Significance of Selection bias
Selection bias is a systematic error arising from non-random participant selection, potentially skewing study results across various disciplines. It occurs when the sample isn't representative of the target population, affecting the validity and generalizability of findings. Researchers use methods like randomization, careful sampling, and statistical corrections to minimize this bias. Recognizing and addressing selection bias is crucial for robust and reliable research outcomes.
Synonyms: Sampling bias, Participant bias, Nonresponse bias, Ascertainment bias, Recruitment bias
The below excerpts are indicatory and do represent direct quotations or translations. It is your responsibility to fact check each reference.
Hindu concept of 'Selection bias'
Selection bias in Hinduism research, as described, involves systematic errors in participant selection for studies. This bias arises when samples aren't representative of the broader Hindu population, potentially skewing results.
From: International Research Journal of Ayurveda and Yoga
(1) This is a systematic error in choosing participants that can affect study results.[1] (2) A systematic error in the selection of participants.[2] (3) A systematic error in selecting participants, with those opting into yoga studies potentially having a predisposition towards alternative health practices.[3]
From: Journal of Ayurveda and Integrated Medical Sciences
(1) This refers to a systematic error in the selection of participants, and the text mentions that creating different studies may create this type of bias.[4] (2) Selection bias is introduced by the selection of individuals, groups, or data for analysis in a way that proper randomization is not achieved, thus failing to ensure the sample obtained is representative of the population intended to be analyzed.[5]
The concept of Selection bias in scientific sources
Selection bias is a systematic error arising from non-random participant selection, distorting results and limiting generalizability. Researchers minimize it through careful methods and acknowledge its potential impact on study validity.
From: International Journal of Environmental Research and Public Health (MDPI)
(1) The possibility of a selection bias in the physician group cannot be entirely dismissed because surgical doctors were hesitant to participate due to the inconvenience of wearing the measurement device during operative procedures.[6] (2) Selection bias is a form of systematic error that the use of the total-population dataset from the NDB aimed to reduce, allowing for the generation of a study sample that is more representative and less influenced by the characteristics of patient selection typical in smaller studies.[7] (3) A potential flaw in study design where the process of choosing participants results in a sample that is not truly representative of the intended population, which was examined in each article.[8] (4) A potential distortion in the study results stemming from the method of choosing participants, specifically arising from the involvement of local governmental personnel and village officials during the data collection process.[9] (5) There might be a degree of selection bias present in the study population because individuals holding strong opinions, either supportive or opposed, were likely more inclined to agree to participate in the research.[10]
From: Sustainability Journal (MDPI)
(1) Selection bias is a potential issue arising from using a small sample of taxi drivers rather than a comprehensive population sample, which can lead to inaccurate or skewed empirical findings regarding their movement patterns.[11] (2) Selection bias arises because the seven pilot regions chosen for the ETS are very special in terms of their economic development, necessitating methods like PSM and controlling for heterogeneity to reduce this bias.[12] (3) A problem arising in nonexperimental reflections where the outcome variable cannot be observed for a farmer in the counterfactual situation, meaning what would have happened if they had not participated.[13] (4) Selection bias arises because households active in the farmland rental market are typically different from those not renting land, necessitating the use of PSM to approximate the counterfactual situation for causal inference.[14] (5) Systematic error introduced into performance estimates because of non-random assignment of individuals to teachers or institutions, which can influence how well these models estimate true effectiveness.[15]
From: The Malaysian Journal of Medical Sciences
(1) The results of this study may have limited generalisability due to this.[16] (2) Because the participants were chosen at random throughout the enrolment process, the potential one was minimised in this study.[17] (3) This refers to a type of bias that can affect the results of the study, as stated in the text.[18] (4) The study's strength was the minimal amount of this, as all eligible patients were invited to participate.[19] (5) A potential flaw in a study design that can influence the results, a consideration when interpreting retrospective studies on transfusion practices.[20]
From: African Journal of Primary Health Care and Family Medicine
(1) The group of people who were contactable and provided consent to participate likely introduced a selection bias because they were all actively interested in joining some form of maintenance programme.[21] (2) Selection bias is a systematic error in selecting participants for a study, potentially leading to unrepresentative results, and the text notes that the purposive sampling method used to select experts for validating the job aid could result in selection bias.[22] (3) The randomisation allocation sequence was concealed from the principal investigator and family physicians to further eliminate conscious or unconscious selection bias.[23] (4) This is a potential issue where the sample might not accurately represent the population, possibly due to the researcher selecting participants based on availability or specific characteristics, which could skew the study's results.[24] (5) This is a potential limitation of the study, and the text acknowledges that the study might be vulnerable to this bias, along with reporting bias and response bias.[25]
