Skip to Main Content

Epidemiology: Sample Selection/Allocation Procedures

Resources for the branch of medicine that deals with the incidence, distribution, and possible control of diseases and other factors relating to health.

Unbiased Allocation Procedures

  • Consecutive (Quota) Sampling: Sampling individuals with a given characteristic as they are presented until enough with that characteristic are acquired. This method is okay for descriptive studies but unfortunately not much better than haphazard sampling for analytical observational studies.
  • Random Sampling: Each individual in the group being sampled has a known probability of being included in the sample obtained from the group before the sampling occurs.
  • Simple Random Sampling / Allocation: Sampling conducted such that each eligible individual in the population has the same chance of being selected or allocated to a group. This sampling procedure is the basis of the simpler statistical analysis procedures applied to sample data. Simple random sampling has the disadvantage of requiring a complete list of identified individuals making up the population (the list frame) before the sampling can be done.
  • Stratified Random Sampling: The group from which the sample is to be taken is first stratified on the basis of a important characteristic related to the problem at hand (e.g., age, parity, weight) into subgroups such that each individual in a subgroup has the same probability of being included in the sample but the probabilities are different between the subgroups or strata. Stratified random sampling assures that the different categories of the characteristic that is the basis of the strata are sufficiently represented in the sample but the resulting data must be analyzed using more complicated statistical procedures (such as Mantel-Haenszel) in which the stratification is taken into account.
  • Cluster Sampling: Staged sampling in which a random sample of natural groupings of individuals (houses, herds, kennels, households, stables) are selected and then sampling all the individuals within the cluster. Cluster sampling requires special statistical methods for proper analysis of the data and is not advantageous if the individuals are highly correlated within a group (a strong herd effect).
  • Systematic Sampling: From a random start in first n individuals, sampling every nth animal as they are presented at the sampling site (clinic, chute, ...). Systematic sampling will not produce a random sample if a cyclical pattern is present in the important characteristics of the individuals as they are presented. Systematic sampling has the advantage of requiring only knowledge of the number of animals in the population to establish n and that anyone presenting the animals is blind to the sequence so they cannot bias it.

Biased Allocation Procedures

  • Haphazard, Convenience, Volunteer, Judgmental Sampling: Any sampling not involving a truly random mechanism. A hallmark of this form of sampling is that the probability that a given individual will be in the sample is unknown before sampling;. The theoretical basis for statistical inference is lost and the result is inevitably biased in unknown ways. Despite their best intentions, humans cannot choose a sample in a random fashion without a formal randomizing mechanism.

Other Allocation Procedures

  • Matching: When confounding cannot be controlled by randomization, individual cases are matched with individual controls that have similar confounding factors, such as age, to reduce the effect of the confounding factors on the association being investigated in analytic studies. Most commonly seen in case-control studies.
  • Restriction (Specification): Eligibility for entry into an analytic study is restricted to individuals within a certain range of values for a confounding factor, such as age, to reduce the effect of the confounding factor when it cannot be controlled by randomization. Restriction limits the external validity (generalizability) to those with the same confounder values.
  • Census: A sample that includes every individual in a population or group (e.g., entire herd, all known cases). A census not feasible when group is large relative to the costs of obtaining information from individuals.

Source Information