Sampling and Sampling Procedures

 In most epidemiologic studies, we deal with a sample of the population  The study population may be:  An entire population  A group of the population with certain characteristics - age - sex - religion - social status  Hospital inpatients

 A sample is a portion of the population, used for survey purposes when you can not examine the entire population because the resources are not adequate.  A sample should be a representative group of the whole population to be studied.  When a sample is representative to the whole population, generalization from the sample can be made.

 A number of techniques can make the sample a representative group of the whole population.  Only the simpler techniques will be considered in this lecture, and when used with care will meet the requirements of epidemiologic studies.  Complex sampling methods need the help of a statistician.

 The precision with which the investigator make generalization from a sample to the entire population is related to the size of the sample.

 Sample selection needs a list of all members (units) of the community from which a sample is selected.  The sampling units may be : 1. Individuals 2. Families 3. Blocks in a city 4. Class in a school 5. Whole school

Probability sampling:  which is the most recommended method because all sampling units have the same probability of being selected and included in the study.  This method assures that the sample is a representative of the whole population.  Inferences from the sample can be made about the whole population (generalization of results to the whole population).

Sampling techniques include the following : Haphazard sample:  Ex- in an experiment, where the experimental animal is chosen as the investigator can catch the animal from the cage.

Selected sample:  The individuals are selected according to the investigator’ opinion that they are typical of the population being studied and is appropriate for the study objective.  The sample may be selected because it is handy sample.  selection of groups known to be co-operative  The disadvantage of this sample is that you can not be confident that this sample represents the population, so generalization cannot be made out of this sample.

Self-selected sample:  The sample consists of individuals who volunteered for an experiment.  Such method can provide some information about the population and can serve as a basis for future adequate studies  Generalization cannot be made out of this sample.

 A sample may be defined as random if every individual in the population has an equal chance of being included in the sample.  Random selection is the basis of this sampling technique.  Any method of selection based on volunteering or selection of groups known to be co-operative is excluded and cannot be used for generalization to the entire population.

It is necessary to have a complete list of sampling units of the total population:  Individual persons  House holds  Schools  cities

To select a simple random sample:  Make a numbered list of the units in the population (assign a number to each individual)  Estimate the size of the sample  Select the required number of sampling units using a table of random numbers.

If the size of the population is not too large:  Write the numbers on small cards  Place them in a bowl and mix them thoroughly  The number representing the sample size is selected from the bowl.

Systematic sample ( more efficient):  In this sampling method, every nth person in the list is chosen and included in the sample  If the list contains 10,000 units and the researchers wants 1,000 units, he will select one person every 10 persons (nth =10)  The first person will be selected at random between numbers from 1-10, then every tenth unit will be selected.

 This sampling method is used when a large survey is planned to cover a district, governorate or the entire country (two stage sampling).  If there is no satisfactory list of the population is available ( there is no list of a city’s population),  a list of groups or clusters of individuals is available, such as city districts, census neighborhoods, villages or schools.  a random sample of these clusters is selected and all individuals in the cluster are included in the study (one stage sampling).

 An initial sample is taken from the units:  Neighborhoods entire district  Villages entire governorate  Governorates entire country  Then a listing of individuals within the chosen units (clusters) is made and a random sample is taken from each (two stage sampling).  The disadvantage to this method is that disease may be accumulated in some clusters giving misleading results.

Stratified random sample:  If the severity of the disease differs according one or more characteristics such as sex, age, or socio-economic status, then the population to be sampled should be divided into subgroups or strata according to the characteristics that affect the disease.  Then random sample is selected within each stratum and all individuals in each stratum are included in the study.

Stratified random sample: To assess the prevalence of a disease like caries which is unevenly distributed among age groups, we have to obtain a sample stratified by age: 1. The study population is subdivided into age groups such as 6-12, 13-18, and 26 and over. 2. A certain number of each age group is then selected randomly and all individuals in each age stratum are included in the study.