2.1: General Considerations

State the objectives clearly and concisely. The statement should include the parameters being estimated and the unit of concern. Usually, it is best to limit the number of objectives, otherwise the sampling strategy and study design can become quite complex. The investigator usually will have a reference or target population in mind. This population is the aggregate of individuals whose characteristics will be elucidated by the study. The population actually sampled is often more restricted than this target population, and it is important that the sampled population be representative of the target population. It would be inappropriate to attempt to make inferences about the occurrence of disease in the swine population of an entire country (the target population) based on a sample of swine from one abattoir or samples obtained from a few large farms (the sampled population). As another example, data from diagnostic laboratories usually are not representative of problems in the source population and hence would not be appropriate for estimating disease prevalence. In planning a sample, note the type and amount of data to be col- 24 I I Basic Principles lected. If the objectives are straightforward and few in number, this aspect of planning is easy. At this stage of planning, explicit definitions of the outcome must be considered. That is, in a study to estimate the frequency of metritis in dairy cows, the outcome {metritis), must be dearly defined. This increases the scientific validity of the study and allows other workers to compare their results (similarities and differences) to those of the survey. Related to this matter is the data collect.ion method (e.g., personal interview, mailed questionnaire, special screening tests). Identifying the validity and accuracy of data collection methods are discussed in Chapter 3. Because the results of samples are subject to some uncertainty due to sampling variation, it is important to consider how precise (quantitatively) the answer needs to be. The results of different samples will, in general, not be equal; the greater the precision required (the smaller the sample to sample variation), the larger the sample must be. Factors that influence the number of sampling units required in surveys are discussed in 2.2.8, analytic studies in 2.4.4. Prior to selecting the sample, the sampled population must be divided into sampling units. The size of the unit can vary from an individual to an aggregate of individuals, such as litters, pens, or herds. The list of all sampling units in the sampled population is called the sampling frame. Often because of practical considerations, although the unit of concern may be individuals, aggregates of individuals are used as the initial sampling unit. For example, although the objective might be to estimate the prevalence of brucella antibodies in cattle (the unit of concern). the initial sampling unit might be the herd, since a list of all cattle in the population would be difficult to construct. In other instances, to estimate the average somatic cell count of milk in dairy herds, the unit of concern is the herd and it also could be the sampling unit (e.g., a convenient way of obtaining a representative sample of milk from the herd would be to take an aliquot portion of milk from the bulk milk tank). Finally, before proceeding with the full study it is important to pretest the procedures to be used. Such pretesting should be sufficiently rigorous to detect deficiencies in the study design. This would include the sample selection, clarity of questionnaires, and acceptability and performance of screening tests. This pretest should also be used to evaluate whether the data to be collected in the actual study are appropriate to answer the original objectives.