Sampling in nursing research is an essential step. This ppt describes sampling process in detail

1. SAMPLING

2. SAMPLING
•It is the process of selecting representative units
from an entire population of study.
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3. Terminology used in Sampling

4. Terminology contd..
• POPULATION: it is the aggregate of all the units in which a researcher is
interested. (E.g problems faced by post graduate nurses.)
• TARGET POPULATION: it is aggregate of all the cases with certain
phenomenon about which researcher would like to make generalization.(
E.g Problems faced by post graduate nurses in Mohali.)
• ACCESSIBLE POPULATION: it is the aggregate of cases that confirm to
designated criteria and are also accessible as subjects for study. (E.g nurses
present at the time of study. Some might be on leave)

5. Terminology contd…
• SAMPLING FRAME: it is list of all the subjects in population from
which the sample is withdrawn. E.g Census
• SAMPLING: The process of selecting a portion of the population to
represent the entire population.
• SAMPLE: It is the subset of population selected to participate in
research study.

6. PURPOSE OF SAMPLING
1. ECONOMICAL: saves time, energy and resources.
2. Improved quality of data (less people , more quality in handling
people.)
3. Quick study results.
4. Precision and accuracy of data.(Interpretation of data is easy.)

7. CHARACTERISTICES OF GOOD SAMPLE
1. Representative.
2. Free from bias and errors.
3. No substitution and incompleteness.
4. Appropriate sample size.

8. SAMPLING PROCESS .. 7 steps
1. Identify and define the target population
2. Describe the accessible population and ensure sampling frame.
3. Specify the sampling unit via inclusion / exclusion criteria.
4. Specify sample selection methods.
5. Determine the sample size.
6. Specify sampling plan.
7. Selecting a desired sample.

9. FACTORS INFLUENCING SAMPLING PROCESS
NATURE OF RESEARCHER NATURE OF SAMPLE CIRCUMSTANCES
• Inexperienced
investigator
• Lack of interest
• Lack of honesty
• Intensive workload
• Inadequate supervision.
• Inappropriate sampling
technique.
• Inadequate sample size,
• Defective sampling
frame.
• Lack of time.
• Large geographic area.
• Lack of co-operation.
• Natural calamities.

10. SAMPLING TECHNIQUES
PROBABILITY SAMPLING
TECHNIQUES
NON PROBABILITY SAMPLING
TECHNIQUES
1.Simple random sampling.
2.Stratified random sampling.
3.Systematic random sampling.
4.Cluster/ multistage sampling.
5.Sequential sampling.
1.Convenient sampling.
2.Purposive sampling.
3.Volunteer sampling.
4.Consecutive sampling.
5.Quota sampling.
6.Snowball sampling.

11. Probability sampling techniques
• It is based on the theory of probability.
• It involves random selection of members from the population.
• Every subject in the population has equal chance of being selected as
study sample.

12. 1. Simple random sampling

13. Simple random sampling
• Every person has an equal chance of being selected as subject.
• Population should be homogenous.
• Methods used are : lottery , table of random numbers, use of
computer.
• ADVANTAGES: most reliable, free from sampling bias.
• DISADVANTAGES: incomplete sampling frame can cause error,
expensive and time consuming.

14. 2. Stratified random sampling.

15. Stratified random sampling
• Heterogenous population is organized in homogenous groups (strata)
e.g on the basis .
• Then random selection from each stratum is done.
• ADVANTAGES: ensures representative sample is heterogenous
population.
• DISADVANTAGES: time consuming, expensive, large population is
required, chances of faulty classification of strata.

16. 3. Systematic random sampling.

17. Systematic random sampling
• K= N/n
• N= total number of target population.
• n= sample size
• E.g, N=300 and n=100, therefore 300/100= 3. we will be selecting
every 3rd person in the population.
• ADVANTAGES: convenient and simple, distribution of sample over
entire population.
• DISADVANATGES: sometimes may result in biased sample.

