Sampling theory is the study of relationships existing between a population and samples drawn 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. There are five main types of probability sampling including simple random sampling, systematic sampling, stratified sampling, cluster sampling, and multi-stage sampling. Theoretically, to obtain a probability sample, the researcher must develop a sampling frame that includes every element in the population. The difference between a sample statistic and a population parameter is called the sampling error (Figure 15-2). With a comparison group, there is an increase in the possibility of preexisting differences between that group and the experimental group receiving the treatment. For each person in the target or accessible population to have an opportunity to be selected for the sample, each person in the population must be identified. The PubMed wordmark and PubMed logo are registered trademarks of the U.S. Department of Health and Human Services (HHS). (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%. Nurse researchers used a convenience sample of 36 toddlers from two developmental clinics to examine the relationship between postnatal weight gain, cortisol, and blood pressure in those who were born extremely preterm. Within the hospitals, nursing units might be randomly selected. Most textbooks on sampling describe this procedure (Levy & Lemsbow, 1980; Thompson, 2002; Yates, 1981). Sampling Methods Probability sampling (random sampling) It is a selection process that ensures each participant the same probability of being selected. Stratified random sampling The likelihood is increased that the sample is representative of the target population and the results are an accurate reflection of reality. In some cases, a hypothetical population is defined for a study. The most common method of random selection is the computer, which can be programmed to select a sample randomly from the sampling frame with replacement. Quantitative, outcomes, and intervention research apply a variety of probability and nonprobability sampling methods. Non-probability sampling methods are those in which elements are chosen through non-random methods for inclusion into the research study and include convenience sampling, purposive sampling, and snowball sampling. Persons who are able to participate fully in the procedure for obtaining informed consent are often selected as subjects. High refusal rates to participate in a study have been linked to individuals with serious physical and emotional illnesses, low socioeconomic status, and weak social networks (Neumark, Stommel, Given, & Given, 2001). The https:// ensures that you are connecting to the TABLE 15-1 All subsets of the population, which may differ from one another but contribute to the parameters of the population, have a chance to be represented in the sample. In large population sets, elements may already have assigned numbers. sharing sensitive information, make sure youre on a federal The sample was selected from the national lists provided by Medical Marketing Services, an independently owned organization that manages medical industry lists (www.mmslists.com/main.asp). All of these factors limit representativeness and limit our understanding of the phenomena important in practice. PMC You can define parameters by conducting a series of descriptive and correlational studies, each of which examines a different segment of the target population; then perform a meta-analysis to estimate the population parameter (Thompson, 2002). You may hold opinions about the adequacy of these techniques, but there is not enough information to make a judgment. Acceptancerate=160(numberaccepting)200(numbermeetingsamplingcriteria)=0.8100%=80%, Acceptancerate=100%refusalrateor100%20%=80%. 2012 Jan;5(1):7-13. doi: 10.4103/0974-1208.97779. Four sampling designs have been developed to achieve probability sampling: simple random sampling, stratified random sampling, cluster sampling, and systematic sampling. Qualitative researchers use nonprobability sampling to identify constructs of interest within a target population to further theory development. (2009) identified specific inclusion and exclusion sampling criteria to designate the subjects in the target population precisely. Probability sampling methods are most commonly applied in quantitative, outcomes, and intervention research. The series is designed to give nurses the knowledge and skills they need to participate in research, step by step. Simple random sampling is the most basic of the probability sampling methods. 40 Ebling Library, Health Sciences Learning Center We can estimate the population parameter by identifying the values obtained in previous studies examining the same variables. 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. A sample of 249 participants met the screening criteria and they were enrolled in the study. Of the 249 women, 223 completed the 24-month testing and were included in the analysis (exercise [treatment group] = 110; comparison = 113). What is Sampling Theory in Nursing Research? An accessible population is the portion of the target population to which the researchers have reasonable access. 2003 Nov;44(3):278-88. doi: 10.1046/j.1365-2648.2003.02803.x. Cluster Sampling Sampling involves selecting a group of people, events, behaviors, or other elements with which to conduct a study. In a study of the relationship between Eating Inventory questionnaire factors (restraint, disinhibition, and hunger) and body adiposity and associated comorbidities (such as diabetes) among a cohort of Czech adults, Hainer and colleagues used quota sampling to provide proportional representation based on gender, age, residential location, education, socioeconomic level, and marital status. It is tempting to exclude uncooperative or assertive individuals. If equal numbers of each group are used, each group would contain at least 25 subjects; however, the white non-Hispanic group would be underrepresented. 