Sampling Methods in Research

Study Notes

Sampling

Definition: The process of selecting a number of study units from a defined study population.

Aim of Sampling

To reduce:
- Cost
- Manpower
- Time

Sample Size

Depends on:
- Disease prevalence
- Availability of cost, manpower, and time
- Aim of the study
Calculated by special equations for each study design
Can be automatically calculated by using statistical programs (e.g., Epi Info)

Types of Sampling

Purposive (selective)
- Samples chosen according to person's own judgment
- Can't be considered as representative samples
- Commonly used in pilot studies
Random
- Each unit of population has an equal chance or probability of being chosen
- Types:
  - Simple random sample
  - Systematic random sample
  - Stratified random sample
  - Multistage random sample
  - Cluster random sample

Sampling Techniques

A. Purposive (selective) / probability sampling:
- 5 types:
  - Convenience sampling
  - Quota sampling
  - Snow ball sampling
  - Self selection sampling
  - Purposive sampling
1. Convenience sampling:
- Used when the sample size is less than the calculated sample size due to limited resources
- Usually used in pilot studies
1. Quota sampling:
- Example: survey for student satisfaction about medical education in a faculty of medicine
- Sample size is distributed according to the population proportions (e.g., 40% of students in Grade 1)
1. Snow ball sampling:
- Used when the health problem under study is hard to reach (e.g., HIV/AIDS among commercial sex workers)
B. Random (non-probability sampling):
- 5 types:
  - Simple random sample
  - Systematic random sample
  - Stratified random sample
  - Multistage random sample
  - Cluster random sample
1. Simple random sample:
- Population should be homogenous and have a definite sampling frame (list of identification of the individuals in the population)
- Uses tables of random sampling numbers or the lottery method to choose the sampling units
1. Systematic random sampling:
- After a population is arranged in a list or form, sample is taken as the following examples (e.g., selecting every 4th individual)
1. Stratified random sampling:
- Used in non-homogenous populations, especially in variables known to affect the subject being studied (e.g., age on height)
- Divides the population into subgroups (strata) and takes a sample randomly from each stratum after determining its size
1. Multistage random sampling:
- Sampling frame is divided into a population of "1st stage sampling units" of which a 1st stage sample is taken by random sampling
- Each of the selected 1st stage units is subdivided into "2nd stage sampling units" of which a sample is taken, and so on
1. Cluster sampling:
- Population is clustered in form of villages or clusters of households
- This cluster sample is liable to bias if the disease under study is clustered in the population

Sampling Definition and Aim

Sampling is the process of selecting a number of study units from a defined study population.
The aim of sampling is to reduce cost, manpower, and time.

Factors Affecting Sample Size

Sample size depends on disease prevalence, availability of cost, manpower, and time, and the aim of the study.
Sample size can be calculated by special equations for each study design or automatically using statistical programs (e.g., Epi info).

Types of Sampling

Purposive (Selective) Sampling: Samples chosen according to the researcher's own judgment, not representative of the population, and commonly used in pilot studies.
Random Sampling: Each unit of the population has an equal chance or probability of being chosen.

Purposive Sampling Techniques

Convenience Sampling: Used when the sample size is less than the calculated sample size due to limited resources, time, or budget.
Quota Sampling: Used to ensure a representative sample by dividing the population into subgroups and selecting a proportionate number of participants from each subgroup.
Snow Ball Sampling: Used to study hard-to-reach populations, such as commercial sex workers or IV drug addicts.
Self Selection Sampling: Participants select themselves to participate in the study.
Purposive Sampling: Samples chosen based on the researcher's own judgment.

Random Sampling Techniques

Simple Random Sampling: Used in homogeneous populations with a definite sampling frame, and samples are selected using random sampling tables or the lottery method.
Systematic Random Sampling: Used in populations with a list or form, and samples are selected at regular intervals.
Stratified Random Sampling: Used in non-homogeneous populations, where the population is divided into subgroups (strata) and a sample is taken from each stratum.
Multistage Random Sampling: Used in complex populations, where the sampling frame is divided into multiple stages, and samples are taken at each stage.
Cluster Random Sampling: Used in clustered populations, such as villages or households, but may be biased if the disease under study is clustered in the population.