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Journal articles on the topic 'Bias'

Author: Grafiati

Published: 4 June 2021

Last updated: 25 July 2025

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1

Bailey, R. A. "Bias bias." New Scientist 199, no. 2664 (2008): 22–23. http://dx.doi.org/10.1016/s0262-4079(08)61727-3.

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2

Tandoc, Edson C., Bruno Takahashi, and Ryan J. Thomas. "Bias vs. Bias." Journalism Practice 12, no. 7 (2017): 834–49. http://dx.doi.org/10.1080/17512786.2017.1343095.

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3

Raine, Rosalind. "Bias measuring bias." Journal of Health Services Research & Policy 7, no. 1 (2002): 65–67. http://dx.doi.org/10.1258/1355819021927584.

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The British National Health Service and other publicly funded health systems operate on the principle that health care should be provided solely on the basis of need. Yet the literature abounds with reports of bias in health care use. In order to defend such a charge, two conditions must be met. The first condition is that treatment decisions must be shown to be unfair in that they are not made solely on the basis of need. This paper demonstrates the importance of considering the fair distribution of health care from two, related, perspectives. The first is that people with equal needs should

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4

Brighton, Henry, and Gerd Gigerenzer. "The bias bias." Journal of Business Research 68, no. 8 (2015): 1772–84. http://dx.doi.org/10.1016/j.jbusres.2015.01.061.

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5

Harcum, E. Rae, and Ellen Rosen. "Bias, bias, who doesn't have the bias?" Contemporary Psychology: A Journal of Reviews 40, no. 6 (1995): 607. http://dx.doi.org/10.1037/005052.

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6

Gibson, John P. "Bias in naming bias." Nature Reviews Genetics 3, no. 1 (2002): 80. http://dx.doi.org/10.1038/nrg700-c1.

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7

Farkas, Donka F. "Bias and anti-bias." Approaches to Hungarian 18 2, no. 1 (2023): 96–126. http://dx.doi.org/10.1075/jul.00016.far.

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Abstract This paper proposes an account of the interpretive effects of two discourse particles in Hungarian, talán and vajon, within the view of context and context change developed in Farkas & Roelofsen (2017), and shows that the restrictions on their distribution follow from their interpretive properties. Building on Gyuris (2022), talán will be treated as signaling epistemic bias in both declaratives and interrogatives. Following Farkas (2022), vajon will be treated as a non-intrusive question marker, which, in the account proposed, is incompatible with bias markers. The restrictions on

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8

Haryati, Setyorini, T. Sihotang Ellen, and F. Sholikah. "Emotional Bias, Cognitive Bias and Herding Bias toward Investment Decision for Indonesian Investor." INTERNATIONAL JOURNAL OF SOCIAL SCIENCE HUMANITY & MANAGEMENT RESEARCH 2, no. 08 (2023): 785–92. https://doi.org/10.5281/zenodo.8228402.

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In making investment decisions, the role of emotions is very important because of investors irrational symptoms in decision making. This study aims to analyze the effect of emotional bias, cognitive bias, and herding bias on the investment decision making of investors in Indonesia. The research approach used is a quantitative approach. By using primary data from respondents spread throughout Indonesia, this study uses the partial least squares as a data analysis technique. The research hypothesis is that there is a positive influence of emotional bias, cognitive bias and herding bias in the pr

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9

G.S., Vidya, and Vijaygeetha M. "Bias in Epidemiology." Indian Journal of Preventive Medicine 4, no. 2 (2016): 75–81. http://dx.doi.org/10.21088/ijpm.2321.5917.4216.4.

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10

Baumgartner, Renate, and Sarah Kuhn. "Bias does not equal bias." TATuP - Zeitschrift für Technikfolgenabschätzung in Theorie und Praxis 30, no. 2 (2021): 69–70. http://dx.doi.org/10.14512/tatup.30.2.69.

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11

Faillie, Jean-Luc. "Indication bias or protopathic bias?" British Journal of Clinical Pharmacology 80, no. 4 (2015): 779–80. http://dx.doi.org/10.1111/bcp.12705.

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12

Sedgwick, P. "Selection bias versus allocation bias." BMJ 346, may24 4 (2013): f3345. http://dx.doi.org/10.1136/bmj.f3345.

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13

Nunan, David, Carl Heneghan, and Elizabeth A. Spencer. "Catalogue of bias: allocation bias." BMJ Evidence-Based Medicine 23, no. 1 (2018): 20–21. http://dx.doi.org/10.1136/ebmed-2017-110882.

