Sampling Methods in Research

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
• 2. 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)
• 3. 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
• 2. 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)
• 3. 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
• 4. 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
• 5. 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.