1. Dr. Dalia El-Shafei Assistant Professor, Community Medicine Department, Zagazig University

2. Epidemiological Study Sample Comprehensive Study a sample selected from the population. Study a sample selected from the population. Study the whole population. Study the whole population.

3. Any group of things or individuals having the same characters. Population

4. Sample It is a group of individuals (or things) selected from larger population and is used to get certain information about this population. Each member of the population is called the sampling unit and the sample will be formed of these sampling units i.e. people. The basis of sampling is to try to get, as much as we can, a true representation of the population itself. It is a group of individuals (or things) selected from larger population and is used to get certain information about this population. Each member of the population is called the sampling unit and the sample will be formed of these sampling units i.e. people. The basis of sampling is to try to get, as much as we can, a true representation of the population itself.

5. Sampling Non-probability Accessibility Quota Probability Simple random Systematic random Stratified random Cluster Multi-stage random Probability sample: probability of selecting an individual is 50% “no selection bias”. Probability sample: probability of selecting an individual is 50% “no selection bias”. Types of sample

6. Probability SampleNon- probability Sample Investigator has minimal role in selection. Sample is representative (each individual has an equal chance of being in the sample). We can generalize the results. Investigator has a role in selection. Sample is not representative (not each individual has an equal chance of being in the sample). We cannot generalize the results

8. Sampling Non-probability Accessibility Quota Probability Simple random Systematic random Stratified random Cluster Multi-stage random Probability sample: probability of selecting an individual is 50% “no selection bias”. Probability sample: probability of selecting an individual is 50% “no selection bias”. Types of sample

9. Accessibility (convenient) sample Convenient & accessible sample units are selected. They may be : -nearest neighbors or relatives. - volunteers. - hospital cases. Used in: - Studying rare diseases which are available only in hospital. - Studying occupational health hazard, you have to take your sample from workers exposed.

10. Quota sampling The investigator will pick a sample of a certain size & structure but the choice of the actual sampling units does not follow a special scheme but left to his choice.

11. Cheap Quick Not require a sampling frame Advantages Not a good representation of the population Great variability between persons in quota sample. Disadvantages

12. Example: interview of all persons passing in a certain street at certain time. The sample is complete when the desired number of population is reached. This can be done in T.V. to known public opinion for the preferable programs but it is seldom used in scientific medical researchers. Example: interview of all persons passing in a certain street at certain time. The sample is complete when the desired number of population is reached. This can be done in T.V. to known public opinion for the preferable programs but it is seldom used in scientific medical researchers.

14. Sampling Non-probability Accessibility Quota Probability Simple random Systematic random Stratified random Cluster Multi-stage random Probability sample: probability of selecting an individual is 50% “no selection bias”. Probability sample: probability of selecting an individual is 50% “no selection bias”. Types of sample

15. Simple random sample Suitable in small population. Not suitable in large population. Process: - construct “Sample frame”. - decide “Sample size”. - select the sampling units randomly “lottery or random table or computer”.

16. For example: if we want to select 5 individuals out of 15. We need first to give number for each individual(15)(sampling frame),then randomly select the needed sample (5 unit) by lottery from a box containing numbers from 1 till 15. If we need 50 pupils to be our sample, we can select them randomly from school list records (our frame is the school). For example: if we want to select 5 individuals out of 15. We need first to give number for each individual(15)(sampling frame),then randomly select the needed sample (5 unit) by lottery from a box containing numbers from 1 till 15. If we need 50 pupils to be our sample, we can select them randomly from school list records (our frame is the school). If the sample will be chosen from a large population (as government) framing is difficult as enlistment of the whole population living there is difficult, therefore we have to use other sampling methods.

18. Systematic random sampling  It is a modified method of the simple random sample.  The selection depends on constant interval (k interval)  Sampling interval=total population/sample size.  1 st number is selected randomly.  Then add the sampling interval to the random start to select subsequent units.

19. Advantages No selection bias Not require sample frame Used for large population

20. Example: We need 5 persons from 15. Sampling interval = 15/5. We take every 3rd person starting from a random number selected from the first 3 numbers.

21. Example: We need to select individuals from outpatient clinic. No frame, no of total population is unknown. We decide the sample size. We start by a random no from (1-10). If we start with no 7, we select every 7 th person come to clinic till reach the sample size.

22. Stratified random sampling Population divided into strata according to some characteristics. From each strata, select the units by using random method. Every character appear in the sample.

23. Example: Population is classified into 2 strata (male & female). Select the same number from male & female. If the age is different, divide the sample of each sex into age groups. Select equal number from each age group randomly.

25. Cluster sampling Process The area is divided into clusters One or 2 clusters are selected randomly All individuals in each cluster are included Cluster: a group of individuals present in certain locality or geographic area.

26. Example: We need to select 5000 individuals live in rural areas in Sharkia Governorate. We suspect that this no. will be found in 2 villages. We select 2 villages randomly. All individuals in the 2 villages are included.

28. Multistage sampling Used in national or widespread study. Selection process is arranged in stages. From each stage, select a sample randomly.

29. Example: Select 2 from 28 governorates randomly. Select 2 cities from each governorate (4 cities). Select one or more district from each city. Select the desired number of houses from each district & so on  individuals.