Good references on sample size for quantitative study when sampling frame is big, say more than three hundred thousands and the listing of all individuals is not possible?
Hello Bibek -
It isn't just how big the sample size may be that matters, it's how the sample is constructed. If you want to be able to infer from a sample to a population, there are two basic ways: (1) by a randomized selection, where the inverse of the probability of selection is used to weight the sample up to the population, or (2) by use of regression modeling to relate the sample data (y) to regressor data (x), where the x are known for the population. Or (3), a combination of (2) and (3). Otherwise you can have seriously biased results. Even (2) alone can be risky.
It is often good to stratify (categorize) your population, regardless, to reduce uncertainty.
A sample size, from your reduced-bias sample, is then determined by how large it needs to be to reduce, typically, standard error of a mean or total, and this also depends upon the details of your sample design, and population or subpopulation standard deviation(s). And this assumes you do not strain resources and lose data quality.
With a large size for each subpopulation or stratum, you may not need to worry about a finite population correction factor.
Because you cannot cleanly identify your population, I assume that presents a challenge in drawing a "representative" sample as described above. Perhaps you are in a situation where you need an area frame, where your sampling unit is at a higher level, and you use a two-stage sample where you first choose among the larger units, and then sample or census at the level you want within the larger units chosen. Therefore, you may want to research the following terms: "multistage sampling," "area sampling," and "cluster sampling."
If you are doing a nonprobability sample with no regressor data, then results can be substantially biased, and there is no way to really measure standard error and no sample size requirement 'formulas.' The best you might do is to divide your population into categories and be sure to sample from each, and repeatedly sample enough that your mean results in each category stop changing to an unacceptable degree ... meaning unacceptable to the certainty your subject matter and application requires.
At any rate, it might be best to start with a pilot study.
Best wishes - Jim
PS - Some references:
Cochran, W.G(1977), Sampling Techniques, 3rd ed., John Wiley & Sons.
Blair, E. and Blair, J(2015), Applied Survey Sampling, Sage Publications.
Lohr, S.L(2010), Sampling: Design and Analysis, 2nd ed., Brooks/Cole.
Särndal, CE, Swensson, B. and Wretman, J. (1992), Model Assisted Survey Sampling, Springer-Verlang.
Kish, Leslie, 1965, Survey Sampling, John Wiley & Sons, Wiley Classics Library Edition Published 1995
Brewer, KRW (2002), Combined survey sampling inference: Weighing Basu's elephants, Arnold: London and Oxford University Press.
Ken Brewer's Waksberg Award article:
Brewer, K.R.W. (2014), “Three controversies in the history of survey sampling,” Survey Methodology,
(December 2013/January 2014), Vol 39, No 2, pp. 249-262. Statistics Canada, Catalogue No. 12-001-X.
http://www.statcan.gc.ca/pub/12-001-x/2013002/article/11883-eng.htm
https://www.researchgate.net/publication/261947825_Projected_Variance_for_the_Model-based_Classical_Ratio_Estimator_Estimating_Sample_Size_Requirements
_______________________
J. Michael Brick on Inference from Nonprobability Sampling:
...............
This may be of interest:
"2014 WSS PRESIDENT’S INVITED SEMINAR,"
http://washstat.org/seminars/2014/20140326_brick.html
In that seminar, Mike Brick addressed a committee report on non-probability sampling of many types:
https://www.researchgate.net/publication/273561892_Summary_Report_of_the_AAPOR_Task_Force_on_Non-probability_Sampling
...............
"The Future of Survey Sampling"
Article in Public Opinion Quarterly 75(5):872-888 · December 2011
Impact Factor: 2.25 · DOI: 10.2307/41345915
https://www.researchgate.net/publication/261967521_The_Future_of_Survey_Sampling
---
"Beyond traditional survey taking: adapting to a changing world
Explorations in Non-Probability Sampling Using the Web," J. Michael Brick
Proceedings of Statistics Canada Symposium 2014
http://www.statcan.gc.ca/sites/default/files/media/14252-eng.pdf
Conference Paper Projected Variance for the Model-based Classical Ratio Estim...
Article Summary Report of the AAPOR Task Force on Non-probability Sampling
Article The Future of Survey Sampling
- Badges
- Science topic
- Similar topics
- Linguistics
- Composition Studies
- Publication