportions of each gender fall into different age categories, race
or ethnic categories, educational categories, etc.
Male
40
Female
60
Total (Fixed quota)
100
22.
4. Snowball
4. Snowball
Get sampled people to nominate others
Researcher collects data on the few members of the
target population he or she can locate,
then asks those individuals to provide information
needed to locate other members of that population
whom they know.
23.
Sampling Errors
A. Size:
sample size should be large as possible
depends upon feasibility (time, person, importance of data)
B. subject variation: Sometimes observation may be changed on
different times (B.P at different times of a day)
C. Observer Variation: When 2 or more persons observe same data
(No same value) E.g:- Taking Blood Pressure reading
D. Technical Fault: By Instrument
E. Incomplete Coverage: If 10 out of 100 are non cooperative (i,e 90
or 10 Non co operative)