Sampling and sampling techniques PPT

Sampling and sampling techniques PPT

1. SAMPLING Presented By Mr. N. Sabari vel Tutor, CON, AIIMS, Jodhpur

2. INTRODUCTION Sampling is a process of selecting a number of individuals for a study in such a way that the individuals represent the larger group from which they were selected

3. NEED FOR A SAMPLEING Studying the entire population for a given problem situation is almost impossible. Sampling is important process for the following reasons:

4. CHARACTERISTICS OF A GOOD SAMPLE Representative Free from bias and error No substitution and incompleteness Appropriate sample size

5. SCHEMATIC PRESENTATION OF SAMPLING population Target population Accessible population Sample Subjects

6. SAMPLING PROCESS Identifying and defining the target population Describing the accessible population and ensure sampling frame Specifying the sampling unit Specifying sample selection methods Determining the sample size Specifying the sampling plan Selecting the desired sample

7. FACTOR INFLUENCING SAMPLING PROCESS Nature of researcher - Inexperience investigator - lack of interest - lack of honest - Intensive workload - Inadequate supervision Nature of the sample - Inappropriate sampling technique - Sample size - Defective sample frame

8. FACTOR INFLUENCING SAMPLING PROCESS Circumstances - Lack of time - large geographical area - lack of cooperation - Natural calamities

9. TYPES OF SAMPLING TECHNIQUES Probability sampling technique Simple random sampling Stratified random sampling Systematic random sampling Cluster and multistage sampling Sequential sampling Nonprobability sampling techniques Purposive sampling Convenience sampling Consecutive sampling Quota sampling Snowball sampling Volunteer sampling Genealogy sampling

10. FEATURES OF PROBABILITY SAMPLING It provide equal chances to all the individuals in the population of getting selected. this is feasible only if the used randomization Probability sampling techniques the chances of sampling bias are relatively less because subjects are randomly selected.

11. SIMPLE RANDOM SAMPLING This is a most pure and basic probability sampling design. The two important aspect need in simple random techniques first population must be homogeneous and researcher have list of members in accessible population The sampling frame can be used in following methods - lottery method - the use of table of random numbers - the use of computer

12. TABLE OF RANDOM NUMBERS Table present rows and columns Choose members list of the population Blindfold chooses a numbers from random table 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 1 37 75 10 49 98 66 03 86 34 80 98 44 22 22 45 83 53 86 23 51 2 50 91 56 41 52 82 98 11 57 96 27 10 27 16 35 34 47 01 36 08 3 99 14 23 50 21 01 03 25 79 07 80 54 55 41 12 15 15 03 68 56 4 70 72 01 00 33 25 19 16 23 58 03 78 47 43 77 88 15 02 55 67 5 18 46 06 49 47 32 58 08 75 29 63 66 89 09 22 35 97 74 30 80 6 65 76 34 11 33 60 95 03 53 72 06 78 28 14 51 78 76 45 26 45 7 83 76 95 25 70 60 13 32 52 11 87 38 49 01 82 84 99 02 64 00 8 58 90 07 84 20 98 57 93 36 65 10 71 83 93 42 46 34 61 44 01 9 54 74 67 11 15 78 21 96 43 14 11 22 74 17 02 54 51 78 76 76 10 56 81 92 73 40 07 20 05 26 63 57 86 48 51 59 15 46 09 75 64 11 34 99 06 21 22 38 22 32 85 26 37 00 62 27 74 46 02 61 59 81 12 02 26 92 27 95 87 59 38 18 30 95 38 36 78 23 20 19 65 48 50 13 43 04 25 36 00 45 73 80 02 61 31 10 06 72 39 02 00 47 06 98 14 92 56 51 22 11 06 86 88 77 86 59 57 66 13 82 33 97 21 31 61 15 67 42 43 26 20 60 84 18 68 48 85 00 00 48 35 48 57 63 38 84 Need to use Random Number Table

13. SIMPLE RANDOM SAMPLING Advantages Most reliable and unbiased methods Requires minimum knowledge of study population Sampling errors can be computed easily. Disadvantages Need up to date complete list of all member of the population. It may be uneconomical and time consuming.

