Products related to Bias:
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Quantitative Longitudinal Data Analysis : Research Methods
First published Open Access under a Creative Commons license as What is Quantitative Longitudinal Data Analysis?, this title is now also available as part of the Bloomsbury Research Methods series. Across the social sciences, there is widespread agreement that quantitative longitudinal research designs offer analysts powerful scientific data resources.But, to date, many texts on analysing longitudinal social analysis surveys have been written from a statistical, rather than a social science data analysis perspective and they lack adequate coverage of common practical challenges associated with social science data analyses. This book provides a practical and up-to-date introduction to influential approaches to quantitative longitudinal data analysis in the social sciences.The book introduces definitions and terms, explains the relative attractions of such a longitudinal design, and offers an introduction to the main techniques of analysis, explaining their requirements, statistical properties and their substantive contribution.
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Unreliable : Bias, Fraud, and the Reproducibility Crisis in Biomedical Research
Reproducibility is fundamental to the scientific method.After reading a paper describing research findings, a scientist should be able to repeat the experiment and obtain the same results.Yet an alarming number—perhaps as high as 90 percent—of published biomedical research papers face challenges in independent replication.Such issues range from honest mistakes to outright fraud.The scope of this crisis, however, underscores deeper systemic issues within the scientific community: its culture, incentives, and institutions. In Unreliable, the distinguished scientist Csaba Szabo examines the causes and consequences of the reproducibility crisis in biomedical research, showing why the factors that encourage misconduct stem from flaws in real-world science.There are many culprits, including commonplace research methods and dubious statistical techniques.Academic career incentives, hypercompetition for grant funding, and a bias toward publishing positive results have exacerbated the problem.Deliberate data manipulation and fabricated findings churned out by “paper mills” are disturbingly common.Academic institutions and publishers, for their part, have perpetuated a culture of impunity. Szabo explores how these failures have hindered scientific progress and impeded the development of new treatments, and he introduces readers to the “science sleuths” who tirelessly uncover misconduct.He proposes comprehensive reforms, from scientific training to the grant system through the publication process, to address the root causes of the crisis.Written in clear language and leavened with a keen sense of irony, Unreliable is an essential account of the reproducibility crisis that gives readers an inside look at how science is actually done.
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Unreliable : Bias, Fraud, and the Reproducibility Crisis in Biomedical Research
Reproducibility is fundamental to the scientific method.After reading a paper describing research findings, a scientist should be able to repeat the experiment and obtain the same results.Yet an alarming number—perhaps as high as 90 percent—of published biomedical research papers face challenges in independent replication.Such issues range from honest mistakes to outright fraud.The scope of this crisis, however, underscores deeper systemic issues within the scientific community: its culture, incentives, and institutions. In Unreliable, the distinguished scientist Csaba Szabo examines the causes and consequences of the reproducibility crisis in biomedical research, showing why the factors that encourage misconduct stem from flaws in real-world science.There are many culprits, including commonplace research methods and dubious statistical techniques.Academic career incentives, hypercompetition for grant funding, and a bias toward publishing positive results have exacerbated the problem.Deliberate data manipulation and fabricated findings churned out by “paper mills” are disturbingly common.Academic institutions and publishers, for their part, have perpetuated a culture of impunity. Szabo explores how these failures have hindered scientific progress and impeded the development of new treatments, and he introduces readers to the “science sleuths” who tirelessly uncover misconduct.He proposes comprehensive reforms, from scientific training to the grant system through the publication process, to address the root causes of the crisis.Written in clear language and leavened with a keen sense of irony, Unreliable is an essential account of the reproducibility crisis that gives readers an inside look at how science is actually done.
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Data Analysis in Qualitative Research : Theorizing with Abductive Analysis
From two experts in the field comes an accessible, how-to guide that will help researchers think more productively about the relation between theory and data at every stage of their work. In Data Analysis in Qualitative Research, Iddo Tavory and Stefan Timmermans provide a how-to guide filled with tricks of the trade for researchers who hope to take excellent qualitative data and transform it into powerful scholarship.In their previous book, Abductive Analysis: Theorizing Qualitative Research, Timmermans and Tavory offered a toolkit for innovative theorizing in the social sciences.In this companion, they go one step further to show how to uncover the surprising revelations that lie waiting in qualitative data—in sociology and beyond. In this book, they lay out a series of tools designed to help both novice and expert scholars see and understand their data in surprising ways.Timmermans and Tavory show researchers how to “stack the deck” of qualitative research in favor of locating surprising findings that may lead to theoretical breakthroughs, whether by engaging with theory, discussing research strategies, or walking the reader through the process of coding data.From beginning to end of a research project, Data Analysis in Qualitative Research helps social scientists pinpoint the most promising paths to take in their approach.
