Analysis of Ordinal Categorical Data: Agresti/Analysis

By Alan Agresti. 2010

996 citations recorded by the source corpus.

View Paper: https://www.semanticscholar.org/paper/fd771c520fa9cf5739be81ec3926925fb4c40e27

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In Artificial Intelligence

Citations in the corpus

Survival rates and causes of mortality of leopards Panthera pardus in southern Africa (2014, methodology): “We used cumulative link mixed models with a logit link function and a multinomial error to investigate the effect of conservation status, age and sex on the cause of leopard mortality (Agresti, 2010).”
Don't Distract Me When I'm Media Multitasking: Toward a Theory for Raising Advertising Recall and Recognition (2016, methodology): “…to one or more characteristics (i.e., representing clustered and therefore dependent data with respect to student status, age, and gender), we apply a multilevel modeling approach commonly referred to as mixed-effects or hierarchical modeling (Agresti 2010; Rabe-Hesketh and Skrondal 2012).”
The wisdom of the crowd in funding: information heterogeneity and social networks of crowdfunders (2018, methodology): “Finally, as our dependent variable is of ordinal nature, we conducted ordered logistic regressions to determine the explanatory power of our independent variables (Agresti 2010; Hair 2010).”
Some Paradoxical Results for the Quadratically Weighted Kappa (2012, methodology): “Alternatively, one can use loglinear models for modeling agreement (Tanner & Young, 1985; Agresti 1988, 2010).”
The study, evaluation, and improvement of university student self-efficacy (2016, methodology): “…methods for undertaking numerical and graphical summaries, correlation, regression, factor analysis, etc. with ordinal data are given in recent and comprehensive texts (e.g. de Vaus 2002; Agresti 2007, 2010, 2012; Bartholomew et al. 2008; Stevens 2009; Bartholomew, Knott, and Moustaki 2011).”
Modelling Uncertainty and Overdispersion in Ordinal Data (2014, methodology): “Standard techniques model these data by using a continuous latent response distribution, which is partially observed through windows of adjacent intervals defined by cutpoints (McCullagh and Nelder, 1989; Agresti, 2010).”
Ordinal regression: A review and a taxonomy of models (2021, methodology): “The distinct limitations of the use of ordinary least squares approaches to modeling ordinal responses have been outlined, for example, by Agresti (2010).”
Connecting religion and work: Patterns and influences of work-faith integration (2011, methodology): “Since the dependent variable and several independent variables were measured on an ordinal (Likert) rather than interval scale, we used ordinal logistic regression to test most relationships (Agresti, 2010).”