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Objectives -- After completing this module, you will be able to:
Required Materials Topic 1: Why is sampling so important -- both for "qualitative" and for "quantitative" studies? I base the videos and readings for this module on the assumption that you have little or no prior knowledge about sampling for research purposes. If you DO have experience and knowledge, you will be able to move through the materials quickly. Feel free to do so. I lay out a specific step-by-step approach to covering the materials based on my assumption of little prior knowledge. I provide a series of videos, documents that I have created (my cheat sheets), and readings that cover what you need to gain in the module in (I hope) an efficient way. The learning guide for this week is not specific to any one of the required materials. Use it as a guide to what you need to get from the materials as a whole. If you cannot answer a question in the learning guide, you missed something that I consider important about sampling. In short, use this learning guide as a sort of checklist and check off the questions in it one by one as you work through the materials for this week to make sure you get a good understanding of the basics of sampling. Learning Guide: Basics of Sampling Topic 2: What are the different types of samples? Types of Samples This is my "so simple it is scary" cheat sheet about the general types of samples, both random and non-random. Basics of Sampling This scary cheat sheet prepares you for the rest of the materials (I hope). The Goals of Research Design You have seen this before. I suggest you keep it at hand as you think about the role of sampling in achieving these goals. Video 1 is short -- 4 minutes. It discusses an important concept -- weighting and lays out the principles of statistical sampling logic -- a concept we will discuss in detail. Pew Methods 101 Basics of Random Sampling. Topic 3: The details of sampling Bernard, pp. 127-145 (All of Chapter 5) Blair, E. & Blair, J. (2015) Applied Survey Sampling, Sage, Thousand Oaks, CA. Ch. 1, Introduction to Sampling, pp. 3-26. e-reserve This reading is repetitive of what is in Bernard and my cheat sheets to some degree. I ask you to read it because sampling is complex and because different very well qualified people do have different perspectives about some key features. For example, Blair & Blair are much more cautious about generalizing conclusions based on non-probability samples than Bernard or me, but do see a role for them in the preliminary stages of a research project -- to test instruments, determine priorities for hypothesis development, and similar work you have to do prior to conducting a study that you can use to draw generalizable conclusions. This is a lengthy reading, BUT you do not have to read the entire chapter in detail. Here is my advice about reading this selection. Read very quickly or even skip sections 1.1 (Introduction) and 1.2 (A Brief History of Sampling). Read section 1.3 (Sampling Concepts) carefully. I think it is superior to my cheat sheet. I encourage you to work through Case Study 1.1 by yourself to see how well you understand the material covered in section 1.3. Read Section 1.4 (Guidelines for Good Sampling), which is excellent -- also see Exhibit 1.2 on page 23. This table is excellent and I encourage you to make sure you understand it clearly. It will be a critical guide to answering many questions in Assignment 3. Bernard, Chapter 6: Sampling Theory. We will discuss this in class. Do NOT be concerned if it is confusing. It confuses me, too, on occasions. We will discuss the key concepts in class. Read the summary section of t his chapter on p. 160 BEFORE you read the chapter itself. Bernard lays out what I want you to understand very clearly in just a few sentences. The Kreamer reading (see blow) will help. If Bernard seems confusing, read kreamer and Blasey first. Kreamer, Helena Chmura & Blasey, Christine. (2016) How Many Subjects? Statistical Power Analysis in Research. Sage Publications, Thousand Oaks, California. Chapter 2, pp. 22-29. e-reserve This is an easy-to-read explanation of the concepts of power and precision, the key paramaters you must use to decide "how big" a sample you need. I don't expect you to actually calculate a sample size in assignments in this class. I do expect you to understand these concepts thoroughly and be able to explain how you would apply these concepts to determine sample size for the research design you create in course assigments. You should also use these concepts in your discussion of the adequacy of the sample in the article you analyze for Assignment 3. The Pew Research Center for the People and the Press conducts a great deal of social research in the United States and