18. 4. Cluster or multistage sampling

19. Cluster or multistage sampling
• Done in very large population e.g country.
• Random selection of geographical area.
• Cluster of population is selected by using simple random sampling
technique.
• ADVANTAGES: quick and easy for large population.
• DISADVANTAGES: possibility of high sampling error.

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5. Sequential sampling

21. Sequential sampling
• Sample size is not fixed.
• Researcher initially selects small sample and tries to make inference.
• if unable to draw results, new subjects are added until clear inference
can be drawn.
• ADVANATGES: study on smallest possible sample is done.
• DISADVANTAGES: requires repeated entry in field to collect sample.

22. Non probability sampling
In this method not all population have equal chance
of getting selected as subjects.

23. 1. Convenient sampling

24. Convenient sampling
• Also known as accidental sampling.
• Selection of most conveniently available people as subjects.
• Most commonly used technique in pilot studies.
• ADVANTAGES: easy, less time consuming, and economic.
• DISADVANTAGES: chances of sampling bias and same may not be
representative of entire population.

25. 2. Purposive sampling

26. Purposive sampling
• Also known as judgemental or authoritative sampling.
• Samples are chosen by researcher by keeping specific purpose in
mind.
• Usually study population is limited. e.g Post disaster victims.
• ADVANTAGES: simple to draw sample and useful in exploratory
studies, saves resources and need less field work.
• DISADVANTAGES: needs adequate knowledge about population under
study, concious bias can occur therefore, the sample selected may not
a be reliable.

27. 3. Volunteer sampling

28. Volunteer sampling
• Participants volunteer to participate in the study.
• Researcher publishes an advertisement or inform target population
through mass media.
• ADVANTAGES: cost effective, less time and energy is required, large
data can be collected in limited time period.
• DISADVANTAGES: sample may not be representative sample and it
lacks generalizability.

29. 4. Consecutive sampling.

30. Consecutive sampling
• Also known as Total enumerative sampling.
• It includes all the subjects that meet the inclusion criteria. e.g post
kidney transplant patients.
• The researcher conduct research one after the other until a
conclusive result is reached, thus , the prefix consecutive.
• ADVANTAGES: less energy, money and time is needed, it ensures
more representativeness of selected sample.
• DISADVANTAGES: no set plans about sample size and sampling
schedule, and there is no gurantee that representative sample will be
selected.

31. 5. Quota sampling

32. Quota sampling
• Population is divided into different groups or class.
• The groups are divided on the basis of age, gender, education level,
race, religion, and socioeconomic status.
• Percentage of groups in total population is fixed.
• ADVANTAGES: chances of reliability and generalizability are high,
suitable for studies where field work has to be carried out. e.g public
opinion polls.
• DISADVANTAGES: missing quota, over representation in sub groups,
bias is possible.

33. 6. Snowball sampling.

34. Snowball sampling.
• Also known as chain referral sampling.
• This technique is used to locate where subjects are hard to locate e.g
drug addicts population.
• Types of snowball sampling:
1. Linear snow ball sampling.
2. Exponential non discriminative sampling.
3. Exponential discriminative sampling.
ADVANTAGES: simple and cost effective process to locate difficult
sample
DISADVANTAGES: less control over sampling method, sample
representation is not guaranteed and sampling bias is major concern.

35. Sampling techniques used in qualitative and quantitative
research
Qualitative research
• Non probability sampling
techniques.
1. Convenience sampling
2. Snowball sampling.
3. Purposive sampling.
4. Quota sampling.
5. Consecutive sampling.
Quantitative research
• Probability sampling techniques.
1. Simple random sampling.
2. Stratified random sampling.
3. Systematic random sampling.
4. Cluster/ multistage sampling.
5. Sequential sampling.
• Non probability sampling
techniques.

36. Estimation of sample size.

37. Estimation of sample size.

38. Estimation of sample size.

39. Estimation of sample size.

40. Problems of sampling
1. Sampling error.
2. Lack of sample representativeness.
3. Difficulty in estimation of sample size.
4. Lack of knowledge about sampling process.
5. Lack of resources.
6. Lack of co-operation.
7. Lack of existing appropriate sampling frame.
8. Callous approach of researcher towards sampling process.