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This article is part of a series of articles featuring the Catalogue of Bias introduced in this volume of BMJ Evidence-Based Medicine that describes allocation bias and outlines its potential impact on research studies and the preventive steps to minimise its risk. Allocation bias is a type of selection bias and is relevant to clinical trials of interventions. Knowledge of interventions prior to group allocation can result in systematic differences in important characteristics that could influence study findings. Allocation bias can overestimate effect size by up to 30%–40%. Sequentially numbe

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14

Nunan, David, Jeffrey Aronson, and Clare Bankhead. "Catalogue of bias: attrition bias." BMJ Evidence-Based Medicine 23, no. 1 (2018): 21–22. http://dx.doi.org/10.1136/ebmed-2017-110883.

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This article is part of a series of articles featuring the Catalogue of Bias introduced in this volume of BMJ Evidence-Based Medicine that describes attrition bias and outlines its potential impact on research studies and the preventive steps to minimise its risk. Attrition bias is a type of selection bias due to systematic differences between study groups in the number and the way participants are lost from a study. Differences between people who leave a study and those who continue, particularly between study groups, can be the reason for any observed effect and not the intervention itself.

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15

Mahtani, Kamal, Elizabeth A. Spencer, Jon Brassey, and Carl Heneghan. "Catalogue of bias: observer bias." BMJ Evidence-Based Medicine 23, no. 1 (2018): 23–24. http://dx.doi.org/10.1136/ebmed-2017-110884.

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This article is part of a series featured from the Catalogue of Bias introduced in this volume of BMJ Evidence-Based Medicine that describes biases and outlines their potential impact in research studies. Observer bias is systematic discrepancy from the truth during the process of observing and recording information for a study. Many healthcare observations are at risk of this bias. Evidence shows that treatment effect estimates can be exaggerated by a third to two-thirds in the presence of observer bias in outcome assessment. Preventing observer bias involves proper masking in intervention st

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16

Chapman, Jens. "Eliminating bias/living with bias?" Evidence-Based Spine-Care Journal 3, no. 03 (2013): 5–6. http://dx.doi.org/10.1055/s-0032-1327802.

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17

DeVito, Nicholas J., and Ben Goldacre. "Catalogue of bias: publication bias." BMJ Evidence-Based Medicine 24, no. 2 (2018): 53–54. http://dx.doi.org/10.1136/bmjebm-2018-111107.

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18

Middleton, Joel A., Marc A. Scott, Ronli Diakow, and Jennifer L. Hill. "Bias Amplification and Bias Unmasking." Political Analysis 24, no. 3 (2016): 307–23. http://dx.doi.org/10.1093/pan/mpw015.

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In the analysis of causal effects in non-experimental studies, conditioning on observable covariates is one way to try to reduce unobserved confounder bias. However, a developing literature has shown that conditioning on certain covariates may increase bias, and the mechanisms underlying this phenomenon have not been fully explored. We add to the literature on bias-increasing covariates by first introducing a way to decompose omitted variable bias into three constituent parts: bias due to an unobserved confounder, bias due toexcludingobserved covariates, and bias due to amplification. This lea

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19

Martínez-Frías, María Luisa. "Interviewer bias and maternal bias." Teratology 47, no. 6 (1993): 531–32. http://dx.doi.org/10.1002/tera.1420470604.

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20

Olson, Kristen. "Survey Participation, Nonresponse Bias, Measurement Error Bias, and Total Bias." Public Opinion Quarterly 70, no. 5 (2006): 737–58. http://dx.doi.org/10.1093/poq/nfl038.

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21

Devi Susilayani, Nasrullah Idris, Sarina, Maswati,. "Pengembangan Alat Ukur Indeks Bias Menggunakan Prisma Berongga dari Lembaran Kaca Komersial Biasa dan Laser He-Ne untuk Pengujian Kualitas Minyak Goreng." Risalah Fisika 1, no. 2 (2017): 39–46. http://dx.doi.org/10.35895/rf.v1i2.45.

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Prisma berongga telah dibuat dari lembaran kaca komersial biasa sebagai instrumen optik sederhana dan murah untuk penentuan secara cepat kualitas minyak goreng dengan pengukuran indeks biasnya. Dimensi lembaran kaca komersial tersebut yang dijadikan sisi-sisi prisma tersebut adalah 10 cm × 10 cm dengan ketebalan 5 cm. Pengukuran indeks bias minyak goreng dilakukan dengan memasukkan sampel minyak goreng ke dalam rongga prisma tersebut, kemudian dilewatkan berkas cahaya helium neon (He-Ne) dan diukur sudut deviasi berkas laser tersebut setelah lewat melalui prisma berongga tersebut. Indeks bias

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22

Stout, Holly. "Bias." Judicial Review 16, no. 4 (2011): 458–82. http://dx.doi.org/10.5235/108546811799320862.