internationally. They are real "sampling gurus" and they explain everything they do -- no mysteries in their approach. This website addresses many issues in probability sampling, including non-response, the impact of cell phones, sampling for under-represented groups and such. Use this resource in Assignment 2 to understand the specific techniques, assumptions and limitations of the sampling procedures used in the article you analyze. It has easy-to-read discussions of contemporary sampling issues, such as the impact of cell phones on telephone sampling. It has a lot of very good material that will also be useful for your own research and Assignment 4 as well. http://people-press.org/methodology/sampling/#3 Advance Preparation You will complete Assignment 2 in a group. I will assign your members. Look through the two lists of articles and pick your personal two or three favorites prior to class this week. Do NOT pick based on topic. That will not work. Look at abstracts and try to identify "good" articles from a research design perspective based on the criteria for a good abstract. I will activate the link to instructions for Assignment 2 after this class session -- it will make more sense after we get through this material. List A Articles for Assignment 2 List B Articles for Assignment 2 Flow Chart for Articles You Read Example of a completed Flow Chart for Articles You Read Additional Resources about Sampling This is a good week to share materials with your colleagues. This is a substantive list of materials about sampling that you can use to complete Assignments 2, 3 & 4. Share a few and earn some extra points! Abrams, L.S. (2010) Sampling "hard to reach" populations in qualitative research. Qualitative Social Work 9(4), 536-550. Ahern, K. & LeBrocque, R. (2005) Methodological issues in the effects of attrition: simple solutions for social scientists. Field Methods 17(1), 53-69. Alessi, M.G. & Miller, C.A. (2012) Comparing a convenience sample against a random sample of duck hunters. Human Dimensions of Wildlife 17(2), 155-158. Ancresen, E.M., Diehr, P.H. & Luke, D.A. (2004) Public health surveillance of low-frequency populations. Annual Review of Public Health, 25, 25-52. Barratt, M.J., Ferris, J.A. & Lenton, S. (2014) Hidden populations, online purposive sampling, and external validity: Taking off the blindfold. Field Methods 27(1), 3-21. Beckett, M. (2000) Converging health inequalities in later life -- an artifact of mortality selection? Journal of Health and Social Behavior 41, 106-119. Benoot, C., Hannes, K. & Bilsen, J. (2016) The use of purposeful sampling in a qualitative evidence synthesis: A worked example on sexual adjustment to a cancer trajectory. BMC Medical Research Methodology 16, 1-12. Bethlehem,
J. (2016) Solving the nonresponse problem with sample matching. Social
Science Computer Review 34(1), 59-77. Bernard, R.H.
(2000). Social Research Methods. Sage Publications, Thousand Oaks.
Pages 143-172. E-reserve Brick, J.M. (2011) The future of survey sampling. Public Opinion Quarterly 75(5), 872-888. Bryant, J.
(2014) Using respondent-driven sampling with "hard to reach"
marginalised young people: Problems with slow recruitment and small network
size. International Journal of Social Research Methodology 17(6),
599-611. Connelly, N.A.,
Brown, T.L. & Decker, D.J. (2003) Factors affecting response rates
to natural resource-focused mail surveys: Empirical evidence of declining
rates over time. Society & Natural Resources 16(6), 541-549.
De Boni, R.,
Do Nascimento Silva, P.L., Bastos, F.I., Pechansky, F. et al. (2012) Reading
the hard-to-reach: A probability sampling method for assessing prevalence
of driving under the influence after drinking in alcohol outlets. PLoS
ONE 7(4), 1-9. Draugalis,
J.R. & Plaza, C. (2009) Best practices for survey research reports
revisited: Implications of target population, probability sampling, and
response rate. American Journal of Pharmaceutical Education 73(8),
1-3. Ellard-Gray,
A., Jeffrey, N.K., Choubak, M. & Crann, S.E. (2015) Finding the hidden
participant: Solutions for recruiting hidden, hard-to-reach, and vulnerable
populations. International Journal of Qualitative Methods 14(5),
1-10. Emery, S.,
Lee, J., Curry, S.J., Johnson, T. et al. (2010) Finding needles in a haystack:
A methodology for identifying and sampling community-based youth smoking
cessation programs. Evaluation Review 34(1), 35-51. Etter, J &
Perneger, T.V. (2000) Snowball sampling by mail: application to a survey
of smokers in the general population. International Journal of Epidemiology
29, 43-48. Evans, K.L.,
Greenwood, J.J.D. & Gaston, K.J. (2007) The positive correlation between
avian species richness and human population density in Britain is not
attributable to sampling bias. Global Ecology and Biogeography,
16(3), 300-304. Gile, K.J.
