A common sampling strategy for surveying finite populations is to
select the sampled units in several stages1. Multistage sampling
refers to sampling plans where the sampling is carried out in stages using
smaller and smaller sampling units at each stage2. In a two-stage sampling
design, a sample of primary units is selected and then a sample of secondary
units is selected within each primary unit. The simplest version of two-stage
sampling is to use simple random sampling at each stage an SRS of primary
units, and an SRS of secondary units within each selected primary unit. The
primary units do not need to be the same size and you do not need to select the
same number of secondary units within each primary unit3.
Multistage samples are used primarily for cost or feasibility
(practicality) reasons. In detail, it becomes an effective tool in collecting primary
data from geographically dispersed population. That is when face-to-face
contact are required to obtain information from the population segment, for
example, semi-structured in-depth interviews.
Selecting the sample in stages has practical benefits in the
selection process itself. It permits the sampler to isolate, in successive
steps, the geographic locations where the survey operations – notably, listing
households and administering interviews – will take place. When listing must be
carried out because of an obsolete sampling frame, a stage of selection can be introduced
to limit the size of the area to be listed4.
As noted from the example made by the United States Census Bureau
(2016), to select an SRS of households in the U.S. would be extremely difficult
because no list of all households exists. However, we could proceed in stages:
an SRS of counties in the U.S., an SRS of locks” within each county, and
an SRS of households within each block. One only need to have a list of
households within each block that was selected.5 With this the multistage
or at least the two-stage sampling methodology is afforded the flexibility to
sample more intensely in primary units which are larger or more variable6.
On the other hand, the disadvantage of two-stage sampling is that
the variance of the resulting estimators are likely to be larger than for an
SRS of the same total number of secondary units. This may well be more than offset
by the cost efficiency of two-stage sampling. Relatedly, the research finding
obtained from the method will never be 100 percent representative of the
population as hinted by the bloated variance of the estimates. Note that a
two-stage sample can never be better than a cluster sample with the same number
of primary units selected because a census within each primary unit is the best
you can do. In addition, in doing the multistage design, the method allows for
high level of subjectivity to the investigator despite the probability nature
of the drawing information from the segment of the population7.
2 Cochran, W. G. (1977). Sampling
Techniques, 3rd ed., John Wiley, New York.
5 US Census Bureau, 2016. METHODOLOGY FOR
THE UNITED STATES POPULATION ESTIMATES: VINTAGE 2016 Nation, States, Counties,
and Puerto Rico – April 1, 2010 to July 1, 2016.
6 Kalton, G. (1983). Quantitative
Applications in the Social Sciences: Introduction to survey sampling Thousand
Oaks, CA: SAGE Publications Ltd doi: 10.4135/9781412984683
Kalton, G. (1983). Quantitative Applications in the Social Sciences:
Introduction to survey sampling Thousand Oaks, CA: SAGE Publications Ltd doi: