Academic literature on the topic 'Categorical Factor'

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Journal articles on the topic "Categorical Factor"

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SHIGEMASU, Kazuo. "FACTOR ANALYSIS OF CATEGORICAL DATA: RECENT DEVELOPMENTS." Kodo Keiryogaku (The Japanese Journal of Behaviormetrics) 18, no. 1 (1990): 41–51. http://dx.doi.org/10.2333/jbhmk.18.41.

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Zhang, Zhiyong, and John R. Nesselroade. "Bayesian Estimation of Categorical Dynamic Factor Models." Multivariate Behavioral Research 42, no. 4 (2007): 729–56. http://dx.doi.org/10.1080/00273170701715998.

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Lee, Tze-San. "The Bayes Factor for the Misclassified Categorical Data." International Journal of Statistics and Probability 7, no. 4 (2018): 91. http://dx.doi.org/10.5539/ijsp.v7n4p91.

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This article addresses the issue of misclassification in a single categorical variable, that is, how to test whether the collected categorical data are misclassified. To tackle this issue, a pair of null and alternative hypotheses is proposed. A mixed Bayesian approach is taken to test these hypotheses. Specifically, a bias-adjusted cell proportion estimator is presented that accounts for the bias caused by classification errors in the observed categorical data. The chi-square test is then adjusted accordingly. To test the null hypothesis that the data are not misclassified under a specified m
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Bhattacharya, Anirban, and David B. Dunson. "Simplex Factor Models for Multivariate Unordered Categorical Data." Journal of the American Statistical Association 107, no. 497 (2012): 362–77. http://dx.doi.org/10.1080/01621459.2011.646934.

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Abascal, Elena, Vidal Díaz de Rada, Ignacio García Lautre, and M. Isabel Landaluce. "Extending dual multiple factor analysis to categorical tables." Journal of Applied Statistics 40, no. 2 (2013): 415–28. http://dx.doi.org/10.1080/02664763.2012.745836.

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Ferrando, Pere J., and Urbano Lorenzo-Seva. "Assessing the Quality and Appropriateness of Factor Solutions and Factor Score Estimates in Exploratory Item Factor Analysis." Educational and Psychological Measurement 78, no. 5 (2017): 762–80. http://dx.doi.org/10.1177/0013164417719308.

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This article proposes a comprehensive approach for assessing the quality and appropriateness of exploratory factor analysis solutions intended for item calibration and individual scoring. Three groups of properties are assessed: (a) strength and replicability of the factorial solution, (b) determinacy and accuracy of the individual score estimates, and (c) closeness to unidimensionality in the case of multidimensional solutions. Within each group, indices are considered for two types of factor-analytic models: the linear model for continuous responses and the categorical-variable-methodology m
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Mislevy, Robert J. "Recent Developments in the Factor Analysis of Categorical Variables." Journal of Educational Statistics 11, no. 1 (1986): 3–31. http://dx.doi.org/10.3102/10769986011001003.

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Despite known shortcomings of the procedure, exploratory factor analysis of dichotomous test items has been limited, until recently, to unweighted analyses of matrices of tetrachoric correlations. Superior methods have begun to appear in the literature, in professional symposia, and in computer programs. This paper places these developments in a unified framework, from a review of the classical common factor model for measured variables through generalized least squares and marginal maximum likelihood solutions for dichotomous data. Further extensions of the model are also reported as work in
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Mislevy, Robert J. "Recent Developments in the Factor Analysis of Categorical Variables." Journal of Educational Statistics 11, no. 1 (1986): 3. http://dx.doi.org/10.2307/1164846.

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Mislevy, Robert J. "RECENT DEVELOPMENTS IN THE FACTOR ANALYSIS OF CATEGORICAL VARIABLES." ETS Research Report Series 1985, no. 1 (1985): i—67. http://dx.doi.org/10.1002/j.2330-8516.1985.tb00109.x.

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Dellaportas, Petros, and Claudia Tarantola. "Model determination for categorical data with factor level merging." Journal of the Royal Statistical Society: Series B (Statistical Methodology) 67, no. 2 (2005): 269–83. http://dx.doi.org/10.1111/j.1467-9868.2005.00501.x.

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Dissertations / Theses on the topic "Categorical Factor"

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Cho, Seung Bin. "Decomposing individual and group differences of categorical variables with genetic factor model." Diss., Columbia, Mo. : University of Missouri-Columbia, 2007. http://hdl.handle.net/10355/4926.

