Non-probability sampling does not involve random selection and so cannot rely on probability theory to ensure that it is representative of the population of interest. Cluster sampling is used in two situations. Stratification ensures that all levels of the identified variable, in this example age, are adequately represented in the sample. If the first name is not replaced, the remaining 49 names have a 9 in 49 chance, or a 0.18 probability, of being selected. The following sections explain these concepts; later in the chapter, these concepts are used to explain various sampling methods. Identifying the best research design to fit the question. Part 2 Sampling Methods - PubMed In some cases, a hypothetical population is defined for a study. (2009) also provided a rationale for the subjects attrition, and the reasons were varied and seemed appropriate and typical for a study lasting 24 months. 62 Similar to stratified random sampling, cluster random sampling uses natural geographic and organizational clusters of potential research participants to create a sampling frame.2 For example, in exploring work satisfaction among clinical nurses using a cluster sampling methodology, the researcher would randomly select cities from which to draw the sample, then randomly select hospitals from within each city, and finally randomly assign nurses from within each hospital to participate in the study. Sampling theory was developed to determine mathematically the most effective way to acquire a sample that would accurately reflect the population under study. Probability sampling methods have been developed to ensure some degree of precision in estimations of the population parameters. Editor's note: This is the third article in a series on clinical research by nurses. Sample attrition should be reported in the published study to determine if the final sample represents the target population. Epidemiologists sometimes use entire populations for their large database studies. In a third step, clusters of dwelling units form the secondary sampling units selected from each substratum [3rd stage cluster sampling]. Am J Nurs. All of these examples use sampling techniques. Sample attrition rate is calculated by dividing the number of subjects withdrawing from a study by the sample size and multiplying the results by 100%. From a sampling theory point of view, randomization means that each individual in the population should have a greater than zero opportunity to be selected for the sample. LibGuides: NURB 361: Introduction to Nursing Research: Quantitative vs Sampling Theory An accessible population is the portion of the target population to which the researchers have reasonable access. Table 15-2 is useful only if the population number is less than 100. 13. Attritionrate=40(numberwithdrawing)160(samplesize)=0.25100%=25% The control group usually receives no care. Sampling error occurs as a result of random variation and systematic variation. The sampling frame in this study included the names of the 746 RNs who were asked to participate in the study. Degirmen, Ozerdogan, Sayiner, Kosgeroglu, and Ayranci (2010, p. 153) conducted a pretest-posttest randomized controlled experimental study to determine the effect of hand and foot massage and foot massage only interventions on the postoperative pain of women who had a cesarean operation. However, the study would have been strengthened by a discussion of the process for random sampling and a clarification of how the subjects were assigned to groups. The series is designed to give nurses the knowledge and skills they need to participate in research, step by step. While less expensive, nonprobability sampling techniques are prone to selection bias and often do not produce a sample that fully represents the target population. Figure 15-1 shows the relationships among the population, target population, and accessible populations. Good arguments exist for both approaches. Boston: Cengage Learning; 2006. p. 76396. These criteria ensure a large target population of. In stratified random sampling, the subjects are randomly selected on the basis of their classification into the selected strata. The development of a thoughtful sampling plan is essential to support the validity of nursing research. The researcher selects subjects from the sampling frame using a sampling plan. 91 For instance, the researcher could require that 30% of the sample have an admission diagnosis of chronic obstructive pulmonary disease. Sample selection is a very important but sometimes underestimated part of a research study. Exclusion criteria limit true randomness. However, some researchers still use a table of random numbers to select a random sample. The retention rates for both groups were very strong and comparable (treatment group 89% and comparison group 90%). 14-15) sampling text. With a comparison group, there is an increase in the possibility of preexisting differences between that group and the experimental group receiving the treatment. Contact Us, Copyright The Board of Regents of the University of Wisconsin System, Library Research Guides - University of Wisconsin Ebling Library. modify the keyword list to augment your search. Sampling methodology influences how well the study represents the target population, and thereby affects the generalizability of the study. 8600 Rockville Pike Alexa Colgrove Curtis is assistant dean of graduate nursing and director of the MPHDNP dual degree program and Courtney Keeler is an associate professor, both at the University of San Francisco School of Nursing and Health Professions. See Table 213-17 for examples of nonprobability sampling from the literature. The second situation is in cases in which the individual elements making up the population are unknown, preventing the development of a sampling frame. "Sampling theory was developed to determine the most effective was of acquiring a sample that accurately reflects the population under study. The comparison group retention was 113 women with a retention rate of 90% (113 125 = 90.4% = 90%). Quota sampling is a variant of convenience sampling that controls for some characteristics within the target population.2 Relative to a convenience sample, a quota sample may better represent certain subpopulations of interest to the researcher. Systematic variation can also occur in studies with high sample attrition. Table 15-2 is useful only if the population number is less than 100. The term study or