Presentation is loading. Please wait.

Presentation is loading. Please wait.

Sampling 9810004M Lydia 9810006M Pippen. Outline  Sampling strategies: Alternative Paradigms  External validity  Defining the population and sample.

Similar presentations

Presentation on theme: "Sampling 9810004M Lydia 9810006M Pippen. Outline  Sampling strategies: Alternative Paradigms  External validity  Defining the population and sample."— Presentation transcript:

1 Sampling 9810004M Lydia 9810006M Pippen

2 Outline  Sampling strategies: Alternative Paradigms  External validity  Defining the population and sample  Sampling strategies  Sample size  Access issues (consent form)

3 Sampling strategies: Alternative Paradigms The definition of sampling: select a given number of people or things from a population. A: Probability sampling: every member of the population actually has a possibility of being selected. B: Nonprobability sampling (purposeful sampling) theoretical sampling) : select members who had the particular experience before.

4 External Validity: Generalization or transferability Generalize findings to the target (larger) population, so need to provide sufficient thick description about the case.

5 Defining the population and sample  Conceptual definitions: use other constructs to explaining the meaning.  Operational definitions: specify how the construct will be measured.  Through the review studies, the researchers should formulate a formal, conceptual definition. Ex: target population=>first-grade students in Taiwan.  Operational definition of the sample (experimentally accessible population): defined as the list of people who fit the conceptual definition. Ex: all the first-grade students in ISU.

6 Sampling strategies 1.Probability sampling 2.Nonprobability(purposeful) (theoretical) sampling 3.Conveience sampling

7 Probability sampling: 1.Simple random sampling 2.Systematic sampling 3.Stratified sampling 4.Cluster sampling 5.Multistage Sampling

8 1.Simple random sampling: Each member of the population has an equal and independent chance of being selected. pro: it’s a simple process con: a complete list of the population might not be available may include some “outside”.

9 2.Systematic sampling: Select every nth name from the population list, so estimate the needed sample size and dividing the number of the names on the list by the sample size. ex:1000/100=10 Pro: not need to have an exact list of all the sampling units. Con: If the files are arranged in a specific pattern, that could result in choosing a biased sample.

10 3.Stratified sampling A: It used when there are subgroups of different size that you wish to investigate. B: Decide the population Into subgroups or levels and then draw randomly from each subgroup. Pro: easy to compare each subgroup result Con: must get information before dividing them

11 4.Cluster sampling It is used with naturally occurring groups of individuals. Ex: city blocks or classroom in a school, and study all the samples there. Pro: save time and money by collecting data at a limited number of sites. Con: small sample size, less precision in estimating the effect.

12 5.Multistage Sampling Combine sampling strategies. Ex: cluster sampling +random sampling Pro: more reliable Con: complex calculations

13  Purposeful or theoretical sampling (Nonprobability): the researcher select their samples with the goal of that allow them to study a case in-depth. 1.Extreme or deviant cases 2.Intensity sampling 3. Maximum-variation sampling 4. Homogeneous sampling 5. Typical-case sampling 6. Stratified purposeful sampling 7. Critical-case sampling 8.Snowball or chain sampling 9.Criterion sampling 10. Theory-based or operational construct sampling 11.Confirming and disconfirming cases 12.Opportunistic sampling 13.Purposeful random sampling 14.Sampling politically important cases

14 1.Extreme or deviant cases The selection of the cases might be to choose individuals or sites that are unusual or special in some way. Ex: analyze the highly successful program and compare them with the fail one. 2.Intensity sampling It’s similar to the extreme-case strategy, except there is less emphasis on extreme. Explore rich information on the typical cases.

15 3. Maximum-variation sampling Maximize the variation within the sample and indicate their major difference. EX: The study of students’ English ability in different location( rural, urban) 4. Homogeneous sampling The researcher seeks to describe the experience of subgroups of people who share similar characteristics. EX: rural teachers’ attitude toward CLT for children.

16 5. Typical-case sampling A: Choose the case in which a program has been implemented to show this case is indeed average. B: It is like Intensity sampling. 6. Stratified purposeful sampling A: It’s a combination of sampling strategies. B: Subgroups are chosen on specified criteria a sample of cases is selected within those strata. 7. Critical-case sampling A: Study a very important, critical case. B: The effect should be representative.

17 8.Snowball or chain sampling The research starts with a key person and introduce the next one to become a chain. 9.Criterion sampling The researcher set up a criterion and identify cases that meet that criterion. Ex: study cases that could pass TOEFL last semester 10.Theory-based or operational construct sampling: A: Define a theoretical construct B: Select the sample who have really that kind of experiment Ex: metacognitive learning on EFL reading development

18 11. Confirming and disconfirming cases: After analyzing sample cases, the researcher has to form grounded theory that fit (confirming) and do not fit (disconfirming) the major points in the literature. 12. Opportunistic sampling : A: The researcher should make a decision on the spot as to the relevance of the activity. B: Take the opportunity to decide the sampling procedure or samples during the study.

19 13. Purposeful random sampling: A: To choose those who will be included in a very small sample. B: Randomly select participants who had similar experiences in a very small sample 14. Sampling politically important cases: The rationale rests on the perceived credibility of the study by the person expected to use the results. (Use particular samples) Ex: KMT DPP

20  Example of qualitative research sampling Convenience sampling: Convenience sampling means that the persons participating in the study were chosen because they were readily available. EX: Neighbors, friends

21 Pros and Cons of purposeful sampling and Convenience sampling: Pro: 1. Spend less cost and time 2. Ease of administration 3. Assures high participation rate 4. Generalization possible to similar subject 5. ( Assures receipt of needed information) Con:1. Difficult to generalize to other subjects 2. Less representative of an identified population 3. Greater subject bias

22 Access issues A. Get permission and agreement with the appropriate person (e.g., school principal, classroom teacher, or parents) B. Obtain consent form from the participants C. How to “label” students if using stratified sampling D. Consider appropriate sample size

23 Sample Size: For different types of research, rule of thumb can be used to determine the appropriate sample size. Rules of thumb: A: Quantitative research rules of thumb: For survey research needs 100 cases. B: Qualitative research rules of thumb: For grounded theory needs30~50 interviews.

24 Access to records Consent form: A. Explain research purpose, duration, and procedures B. Describe any risk or discomfort C. Describe confidentiality or anonymity D. Provide the name of person to contact with E. Provide voluntary participation, and available to refuse or withdraw any time

Download ppt "Sampling 9810004M Lydia 9810006M Pippen. Outline  Sampling strategies: Alternative Paradigms  External validity  Defining the population and sample."

Similar presentations

Ads by Google