MULTISTAGE SAMPLING

 

Multistage Sampling

Multistage Sampling is very useful when the population is widespread and it is not possible to list all members of the sampling unit.

It is a complex of Cluster Sampling.

Cluster Sampling is a type of sampling that involves dividing the population into groups or clusters.

Then one or more clusters are chosen at random and everyone within the chosen cluster is sampled.

Cluster Sampling sometimes involves selecting samples in two stages but Multistage Sampling involves more than two stages of selecting the sample.

Sampling involves more than two stages of selecting the sample. To understand the whole process of Multistage Sampling Technique, let us take an example

“A Study of Problems in Managing Mid-day Meal by Principals of Middle Schools of Madhya Pradesh State”

·       In this study the sampling unit is Principals of Middle Schools of Madya Pradesh State.

·       To select the sample of Principals of Middle Schools, first one should select Districts.

·       Suppose one decides to select 15 Districts randomly out of 48 Districts.

·       From the selected Districts, one may not be able to take all Principals of Middle Schools as the number is too large.

o In the first stage Districts are selected randomly.

o In the second stage, the Middle Schools from selected Districts are selected randomly.

o   From Principals of selected Middle Schools, the Principals are selected randomly. This is how the sample of Principals of Middle Schools is selected in three stages.

o   In Multistage Sampling, after having selected Principals randomly, one can divide the Sample of Principals as per their gender, namely males and females.

o In the fourth stage, one can use the Stratified Random Sampling Technique. Thus, during the process of selecting a sample through the use of Multistage Sampling, one can also use the Stratified Random Sampling Technique at the appropriate stage.

Thus, the Multistage Sampling Technique involves selecting a sample randomly in more than two stages.


 

 

 


Types of Multistage Sampling

a.      Multistage cluster sampling

Multistage cluster sampling is a complex type of cluster sampling. The researcher divides the population into groups at various stages for better data collection, management, and interpretation. These groups are called clusters.

For example, a researcher wants to know the different eating habits in Western Europe. It is practically impossible to collect data from every household. The researcher will first choose the countries of interest. From these countries, he/she chooses the regions or states to survey. And from these regions, he/she further narrows down his research by choosing specific cities and towns that represent the region. The researcher does not interview all the residents of the city or town. He/she further chooses particular respondents from the selected cities to participate in the research. Here we see that clusters are selected at various stages until the researcher narrows down to the sample required. 

 

b.     Multistage random sampling

The concept of multistage random sampling technique is similar to multistage cluster sampling. But in this case, the researcher chooses the samples randomly at each stage. Here, the researcher does not create clusters, but he/she narrows down the convenience sample by applying random sampling.

For example, a researcher wants to understand pet feeding habits among people living in the USA. For this, he/she requires a sample size of 200 respondents. The researcher selects 10 states out of 50 at random. Further, he/she randomly picks out 5 districts per state. From these 50 randomly selected states, he/she then chooses 4 pet-owning households to conduct his research.

 


Advantages of Multistage Sampling Technique

1. It is cost effective.

2. It is feasible.

3. It is easy to find sampling unit.

4. It is normally more accurate than Cluster Sampling of the same size

 

Disadvantages of Multistage Sampling Technique

1.     It is not as accurate as the Random Sampling Technique if the sample in of the same size.

2.     More testing is difficult to do.

3.      Further analysis is difficult

 

Applications of Multistage Sampling

  1. Multistage sampling can be applied to a multistage design where the population is too large and it is practically impossible to research every individual.
  2. Multi-stage sampling can also be used to conduct surveys on the employees of a multinational corporation that is in multiple locations in multiple countries of the world.
  3. Researchers can use multistage sampling to collect the perceptions of various students on a particular study even when they are in different locations or universities and studying different courses.
  4. Researchers also apply multi-stage sampling when they have limited time to conduct a study. Information drawn from the small sample can then be used to draw inferences on the entire population.

Conclusion

Multistage sampling is a complex form of cluster sampling, however, it is useful when your research population is large. It will help you to eliminate the impracticality of making use of a large sample size. It also limits the risk of bias as the cluster sample is selected randomly

 

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