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. The values are randomly scattered around the mean. Sampling, data collection, and data analysis. Only gold members can continue reading. The theoretical, mathematical rationale for decisions related to sampling emerged from survey research, although the techniques were first applied to experimental research by agricultural scientists. Systematic variation or bias is most likely to occur when the sampling process is not random. In a third step, clusters of dwelling units form the secondary sampling units selected from each substratum [3rd stage cluster sampling]. 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]. 10. The likelihood is increased that the sample is representative of the target population and the results are an accurate reflection of reality. For example, identifying all women in active labor in the United States, all people grieving the loss of a loved one, or all people coming into an emergency department would be impossible. You may search for similar articles that contain these same keywords or you may 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 researcher can use a computer to select these numbers randomly to obtain a sample. However, sampling criteria should not become so restrictive that the researcher cannot find an adequate number of study participants. As the sample size becomes larger, overall variation in sample values decreases, with more values being close to the sample mean. These criteria ensure a large target population of heterogeneous or diverse potential subjects. 69 However, many researchers use nonprobability sampling because in many cases, probability sampling is not practical, feasible, or ethical. The sampling frame in this study included the names of the 746 RNs who were asked to participate in the study. Another technique is to assign a number to each name in the sampling frame. We can estimate the population parameter by identifying the values obtained in previous studies examining the same variables. Probability sampling methods are most commonly applied in quantitative, outcomes, and intervention research. Therefore, the sampling design of the NHIS includes oversampling of minorities. (Fouladbakhsh & Stommel, 2010, pp. Epub 2017 Nov 2. To accomplish this goal, the researcher must acquire a list of every member of the population through the use of the sampling criteria to define membership. 30 Hogan TM, et al. 2020 Oct;120(10):41-44. doi: 10.1097/01.NAJ.0000718644.96765.b3. Good arguments exist for both approaches. An official website of the United States government. Essentials of epidemiology in public health. In cluster sampling, the researcher develops a sampling frame that includes a list of all the states, cities, institutions, or organizations with which elements of the identified population would be linked. Weight gain and blood pressure in toddlers born very preterm. Twiss et al. Values of individual subjects vary from the value of the sample mean. These sampling criteria probably were narrowly defined by the researchers to promote the selection of a homogeneous sample of postmenopausal BCSs with bone loss. In: 5. The nurse researcher may further decide to require specific proportions of admission diagnoses in the sample. Sampling methodology influences how well the study represents the target population, and thereby affects the generalizability of the study. In: Introductory econometrics: a modern approach. Freedman D, et al. 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. The sample must be randomly selected from the sampling frame. The sample selection strategy (the sampling plan) is constructed with the intent to minimize selection bias in the selection of participants from within the sampling frame. In the example just presented with a sample size of 160, if 40 subjects withdrew from the study, then 120 subjects were retained or completed the study. Quantitative researchers opt for nonprobability sampling techniques largely for convenience and containment of cost and time. This situation usually occurs because of an interaction of the systematic bias with the treatment. This correlation can cause a decrease in precision and an increase in sampling error. doi: 10.7759/cureus.16260. In a study of how psychiatric nurses work with suicidal patients, Cutcliffe and colleagues interviewed a group of clients who had been treated for a suicidal crisis. 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. Today, federal funding for research is strongly linked to including these populations in studies. The sampling plan of a research study is presented in the methods section of a research proposal or research article. Good arguments exist for both approaches. For example, one could conduct a study in which the defined population was all living recipients of heart and lung transplants. For example, individuals who successfully lose weight would be a hypothetical population. 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. Burlington, MA: Jones and Bartlett Learning; 2020. Acceptancerate=100%refusalrateor100%20%=80% The sampling theory . 8600 Rockville Pike The number touched is the starting place. In some studies, the entire population is the target of the study. Biases may be introduced that make generalization to the broader target population difficult to defend. The target population is the entire set of individuals or elements who meet the sampling criteria, such as women who have experienced a myocardial infarction in the past year. If potential subjects have diminished autonomy or are unable to give informed consent, consent must be obtained from their legal representatives. In some studies, the entire population is the target of the study. The sample retention was 223 women for a retention rate of 90% (223 249 100% = 89.6% = 90%), and the sample attrition rate was 26 women for an attrition rate of 10% (100% 90% = 10%). A refusal rate is the number and percentage of subjects who declined to participate in the study. The series is designed to give nurses the knowledge and skills they need to participate in research, step by step. 10 For example, there is no list of all the heart surgery patients who complete rehabilitation programs in the United States. Quantitative, outcomes, and intervention research The researcher selects subjects from the sampling frame using a sampling plan. The most common method of random selection is the computer, which can be programmed to select a