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200107P - TECHNIQUES OF SAMPLING

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Presentation to the Module I: Clinical Epidemiology at a Clinical Research Coordinator Course held on 5-9 January 2020 at Faculty of Medicine, King Fahad Medical City, Riyadh. by Professor Omar Hasan Kasule Sr. MB ChB (MUK), MPH (Harvard), DrPH (Harvard), Chairman of the KFMC IRB


LEARNING OBJECTIVES:

  • Target and study populations
  • Definition and types of samples
  • Methods of sampling: advantages and disadvantages
  • The simple random sample: definition, types, methods of selection, and uses 


KEYWORDS AND TERMS:

  • Population: study population, target population
  • Sample element
  • Sampling with replacement, without replacement
  • Sampling, cluster sampling
  • Sampling, convenience sampling, quota sampling 
  • Sampling, multistage random sampling
  • Sampling, sampling bias
  • Sampling, sampling frame
  • Sampling, sampling method
  • Sampling, sampling technique 
  • Sampling, statistical sampling
  • Sampling, stratified random sampling
  • Sampling, systematic random sampling
  • Selection bias 


SAMPLES AND POPULATIONS: Terminology

  • The word population in statistical usage is defined as a set of objects, states, or events with a common observable characteristic or attribute. Elements are the members of the population or a sample thereof.
  • A sample is a representative subset of the population selected to obtain information on the population. 
  • A Sampling plan is a whole process of selecting a sample.
  • Sampling design is both the sampling plan and the estimation methods.
  • Sampling starts by defining a sampling frame (list of individuals to be sampled).
  • The sampling units are the people or objects to be sampled. 


SAMPLES and POPULATIONS: Con’t. 

  • Samples are studied because of lower and easier logistics.
  • Some populations are hypothetical and cannot be studied except by sampling.
  • Samples are used for estimation of population parameters, estimation of the total population, and inference on populations.
  • The sample is selected from the study population (population of interest).
  • The study population is definable in an exact way and is part of the target population.
  • The population studied may be finite or infinite. 


RANDOM (PROBABILITY) SAMPLING

  • In random sampling, any element has the same inclusion probability. 
  • Random does not always assure representativeness, especially for small samples.
  • Sampling with replacement is based on the binomial and sampling without replacement is based on the hypergeometric random distribution. The two types are similar for large samples. 
  • Simple random sampling is a random selection from the population used when the population is approximately homogenous. 
  • Stratified random sampling involves dividing the population into groups called strata and simple random sampling is carried out in each stratum. 
  • Systematic random sampling is used if an ordered list is available such that every nth unit is included. 
  • Multi-stage random sampling is a simple random sampling of 2 or more stages. 


NON-SCIENTIFIC SAMPLING

  • Convenience or casual sampling is subjective, depends on whims, and there is no concern about objectivity.
  • A quota sample is a subjective selection of a pre-fixed number from each category. 


OTHER TYPES OF SAMPLING

  • Cluster sampling uses clusters (groups of individuals) as sampling units instead of individuals. 
  • Epidemiological samples involve random sampling of human populations. There are basically three types of epidemiological sampling schemes: cross-sectional, case-control, and follow-up (or cohort).
  • Environmental sampling, static or continuous, uses direct measurements and has the advantages of being objective, individualized, quantitative, specific, and sensitive.