research participant or informant is used in the context of the naturalistic paradigm of qualitative research (Fawcett & Garity, 2009; Munhall, 2012). The https:// ensures that you are connecting to the may email you for journal alerts and information, but is committed An Introduction to Sampling Theory The applet that comes with this WWW page is an interactive demonstration that will show the basics of sampling theory. If you know the refusal rate, you can also subtract the refusal rate from 100% to obtain the acceptance rate. Key concepts of sampling theory include populations, target population, sampling or eligibility criteria, accessible population, elements, representativeness, sampling frames, and sampling methods or plans. In the first stage, 339 primary sampling units were selected from about 1,900 area sampling units representing counties, groups of adjacent counties, or metropolitan areas covering the 50 states and the District of Columbia [1st stage cluster sampling]. Factors that affect self-care behaviour of female high school students with dysmenorrhoea: a cluster sampling study. The method of achieving this opportunity is referred to as random sampling. The difference is random because the value of each subject is likely to vary in a different direction. For instance, perhaps a nurse researcher is interested in examining work satisfaction among clinical nurses within a large health care system. In these types of studies, the sampling criteria need to be specific and designed to make the population as homogeneous or similar as possible to control for the extraneous variables. Sampling theory describes two sampling domains: probability and nonprobability. (2009) identified that 249 participants or subjects met the sampling criteria and 249 were enrolled in the study indicating that the acceptance rate for the study was 100%. The IQs of the subjects have introduced a systematic bias. Even if the original sample is random, persons who volunteer or consent to participate in a study may differ in important ways from persons who are unwilling to participate. Yang MF, et al. For example, individuals who successfully lose weight would be a hypothetical population. A statistic is then estimated and applied to the whole population. The eligible RNs were those who had a functioning work e-mail account and who worked fulltime, on inpatient units, providing direct patient care. (Djukic et al., 2010, pp. In some cases, this random selection continues through several stages and is referred to as multistage cluster sampling. Twiss et al. If the method of selecting subjects produces a sample with a systematic bias, increasing the sample size would not decrease the sampling error. Values of individual subjects vary from the value of the sample mean. The outcomes of the study were that foot and hand massage interventions significantly reduced postoperative pain experienced by the women and that foot and hand massage was significantly more effective than foot massage only. A, You might identify broad sampling criteria for a study, such as all adults older than 18 years of age able to read and write English. Bethesda, MD 20894, Web Policies For example, suppose a researcher is conducting a study of stress among medicalsurgical nurses. Quantitative, outcomes, and intervention research apply a variety of probability and nonprobability sampling methods. However, tables are available for larger populations, such as the random numbers table provided in the online resources for this textbook or the Thompson (2002, pp. Quantitative, outcomes, and intervention research Abstract. Systematic variation, or systematic bias, is a consequence of selecting subjects whose measurement values are different, or vary, in some specific way from the population. In the example mentioned earlier, 200 potential subjects met the sampling criteria; 160 agreed to participate in the study, and 40 refused. Sampling Design in Nursing Research - PubMed If the accessible population is limited to a particular setting or type of setting, the individuals seeking care at that setting may be different from the individuals who would seek care for the same problem in other settings or from individuals who self-manage their problems. Bethesda, MD 20894, Web Policies The sampling strategy employed is of utmost importance to ensure that a representative sample of participants is chosen. 33 The criteria are developed from the research problem, the purpose, a review of literature, the conceptual and operational definitions of the study variables, and the design. It is important that assessment techniques possess both validity and reliability. Probability samples reduce sampling error. Degirmen et al. Not having the time or budget to administer a survey to all 200 nurses, the researcher chooses instead to randomly select a sample of 50 nurses using a computerized randomization tool. The term study or research participant or informant is used in the context of the naturalistic paradigm of qualitative research (Fawcett & Garity, 2009; Munhall, 2012). Capili B. For example, the researcher might first randomly select states and next randomly select cities within the sampled states. Subjects are selected to maximize the effects of the independent variable and minimize the effects of variation in other extraneous variables so that they have a limited impact on the dependent variable scores. You may search for similar articles that contain these same keywords or you may Sampling error reduces the power of a study, or the ability of the statistical analyses conducted to detect differences between groups or to describe the relationships among variables (Aberson, 2010; Cohen, 1988). Common methods of probability sampling include the following6: In simple random sampling, study participants are randomly selected from the sampling frame using a randomization mechanism, as previously discussed. The 833 NPs and 689 PAs add to 1522 subjects and it is unclear why the sample size is identified as 1536 unless there are missing data from subjects. 8600 Rockville Pike 15. The higher the retention rate, the more representative the sample is of the target population, and the more likely the study results are an accurate reflection of reality. These sampling criteria probably were narrowly defined by the researchers to promote the selection of a homogeneous sample of postmenopausal BCSs with bone loss.
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