sample randomly from the sampling frame with replacement. Stratification ensures that all levels of the identified variable, in this example age, are adequately represented in the sample. What Adult Electrocardiogram (ECG) Diagnoses or Findings are Most Important for Advanced Care Paramedics to Know? Sampling theory was developed to determine mathematically the most effective way to acquire a sample that would accurately reflect the population under study. Community-Based Survey Exploring Use of the Dietary Supplement Creatine by Adult Non-Athletes. This chapter examines sampling theory and concepts; sampling plans; probability and nonprobability sampling methods for quantitative, qualitative, outcomes, and intervention research; sample size; and settings for conducting studies. There are still many purposive methods of nonprobability sampling that researchers employ to approximate the population of interest. Confused about theoretical sampling? 3rd ed. Sample size estimation and power analysis for clinical research studies. Representativeness is usually evaluated by comparing the numerical values of the sample (a, The difference between a sample statistic and a population parameter is called the, Systematic variation or bias is most likely to occur when the sampling process is not random. The comparison group retention was 113 women with a retention rate of 90% (113 125 = 90.4% = 90%). In network or snowball sampling, study participants recruit other potential participants with similar characteristics or experiences relating to the study objectives. The advertiser boasts that four of five doctors recommend its product; the newscaster announces that John Jones is predicted to win the senate election by a margin of 3 to 1; the newspaper reports that scientists studies have found that taking a statin drug, such as atorvastatin (Lipitor), significantly reduces the risk of coronary artery disease. For example, if in conducting your research you selected a stratified random sample of 100 adult subjects using age as the variable for stratification, the sample might include 25 subjects in the age range 18 to 39 years, 25 subjects in the age range 40 to 59 years, 25 subjects in the age range 60 to 79 years, and 25 subjects 80 years or older. Sampling error is usually larger with small samples and decreases as the sample size increases. The selection included all of the most populous primary sampling units in the United States and stratified probability samples (by state, area poverty level, and population size) of the less populous ones. The difference between a sample statistic and a population parameter is called the sampling error (Figure 15-2). representative in relation to the variables you are studying and to other factors that may influence the study variables. Variables commonly used for stratification are age, gender, ethnicity, socioeconomic status, diagnosis, geographical region, type of institution, type of care, care provider, and site of care. Random variation is the expected difference in values that occurs when one examines different subjects from the same sample. With a stratified random sample, you could use a smaller sample size to achieve the same degree of representativeness as a large sample acquired through simple random sampling. The retention rates for both groups were very strong and comparable (treatment group 89% and comparison group 90%). The study sample might have been stronger with a more equal number of NP and PA subjects. Each column will present the concepts that underpin evidence-based practice-from research design to data interpretation. The treatment group retention was 110 women with a retention rate of 89% (110 124 100% = 88.7% = 89%). The number of individuals in the population, who they are, how much weight they have lost, how long they have kept the weight off, and how they achieved the weight loss are unknown. For example, if the researcher is selecting 10 subjects from a population of 50, the first name has a 1 in 5 chance (10 draws, 50 names), or a 0.2 probability, of being selected. Sample surveys. Sampling involves selecting a group of people, events, behaviors, or other elements with which to conduct a study. This study has an excellent acceptance rate (100%) and a very strong sample retention rate of 90% for a 24-month-long study. To use a table of random numbers, the researcher places a pencil or a finger on the table with the eyes closed. Gray JR, et al. Using random sampling, the researcher cannot decide that person. Explore the historical and contemporary theories that are the foundation of nursing practice today. 444-445). A sampling plan defines the process of making the sample selections; sample denotes the selected group of people or elements included in a study. Biases may be introduced that make generalization to the broader target population difficult to defend. In systematic random sampling (SYS), units are selected from the frame at regular intervals, and a sampling interval and a random start are required. The chapter concludes with a discussion of the process for recruiting and retaining subjects or participants for study samples in various settings. 2023 Feb 4;11(4):452. doi: 10.3390/healthcare11040452. Table 15-2 shows a section from a random numbers table. Sampling criteria, also referred to as eligibility criteria, include a list of characteristics essential for membership or eligibility in the target population. and transmitted securely. modify the keyword list to augment your search. [A comparison of convenience sampling and purposive sampling]. Quantitative, outcomes, and intervention research Refusalrateformula=number potential subjectsrefusing to participatenumber potentialsubjects meeting sample criteria100% 15 Editor's note: This is the third article in a series on clinical research by nurses. 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. A sampling plan describes the strategies that will be used to obtain a sample for a study. All the values in the sample may tend to be higher or lower than the mean of the population (Thompson, 2002). For instance, perhaps a nurse researcher is interested in examining work satisfaction among clinical nurses within a large health care system. network sampling (otherwise known as snowball sampling). The comparison group retention was 113 women with a retention rate of 90% (113 125 = 90.4% = 90%). 