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Thesis (M.A.)--University of Missouri-Columbia, 2007.<br>The entire dissertation/thesis text is included in the research.pdf file; the official abstract appears in the short.pdf file (which also appears in the research.pdf); a non-technical general description, or public abstract, appears in the public.pdf file. Title from title screen of research.pdf file (viewed on January 3, 2008) Includes bibliographical references.
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Farouni, Tarek. "Latent Variable Models of Categorical Responses in the Bayesian and Frequentist Frameworks." The Ohio State University, 2014. http://rave.ohiolink.edu/etdc/view?acc_num=osu1412374136.

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Clark, Jonathan Caleb. "Evaluating Model Fit for Longitudinal Measurement Invariance with Ordered Categorical Indicators." BYU ScholarsArchive, 2020. https://scholarsarchive.byu.edu/etd/8725.

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Current recommended cutoffs for determining measurement invariance have typically derived from simulation studies that have focused on multigroup confirmatory factor analysis, often using continuous data. These cutoffs may be inappropriate for ordered categorical data in a longitudinal setting. This study conducts two Monte Carlo studies that evaluate the performance of four popular model fit indices used to determine measurement invariance. The comparative fit index (CFI), Tucker-Lewis Index (TLI), and root mean square error of approximation (RMSEA) were all found to be inconsistent across va
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Guo, Ling. ""Clustering categorical response" application to lung cancer problems in living scales." unrestricted, 2008. http://etd.gsu.edu/theses/available/etd-04202008-163156/.

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Thesis (M.S.)--Georgia State University, 2008.<br>Title from file title page. Jiawei Liu, Yu-sheng Hsu, committee co-chairs; Jeff Qin, committee member. Electronic text (82 p. : ill. (some col.)) : digital, PDF file. Description based on contents viewed Aug. 20, 2008. Includes bibliographical references (p. 65-66).
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Ethington, Corinna A. "The robustness of LISREL estimates in structural equation models with categorical data." Diss., Virginia Polytechnic Institute and State University, 1985. http://hdl.handle.net/10919/54504.

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This study was an examination of the effect of type of correlation matrix on the robustness of LISREL maximum likelihood and unweighted least squares structural parameter estimates for models with categorical manifest variables. Two types of correlation matrices were analyzed; one containing Pearson product-moment correlations and one containing tetrachoric, polyserial, and product-moment correlations as appropriate. Using continuous variables generated according to the equations defining the population model, three cases were considered by dichotomizing some of the variables with varying degr
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Chantarat, Navara. "Modern design of experiments methods for screening and experimentations with mixture and qualitative variables." Columbus, OH : Ohio State University, 2003. http://rave.ohiolink.edu/etdc/view?acc%5Fnum=osu1064198056.

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Thesis (Ph. D.)--Ohio State University, 2003.<br>Title from first page of PDF file. Document formatted into pages; contains xiv, 119 p.: ill. (some col.). Includes abstract and vita. Advisor: Theodore T. Allen, Dept. of Industrial and Systems Engineering. Includes bibliographical references (p. 111-119).
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Allen, Holly Lee. "Factor Structure of the Jordan Performance Appraisal System: A Multilevel Multigroup Study Using Categorical and Count Data." BYU ScholarsArchive, 2020. https://scholarsarchive.byu.edu/etd/8726.

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Development of the Jordan Performance Appraisal System (JPAS) was completed in 1996. This study examined the factor structure of the classroom observation instrument used in the JPAS. Using observed classroom instructional quality ratings of 1220 elementary teachers of Grades 1-6 in the Jordan School District, this study estimated the factor structure of the data and the rater effect on relevant structural parameters. This study also tested for measurement invariance at the within and between levels across teachers of two grade-level groups (a) lower grades: Grades 1-3 and (b) upper grades: Gr
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Olson, Brent. "Evaluating the error of measurement due to categorical scaling with a measurement invariance approach to confirmatory factor analysis." Thesis, University of British Columbia, 2008. http://hdl.handle.net/2429/332.

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It has previously been determined that using 3 or 4 points on a categorized response scale will fail to produce a continuous distribution of scores. However, there is no evidence, thus far, revealing the number of scale points that may indeed possess an approximate or sufficiently continuous distribution. This study provides the evidence to suggest the level of categorization in discrete scales that makes them directly comparable to continuous scales in terms of their measurement properties. To do this, we first introduced a novel procedure for simulating discretely scaled data that was both i
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Coughlin, Kevin Barry. "An Analysis of Factor Extraction Strategies: A Comparison of the Relative Strengths of Principal Axis, Ordinary Least Squares, and Maximum Likelihood in Research Contexts that Include both Categorical and Continuous Variables." Scholar Commons, 2013. http://scholarcommons.usf.edu/etd/4459.