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23

Delgado-Rodriguez, M. "Bias." Journal of Epidemiology & Community Health 58, no. 8 (2004): 635–41. http://dx.doi.org/10.1136/jech.2003.008466.

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24

Muir, D. C. "Bias." Occupational and Environmental Medicine 50, no. 12 (1993): 1122–23. http://dx.doi.org/10.1136/oem.50.12.1122.

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25

Berlet, Gregory C. "Bias." Foot & Ankle Specialist 4, no. 2 (2011): 76. http://dx.doi.org/10.1177/1938640011402007.

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26

Sitthi-amorn, C., and V. Poshyachinda. "Bias." Lancet 342, no. 8866 (1993): 286–88. http://dx.doi.org/10.1016/0140-6736(93)91823-5.

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27

Fearn, Tom. "Bias." NIR news 9, no. 6 (1998): 4–5. http://dx.doi.org/10.1255/nirn.491.

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28

Neher, Jon O. "Bias." Evidence-Based Practice 23, no. 1 (2020): 2. http://dx.doi.org/10.1097/ebp.0000000000000768.

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29

Gigerenzer, Gerd. "The Bias Bias in Behavioral Economics." Review of Behavioral Economics 5, no. 3-4 (2018): 303–36. http://dx.doi.org/10.1561/105.00000092.

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30

Gawronski, Bertram, Alison Ledgerwood, and Paul W. Eastwick. "Implicit Bias ≠ Bias on Implicit Measures." Psychological Inquiry 33, no. 3 (2022): 139–55. http://dx.doi.org/10.1080/1047840x.2022.2106750.

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31

Sedgwick, P. "Non-response bias versus response bias." BMJ 348, apr09 1 (2014): g2573. http://dx.doi.org/10.1136/bmj.g2573.

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32

Hedden, Brian. "Hindsight bias is not a bias." Analysis 79, no. 1 (2018): 43–52. http://dx.doi.org/10.1093/analys/any023.

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33

Norman, Geoff. "The Bias in researching cognitive bias." Advances in Health Sciences Education 19, no. 3 (2014): 291–95. http://dx.doi.org/10.1007/s10459-014-9517-5.

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34

Cislak, Aleksandra, Magdalena Formanowicz, and Tamar Saguy. "Bias against research on gender bias." Scientometrics 115, no. 1 (2018): 189–200. http://dx.doi.org/10.1007/s11192-018-2667-0.

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35

Garb, Howard N. "Race Bias, Social Class Bias, and Gender Bias in Clinical Judgment." Clinical Psychology: Science and Practice 4, no. 2 (1997): 99–120. http://dx.doi.org/10.1111/j.1468-2850.1997.tb00104.x.

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36

Pearce, N., and L. Richiardi. "Commentary: Three worlds collide: Berkson's bias, selection bias and collider bias." International Journal of Epidemiology 43, no. 2 (2014): 521–24. http://dx.doi.org/10.1093/ije/dyu025.

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37

A., Subramaniam V. "Overconfidence Bias in Thirukkural." International Journal of Trend in Scientific Research and Development Volume-3, Issue-2 (2019): 113–15. http://dx.doi.org/10.31142/ijtsrd20296.

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38

Friedecký, B. "Bias, uncertainty, total error." Klinická biochemie a metabolismus 17, no. 2 (2009): 106–8. https://doi.org/10.61568/kbm.2009.024.

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39

Zahro, Dalilah El, and Mohamad Nur Singgih. "Pengaruh Herding Bias, Overconfidence Bias, dan Cognitive Dissonance Bias terhadap Keputusan Investasi." Business Management Research 3, no. 2 (2024): 72–83. http://dx.doi.org/10.26905/bismar.v3i2.13772.

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The purpose of this study is to analyze investor behavior influenced by herding bias, overconfidence bias, and cognitive dissonance bias on investment decision making. Investors were given a questionnaire as part of the quantitative data collection for this study. This study used data from a sample of 102 investors who had all been active in the capital market for at least one year, had traded, and had invested at least twice. Several statistical analyses, including convergent and discriminant validity tests, composite reliability, and significance tests, were performed on the data collected f

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40

Daniel, Sharon, Gideon Koren, Eitan Lunenfeld, and Amalia Levy. "Reply to ‘Indication bias or protopathic bias?’." British Journal of Clinical Pharmacology 80, no. 4 (2015): 781. http://dx.doi.org/10.1111/bcp.12708.