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. Finally, within each secondary sampling unit, all African American and Hispanic households were selected for interviews, whereas other households were sampled at differing rates within the substrata. For more information on the use of this applet see the bottom of this page. In nursing, nurses collect data to diagnose people in order to make decisions about their care. Sampling theory describes two sampling domains: probability and nonprobability. Quantitative, outcomes, and intervention research With this knowledge, you can make intelligent judgments about sampling when you are critically appraising studies or developing a sampling plan for your own study. Sampling theory was developed to determine mathematically the most effective way to acquire a sample that would accurately reflect the population under study. Inferential statistical analyses are based on the assumption that the sample from which data were derived has been obtained randomly. Copyright 2021 Wolters Kluwer Health, Inc. All rights reserved. Probability samples reduce sampling error. The number touched is the starting place. The extent of the difference is the sampling error (see Figure 15-2). Thus, persons who are legally or mentally incompetent, terminally ill, or confined to an institution are more difficult to access as subjects (see Chapter 9). However, some researchers still use a table of random numbers to select a random sample. The study by Twiss et al. People who do not have access to care are usually excluded from health-focused studies. Probability sampling. The sampling plan may use probability (random) sampling methods or nonprobability (nonrandom) sampling methods. Purposeful sampling, also known as selective sampling, is used in both quantitative and qualitative research. This article reviews probability and non-probability sampling methods, lists and defines specific sampling techniques, and provides pros and cons for c 2021 Jan 1;121(1):64-67. doi: 10.1097/01.NAJ.0000731688.58731.05. Hospitals within the randomly selected cities might then be randomly selected. However, the sample was a great strength of this study and appeared to represent the target population of NPs and PAs currently practicing in primary care in the United States. In some cases, this random selection continues through several stages and is referred to as multistage cluster sampling. The treatment group retention was 110 women with a retention rate of 89% (110 124 100% = 88.7% = 89%). Subjects may be limited to individuals who are not participating in any other study. Cardiovascular nursing research covers a wide array of topics from health services to psychosocial patient experiences. FOIA HHS Vulnerability Disclosure, NLM Support Center The retention rate is calculated by dividing the number of subjects completing the study by the initial sample size and multiplying by 100%. Samples may be sought for focus groups, personal interviews (structured, semistructured or unstructured) or for participatory, observational and ethnographic work. However, some of the outcomes are more valid than others, partly because of the sampling techniques used. Schiamberg LB, et al. Probability sampling methods have been developed to ensure some degree of precision in estimations of the population parameters. Sample attrition is the withdrawal or loss of subjects from a study. 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). 66 The retention rates for both groups were very strong and comparable (treatment group 89% and comparison group 90%). These samples are more likely to represent the population than samples obtained with nonprobability sampling methods. The use of a computer to select a sample randomly is usually the most efficient and unbiased process. Because this is a quasi-experimental study that examined the impact of the treatment on the dependent or outcome variables, the increased controls imposed by the sampling criteria strengthened the likelihood that the study outcomes were caused by the treatment and not by extraneous variables. This pointthat studying an entire population is, in most cases, unnecessaryis the key to the theory of sampling. Cluster sampling is a probability sampling method applied when the population is heterogeneous; it is similar to stratified random sampling but takes advantage of the natural clusters or groups of population units that have similar characteristics (Fawcett & Garity, 2009). In studies involving a treatment, subjects in the control group who do not receive the treatment may be more likely to withdraw from the study. Purposeful sampling for qualitative data collection and analysis in mixed method implementation research. 444-445) When you have studied your sample you infer that what you have learned applies to the whole population. The researcher, who has a vested interest in the study, could (consciously or unconsciously) select subjects whose conditions or behaviors are consistent with the study hypothesis. However, random sampling must take place in an accessible population that is representative of the target population. Probability samples reduce sampling error. All of these factors limit representativeness and limit our understanding of the phenomena important in practice. To achieve these goals, researchers need to understand the techniques of sampling and the reasoning behind them. A, Sample Attrition and Retention Rates in Studies. The sampling theory was established to help find the most suitable method of acquiring a sample that exactly represents the study population using mathematical formulae. Qualitative research is generally based on non-probability and purposive sampling rather than probability or random approaches. Thus, probability sampling methods are often referred to as random sampling methods. Nutrients. The sample is most like the target population if the attrition rate is low (<10% to 20%) and the subjects withdrawing from the study are similar to the subjects completing the study.
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what is sampling theory in nursing research