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). Please read ahead to understand more about what this program does. These biases are similar to biases that may be encountered in a nonrandom sample (Thompson, 2002). The final sample was large (1536 subjects) with strong representation for both NPs (833 subjects) and PAs (689 subjects). The remaining 26 women (exercise = 14; comparison = 12) withdrew from the study before 24 months. Obese individuals who choose to enter a program to lose weight may differ from obese individuals who do not enter a program. A hypothetical population assumes the presence of a population that cannot be defined according to sampling theory rules, which require a list of all members of the population. Application of simple random sampling and the attrition of only three (4%) subjects from the study seem to provide a sample representative of the target population. 44 A sampling method is similar to a design; it is not specific to a study. 02 Stratified random sampling Djukic, Kovner, Budin, and Norman (2010) studied the effect of nurses perceived physical work environment on their job satisfaction and described their sampling frame in the following excerpt. The 5th Edition, continues to meet the needs of today's students with an expanded focus on the middle range theories and practice models. This goal can be accomplished in various ways, limited only by the imagination of the researcher. The control group usually receives no care. 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. There are still many purposive methods of nonprobability sampling that researchers employ to approximate the population of interest. 444-445). government site. 07 You may also needUsing Statistics to Determine DifferencesUsing Statistics to Describe VariablesMeasurement ConceptsUsing Statistics to PredictSelecting a Quantitative Research DesignCollecting and Managing DataFrameworksDisseminating Research Findings Subjects within each stratum are expected to be more similar (homogeneous) in relation to the study variables than they are to be similar to subjects in other strata or the total sample. For example, one could conduct a study in which the defined population was all living recipients of heart and lung transplants. 4th ed. These biases are similar to biases that may be encountered in a nonrandom sample (Thompson, 2002). Community-Based Survey Exploring Use of the Dietary Supplement Creatine by Adult Non-Athletes. In a second step, primary sampling units were partitioned into substrata (up to 21) based on concentrations of African American and Hispanic populations [2nd stage cluster sampling]. Only gold members can continue reading. The following sections explain these concepts; later in the chapter, these concepts are used to explain various sampling methods. Sampling refers to the process used to select a portion of the population for study. Probability Sampling Methods Professional Development, Leadership and Scholarship, Professional Partners Supporting Diverse Family Caregivers Across Settings, Supporting Family Caregivers: No Longer Home Alone, Nurse Faculty Scholars / AJN Mentored Writing Award. 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. Epidemiologists sometimes use entire populations for their large database studies. A systematic review of research papers in the Journal of Advanced Nursing. Quantitative, outcomes, and intervention research apply a variety of probability and nonprobability sampling methods. If your sample is very similar to the population you have a strong case to say that the same things you found in the sample also apply in the population. The total 75 study patients [sample] out of the 281 were selected by random sampling method from the patients presenting orders [sampling frame] and evenly divided into three groups; a control group, a foot and hand massage group, and a foot massage group, each of which included 25 patients. Because some patients accepted the intervention before the operation, but changed their mind after the operation (3 patients in total), not all patients participated in the study. (Degirmen et al., 2010, p. 154). Engaging theoretical sampling in diverse grounded theory studies. Systematic random sampling is the selection of participants in a preordained, orderly sequence. Am J Nurs 2021;121(1):647. For a sample to be representative, it must be similar to the target population in as many ways as possible. Systematic variation can also occur in studies with high sample attrition. (2009) conducted a quasi-experimental study to examine the effects of strength and weight training (ST) exercises on muscle strength, balance, and falls of breast cancer survivors (BCSs) with bone loss (population). The sampling component is an important part of the research process that needs to be carefully thought out and clearly described. Chan JN, Chau J. (2006) used a stratified random sampling method to obtain their sample of nurse practitioners (NPs) and physician assistants (PAs) for the purpose of studying the ethical conflict of these healthcare providers associated with managed care. 2021 Jun 1;121(6):56-60. doi: 10.1097/01.NAJ.0000753668.78872.0f. Exclusion sampling criteria are characteristics that can cause a person or element to be excluded from the target population. The treatment group retention was 110 women with a retention rate of 89% (110 124 100% = 88.7% = 89%). Imagine trying to arrange personal meetings with 100 people, each in a different part of the United States. In some studies, the entire population is the target of the study. Probability sampling is the random selection of elements from the population, where each element of the population has an equal and independent chance of being included in the sample. The use of a computer to select a sample randomly is usually the most efficient and unbiased process. 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. The IQs of the subjects have introduced a systematic bias. This situation could occur, for example, if all the subjects were college students, which has been the case in the development of many measurement methods in psychology. All of these factors limit representativeness and limit our understanding of the phenomena important in practice. 