Psychology
Sampling Frames
Sampling frames in psychology refer to the list or source from which a sample is drawn. It is a crucial aspect of research design as it determines the representativeness of the sample. The sampling frame should accurately reflect the population being studied to ensure the generalizability of research findings.
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7 Key excerpts on "Sampling Frames"
No longer available |Learn more- (Author)
- 2014(Publication Date)
- Orange Apple(Publisher)
People not in the frame have no prospect of being sampled. Statistical theory tells us about the uncertainties in extrapolating from a sample to the frame. In extrapolating from frame to population, its role is motivational and suggestive. To the scientist, however, representative sampling is the only justified procedure for choosing individual objects for use as the basis of generalization, and is therefore usually the only acceptable basis for ascertaining truth. —Andrew A. Marino It is important to understand this difference to steer clear of confusing prescriptions found in many web pages. In defining the frame, practical, economic, ethical, and technical issues need to be addressed. The need to obtain timely results may prevent extending the frame far into the future. ________________________ WORLD TECHNOLOGIES ________________________ The difficulties can be extreme when the population and frame are disjoint. This is a particular problem in forecasting where inferences about the future are made from historical data. In fact, in 1703, when Jacob Bernoulli proposed to Gottfried Leibniz the possibility of using historical mortality data to predict the probability of early death of a living man, Gottfried Leibniz recognized the problem in replying: Nature has established patterns originating in the return of events but only for the most part. New illnesses flood the human race, so that no matter how many experiments you have done on corpses, you have not thereby imposed a limit on the nature of events so that in the future they could not vary. —Gottfried Leibniz Kish posited four basic problems of Sampling Frames: 1. Missing elements: Some members of the population are not included in the frame. 2. Foreign elements: The non-members of the population are included in the frame. 3. Duplicate entries: A member of the population is surveyed more than once. 4. Groups or clusters: The frame lists clusters instead of individuals.
eBook - PDFResearch Methods For Business
A Skill Building Approach
- Uma Sekaran, Roger Bougie(Authors)
- 2020(Publication Date)
- Wiley(Publisher)
For this purpose, the first 15 people who chose the special item might be interviewed, and their reactions obtained. In such cases, having instant information may be more gainful than obtaining the most representative facts. It should, however, be noted that the results of such convenient samples are not reliable and can never be generalized to the population. Sampling is the process of selecting a sufficient number of the right elements from the popula-tion, so that a study of the sample and an understanding of its properties or characteristics make it possible for us to generalize such properties or characteristics to the population elements. The major steps in sampling include: 1. Define the population. 2. Determine the sample frame. 3. Determine the sampling design. 4. Determine the appropriate sample size. 5. Execute the sampling process. THE SAMPLING PROCESS 226 CHAPTER 14 Sampling DEFINING THE POPULATION Sampling begins with precisely defining the target population. The target population must be defined in terms of elements, geographical boundaries and time. For instance, for a banker inter-ested in saving habits of blue-collar workers in the mining industry in the United States, the target population might be all blue-collar workers in that industry throughout the country. For an advertising agency interested in reading habits of elderly people, the target population might be the German population aged 50 and over. These examples illustrate that the research objective and the scope of the study play a crucial role in defining the target population. DETERMINING THE SAMPLE FRAME The sampling frame is a (physical) representation of all the elements in the population from which the sample is drawn. The payroll of an organization would serve as the sampling frame if its members are to be studied. Ideally, a sampling frame is a complete and correct list of the population elements. However, practical circumstances often make such a list incorrect and incomplete.
eBook - PDFResearch Methods For Business
A Skill Building Approach
- Uma Sekaran, Roger Bougie(Authors)
- 2016(Publication Date)
- Wiley(Publisher)
These examples illustrate that the research objective and the scope of the study play a crucial role in defining the target population. Determining the sample frame The sampling frame is a (physical) representation of all the elements in the population from which the sample is drawn. The payroll of an organization would serve as the sampling frame if its members are to be studied. Likewise, the university registry containing a listing of all students, faculty, administrators, and support staff in the university during a particular academic year or semester could serve as the sampling frame for a study of the university population. A roster of class students could be the sampling frame for the study of students in a class. The telephone directory is also frequently used as a sampling frame for some types of study, even though it has an inherent bias inasmuch as some numbers are unlisted and certain others may have become obsolete. Although the sampling frame is useful in providing a listing of each element in the population, it may not always be a current, up‐to‐date document. For instance, the names of members who have recently left the organization or dropped out of the university, as well as members who have only recently joined the organiza- tion or the university may not appear in the organization's payroll or the university registers on a given day. The most recently installed or disconnected telephones will not, likewise, be included in the current telephone directory. Hence, though the sampling frame may be available in many cases, it may not always be entirely cor- rect or complete. When the sampling frame does not exactly match the population coverage error occurs. In some cases, the researcher might recognize this problem and not be too concerned about it, because the dis- crepancy between the target population and the sampling frame is small enough to ignore.
