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Books on the topic 'Ordinal data analysis'

Author: Grafiati
Published: 4 June 2021
Last updated: 16 February 2022

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1

Agresti, Alan. Analysis of ordinal categorical data. 2nd ed. Hoboken, N.J: Wiley, 2010.

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2

Agresti, Alan. Analysis of ordinal categorical data. 2nd ed. Hoboken, N.J: Wiley, 2010.

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3

Diday, Edwin, Yves Lechevallier, and Otto Opitz. Ordinal and Symbolic Data Analysis. Berlin, Heidelberg: Springer Berlin Heidelberg, 1996. http://dx.doi.org/10.1007/978-3-642-61159-9.

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4

Agresti, Alan. Analysis of Ordinal Categorical Data. Hoboken, NJ, USA: John Wiley & Sons, Inc., 2010. http://dx.doi.org/10.1002/9780470594001.

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5

Analysis of ordinal categorical data. 2nd ed. Hoboken, N.J: Wiley, 2010.

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6

Ordinal methods for behavioral data analysis. Mahwah, N.J: Erlbaum, 1996.

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7

International Conference on Ordinal and Symbolic Data Analysis (1995 Paris, France). Ordinal and symbolic data analysis: Proceedings of the International Conference on Ordinal and Symbolic Data Analysis--OSDA '95, Paris, June 20-23, 1995. Berlin: Springer, 1996.

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8

Svensson, Elisabeth. Analysis of systematic and random differences between paired ordinal categorical data. Göteborg: University of Göteborg, 1993.

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9

Biswas, Atanu. Modelling and analysis of multivariate ordinal categorical data in longitudinal set up. Ahmedabad: Indian Institute of Management, 2013.

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10

service), SpringerLink (Online, ed. Permutation Complexity in Dynamical Systems: Ordinal Patterns, Permutation Entropy and All That. Berlin, Heidelberg: Springer-Verlag Berlin Heidelberg, 2010.

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11

Edwardes, Michael D. deBurgh. The analysis of ordinal data. 1986.

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12

Agresti, Alan. Analysis of Ordinal Categorical Data. Wiley & Sons, Incorporated, John, 2012.

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13

Agresti, Alan. Analysis of Ordinal Categorical Data. Wiley & Sons, Incorporated, John, 2012.

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14

Agresti, Alan. Analysis of Ordinal Categorical Data. Wiley & Sons, Incorporated, John, 2012.

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15

Cliff, Norman. Ordinal Methods for Behavioral Data Analysis. Taylor & Francis Group, 2016.

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16

Cliff, Norman. Ordinal Methods for Behavioral Data Analysis. Psychology Press, 2014. http://dx.doi.org/10.4324/9781315806730.

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17

Skinner, Justin Michael Edward. The analysis of repeated ordinal data using latent trends. 1999.

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18

(Editor), Edwin Diday, Yves Lechevallier (Editor), and Otto Opitz (Editor), eds. Ordinal and Symbolic Data Analysis: Proceedings of the International Conference on Ordinal and Symbolic Data Analysis - OSDA 95, Paris, June 20 - 23, 1995 ... Data Analysis, and Knowledge Organization). Springer, 1996.

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19

Liu, Xing. Applied Ordinal Logistic Regression Using Stata: From Single-Level to Multilevel Modeling. SAGE Publications, Inc, 2015.

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20

Uysal, Suzan, and Stephan A. Mayer. Neurological and Functional Outcomes Assessment. Edited by David L. Reich, Stephan Mayer, and Suzan Uysal. Oxford University Press, 2017. http://dx.doi.org/10.1093/med/9780190280253.003.0006.

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The evidence base for neuroprotection in critical care and perioperative medicine rests on outcomes research, a critical component of which is the quantitative assessment of the functional effects of neurological injury. Outcomes assessment is conceptualized hierarchically in terms of global outcome, impairment, disability, handicap, and health-related quality of life. This chapter describes the different classes of outcome measures and the instruments within each class that are most commonly used in clinical neuroprotection research. Desirable characteristics of outcome measures are described, as well as considerations for statistical analysis of ordinal scale data. The authors describe several resources for clinicians and clinical researchers to aid in choosing or evaluating outcome measures for clinical neuroprotection trials.
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21

Lassiter, Daniel. Measurement theory and the typology of scales. Oxford University Press, 2017. http://dx.doi.org/10.1093/oso/9780198701347.003.0002.

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Most previous work on graded modality has relied on qualitative orderings, rather than degree semantics. This chapter introduces Representational Theory of Measurement (RTM), a framework which makes it possible to translate between qualitative and degree-based scales. I describe a way of using RTM to extend the compositional degree semantics introduced in chapter 1 to qualitative scales. English data are used to motivate the application of the RTM discussion between ordinal, interval, and ratio scales to scalar adjectives, with special attention to the kinds of statements that are semantically interpretable relative to different scale types. I also propose and motivate empirically a distinction between ‘additive’ and ‘intermediate’ scales, which interact differently with the algebraic join operation (realizing sum formation or disjunction, depending on the domain). This distinction is reflected in inferential properties of non-modal adjectives in English, and is also important for the analysis of graded modality in later chapters.
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22

Li, Quan. Using R for Data Analysis in Social Sciences. Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780190656218.001.0001.

