Overview of Sampling Methods II
-
Upload
chandelle-daria -
Category
Documents
-
view
32 -
download
0
description
Transcript of Overview of Sampling Methods II
![Page 1: Overview of Sampling Methods II](https://reader035.fdocuments.in/reader035/viewer/2022062517/5681354d550346895d9ca920/html5/thumbnails/1.jpg)
SADC Course in Statistics
Overview of Sampling Methods II
(Session 04)
![Page 2: Overview of Sampling Methods II](https://reader035.fdocuments.in/reader035/viewer/2022062517/5681354d550346895d9ca920/html5/thumbnails/2.jpg)
2To put your footer here go to View > Header and Footer
Learning ObjectivesBy the end of this session, you will be able to
• describe accessibility sampling, quota samples, purposive sampling
• explain what is meant by a systematic sample, cluster sample, a multistage sample
• take a sample according to one of the above sampling schemes
• explain the difference between probability and non-probability samples.
![Page 3: Overview of Sampling Methods II](https://reader035.fdocuments.in/reader035/viewer/2022062517/5681354d550346895d9ca920/html5/thumbnails/3.jpg)
3To put your footer here go to View > Header and Footer
• Accessibility sampling – sample only the most convenient sampling units – sometimes called convenience sampling (not advised)
• Purposive sampling – sampling a given number of ‘typical’ or ‘representative’ sampling units
• Quota sampling - a particular form of purposing sampling where choice of actual sample is left to the enumerator’s discretion– enumerator asked to fill a pre-specified quota (a
fixed sample size for each sample segment )
Pre-statistical sampling
![Page 4: Overview of Sampling Methods II](https://reader035.fdocuments.in/reader035/viewer/2022062517/5681354d550346895d9ca920/html5/thumbnails/4.jpg)
4To put your footer here go to View > Header and Footer
Difficulties with above schemes
• Accessibility samples will usually be highly biased – not an advisable approach
• Purposive sampling often done at initial stages of sampling to ensure good coverage – with good reason sometimes – more on this later
• Quota sampling (often done in opinion polls, market surveys, etc) has the advantage of being cheap and quick and not requiring the existence of a sampling frame. However, it can lead to an very biased sample if interviewer convenience has a big effect (often NOT the case for telephone polling)
![Page 5: Overview of Sampling Methods II](https://reader035.fdocuments.in/reader035/viewer/2022062517/5681354d550346895d9ca920/html5/thumbnails/5.jpg)
5To put your footer here go to View > Header and Footer
Probability sampling• These are samples where every individual
in the population has a known non-zero probability of entering the sample.
• Such schemes allow the sampling error to be quantified and the chance of bias reduced.
• Simple and stratified random sampling discussed in the previous session are examples of probability based sampling procedures – others outlined below.
• In practice, partial deviations from prob-ability sampling occur with good reason.
![Page 6: Overview of Sampling Methods II](https://reader035.fdocuments.in/reader035/viewer/2022062517/5681354d550346895d9ca920/html5/thumbnails/6.jpg)
6To put your footer here go to View > Header and Footer
Systematic samplingThis method requires a well-established sampling frame, i.e. list of all population members.
The procedure involves selecting one element at random from the first k elements in the list, then selecting every kth unit thereafter, progressing through the list in a systematic way.
This leads to approximately (1/k)*100% of the population entering the sample
![Page 7: Overview of Sampling Methods II](https://reader035.fdocuments.in/reader035/viewer/2022062517/5681354d550346895d9ca920/html5/thumbnails/7.jpg)
7To put your footer here go to View > Header and Footer
Remarks about systematic sampling
• The process is simple, and is useful where a list of units already exists, e.g. telephone directory, list of customers in a bank
• It can also be useful in studies requiring a good geographical spread, by imposing a grid on a map of the region.
• It assumes that the original list from which the sample is drawn is itself organised in a “random” manner which is independent of the key variables of interest in the study.
![Page 8: Overview of Sampling Methods II](https://reader035.fdocuments.in/reader035/viewer/2022062517/5681354d550346895d9ca920/html5/thumbnails/8.jpg)
8To put your footer here go to View > Header and Footer
Limitations of systematic sampling
• The assumption that the original list is random may not be true.
• The theory is less well developed. Hence analysis of the data relies on assuming that the sample is like a simple random sample.
• Requires the availability of a good sampling frame and knowledge of the size of the target population.
![Page 9: Overview of Sampling Methods II](https://reader035.fdocuments.in/reader035/viewer/2022062517/5681354d550346895d9ca920/html5/thumbnails/9.jpg)
9To put your footer here go to View > Header and Footer
Cluster sampling
• Taking a simple random sample can be administratively difficult.
• More convenient to divide the population into non-overlapping groups (clusters)
• Then sample a few clusters at random
• Then enumerate all members in the chosen clusters
This process is referred to as cluster sampling.More discussion on this will follow in sessions13 and 14.
![Page 10: Overview of Sampling Methods II](https://reader035.fdocuments.in/reader035/viewer/2022062517/5681354d550346895d9ca920/html5/thumbnails/10.jpg)
10To put your footer here go to View > Header and Footer
Cluster sampling – further notes
• In the initial division of the population, aim to make each cluster as heterogeneous as possible.
• The sampling frame is required only for the chosen clusters, so useful when a sampling frame does not exist for the whole population
• The division of the population into clusters is different from that used in identifying strata. Here, the aim is to have high within- cluster variation.
![Page 11: Overview of Sampling Methods II](https://reader035.fdocuments.in/reader035/viewer/2022062517/5681354d550346895d9ca920/html5/thumbnails/11.jpg)
11To put your footer here go to View > Header and Footer
Multi-stage sampling• Consider again the population divided into a
number of clusters.
• But now, instead of including all units in the cluster, take a random sample of units within each cluster.
• Above would be called a two-stage sampling design
• This may be extended to more than two-stages– e.g. may select districts, then enumerations
areas within districts, then household within enumeration areas, to give a 3-stage design.
![Page 12: Overview of Sampling Methods II](https://reader035.fdocuments.in/reader035/viewer/2022062517/5681354d550346895d9ca920/html5/thumbnails/12.jpg)
12To put your footer here go to View > Header and Footer
Multi-stage sampling• Most large-scale surveys are conducted
using a multi-stage sampling procedure.
• Can be used in combination with stratification, e.g. – first divide population into strata– continue the sampling within each
stratum according to a multi-stage sampling procedure
• There will be more discussion concerning multi-stage sampling procedures in sessions 13 and 14.
![Page 13: Overview of Sampling Methods II](https://reader035.fdocuments.in/reader035/viewer/2022062517/5681354d550346895d9ca920/html5/thumbnails/13.jpg)
13To put your footer here go to View > Header and Footer
References
• Moser, C.A. and Kalton, G. (1971) Survey Methods in Social Investigations. Gower Publishing Company Limited.
• Scheaffer, R.L., Mendenhall, W., Ott, L. (1990) Elementary survey sampling, (4th Edition). PWS-Kent Publishing Company, pp. 390.
• Woodward, M. and Francis, L.M.A. (1988) Statistics for Health Management and Research (see Chapter 10 for an overview). Edward Arnold, London. ISBN 0-340-42009-X
![Page 14: Overview of Sampling Methods II](https://reader035.fdocuments.in/reader035/viewer/2022062517/5681354d550346895d9ca920/html5/thumbnails/14.jpg)
14To put your footer here go to View > Header and Footer
Some practical work follows …