eBook - PDFResearch Methods For Business
A Skill Building Approach
- Roger Bougie, Uma Sekaran(Authors)
- 2021(Publication Date)
- Wiley(Publisher)
For this purpose, the first 15 people who chose the special item might be interviewed, and their reactions obtained. In such cases, having instant information may be more gainful than obtaining the most representative facts. It should, however, be noted that the results of such convenient samples are not reliable and can never be generalized to the population. Sampling is the process of selecting a sufficient number of the right elements from the popula- tion, so that a study of the sample and an understanding of its properties or characteristics make it possible for us to generalize such properties or characteristics to the population elements. The major steps in sampling include: 1. Define the population. 2. Determine the sample frame. 3. Determine the sampling design. 4. Determine the appropriate sample size. 5. Execute the sampling process. THE SAMPLING PROCESS 226 CHAPTER 14 Sampling DEFINING THE POPULATION Sampling begins with precisely defining the target population. The target population must be defined in terms of elements, geographical boundaries and time. For instance, for a banker inter- ested in saving habits of blue-collar workers in the mining industry in the United States, the target population might be all blue-collar workers in that industry throughout the country. For an advertising agency interested in reading habits of elderly people, the target population might be the German population aged 50 and over. These examples illustrate that the research objective and the scope of the study play a crucial role in defining the target population. DETERMINING THE SAMPLE FRAME The sampling frame is a (physical) representation of all the elements in the population from which the sample is drawn. The payroll of an organization would serve as the sampling frame if its members are to be studied. Ideally, a sampling frame is a complete and correct list of the population elements. However, practical circumstances often make such a list incorrect and incomplete.
- Tarun Kumar Roy, Rajib Acharya, Arun Roy(Authors)
- 2016(Publication Date)
- Cambridge University Press(Publisher)
4.1 INTRODUCTION Availability of a sampling frame is a basic requirement for application of a probability sampling technique. In order that each and every element in a population has a known and non-zero chance of being included in a sample, an ideal frame should consist of all elements occurring only once and it should exclude any other element that is irrelevant for the study. The basic techniques, such as SRS, stratified sampling and systematic sampling, discussed in Chapter 2, presume availability of such a list of elements if elements are being selected directly. In cluster and multistage sampling, a list of all areal units comprising a population is required initially. They are often selected using a PPS sampling (also discussed in Chapter 2), which assumes an availability of size or at least an estimated size of each cluster. For selection of elements in the final stage of a multistage design, a frame consisting of elements in selected areas would be required. This is generally obtained through listing of dwellings or households in a population- based survey. It is indeed difficult to have a perfect frame in every situation. Let us consider, for example, a common situation of studying a population having certain characteristics, say, suffering from a particular disease. A usual available list will consist of both the elements, households having a member suffering from the disease and those without anyone suffering. The latter element may be irrelevant and, therefore, considered as a blank. The present chapter discusses a few applications of probability sampling in the absence of an ideal frame, following three broad situations that are generally encountered: (a) Sampling populations having specific attributes, that is, a frame consisting of elements as well as blanks. (b) Sampling populations using a defective frame, that is, a frame which is either incomplete or consists of duplications (same element occurring more than once).
eBook - PDFChild Psychiatric Epidemiology
Concepts, Methods and Findings
- Frank C. Verhulst, Hans M. Koot(Authors)
- 1991(Publication Date)
- SAGE Publications, Inc(Publisher)
The SD of the sampling distribution is in-versely related to the sample size. This means that the number of SD units required to contain a specified proportion of sample means will increase with small samples, that is, the confidence intervals for small samples are larger than for large samples. For a sample size of 100, for example, 95% of the sample means fall within the area defined by ± 1.96 SDs around the population mean, while a sample size of 10 would require ± 2.26 SDs to contain 95% of the sample means. SAMPLING FRAME A sampling frame can be regarded as the operational definition of a target population. It usually consists of a list of subjects. Two types of target populations can be distinguished: general populations and special populations. General populations are usually defined by place of resi-dence and age. Special populations are more narrowly defined, usually by conditions of individuals that have importance for the study, such as children from schizophrenic mothers. In some countries, such as the Netherlands, general population samples may be derived from municipal population registers, which contain virtually all names of members of the population. In many instances, however, such complete listings are not available. An alternative is to compile a list from multiple sources. For example, to obtain incidence and prevalence rates of psychiatric disorders, Sampling 101 one of the Sampling Frames used in the Epidemiological Catchment Area (ECA) project (Helzer et al., 1985) was based on utility listings. A nearly complete listing of household addresses in one of the catchment areas involved in the study was constructed from electrical service ad-dresses made available by three utilities serving the area. Another example is the use of listings from organizations, such as schools, in which most or all subjects in an area are likely to participate.
eBook - PDFResearch Methods
A Tool for Life
- Bernard C. Beins(Author)
- 2017(Publication Date)
- Cambridge University Press(Publisher)
People from different backgrounds may respond in dif- ferent ways to the same stimulus. So concepts may take on different operational definitions in different cultural contexts. In addition to specifying operational definitions, researchers must also decide who they are going to sample and how they are going to do it. One general classification is called probability sampling. This approach requires identification of the population of interest and a well-specified means of selecting individuals for the research. The simplest and most well-known type is simple random sampling, in which every person in the popu- lation has an equal chance to participate in the research. But there are also complicated designs involving probability sampling. The benefit of these approaches is that researchers can be confident that the sample represents the population. A more common approach in psychology is to use nonprobability samples. The main nonprobability approach is to use convenient samples, often of college students. Although these samples are quite convenient, there is some concern that the results may not pertain to a wider population. MEASUREMENT AND SAMPLING 119 After researchers collect their data, they must face the question as to whether their measurements and their results are reliable. That is, if the investigators were to conduct another similar study, would they obtain the same results? If measurements and results are reliable, they may also be valid. That is, the measurements and results might help answer the researchers’ questions. There are multiple forms of reliability and validity that are relevant in different circumstances. Finally, when researchers collect their data, the results are sometimes qualitative, involving how many observations fall into a category. At other times, the results are quantitative, leading to various types of statistical analysis.
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