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This study is intended to provide researchers with empirically derived guidelines for conducting factor analytic studies in research contexts that include dichotomous and continuous levels of measurement. This study is based on the hypotheses that ordinary least squares (OLS) factor analysis will yield more accurate parameter estimates than maximum likelihood (ML) and principal axis factor anlaysis (PAF); the level of improvement in estimates will be related to the proportion of observed variables that are dichotomized and the strength of communalities within the data sets. To achieve this st
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Russell, Justin. "The Structure of Child and Adolescent Aggression: Confirmatory Factor Analysis of a Brief Peer Conflict Scale." ScholarWorks@UNO, 2014. http://scholarworks.uno.edu/td/1892.

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The importance of simultaneous consideration of forms and functions in youth measures of aggressive behavior is well established. Competing models have presented these highly interrelated constructs as either independent (e.g., reactive or overt) or paired factors (e.g., reactive and overt). The current study examines these models in the context of assessing the viability of a new self-report measure, the Peer Conflict Scale – 20 Item Version. Confirmatory factor analyses were conducted on PCS 20 responses from 1,048 school-age youth living in the Gulf Coast region. Both models significantly i
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Books on the topic "Categorical Factor"

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Mullins-Sweatt, Stephanie, Douglas B. Samuel, and Ashley Helle. Clinical Utility of the Five Factor Model. Edited by Thomas A. Widiger. Oxford University Press, 2016. http://dx.doi.org/10.1093/oxfordhb/9780199352487.013.7.

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The purpose of this chapter is to discuss the clinical utility of the Five Factor Model (FFM). This chapter will consider the clinical application of the FFM for treatment in general, but its primary focus will be on the clinical utility of an FFM of personality disorders. Discussed herein will be the three fundamental components of clinical utility: ease of usage, communication, and treatment planning. Empirical research concerning the clinical utility of the FFM also will be considered in terms of the three components. Finally, research and examination of clincians’ perspectives of the utilt
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Bollen, Kenneth A., Sophia Rabe‐Hesketh, and Anders Skrondal. Structural Equation Models. Edited by Janet M. Box-Steffensmeier, Henry E. Brady, and David Collier. Oxford University Press, 2009. http://dx.doi.org/10.1093/oxfordhb/9780199286546.003.0018.

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This article explains the use of factor analysis types of models to develop measures of latent concepts which were then combined with causal models of the underlying latent concepts. In particular, it offers an overview of the classic structural equation models (SEMs) when the latent and observed variables are continuous. Then it looks at more recent developments that include categorical, count, and other noncontinuous variables as well as multilevel structural equation models. The model specification, assumptions, and notation are covered. This is followed by addressing implied moments, ident
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Jonas, Silvia. Modal Structuralism and Theism. Oxford University Press, 2017. http://dx.doi.org/10.1093/oso/9780198796732.003.0009.

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Drawing an analogy between modal structuralism about mathematics and theism, this chapter offers a structuralist account that implicitly defines theism in terms of three basic relations: logical and metaphysical priority, and epistemic superiority. On this view, statements like “God is omniscient” have a hypothetical and a categorical component. The hypothetical component provides a translation pattern according to which statements in theistic language are converted into statements of second-order modal logic. The categorical component asserts the logical possibility of the theism structure on
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Hoste, Eric A. J., John A. Kellum, and Norbert Lameire. Definitions, classification, epidemiology, and risk factors of acute kidney injury. Edited by Norbert Lameire. Oxford University Press, 2018. http://dx.doi.org/10.1093/med/9780199592548.003.0220_update_001.

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The lack of a precise biochemical definition of acute kidney injury (AKI) resulted in at least 35 definitions in the medical literature, which gave rise to a wide variation in reported incidence and clinical significance of AKI, impeded a meaningful comparison of studies.The first part of this chapter describes and discusses different definitions and classification systems of AKI. Patient outcome and the need for renal replacement therapy are directly related to the severity of AKI, an observation that supports the use of a categorical staging system rather than a simple binary descriptor. The
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Cockett, J. R. B., and R. A. G. Seely. Proof Theory of the Cut Rule. Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780198748991.003.0010.