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Who is your Blackpink bias and bias wrecker and why?
My Blackpink bias is Lisa because of her incredible stage presence, powerful dancing, and unique fashion sense. She always brings a high level of energy and charisma to their performances. My bias wrecker is Jisoo because of her stunning visuals, sweet personality, and strong vocal abilities. She has a way of capturing my attention with her charm and talent.
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What is your Itzy bias and who is your bias-wrecker?
My Itzy bias is Lia, because I love her powerful vocals and stage presence. My bias-wrecker is Yuna, because she has a captivating and charismatic aura that always catches my attention. Both of them are incredibly talented and bring something unique to the group, making it hard to choose just one favorite member!
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Who is your bias?
As an AI language model, I do not have personal preferences or biases. My purpose is to provide information and assistance to the best of my abilities without any personal inclinations.
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'Exclusion due to bias?'
Exclusion due to bias refers to the act of leaving out or discriminating against individuals or groups based on preconceived notions, stereotypes, or prejudices. This can occur in various aspects of life, such as employment, education, housing, or social interactions. Exclusion due to bias can have detrimental effects on the individuals or groups being targeted, leading to feelings of marginalization, inequality, and injustice. It is important to address and challenge bias in order to create a more inclusive and equitable society.
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Heteronormative Bias
Sexuality and Gender Now uses a psychoanalytic approach to arrive at a more informed view of the experience and relationships of those whose sexuality and gender may not align with the heterosexual "norm".This book confronts the heteronormative bias dominant in psychoanalysis, using a combination of theoretical and clinical material, offering an important training tool as well as being relevant for practicing clinicians.The contributors address the shift clinicians must make not only to support their patients in a more informed and non-prejudicial way, but also to recognise their own need for support in developing their clinical thinking.They challenge assumptions, deconstruct theoretical ideas, extend psychoanalytic concepts, and, importantly, show how clinicians can attend to their pre-conscious assumptions.They also explore the issue of erotic transference and countertransference, which, if unaddressed, can limit the possibilities for supporting patients more fully to explore their sexuality and gender.Theories of psychosexuality have tended to become split off from the main field of psychoanalytic thought and practice or read from an assumed moral high ground of heteronormativity.The book specifically addresses this bias and introduces new ways of using psychoanalytic ideas.The contributors advocate a wider and more flexible attitude to sexuality in general, which can illuminate an understanding of all sexualities, including heterosexuality. Sexuality and Gender Now will be essential reading for professionals and students of psychoanalysis who want to broaden their understanding of sexuality and gender in their clinical practice beyond heteronormative assumptions.
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Bias Bungalows
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RF Blocker Bias Coaxial Feed Bias Tee 10MHz-6GHz Broadband Radio Frequency Microwave Coaxial Bias
RF Blocker Bias Coaxial Feed Bias Tee 10MHz-6GHz Broadband Radio Frequency Microwave Coaxial Bias
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RF Blocker Bias Coaxial Feed Bias Tee 10MHz-6GHz Broadband Radio Frequency Microwave Coaxial Bias
RF Blocker Bias Coaxial Feed Bias Tee 10MHz-6GHz Broadband Radio Frequency Microwave Coaxial Bias
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What is BTS's bias?
BTS's bias refers to the member of the group that a fan favors or supports the most. Each fan may have a different bias based on their personal preferences and connections with the members. The bias can change over time as fans get to know the members better and as the group releases new music and content. Overall, BTS's bias is a personal choice and can vary among their diverse fanbase.
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What does bias mean?
Bias refers to a prejudice or inclination towards a particular perspective, idea, or group, which may result in unfair treatment or judgment. It can manifest in various forms, such as personal biases based on individual experiences or societal biases rooted in cultural norms and stereotypes. Bias can impact decision-making, behavior, and attitudes, and it is important to recognize and address biases in order to promote fairness and equality.
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Who is your bias and who is your bias-wrecker in WayV?
My bias in WayV is Ten because of his incredible dancing skills and stage presence. My bias-wrecker in WayV is Xiaojun because of his powerful vocals and charming personality. Both of them never fail to impress me with their talents and charisma.
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Who is your bias and who is your bias-wrecker in ITZY?
My bias in ITZY is Yuna. I admire her talent, charisma, and stage presence. My bias-wrecker in ITZY is Ryujin. Her powerful dance skills and unique charm always catch my attention.
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