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This book seeks to teach undergraduate and graduate students in social sciences how to use R to manage, visualize, and analyze data in order to answer substantive questions and replicate published findings. This book distinguishes itself from other introductory R or statistics books in three ways. First, targeting an audience rarely exposed to statistical programming, it adopts a minimalist approach and covers only the most important functions and skills in R that one will need for conducting reproducible research projects. Second, it emphasizes meeting the practical needs of students using R in research projects. Specifically, it teaches students how to import, inspect, and manage data; understand the logic of statistical inference; visualize data and findings via histograms, boxplots, scatterplots, and diagnostic plots; and analyze data using one-sample t-test, difference-of-means test, covariance, correlation, ordinary least squares (OLS) regression, and model assumption diagnostics. Third, it teaches students how to replicate the findings in published journal articles and diagnose model assumption violations. The principle behind this book is to teach students to learn as little R as possible but to do as much reproducible, substance-driven data analysis at the beginner or intermediate level as possible. The minimalist approach dramatically reduces the learning cost but still proves adequate information for meeting the practical research needs of senior undergraduate and beginning graduate students. Having completed this book, students can use R and statistical analysis to answer questions regarding some substantively interesting continuous outcome variable in a cross-sectional design.
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23

Witkov, Carey, and Keith Zengel. Chi-Squared Data Analysis and Model Testing for Beginners. Oxford University Press, 2019. http://dx.doi.org/10.1093/oso/9780198847144.001.0001.

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This book is the first to make chi-squared model testing, one of the data analysis methods used to discover the Higgs boson and gravitational waves, accessible to undergraduate students in introductory physics laboratory courses. By including uncertainties in the curve fitting, chi-squared data analysis improves on the centuries old ordinary least squares and linear regression methods and combines best fit parameter estimation and model testing in one method. A toolkit of essential statistical and experimental concepts is developed from the ground up with novel features to interest even those familiar with the material. The presentation of one- and two-parameter chi-squared model testing, requiring only elementary probability and algebra, is followed by case studies that apply the methods to simple introductory physics lab experiments. More challenging topics, requiring calculus, are addressed in an advanced topics chapter. This self-contained and student-friendly introduction to chi-squared analysis and model testing includes a glossary, end-of-chapter problems with complete solutions, and software scripts written in several popular programming languages, that the reader can use for chi-squared model testing. In addition to introductory physics lab students, this accessible introduction to chi-squared analysis and model testing will be of interest to all who need to learn chi-squared model testing, e.g. beginning researchers in astrophysics and particle physics, beginners in data science, and lab students in other experimental sciences.
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24

Differential Equation Analysis In Biomedical Science And Engineering Ordinary Differential Equation Applications With R. John Wiley & Sons Inc, 2013.

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25

Numerical Methods For Ordinary Differential Equations Initial Value Problems. Springer, 2010.

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26

Quantitative Methods in Population Health: Extensions of Ordinary Regression. Wiley & Sons, Incorporated, John, 2003.

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27

Palta, Mari. Quantitative Methods in Population Health: Extensions of Ordinary Regression. Wiley & Sons, Incorporated, John, 2007.

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28

Halperin, Sandra, and Oliver Heath. 16. Patterns of Association. Oxford University Press, 2017. http://dx.doi.org/10.1093/hepl/9780198702740.003.0016.

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This chapter discusses the principles of bivariate analysis as a tool for helping researchers get to know their data and identify patterns of association between two variables. Bivariate analysis offers a way of establishing whether or not there is a relationship between two variables, a dependent variable and an independent variable. With bivariate analysis, theoretical expectations can be compared against evidence from the real world to see if the theory is supported by what is observed. The chapter examines the pattern of association between dependent and independent variables, with particular emphasis on hypothesis testing and significance tests. It discusses ordinary least squares (OLS) regression and cross-tabulation, two of the most widely used statistical analysis techniques in political research. Finally, it explains how to state the null hypothesis, calculate the chi square, and establishing the correlation between the dependent and independent variables.
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29

Quantitative Methods in Population Health: Extensions of Ordinary Regression (Wiley Series in Probability and Statistics). Wiley-Interscience, 2003.

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30

Cox, Mary Elisabeth. Hunger in War and Peace. Oxford University Press, 2019. http://dx.doi.org/10.1093/oso/9780198820116.001.0001.