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41

Sun, Xiaohan. "Decision bias: Consumer behaviour influenced by bias." Journal of Education, Humanities and Social Sciences 23 (December 13, 2023): 527–31. http://dx.doi.org/10.54097/ehss.v23i.13111.

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This essay will explain the impact of decision bias on everyday consumer behaviour. Firstly, the meaning of decision bias will be explained and then examples of the behavioural processes by which consumer behaviour is affected by it will be presented. Next, the processes by which consumer behaviour is affected will be specifically analysed by introducing four types of bias, confirmation bias, valuation bias, loss aversion, and overconfidence. Finally, the complexity and importance of the study of decision bias in practical decision making is further discussed using the example of consumers buy

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42

Westreich, Daniel. "Berksonʼs Bias, Selection Bias, and Missing Data". Epidemiology 23, № 1 (2012): 159–64. http://dx.doi.org/10.1097/ede.0b013e31823b6296.

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43

Daniels, Craig E., Victor M. Montori, and Denise M. Dupras. "Effect of Publication Bias on Retrieval Bias." Academic Medicine 77, no. 3 (2002): 266. http://dx.doi.org/10.1097/00001888-200203000-00019.

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44

Dehn, Doris M., and Edgar Erdfelder. "What kind of bias is hindsight bias?" Psychological Research 61, no. 2 (1998): 135–46. http://dx.doi.org/10.1007/s004260050020.

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45

Mitchell, Gregory. "Measuring Situational Bias or Creating Situational Bias?" Psychological Inquiry 28, no. 4 (2017): 292–96. http://dx.doi.org/10.1080/1047840x.2017.1373553.

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46

Frusciante, Noemi, and Ravi K. Sheth. "Lagrangian bias in the local bias model." Journal of Cosmology and Astroparticle Physics 2012, no. 11 (2012): 016. http://dx.doi.org/10.1088/1475-7516/2012/11/016.

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47

Przepiorka, Donna, and Elihu Estey. "When is selection bias not selection bias?" American Journal of Hematology 52, no. 4 (1996): 330–31. http://dx.doi.org/10.1002/(sici)1096-8652(199608)52:4<330::aid-ajh20>3.0.co;2-g.

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48

Harshila, Gujar. "Addressing Unconscious Bias: Tools and Techniques to Mitigate Bias in the Workplace." Journal of Scientific and Engineering Research 11, no. 4 (2024): 351–54. https://doi.org/10.5281/zenodo.13604160.

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Unconscious bias in the workplace can undermine diversity and inclusion efforts, leading to inequitable outcomes and a less inclusive work environment. This book explores the tools and techniques to identify, address, and mitigate unconscious bias in organizations. By understanding the roots of unconscious bias and implementing targeted strategies, organizations can foster a more inclusive culture, enhance employee engagement, and improve overall performance.

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49

Afriani, Dila, and Halmawati Halmawati. "Pengaruh Cognitive Dissonance Bias, Overconfidence Bias Dan Herding Bias Terhadap Pengambilan Keputusan Investasi." JURNAL EKSPLORASI AKUNTANSI 1, no. 4 (2019): 1650–65. http://dx.doi.org/10.24036/jea.v1i4.168.

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This study aims to determine whether cognitive dissonance bias, overconfidence bias and herding bias have a significant effect on stock investment decision making partially and simultaneously. the sample in this study were students of the Faculty of Economics, Padang State University. The sampling technique was simple random sampling . A total of 133 questionnaires were returned in complete condition and processed. by using multiple linear regression techniques, the results show that cognitive dissonance bias and overconfidence bias do not affect stock investment decisions. Herding bias has a

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50

Knobloch-Westerwick, Silvia, Cornelia Mothes, and Nick Polavin. "Confirmation Bias, Ingroup Bias, and Negativity Bias in Selective Exposure to Political Information." Communication Research 47, no. 1 (2017): 104–24. http://dx.doi.org/10.1177/0093650217719596.

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Selective reading of political online information was examined based on cognitive dissonance, social identity, and news values frameworks. Online reports were displayed to 156 Americans while selective exposure was tracked. The news articles that participants chose from were either conservative or liberal and also either positive or negative regarding American political policies. In addition, information processing styles (cognitive reflection and need-for-cognition) were measured. Results revealed confirmation and negativity biases, per cognitive dissonance and news values, but did not corrob

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