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%). Women were included if they were 35-77 years of age, had a history of stage 0 (in situ), I, or II breast cancer, a BMD [bone mineral density] T-score of 1.0 or less at any of three sites (hip, spine, forearm), were at least 6 months post breast-cancer treatment and 12 months postmenopausal, resided within 100 miles of one of four research sites (Omaha, Lincoln, Kearney, and Scottsbluff, NE), and had their physicians permission to participate [inclusion sampling criteria]. Cluster sampling provides a means for obtaining a larger sample at a lower cost. Tucker J; UK Neonatal Staffing Study Group. Nutrients. Cluster sampling is used in two situations. The comparison group retention was 113 women with a retention rate of 90% (113 125 = 90.4% = 90%). Ample research demonstrates the effectiveness of simulation-based experiences for improving learner performance. Thus, a study that uses random sampling techniques may have such restrictive sampling criteria that the sample is not truly random. Biases may be introduced that make generalization to the broader target population difficult to defend. Some populations are elusive and constantly changing. Twiss et al. The population is a particular group of people, such as people who have had a myocardial infarction, or type of element, such as nasogastric tubes, that is the focus of the research. Bethesda, MD 20894, Web Policies (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 remaining 26 women (exercise = 14; comparison = 12) withdrew from the study before 24 months. The articles will be accompanied by a podcast offering more insight and context from the author. A study might have inclusion or exclusion sampling criteria (or both). However, some of the outcomes are more valid than others, partly because of the sampling techniques used. Quantitative researchers opt for nonprobability sampling techniques largely for convenience and containment of cost and time. Cluster sampling provides a means for obtaining a larger sample at a lower cost. Systematic Variation Degirmen et al. A statistic is then estimated and applied to the whole population. The site is secure. The variable or variables chosen for stratification need to be correlated with the dependent variables being examined in the study. Systematic variation or bias is most likely to occur when the sampling process is not random. An official website of the United States government. 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. 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. Related Sampling Exclusion sampling criteria are characteristics that can cause a person or element to be excluded from the target population. However, random sampling must take place in an accessible population that is representative of the target population. Minimizing sampling error. Sampling Theory. To use a table of random numbers, the researcher places a pencil or a finger on the table with the eyes closed. However, it has some disadvantages. Sampling error decreases, power increases, data collection time is reduced, and the cost of the study is lower if stratification is used (Fawcett & Garity, 2009; Thompson, 2002). Key concepts of sampling theory include populations, target population, sampling or eligibility criteria, accessible population, elements, representativeness, sampling frames, and sampling methods or plans. The control group usually receives no care. 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. Sampling, data collection, and data analysis. A podcast with the authors is available at www.ajnonline.com. A sampling plan defines the process of making the sample selections; sample denotes the selected group of people or elements included in a study. 56 In Nyquist-Shannon sampling theory, a given polychromatic (i.e., multiple frequency) temporal (or spatial) continuous function, f(x), with known maximum spatial frequency Xmax, is determined by its sampled ordinates at a series of points spaced less than or equal to a distance of 1/(2Xmax) apart (Shannon, 1949) The threshold 2Xmax is called the Nyquist rate and is an . 69 That said, nonprobability sampling has important drawbacks. The sampling frame in this study included the names of the 746 RNs who were asked to participate in the study. 14. In addition, a sample must represent the demographic characteristics, such as age, gender, ethnicity, income, and education, which often influence study variables. The sampling plan of a research study is presented in the methods section of a research proposal or research article. The researcher can use a computer to select these numbers randomly to obtain a sample. Populations and Elements 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. Data from subjects associated with the same institution are likely to be correlated and not completely independent. You may hold opinions about the adequacy of these techniques, but there is not enough information to make a judgment. Theoretical sampling Sampling involves selecting a group of people, events, behaviors, or other elements with which to conduct a study. Grounded theory (GT) is a research method concerned with the generation of theory,1 which is 'grounded' in data that has been systematically collected and analysed.2 It is used to uncover such things as social relationships and behaviours of groups, known as social processes.3 It was developed in California, USA by Glaser and Strauss during their study'Awareness of Dying'.1 It is a . In the aforementioned situation, if proportions are used and the sample size is 100, the study would include only five Asians, hardly enough to be representative. Attritionrate=40(numberwithdrawing)160(samplesize)=0.25100%=25% (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 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. In a study of factors that affect the self-care behaviors of female high school students with dysmenorrhea, researchers randomly sampled five classes to survey within each grade. 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. Qualitative research usually includes nonprobability sampling methods. 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. (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. Continuing with the opioid example above, the nurse researcher may ask study participants who started opioid use during adolescence to recruit other participants with a similar substance use history. These studies are referred to as population studies (Barhyte, Redman, & Neill, 1990). 