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What is the impact of war on non-combatants, particularly women and children? In this innovative analysis of nutritional deprivation among ordinary German citizens during the First World War, Mary Elisabeth Cox finds that the effects of the war and the Allied interdiction of food supplies—which became known in Germany as the ‘Hungerblockade’—resulted in diminished heights and weights of children far from the battlefield. During the war, Germany defiantly proclaimed that their country could not be starved out. In a military sense, this was likely to be the case, and many modern historians argue persuasively that Germany lost on the battlefield. Yet modern analyses of height and weight records for hundreds of thousands of school children reveal a grim truth: even if Germany did not lose the war because of food insecurity, the war blockade resulted in hunger for millions of German infants. Desperately struggling to feed their families under the growing spectre of starvation, many mothers chose to sacrifice their own well-being for the benefit of their families. National and local policies within Germany often exasperated food insecurity. Modern analysis of anthropometric data now brings into question both long-held assumptions about the divide between rural and urban health, and legal and moral arguments in support of the blockade. Combined with contemporary letters, diaries, and news reports, these data provide an expanded picture of the levels of health and nutritional deprivation across society. This story of one of the most vicious wars in history is not devoid of compassion. Following the eventual lifting of the British blockade, the victorious powers and nations throughout the world sent millions of tons of food into Germany, relief which is mirrored in drawings and letters of gratitude from hundreds of German school children, and which can be seen as a surge of growth in height and weight measurements.
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31

Jue, Melody, and Rafico Ruiz, eds. Saturation. Duke University Press, 2021. http://dx.doi.org/10.1215/9781478013044.

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Bringing together media studies and environmental humanities, the contributors to Saturation develop saturation as a heuristic to analyze phenomena in which the elements involved are difficult or impossible to separate. In ordinary language, saturation describes the condition of being thoroughly soaked, while in chemistry it is the threshold at which something can be maximally dissolved or absorbed in a solution. Contributors to this collection expand notions of saturation beyond water to consider saturation in sound, infrastructure, media, Big Data, capitalism, and visual culture. Essays include analyses of the thresholds of HIV detectability in bloodwork, militarism's saturation of oceans, and the deleterious effects of the saturation of cellphone and wi-fi signals into the human body. By channeling saturation to explore the relationship between media, the environment, technology, capital, and the legacies of settler colonialism, Saturation illuminates how elements, the natural world, and anthropogenic infrastructures, politics, and processes exist in and through each other. Contributors. Marija Cetinić, Jeff Diamanti, Bishnupriya Ghosh, Lisa Yin Han, Stefan Helmreich, Mél Hogan, Melody Jue, Rahul Mukherjee, Max Ritts, Rafico Ruiz, Bhaskar Sarkar, John Shiga, Avery Slater, Janet Walker, Joanna Zylinska
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32

Skocpol, Theda, and Caroline Tervo, eds. Upending American Politics. Oxford University Press, 2020. http://dx.doi.org/10.1093/oso/9780190083526.001.0001.

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Analysts and citizens alike struggle to comprehend recent gyrations in US politics. The country did an apparent U-turn in just eight short years, from the election of Barack Obama and an all-Democratic Congress in 2008 to the election of Donald Trump and confirmation of GOP control of Congress in 2016. Twice in under a decade, ordinary citizens reacted by organizing local grassroots groups all over the country—with Tea Parties starting in 2009 and anti-Trump resistance groups starting in late 2016. Upending American Politics offers a fresh perspective on these developments by focusing on recent and newly changing organizational configurations, such as voluntary local citizens’ groups, elite advocacy organizations, consortia of wealthy donors, and candidate-led political campaigns. Contributors have collected many new kinds of data to document and probe changing organizational configurations at the national level and in the pivotal states of Wisconsin, North Carolina, Michigan, Florida, Texas, and Pennsylvania. The volume offers insightful answers to key questions: Why has partisan polarization unfolded in a heavily rightward-tilted manner that sees Republicans embracing ever-more extreme positions? Why have widespread grassroots citizens movements erupted twice just eight years, and what impact have these movements had on the major political parties?
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33

Vargas Cervantes, Susana. The Little Old Lady Killer. NYU Press, 2019. http://dx.doi.org/10.18574/nyu/9781479876488.001.0001.

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The Little Old Lady Killer focuses on the female serial killer Juana Barraza Samperio, a Mexican lucha libre wrestler who, disguised as a government nurse, strangled sixteen elderly women in Mexico City. The search for the Mataviejitas (the killer of old women) was the first ever undertaken for a serial killer in Mexico. Following international profiling norms for serial killers, the police were initially looking for an ordinary-looking man, but after witness accounts described the Mataviejitas as wearing a wig and makeup, police changed their focus and began to search for a “travesti.” The book undertakes an analysis of the classed, gendered, and sexed transitions described in police reports and media accounts in relation to international criminological discourses and Mexican popular culture. On January 26, 2006, Juana Barraza was arrested as she fled the home of an elderly woman who had just been strangled with a stethoscope. Two years later, Barraza was convicted and sentenced to 759 years and 17 days; she remains in Santa Martha Acatitla to this day. I argue that La Dama del Silencio, Barraza’s masked wrestling identity, more than the woman herself became figured in official and popular discourse as the serial killer, La Mataviejitas. This displacement of personas reinforces national imaginaries of masculinity, femininity, and criminality. The national imaginaries of what constitutes a criminal female or male, in turn, determine crucial notions of mexicanidad within the country’s pigmentocratic culture, who counts as a victim, and how a criminal is constructed.
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