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This chapter describes the categorical proof theory of the cut rule, a very basic component of any sequent-style presentation of a logic, assuming a minimum of structural rules and connectives, in fact, starting with none. It is shown how logical features can be added to this basic logic in a modular fashion, at each stage showing the appropriate corresponding categorical semantics of the proof theory, starting with multicategories, and moving to linearly distributive categories and *-autonomous categories. A key tool is the use of graphical representations of proofs (“proof circuits”) to repr
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Eklund, Matti. Concluding Remarks. Oxford University Press, 2017. http://dx.doi.org/10.1093/oso/9780198717829.003.0011.

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In this book it has been argued that the ardent realist’s best shot is to hold that normative role can determine reference. But it has not been claimed either that normative role in fact can determine reference, or that ardent realism is in fact vindicated if it is so. No categorical claims about the fate of ardent realism have been defended. In fact, various arguments have aimed to cast doubt on natural suggestions regarding how to settle the question of whether ardent realism is in fact true. In this chapter, it is suggested that a certain kind of principled agnosticism may be the right resp
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Van Dam, Nicholas T., Brian M. Iacoviello, and James W. Murrough. Diagnosis and Epidemiology of Depression. Edited by Dennis S. Charney, Eric J. Nestler, Pamela Sklar, and Joseph D. Buxbaum. Oxford University Press, 2017. http://dx.doi.org/10.1093/med/9780190681425.003.0023.

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Depressive disorders are among the most disabling medical illnesses worldwide and limited efficacy of currently available medication and psychotherapy treatments adds to this large public health burden. In the current chapter, we consider findings from several large-scale health surveys to estimate the burden of illness, and review the current data available regarding prognosis, psychiatric and medical comorbidities, and socio-demographic factors influencing the prevalence and course of depression. We also consider emerging alternative methods of conceptualizing depression and other mental dis
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Kishida, Kohei. Categories and Modalities. Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780198748991.003.0009.

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Category theory provides various guiding principles for modal logic and its semantic modeling. In particular, Stone duality, or “syntax-semantics duality”, has been a prominent theme in semantics of modal logic since the early days of modern modal logic. This chapter focuses on duality and a few other categorical principles, and brings to light how they underlie a variety of concepts, constructions, and facts in philosophical applications as well as the model theory of modal logic. In the first half of the chapter, I review the syntax-semantics duality and illustrate some of its functions in K
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Mithun, Marianne. Argument Marking in the Polysynthetic Verb and Its Implications. Edited by Michael Fortescue, Marianne Mithun, and Nicholas Evans. Oxford University Press, 2017. http://dx.doi.org/10.1093/oxfordhb/9780199683208.013.4.

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It is generally agreed that the essence of polysynthesis goes beyond sheer numbers of morphemes per word, but which other properties might be criterial is unclear. Most frequently cited is the marking of core arguments within the verb, such that the key elements of the clause, predicate, and arguments, are contained within that one word. Also often cited are noun incorporation, applicatives, rich inventories of adverbial affixes, and pragmatically motivated word order. But argument marking on the verb is not categorical: pronominal affix paradigms show a range of differential marking patterns
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Cleary, Paul, Sam Ghebrehewet, and David Baxter. Essential statistics and epidemiology. Oxford University Press, 2016. http://dx.doi.org/10.1093/med/9780198745471.003.0022.

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This chapter provides a grounding in basic statistics, descriptive epidemiology, analytical epidemiology, and hypothesis testing appropriate for health protection practitioners. The analysis of categorical data using frequency distributions, and charts, and the interpretation of epidemic curves is described. The description of quantitative data including central tendency, standard deviation, and interquartile range is concisely explained. The role of geographical information systems and different disease map types is used to demonstrate how disease clusters may be detected. Determining possibl
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Book chapters on the topic "Categorical Factor"

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Watkins, Marley W. "Exploratory Factor Analysis With Categorical Variables." In A Step-by-Step Guide to Exploratory Factor Analysis with SPSS. Routledge, 2021. http://dx.doi.org/10.4324/9781003149347-16.

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Watkins, Marley W. "Exploratory Factor Analysis with Categorical Variables." In A Step-By-Step Guide to Exploratory Factor Analysis with Stata. Routledge, 2021. http://dx.doi.org/10.4324/9781003149286-16.

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Holmes Finch, W., and Brian F. French. "Equivalence Testing for Factor Invariance Assessment with Categorical Indicators." In Springer Proceedings in Mathematics & Statistics. Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-01310-3_21.