14-15) sampling text. Curr Epidemiol Rep. 2017 Dec;4(4):346-352. doi: 10.1007/s40471-017-0130-z. 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. Systematic variation or bias is most likely to occur when the sampling process is not random. 06 If the sampling frame is small, the researcher can write names on slips of paper, place the names in a container, mix well, and draw out one at a time until the desired sample size has been reached. The refusal rate is calculated by dividing the number of potential subjects refusing to participate by the number of potential subjects meeting sampling criteria and multiplying the results by 100%. Confused about theoretical sampling? HHS Vulnerability Disclosure, Help doi: 10.7759/cureus.16260. I think this all sounds like a pretty standard way to . Accessibility Sampling. Researchers need to provide logical reasons for their inclusion and exclusion sampling criteria, and certain groups should not be excluded without justification. The method you use to pick individuals out of the group to study. The sample theory is merely applicable to the random samples. These sampling criteria probably were narrowly defined by the researchers to promote the selection of a homogeneous sample of postmenopausal BCSs with bone loss. official website and that any information you provide is encrypted In descriptive or correlational studies, the sampling criteria may be defined to ensure a heterogeneous population with a broad range of values for the variables being studied. Sampling methodology influences how well the study represents the target population, and thereby affects the generalizability of the study. To use a table of random numbers, the researcher places a pencil or a finger on the table with the eyes closed. 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. Patient satisfaction with triage nursing care in Hong Kong. Sampling theory was developed to determine mathematically the most effective way to acquire a sample that would accurately reflect the population under study. To avoid disparities in the representation of any one hospital in a random sample of clinical nurses within the health care system, the researcher can use stratified random sampling to randomly select a designated number of nurses within each hospital. It is used to measure a concept of interest. 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. Since researchers generally do not have access to the full population of interest for a research project (the target population), they must rely on studying a subset of that population (the study sample or sample population). Age limitations are often specified, such as adults 18 years and older. Simple random sampling is the most basic of the probability sampling methods. For example, a narrow definition of the accessible population reduces the ability to generalize from the study sample to the target population and diminishes the meaningfulness of the findings. 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). 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. The higher the refusal rate, the less the sample is representative of the target population. Gray JR, et al. 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. 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. Convenience sampling In a study by the UK Neonatal Staffing Study Group of the association between patient volume, staffing levels, and workload and risk-adjusted outcomes of neonatal mortality and hospital-acquired infections, the sample was stratified into units by patient volume (high, medium, low), pediatrician availability (high and low), and nurse-to-patient ratios (high and low). 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. These values do not vary randomly around the population mean. Steinke EE. Critical questions are provided to help researchers choose a sampling method. For instance, suppose a clinical unit is made up predominantly of male patients during the time of the study. Unable to load your collection due to an error, Unable to load your delegates due to an error. Rodriguez J, et al. Cluster sampling is used in two situations. (2010) clearly identified their target population as women needing cesarean operations, and the 281 women with presenting orders provided the sampling frame for the study. The individual units of the population and sample are called elements. The population is a particular group of people, such as people who have had a myocardial infarction, or type of element, such as nasogastric tubes, that is the focus of the research. Refusal and Acceptance Rates in Studies An ideal measuring instrument is one which results in measures that are relevant, accurate, objective, sensitive and efficient. In stratified random sampling, a population is first categorized into specific, nonoverlapping groups (or strata); random samples are then taken from within each group (see Figure 1).5 Stratified sampling facilitates the representation of important participant characteristics in the study sample and improves data collection from underrepresented subgroups. Patients who answered the call and agreed to participate were included in the study. 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. 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. These inclusion and exclusion sampling criteria were appropriate for the study to reduce the effect of possible extraneous variables that might have an impact on the treatment (ST exercises) and the measurement of the dependent variables (muscle strength, balance, and falls). The difference between a sample statistic and a population parameter is called the sampling error (Figure 15-2). These researchers obtained their sample using a simple random sampling method that is described in the following excerpt from their study. Probability sampling. 2012 Jan;5(1):7-13. doi: 10.4103/0974-1208.97779. In addition, a researcher cannot exclude a subset of people from selection as subjects because he or she does not agree with them, does not like them, or finds them hard to deal with. This study has an excellent acceptance rate (100%) and a very strong sample retention rate of 90% for a 24-month-long study. The number touched is the starting place. Twiss et al. Generalizing means that the findings can be applied to more than just the sample under study because the sample is representative of the target population.
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