From: South African Family Practice
(1) A potential systematic error introduced into the study results because the method of choosing participants, relying on accessibility, might not have resulted in a truly representative sample of the entire student body.[26] (2) A distortion of statistical analysis, resulting from the method of collecting samples, and which occurs when reviewing active patient files.[27] (3) Occurs when the sample is not representative of the population, leading to skewed results and limiting the generalizability of the findings.[28] (4) Selection bias may have been introduced because patients were selected for the study by the family physician, which could skew the results.[29] (5) Selection bias may limit the generalisability of the findings due to the use of convenience sampling, which means that the sample may not accurately represent the broader population.[30]
From: Journal of Public Health in Africa
(1) A systematic error in research where the sample is not representative of the population, leading to skewed results and inaccurate conclusions.[31] (2) A distortion of statistical results due to the method of selecting participants.[32] (3) It is a systematic error in choosing participants for a study.[33] (4) When illegal burials happens, it might present this against poverty related cause-specific mortalities.[34] (5) This is a potential limitation of the study, as recruitment in pharmacies might have introduced it, and it could affect the representativeness of the sample.[35]
From: South African Journal of Physiotherapy
(1) This refers to the systematic error that can occur when selecting studies for review, potentially skewing the results, and should be mitigated.[36] (2) This is a potential source of error in the study, stemming from the sampling method and the availability of potential participants.[37] (3) This is a potential skewing of results in a study, and it may have been created because of the limited sample size that was used, which may have led to the population not being fully representative of the state.[38] (4) The study used simple random sampling of dwelling units to reduce this, aiming to ensure that the sample of women was representative of the population within the health district.[39] (5) This is a potential problem in the study due to the response rate of less than 100%.[40]
From: South African Journal of HIV Medicine
(1) A potential systematic error introduced because participants were recruited from a specific trial investigating neurocognitive impairment, possibly leading to a study group not perfectly representative of the general treated population.[41] (2) This refers to the bias introduced by the selection of individuals, and the study was limited by this because patients older than 65 years old and those with a Karnofsky score of lower than 80 were excluded.[42] (3) This is a problem in research where the participants in a study are not representative of the whole population, and can skew the results.[43] (4) This term refers to a structural approach to selection bias, as explored in a specific research context, looking at its various elements.[44] (5) This is a type of bias that can occur in studies when the participants selected for the study are not representative of the population being studied.[45]
From: Asian Journal of Pharmaceutics
(1) Second, selection or attrition bias could have been present in nearly 40% of the trials.[46] (2) This might have occurred since participants who attend primary health care centers typically care more about their health.[47] (3) A systematic error in the selection of participants for a study.[48] (4) It is a study limitation due to convenient sampling which may affect the study's results.[49]
From: International Journal of Pharmacology
(1) Chin et al. 21 and Choudhry et al. 22 showed little chance of bias in the domains of allocation concealment, random sequence creation and.[50] (2) A risk of selection bias was introduced in some studies due to the unspecified randomization methods used for grouping patients.[51] (3) This bias can occur when literature searches are not sufficiently comprehensive, failing to identify all relevant studies.[52]
From: Onderstepoort Journal of Veterinary Research
(1) The improper administration of antimicrobial drugs, particularly when applied in insufficiently low doses within fish farms, has been documented as a factor that facilitates selection bias, thus influencing pathogen variability.[53] (2) This is the systematic error that can influence the results of the study, and the study had several sources of selection bias.[54]
From: South African Journal of Psychiatry
(1) Systematic differences between those who participate and those who do not.[55] (2) A systematic error in sampling, where certain individuals are more likely to be included in the study.[56] (3) This is a type of error that can occur when the study participants are not representative of the population, which may impact the study results.[57] (4) This existed in the study population due to the use of a convenience sample, which means the results cannot be broadly applied to the general population.[58] (5) A factor that may have influenced the study's results, as the primary researcher is a doctor, and more doctors may have chosen to participate, potentially affecting the representation of different professions.[59]
From: Religions Journal (MDPI)
(1) This is another limitation in this work, and moving forward, more nuanced programming recruitment and evaluation is recommended to address this.[60] (2) The problem of this complicates efforts to compare the performance of volunteers for faith-based programs with those who did not.[61] (3) If research depicts victim-survivors as traumatized from the outset, there is the possibility of selection bias where only people who identify with the proposed image of victims respond to the call for participation.[62]
From: International Journal of Pharmacology
(1) A potential bias in the study that may arise from including only Chinese and English literature on breast cancer.[63] (2) A systematic error that occurs when participants are not randomly selected, potentially influencing study outcomes.[64]