Applied Regression Models in the Social Sciences

Most social science research analyzes data from samples drawn from larger populations. However, most of the standard statistical methods used for analyzing the data are based on the assumption that the sample data have been drawn with simple random samples. But few probability samples are completely random. Some sample respondents may be more heavily weighted than other respondents, and some respondents may be included in the sample by virtue of their membership in groups based on race, sex, age, and other characteristics. Nonetheless, many investigators treat their samples as random where each person in the larger population has an equal chance or probability of being included in the sample. We discuss in this chapter the methods that need to be followed to enable researchers to make correct inferences to the larger population with sample data that are not completely random. We review the three main types of probability samples. Then we discuss how and why researchers need to address and take into account the design of their samples.