14. STRATIFIED RANDOM SAMPLING This method is used for heterogeneous population Researcher divides the entire population into different homogeneous subgroups or strata. The strata are divided according to certain traits such as age, gender, religion, socio economical status, diagnosis, education, geographical region, types of institute, types of registered nurse. Stratified sampling is further divide in two categories - Proportionate stratified random sampling - Disproportionate stratified random sampling

15. STRATUM A B C Population size 100 200 300 Sampling fraction 1/2 1/2 1/2 Final sample size 50 100 150

16. STRATUM A B C Population size 100 200 300 Sampling fraction 1/2 1/4 1/6 Final sample size 50 50 50

17. STRATIFIED RANDOM SAMPLING Advantages It is often more convenient to recruit a stratified sample than a simple random sample. Comparison is possible in two groups. Ensure representative sample in heterogeneous population. Disadvantages Require complete information of population Large population is required. Chance of faulty calculation strata.

18. SYSTEMATIC RANDOM SAMPLING This is a method of selecting subjects from a larger population in which the first subject is selected randomly. The process of selecting individuals within the defined population from a list by taking every K th name.

19. SYSTEMATIC RANDOM SAMPLING

20. SYSTEMATIC RANDOM SAMPLING Advantages Convenient and simple to carry out Time consuming and cheaper than simple random technique Disadvantage If first Subject is not randomly selected, then it becomes non random sampling techniques. Sometimes may result in biased sample.

21. CLUSTER OR MULTISTAGE SAMPLING Cluster sampling technique is chosen when the population is too large and mostly using geographical unit. ( E.g.) To survey the academic performance of Indian high school students. The population is divided into subgroups (clusters) like families. Then each selected sampling unit, a sample of population is drawn by either simple random selection or stratified random sampling.

22. CLUSTER OR MULTISTAGE SAMPLING Advantages This is a less expensive method. It is less time consuming. Easier to apply large geographical area. Disadvantages The chance of error exists. This may be less accurate than a simple random sample.

23. SEQUENTIAL SAMPLING This method of sample selection is slightly different from other methods. Here the sample size is not fixed. The investigator initially select small sample and tries out to make inferences, if not able to draw results, he can adds more subject until clear cut inferences can be drawn.

24. SEQUENTIAL SAMPLING ( E.g.) A researcher is studying association between smoking and lung cancer. Number of subjects Smokers (A) Non smokers (B) Having lung cancer ( A) ( B) 20 7 12 2 1 30 18 22 5 3 50 28 22 10 4

25. NON PROBABILITY SAMPLING Random sampling is not possible in all settings as most researchers are bound by constraints such as time, money and resources. Non-probability sampling refers to techniques where the sample is assembled in a process that does not give all the individuals in the population an equal chance of being selected This type of sampling can be used when it needed to show that a particular trait is existent in population, qualitative, pilot or exploratory study.

26. PURPOSIVE SAMPLING Purposive sampling is more commonly known as judgmental or authoritative sampling. In this type of sampling subjects are chosen to be part of the sample with a specific purpose in mind. Researcher believe that some subjects are fit for research compared to other individuals. ( E.g.) A researcher wants to study the lived experiences of post disaster depression among people living in earthquake affected area of Gujarat

27. PURPOSIVE SAMPLING Uses of purposive sampling It is usually used when a limited number of individual possess the trait of interest. Advantages Simple to draw sample and useful in explorative studies. Save resources, as it requires less field work. Disadvantage Require considerable knowledge about the population. It is not always reliable sample, as conscious bias may exist

28. CONVENIENCE SAMPLING It is probably the most common of all sampling techniques used by nurse researchers. Here, the subjects are selected as per the convenience of the researcher or their easy accessibility to the researcher. Subjects are chosen mostly because they are easy to recruit. ( E.g.) A researcher want to conduct a study on older people residing in jodhpur and the researcher observe that he can meet several older people coming for morning walk in park, he can choose these people as his research subjects.