& Handcock, M.S. (2010) Respondent-driven sampling: An assessment
of current methodology. Sociological Methodology 40(1):, 285-327. Glick, P. (2008) Restating the case: The benefits of diverse samples for theory development. Psychological Inquiry 19(2), 78-83. Griffith, D.A., Morris, E.S. & Thakar, V. (2016) Spatial autocorrelation and qualitative sampling: The case of snowball type sampling designs. Annals of the American Association of Geographers 106(4), 773-787. Guo, Y., Li,
X., Fang, X., Lin, X. et al. (2011) A comparison of four sampling methods
among men having sex with men in China : Implications for HIV/STD surveillance
and prevention. AIDS Care 23(11), 1400-1409. Gupta, S.,
Shuaib, M., Becker, S., Rahman, M.M. & Peters, D.H. (2011) Multiple
indicator cluster survey 2003 in Afghanistan: Outdated sampling frame
and the effect of sampling weights on estimates of maternal and child
health coverage. Journal of Health, Population & Nutrition
29(4), 388-399.. Henry, G.T. (2008) Practical sample design. PP. 33-59 in Practical Sampling, Sage, London. e-reserve Jacobson, C.A., Brown, T.L. & Scheufele, D. (2007) Gender-biased data in survey research regarding wildlife. Society & Natural Resources 20(4), 373-377. Kondo, M.C.,
Bream, K.D.W., Barg, F.K. & Branas, C.C. (2014) A random spatial sampling
method in a rural developing nation. BMC Public Health 14(1),
1-15. Korner, T. & Nimmergut, A. (2004) Using an access panel as a sampling frame for voluntary household surveys. Statistical Journal of the UN Economic Commission for Europe 21(1), 33-52. Livingston,
M., Dietze, P., Ferris, J. et al. (2013) Surveying alcohol and other drug
use through telephone sampling: A comparison of landline and mobile phone
samples. BMC Medical Research Methodology 13(1), 1-7. Miller, P.G.,
Johnston, J. Dunn, M., Fry, C.L. & Degenhardt, L. (2010) Comparing
probability and non-probability sampling methods in ecstasy research:
Implications for the internet as a research tool. Substance Use &
Misuse 45(3), 437-450. Mookherji,
S. & LaFond, A. (2013) Strategies to maximize generalization from
multiple case studies: Lessons from the Africa Routine Immunization System
Essentials (ARISE) project. Evaluation 19(3), 284-303. Murray, G.R.,
Rugeley, C.R., Mitchell, D. & Mondak, J.J. (2013) Convenient yet not
a convenience sample: Jury pools as experimental subject pools. Social
Science Research 42(1), 246-253. Nguyen, P. (2004) The census, sampling and African Americans. Western Journal of Black Studies 28(1), 292-302. Noy, C. (2008)
Sampling knowledge: The hermeneutics of snowball sampling in qualitative
research. International Journal of Social Research Methodology
11(4), 327-344. Ozdemir, R.S.
, St. Louis, K.O. & Topbas, S. (2011) Public attitudes toward stuttering
in Turkey: Probability versus convenience sampling. Journal of Fluency
Disorders 36(4), 262-267. Pike, G.R. (2007) Assessment measures: Using samples in assessment research. Assessment Update 19(2), 12-14. Polit, D.F.
& Beck, C.T. (2010). Generalization in quantitative and qualitative
research: Myths and strategies. International Journal of Nursing Studies.
47(11) 1451-1458. Reddy, S & Davalos, L.M. (2003) Geographical sampling bias and its implications for conservation priorities in Africa. Journal of Biogeography 30, 1719-1727. Roy, K., Zvonkovic,
A., Goldberg, A., Sharp, E. & LaRossa, R. (2015) Sampling richness
and qualitative integrity: Challenges for research with families. Journal
of Marriage and Family 77(1), 243-260. Rumpf, H.J.,
Bischof, G., Hapke, U., Meyer, C. & John, J. (2000) Studies on natural
recovery from alcohol dependence: sample selection bias by media solicitation?
Addiction 95(5), 765- 775. Sadler, G.R.,
Lee, H.C., Lim, R.S. & Fullerton, J. (2010) Recruitment of hard-to-reach
population subgroups via adaptations of the snowball sampling strategy.
Nursing & Health Sciences 12(3), 369-374. Seawright, J. & Gerring, J. (2008) Case selection techniques in case study research: A menu of qualitative and quantitative options. Political Research Quarterly 61(2), 294-308. Simmons, A.D.
& Bobo, L.D. (2015) Can non-full-probability internet surveys yield
useful data? A comparison with full-probability face-to-face surveys in
the domain of race and social inequality attitudes. Sociological Methodology
45(1), 357-387. Slep, A.M.S., Heyman, R.E., Williams, M.C., VanDyke, C.E. & O'Leary, S.G. (2006) Using random telephone sampling to recruit generalizable samples for family violence studies. Journal of Family Psychology 20(4), 680-689. Sydor, A. (2013)
Conducting research into hidden or hard-to-reach populations. Nurse
Researcher 20(3), 33-37. Tuckett, A.
(2004) Qualitative research sampling: The very real complexities. Nurse
Researcher 12(1), 47-60. White, V.M.,
Hill, D.J. & Effendi, Y. (2004) How does active parental consent influence
the findings of drug-use surveys in schools? Evaluation Review 28(3),
246-252. Yin, R.K. (2013) Validity and generalization in future case study evaluations. Evaluation 19(3), 321-332. Wretman, J. (2010) Reflections on probability vs nonprobability sampling. In M. Carlson, H. Nyquist & M. Villani (eds.), Official Statistics -- Methodology and Applications in Honour of Daniel Thorburn, pp. 29-35. Available at http://officialstatistics.files.wordpress.com/2010/05/bok03.pdf Zhu, J.J.H., Mo, Q., Wang, F. & Lu, H. (2010) A random digit search (RDS) method for sampling of blogs and other user-generated content. Social Science Computer Review. 29(3), 327-339. |