Advertising
CHAPTER 5
Choosing the type of probability sampling
What you will learn in this chapter: •• •• •• •• •• •• The types of probability sampling and how they differ from each other Steps in carrying out the major probability sample designs The strengths and weaknesses of the various types of probability sampling Differences between stratified sampling and quota sampling Differences between stratified sampling and cluster sampling Differences between multistage cluster sampling and multiphase sampling
INTRODUCTION
Once a choice is made to use a probability sample design, one must choose the type of probability sampling to use. This chapter includes descriptions of the major types of probability sampling. It covers steps involved in their administration, their subtypes, their weaknesses and strengths, and guidelines for choosing among them. There are four major types of probability sample designs: simple random sampling, stratified sampling, systematic sampling, and cluster sampling (see Figure 5.1). Simple random sampling is the most recognized probability sampling procedure. Stratified sampling offers significant improvement to simple random sampling. Systematic sampling is probably the easiest one to use, and cluster sampling is most practical for large national surveys. These sampling procedures are described below.
125
126
Sampling Essentials
Figure 5.1 Major Types of Probability Sampling
Probability Sample Designs
Simple Random Sampling
Stratified Sampling
Systematic Sampling
Cluster Sampling
SIMPLE RANDOM SAMPLING What Is Simple Random Sampling?
Simple random sampling is a probability sampling procedure that gives every element in the target population, and each possible sample of a given size, an equal chance of being selected. As such, it is an equal probability selection method (EPSEM).
What Are the Steps in Selecting a Simple Random Sample?
There are six major steps in selecting a simple random sample: 1. Define the
Choosing the type of probability sampling
What you will learn in this chapter: •• •• •• •• •• •• The types of probability sampling and how they differ from each other Steps in carrying out the major probability sample designs The strengths and weaknesses of the various types of probability sampling Differences between stratified sampling and quota sampling Differences between stratified sampling and cluster sampling Differences between multistage cluster sampling and multiphase sampling
INTRODUCTION
Once a choice is made to use a probability sample design, one must choose the type of probability sampling to use. This chapter includes descriptions of the major types of probability sampling. It covers steps involved in their administration, their subtypes, their weaknesses and strengths, and guidelines for choosing among them. There are four major types of probability sample designs: simple random sampling, stratified sampling, systematic sampling, and cluster sampling (see Figure 5.1). Simple random sampling is the most recognized probability sampling procedure. Stratified sampling offers significant improvement to simple random sampling. Systematic sampling is probably the easiest one to use, and cluster sampling is most practical for large national surveys. These sampling procedures are described below.
125
126
Sampling Essentials
Figure 5.1 Major Types of Probability Sampling
Probability Sample Designs
Simple Random Sampling
Stratified Sampling
Systematic Sampling
Cluster Sampling
SIMPLE RANDOM SAMPLING What Is Simple Random Sampling?
Simple random sampling is a probability sampling procedure that gives every element in the target population, and each possible sample of a given size, an equal chance of being selected. As such, it is an equal probability selection method (EPSEM).
What Are the Steps in Selecting a Simple Random Sample?
There are six major steps in selecting a simple random sample: 1. Define the
References: FOR FURTHER STUDY Binson, D., Canchola, J. A., & Catania, J. A. (2000). Random selection in a national telephone survey: A comparison of the Kish, next birthday, and last-birthday methods. Journal of Official Statistics, 16, 53–59. Burnam, M. A., & Koegel, P. (1988). Methodology for obtaining a representative sample of homeless persons: The Los Angeles Skid Row Study. Evaluation Review, 12, 117–152. Bryant, B. E. (1975). Respondent selection in a time of changing household composition. Journal of Marketing Research, 12, 129–135. Czaja, R., Blair, J., & Sebestik, J. P. (1982). Respondent selection in a telephone survey: A comparison of three techniques. Journal of Marketing Research, 19, 381–385. Hagan, D. E., & Collier, C. M. (1983). Must respondent selection procedures for telephone surveys be invasive? Public Opinion Quarterly, 47, 547–556. Kish, L. (1949). A procedure for objective respondent selection within the household. Journal of the American Statistical Association, 44, 380–387. Kish, L. (1965). Survey sampling. New York: Wiley & Sons. Lavrakas, P. J., Bauman, S. L., & Merkle, D. M. (1993). The last-birthday method and within-unit coverage problems. Proceedings of the section on survey research methods, American Statistical Association, 1107−1112. Levy, P. S., & Lemeshow, S. (2008). Sampling of populations: Methods and applications. New York: Wiley & Sons. Salmon, C. T., & Nichols, J. S. (1983). The next-birthday method of respondent selection. Public Opinion Quarterly, 47, 270–276. Scheaffer, R. L., Mendenhall, W., & Ott, L. (2006). Elementary survey sampling. Belmont, CA: Duxbury Press. Sudman, S. (1976). Applied sampling. New York: Academic Press. Thompson, S. K. (2002). Sampling. New York: Wiley & Sons. Troldahl, V. C., & Carter, R. E. (1964). Random selection of respondents within households in phone surveys. Journal of Marketing Surveys, 1, 71–76.