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Arminger, Gerhard. "Dynamic Factor Models for the Analysis of Ordered Categorical Panel Data." In Lecture Notes in Statistics. Springer New York, 1999. http://dx.doi.org/10.1007/978-1-4612-1842-5_9.

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Quicke, Donald, Buntika A. Butcher, and Rachel Kruft Welton. "Analysis of variance (ANOVA)." In Practical R for biologists: an introduction. CABI, 2021. http://dx.doi.org/10.1079/9781789245349.0155.

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Abstract Analysis of variance is used to analyze the differences between group means in a sample, when the response variable is numeric (real numbers) and the explanatory variable(s) are all categorical. Each explanatory variable may have two or more factor levels, but if there is only one explanatory variable and it has only two factor levels, one should use Student's t-test and the result will be identical. Basically an ANOVA fits an intercept and slopes for one or more of the categorical explanatory variables. ANOVA is usually performed using the linear model function lm, or the more specific function aov, but there is a special function oneway.test when there is only a single explanatory variable. For a one-way ANOVA the non-parametric equivalent (if variance assumptions are not met) is the kruskal.test.
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Quicke, Donald, Buntika A. Butcher, and Rachel Kruft Welton. "Analysis of variance (ANOVA)." In Practical R for biologists: an introduction. CABI, 2021. http://dx.doi.org/10.1079/9781789245349.0013a.

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Abstract Analysis of variance is used to analyze the differences between group means in a sample, when the response variable is numeric (real numbers) and the explanatory variable(s) are all categorical. Each explanatory variable may have two or more factor levels, but if there is only one explanatory variable and it has only two factor levels, one should use Student's t-test and the result will be identical. Basically an ANOVA fits an intercept and slopes for one or more of the categorical explanatory variables. ANOVA is usually performed using the linear model function lm, or the more specific function aov, but there is a special function oneway.test when there is only a single explanatory variable. For a one-way ANOVA the non-parametric equivalent (if variance assumptions are not met) is the kruskal.test.
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McArdle, John J., and John R. Nesselroade. "Extensions to longitudinal categorial factors." In Longitudinal data analysis using structural equation models. American Psychological Association, 2014. http://dx.doi.org/10.1037/14440-021.

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Foster, Dean P., Robert A. Stine, and Richard P. Waterman. "Modeling Categorical Factors with Two Levels." In Business Analysis Using Regression. Springer New York, 1998. http://dx.doi.org/10.1007/978-1-4612-0683-5_6.

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Schiffner, Julia, Gero Szepannek, Thierry Monthé, and Claus Weihs. "Localized Logistic Regression for Categorical Influential Factors." In Advances in Data Analysis, Data Handling and Business Intelligence. Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-642-01044-6_17.

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Chang, Chia-Hui, and Zhi-Kai Ding. "Categorical Data Visualization and Clustering Using Subjective Factors." In Data Warehousing and Knowledge Discovery. Springer Berlin Heidelberg, 2004. http://dx.doi.org/10.1007/978-3-540-30076-2_23.

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Conference papers on the topic "Categorical Factor"

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Pita, Robespierre, Gabriela Borges, Nivea Bispo, Daniela Almeida, Rosemeire Fiaccone, and Marcos E. Barreto. "K-Fact: Using the Frequency Factor for Clustering Categorical Data." In 2019 8th Brazilian Conference on Intelligent Systems (BRACIS). IEEE, 2019. http://dx.doi.org/10.1109/bracis.2019.00113.

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Karduni, Alireza, Ryan Wesslen, Isaac Cho, and Wenwen Dou. "Du Bois Wrapped Bar Chart: Visualizing Categorical Data with Disproportionate Values." In CHI '20: CHI Conference on Human Factors in Computing Systems. ACM, 2020. http://dx.doi.org/10.1145/3313831.3376365.

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Hussain, Nasir. "Categorical Classification of Factors Effecting Knowledge Management in Software Crowdsourcing: Hypothetical Framework." In 14th International Conference on Evaluation of Novel Approaches to Software Engineering. SCITEPRESS - Science and Technology Publications, 2019. http://dx.doi.org/10.5220/0007811005780585.

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Forciniti, Carmen, Laura Eboli, Gabriella Mazzulla, and Francisco Calvo. "Exploring the Factors that Impact on Transit Use through an Ordered Probit Model: the Case of Metro of Madrid." In CIT2016. Congreso de Ingeniería del Transporte. Universitat Politècnica València, 2016. http://dx.doi.org/10.4995/cit2016.2016.3205.

