Statistics You Need
Saif Aldeen Saleh AlRyalat, Shaher Momani in A Beginner's Guide to Using Open Access Data, 2019
Sampling is the process of selecting representative elements of a population for inclusion in a study that allows inferences and generalizations about the population without actually examining each element in the population. The first step is to define the target population. For example, if you are studying a condition in a city, then your target population is the city's population; but if you are studying a condition in an entire country, then your target population would be the country's population. After defining your target population, there are two main sampling techniques to follow: probability and nonprobability sampling (Kothari, 2004). Probability sampling (e.g., simple random sampling) is where elements are chosen randomly and every element has an equal and independent chance of being selected. Although this type of sampling is laborious, it is a better representation of your target population. On the other hand, nonprobability sampling (e.g., convenience sampling) is where elements are chosen by nonrandom methods and there is no way of ensuring that every element has an equal chance of being selected. Although this type of sampling is less rigorous, it is also less representative of your target population.
Understanding research
Geraldine Lee-Treweek, Tom Heller, Hilary MacQueen, Julie Stone, Sue Spurr in Complementary and Alternative Medicine: Structures and Safeguards, 2020
Sampling is the selection of particular individuals or results as being representative of all individuals or results. It is an area fraught with hazards. Everybody tends to remember their successes, or instances that illustrate their beliefs particularly well, but the cases that stick in their minds may not represent the true story. If a practitioner sees 10 people who have a particular disease, three may not complete the treatment, five may improve a little and two may improve a great deal. The practitioner will tend to remember the two successful examples and use them as the basis for writing and teaching. Similarly, the hypothetical GP quoted above may tend to remember one or two particularly difficult people who used CAM, and forget the many others who use it without problems or without their GP’s knowledge.
S
Filomena Pereira-Maxwell in Medical Statistics, 2018
The process of selecting a group of individuals from a population, with the aim to use the information provided by the sample to draw conclusions about a source or a target population. In surveys and cross-sectional studies, random and non-random sampling methods are used. Among the former, frequently used methods are simple random sampling, stratified sampling, cluster sampling and multistage sampling. Systematic sampling and quota sampling are examples of non-random methods frequently used in market research. The ability to generalize from sample to population relies on its representativeness or lack of bias. Sampling is not usually employed in comparative studies (with the exception of selection of controls in case-control studies, which may be carried out through sampling), where comparability and internal validity are the main concerns regarding avoidance of bias. See COCHRAN (1977) and LEVY & LEMESHOW (2009) for comprehensive guides to sampling techniques. See also efficiency.
Exploring Perceptions of Parents on the Use of Emergency Department On-site Primary Care Services for the Treatment of Children With Non-urgent Conditions
Published in Comprehensive Child and Adolescent Nursing, 2021
Mfon Sam, Dianne L. Cook, Andrew G. Rowland, James Butler
Random sampling involves some form of random selection of the population members. Each population member has a known and typically equal probability of being selected. Simple random sampling (sometimes referred to simply as random sampling) is the most straightforward type of random sampling. A sampling frame is constructed – that is, a list of all people belonging to the population. Constructing a sampling frame requires knowledge of exactly who is in the population. A sample of a fixed size is selected at random from this list, with all members of the population having the same probability of being selected, independently of all others. The probability that a population member will be chosen is known in advance (Sedgwick, 2013). In contrast, in this study, convenience sampling involved selecting patients because it was convenient and they were easily accessible. Despite the potential limitations of convenience sampling, it is often used to recruit participants to a study because it is easy to do (Sedgwick, 2013).
Is mild asthma truly mild? The patients’ real-life setting
Published in Expert Review of Respiratory Medicine, 2022
Gabriella Guarnieri, Veronica Batani, Gianenrico Senna, Annarita Dama, Andrea Vianello, Marco Caminati
Some limitations deserve to be highlighted. First of all, the study sample selection, described in methods, is not free from potential bias. In fact, non-probability sampling does not rely on population size calculation according to the specific study aims and the sample, which is not chosen at random, is unlikely to be representative of the population being studied. Although this limitation hampers the external validity and the possibility to make generalizations from the recorded observations, it allows easy and quick gathering of exploratory data and to orient future investigations. Furthermore, the survey methodology itself may suffer from some disadvantages. All the collected information is completely patients’ self reported and may be somehow conditioned by the interface with the interviewer and the short interview duration, which limits the number of details increasing the response accuracy. In addition, the interview questionnaire, although developed by experts in the field, did not undertake any validation process. A further potential source of bias might be related to the concomitance of our survey with COVID-19 pandemic. However, according to a robust study investigating the prescribing patterns and treatment adherence in asthma patients during that time, COVID-19 pandemic did not significantly impact on the adherence, which remained as low as usual, showing only a slight improvement during the first year of the pandemic [24].
Experiences on Providing Home Care for A Relative with Heart Failure: A Qualitative Study
Published in Journal of Community Health Nursing, 2020
Sami Al-Rawashdeh, Ala Ashour, Ali Alshraifeen, Mohammad Rababa
We acknowledge that there are limitations to this study that may hinder the generalizability of its findings. The use of non-probability convenience sampling may affect the sample representativeness of the larger population, as persons not included in the study might have different experiences. Therefore, further studies are required with more diverse populations of family caregivers as well as family caregivers from other ethnic groups. Also, as in other qualitative studies, the potential of researcher bias is one of the main issues. To minimize the bias, two authors who were not involved directly in the data collection or study design worked with the first author on the data analysis. Despite these limitations, this study has many strengths, including the recruitment of male family caregivers (who are uncommon in Arab culture), family caregivers other than spouses, and family caregivers from different ethnic groups (within an Islamic and Arab context). These were identified as research gaps in the review of the literature on the experience of family caregivers of persons with HF or other chronic illnesses (Hodson, 2017; Janevic & Connell, 2001; Zhang & Lee, 2017).
Related Knowledge Centers
- Copper
- Randomization
- Sampling Frame
- Selection Bias
- Stratified Sampling
- Survey Methodology
- Observation
- Acceptance Sampling
- Opinion Poll
- Sampling Fraction