Multi-stage sampling

a cube made of cubes

Multi-stage sampling represents a more complicated form of cluster sampling in which larger clusters are further subdivided into smaller, more targeted groupings for the purposes of surveying.

Despite its name, multi-stage sampling can in fact be easier to implement and can create a more representative sample of the population than a single sampling technique. Particularly in cases where a general sampling frame requires preliminary construction, multi-stage sampling can help reduce costs of large-scale survey research and limit the aspects of a population which needs to be included within the frame for sampling.

In traditional cluster sampling, a total population of interest is first divided into ‘clusters’ (for example, a total population into geographic regions, household income levels, etc.), and from each cluster individual subjects are selected by random sampling. This approach however, may be considered overly-expensive or time consuming for the investigator. Using multi-stage sampling, investigators can instead divide these first-stage clusters further into second-stage cluster using a second element (for example, first ‘clustering’ a total population by geographic region, and next dividing each regional cluster into second-stage clusters by neighborhood). Multi-stage sampling begins first with the construction of the clusters. Next, the investigator identifies which elements to sample from within the clusters, and so on until they are ready to survey.

Examples

In Iyoke et al. (2006) Researchers used a multi-stage sampling design to survey teachers in Enugu, Nigeria, in order to examine whether socio-demographic characteristics determine teachers’ attitudes towards adolescent sexuality education. First-stage sampling included a simple random sample to select 20 secondary schools in the region. The second stage of sampling selected 13 teachers from each of these schools, who were then administered questionnaires.

Advice for choosing this method

  • Consider how large your population is. Also consider how easy it will be to reach those selected for surveying.  What are the costs involved?  Most large-scale surveys, such as governmental surveys, use some sort of multi-stage sampling to increase the logistical ease and reduce the financial costs associated with conducting large-scale surveys.
  • Consult an experienced researcher, preferably one with expertise in survey design, about the construction and implementation of multi-stage designs.
  • Make sure each stage of the survey procedure is implemented according to high standards.  As each stage of the multi-stage process is itself a sampling technique, each stage must be held to the standards as if it were the only stage.  If one stage is done poorly, then this has ramifications for the rest of the data collection as well as for statistical analyses conducted further along in the research process.
  • The usual sampling rules apply – take all reasonable steps to ensure that the response rate is high.

Advice for using this method

  • Think carefully about how to implement the multi-stage approach.  As there is no strict definition to multi-stage sampling, there is no formulaic way as to how to combine the various sampling options (such as clustering, stratified, and simple random).  The multi-stage sampling procedure should be constructed in such a way to be cost and time effective while retaining both the randomness and sufficient size of the sample.  If using multi-stage sampling for the first time it is best to consult an expert experienced in complex survey design.

Resource

Agresti A, and Finlay, B. (2008) Statistical Options for the Social Sciences, 4th edition. (Upper Saddle River, NJ: Prentice Hall).

Food and Agricultural Organisation of the United Nations (FAO) (1997). Chapter 7: Sampling In Marketing Research. In Marketing research and information systems. (Marketing and Agribusiness Texts - 4). Agriculture and Consumer Protection, FAO. Retrieved from http://www.fao.org/docrep/W3241E/w3241e08.htm#cluster%20and%20multistage%20sampling

Iyoke, C.a et al. (2006) “Teachers’ Attitude is Not an Impediment to Adolescent Sexuality Education in Enugu, Nigeria.” African Journal of Reproductive Health/La Revue Africaine de la Sant Reproductive 10 (1): 81-90

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