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1. Sampling has many different concepts. Read Chapter 11 and then discuss the following: List and define several sampling terms. What is sampling? What is random sampling?
Sampling is the process of selecting a subset of observations from an entire population of interest so that characteristics from the subset can be used to draw conclusions or make inferences about the population (Shi, 2008, pg.266).
Random sampling consists of selecting units in an unbiased manner to form a representative sample from a population of interest (Shi, 2008, pg. 166). Simple random sampling means that every unit in a population has an equal probability of being included in the sample (Shi, 2008, pg. 271).
There are many sampling terms frequently used in sampling. These include unit of analysis, sampling element, sampling unit, observation unit, population, sampling frame, sampling design, sampling error, sampling bias, variable, statistics, and parameters (Shi, 2008, pg.267). You will find a few of these terms defined below.
Unit of analysis refers to the object about which the researcher wishes to draw conclusions based on the study. The purpose of the study typically dictates what or who is to be studied and hence what the appropriate unit of analysis is (Shi, 2008, pg. 267). According to Shi, a variety of units may be studied, including individuals (e.g., patients, or doctors), groups (e.g., families, couples, census blocks, cities, or geographic regions), institutions (e.g., hospitals, nursing homes, or group practices), or events (traffic accidents or diseases) (pg. 267). This type of analysis in a study are usually the sampling elements and the units of observation.
Sampling element refers to the unit of sample to be surveyed, and provides the information base for analysis (Shi, 2008, pg.267). According to Shi (2008), in health service research, typically, sampling units are individuals, households, or organizations (pg.268). Social groups, industries, or nation states can also be used as sampling element (Shi, 2008, pg. 268).
Sampling unit is the actual unit that is considered for selection. The sampling unit and sampling element are the same in single-stage sampling but different in multistage sampling (Shi, 2008, pg.268).
Observation unit is the unit from which data are actually collected (Shi, 2008, pg. 268). According to Shi (2008), the observation unit and sampling element may be different when, for example, heads of households (observation unit) are surveyed about all household members (sampling element), or administrators (observation unit) are questioned about characteristics of organizations or their clients (sampling elements) (pg. 268).
Population refers to the target for which Investigators generate the study results. A population may be defined as universe or study relevant (Shi, 2008, pg. 268). A universe population consists of a theoretically specified aggregation of sampling units. While a study population includes only the aggregation of sampling units from which the sample is to be selected (Shi, 2008, pg. 268). According to Shi (2008), A study population is usually smaller than a universe population, because some sampling units may be omitted from the sampling population (pg.268).
2. Valid research results depend on high response rates. Read Chapter 8 and discuss: How can response rates be improved?
According to Shi (2008), there are many ways to enhance the response rate for a gibe survey. Examples include shortening the questionnaire, obtaining sponsorship by a relevant authority, using a novel and appealing format, and paying respondents (pg. 204). Regardless which alternatives have been used, a follow-up mailing is a required sequence for increasing return rates, particularly in large-scale mail surveys (Shi, 2008, pg. 204). In general, the longer a potential respondent delays replying, the less likely that person will do so at all. Therefore, properly timed follow-up mailings, then provide additional stimuli for achieving responses (Shi, 2008, pg. 204).
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