29. CONVENIENCE SAMPLING Uses of convenience study In pilot study convenience sample is usually used because it allow the researcher to obtain basic data and trends for his study without the complication of using random sample selection methods Advantages This technique is considering easiest, cheapest, and time consuming. Disadvantages It may not be representative of the entire population so bias occurs. The results are less reliable, Generalisability of the study results is limited.

30. VOLUNTEER SAMPLING Target subjects are informed through mass media to participate in study and interested participants may voluntarily contact researcher to participate in the study. ( E.g.) A nurse researcher is interested to assess the effectiveness of selected yoga techniques on the reduction of blood pressure.

31. VOLUNTEER SAMPLING Advantages Cost effect sampling techniques This technique help to collect large size data in limited period of time Disadvantages Sample bias occur Only interested people contact to participants Study result may lack of generalisability.

32. CONSECUTIVE SAMPLING Picks up all the available subject who are meeting the present inclusive and exclusive criteria. This method is better one comparing to other non probability sample techniques because it make a better representation of the entire population. ( E.g.) researcher want to study the activity pattern of post kidney transplant patients, he can select all post kidney transplant patient who meet the designed inclusive and exclusive criteria.

33. CONSECUTIVE SAMPLING Advantages Ensure more representative sample Convenient and less time consuming Disadvantages Researcher has no set plan about sample schedule Result from the sampling techniques cannot be create conclusion and interpretation pertaining to the entire population.

34. QUOTA SAMPLING

35. QUOTA SAMPLING This is a non-probability sampling technique where the population is first divided into subgroups or quotas, just as the population is divided into strata in stratified sampling. Subjects are selected conveniently (not randomly) from the strata, either proportionally or disproportionally, depending on the study requirements. ( E.g.) Researcher need 100 college students for study in quota he must select 25 first year students, another 25 second year students, 25 third year and 25 fourth year students.

36. SNOWBALL SAMPLING In this technique, the initial study participants are asked to suggest someone else who can meet the study criteria and be willing to participate in the study. This is usually done when the population size is very small and the researcher is unable to locate study participants on her own. ( E.g.) A researcher want to conduct a study on prevalence of HIV/AIDS among commercial sex workers.

37. TYPES OF SNOWBALL SAMPLING Linear snowball sampling: In this type, each selected subject is asked to provide the reference of one person who is similar to him. This process is like a linear chain hence it is termed as linear snowball sampling. This method is appropriate when the desired sample size is small.

38. TYPES OF SNOWBALL SAMPLING Exponential non-discriminative snowball sampling: Here, the subject initially recruited is asked to provide a reference to at least two similar subjects, and each of them further provides references to two subjects. It is appropriate when the desired sample size is large.

39. TYPES OF SNOWBALL SAMPLING Exponential discriminative snowball sampling: The subject initially recruited is asked to refer two subjects. From these two subjects, reference is sought from only one. It may enhance the representativeness of the sample.

40. GENEALOGY SAMPLING In this method all the members of entire families are selected rather than selecting the different households in the villages or area. The genealogy sampling begins with identifying a first participants who is convinced to participate in the study and then further he refer to close relatives of his family, who even may be living in other areas of village. This technique is primarily used in rural population and frequently used in genetics study.

41. SAMPLING IN QUALITATIVE STUDIES Convenience sampling technique Snowball sampling technique Purposive sampling techniques Maximum variation sampling Homogenous sampling Extreme case sampling Intensity sampling Reputational sampling

42. SAMPLE SIZE CALCULATION Allowable Error Method in Descriptive study n = (4Pq/L 2 )   n = number of samples P = Mean difference in previous study =2.4 q=100-p q=97.6 L= Allowable error n= (4x2.4x97.6)/5x5 n=37 37 +4= 41 (considering10 percent dropout) Sample size n=41

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