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The configuration of urban areas is the result of a cyclic relationship between land use and transportation system: the changes in transportation system arrangements influence the localisation of residence and economic activities, as well as the changes in land use affect transportation system characteristics. In this context, by operating on land use, travel demand can be shift from the individual transportation modes to transit systems. In the literature, many conceptual models were proposed to describe the complex relationship between land use and travel behaviour. In addition to spatial va
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Sethi, Kapil, Ankit Gupta, and Varun Jaiswal. "Machine Learning Based Performance Evaluation System Based On Multi-Categorial Factors." In 2018 Fifth International Conference on Parallel, Distributed and Grid Computing (PDGC). IEEE, 2018. http://dx.doi.org/10.1109/pdgc.2018.8745781.

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Kerdprasop, Nittaya, Kittisak Kerdprasop, and Paradee Chuaybamroong. "Categorical Modeling Method to Analyze Factors Relating to Longevity of Populations in the East and Southeast Asia." In AICCC 2019: 2019 2nd Artificial Intelligence and Cloud Computing Conference. ACM, 2019. http://dx.doi.org/10.1145/3375959.3375972.

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Avşar, Alkım Z., and Paul T. Grogan. "Effects of Locus of Control Personality Trait on Team Performance in Cooperative Engineering Design Tasks." In ASME 2020 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. American Society of Mechanical Engineers, 2020. http://dx.doi.org/10.1115/detc2020-22641.

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Abstract Teams in engineering design tackle problems that exceed the abilities of individuals. Improved understanding of how personality traits influence human behaviors and interaction may help create new methods and tools to support design teams. This paper seeks to understand how the Locus of Control (LOC) personality trait influences designer behaviors and team performance. A designer experiment studies 12 participant pairs controlled for categorical LOC pairing factors (internal-internal, external-external, and internal-external). Each design team completes six simplified cooperative para
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Hu, Liang, Songlei Jian, Longbing Cao, and Qingkui Chen. "Interpretable Recommendation via Attraction Modeling: Learning Multilevel Attractiveness over Multimodal Movie Contents." In Twenty-Seventh International Joint Conference on Artificial Intelligence {IJCAI-18}. International Joint Conferences on Artificial Intelligence Organization, 2018. http://dx.doi.org/10.24963/ijcai.2018/472.

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New contents like blogs and online videos are produced in every second in the new media age. We argue that attraction is one of the decisive factors for user selection of new contents. However, collaborative filtering cannot work without user feedback; and the existing content-based recommender systems are ineligible to capture and interpret the attractive points on new contents. Accordingly, we propose attraction modeling to learn and interpret user attractiveness. Specially, we build a multilevel attraction model (MLAM) over the content features -- the story (textual data) and cast members (
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Zhao, Sicheng, Guiguang Ding, Yue Gao, and Jungong Han. "Approximating Discrete Probability Distribution of Image Emotions by Multi-Modal Features Fusion." In Twenty-Sixth International Joint Conference on Artificial Intelligence. International Joint Conferences on Artificial Intelligence Organization, 2017. http://dx.doi.org/10.24963/ijcai.2017/651.

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Existing works on image emotion recognition mainly assigned the dominant emotion category or average dimension values to an image based on the assumption that viewers can reach a consensus on the emotion of images. However, the image emotions perceived by viewers are subjective by nature and highly related to the personal and situational factors. On the other hand, image emotions can be conveyed by different features, such as semantics and aesthetics. In this paper, we propose a novel machine learning approach that formulates the categorical image emotions as a discrete probability distributio
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Huang, Chao, Chuxu Zhang, Peng Dai, and Liefeng Bo. "Cross-Interaction Hierarchical Attention Networks for Urban Anomaly Prediction." In Twenty-Ninth International Joint Conference on Artificial Intelligence and Seventeenth Pacific Rim International Conference on Artificial Intelligence {IJCAI-PRICAI-20}. International Joint Conferences on Artificial Intelligence Organization, 2020. http://dx.doi.org/10.24963/ijcai.2020/601.

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Abstract:
Predicting anomalies (e.g., blocked driveway and vehicle collisions) in urban space plays an important role in assisting governments and communities for building smart city applications, ranging from intelligent transportation to public safety. However, predicting urban anomalies is not trivial due to the following two factors: i) The sequential transition regularities of anomaly occurrences is complex, which exhibit with high-order and dynamic correlations. ii) The Interactions between region, time and anomaly category is multi-dimensional in real-world urban anomaly forecasting scenario. How
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