@Misc{ordinal-pkg,
    title = {\pkg{ordinal}---Regression Models for Ordinal Data },
    author = {R. H. B. Christensen},
    year = {2019},
    note = {\proglang{R} package version 2019.12-10},
    url = {http://www.cran.r-project.org/package=ordinal/},
}

  @Manual{emmeans,
    title = {\pkg{emmeans}: Estimated Marginal Means, aka Least-Squares Means},
    author = {Russell Lenth},
    year = {2020},
    note = {R package version 1.4.6},
    url = {https://CRAN.R-project.org/package=emmeans},
  }
  
    @Manual{margins,
    title = {\pkg{margins}: Marginal Effects for Model Objects},
    author = {Thomas J. Leeper},
    year = {2018},
    note = {R package version 0.3.23},
  }

  @Article{ggeffects,
    title = {\pkg{ggeffects}: Tidy Data Frames of Marginal Effects from Regression Models.},
    volume = {3},
    doi = {10.21105/joss.00772},
    number = {26},
    journal = {Journal of Open Source Software},
    author = {Daniel Lüdecke},
    year = {2018},
    pages = {772},
  }

@Article{effects1,
    title = {Visualizing Fit and Lack of Fit in Complex Regression Models with Predictor Effect Plots and Partial Residuals},
    author = {John Fox and Sanford Weisberg},
    journal = {Journal of Statistical Software},
    year = {2018},
    volume = {87},
    number = {9},
    pages = {1--27},
    doi = {10.18637/jss.v087.i09},
    url = {https://www.jstatsoft.org/v087/i09},
  }

@Article{effects2,
    title = {Effect Displays in \proglang{R} for Multinomial and Proportional-Odds Logit Models: Extensions to the \pkg{effects} Package},
    author = {John Fox and Jangman Hong},
    journal = {Journal of Statistical Software},
    year = {2009},
    volume = {32},
    number = {1},
    pages = {1--24},
    url = {http://www.jstatsoft.org/v32/i01/},
  }  

  @Manual{generalhoslem,
    title = {\pkg{generalhoslem}: Goodness of Fit Tests for Logistic Regression Models},
    author = {Matthew Jay},
    year = {2019},
    note = {R package version 1.3.4},
    url = {https://CRAN.R-project.org/package=generalhoslem},
  }

@article{ananth97,
    author = {Ananth, C V and Kleinbaum, D G},
    title = "{Regression Models for Ordinal Responses: A Review of Methods and Applications.}",
    journal = {International Journal of Epidemiology},
    volume = {26},
    number = {6},
    pages = {1323-1333},
    year = {1997},
    month = {12},
    issn = {0300-5771},
    doi = {10.1093/ije/26.6.1323},
    url = {https://doi.org/10.1093/ije/26.6.1323},
    eprint = {https://academic.oup.com/ije/article-pdf/26/6/1323/18477637/261323.pdf},
}

@Article{ordinalgmifs,
    title = {\pkg{ordinalgmifs}: An \proglang{R} Package for Ordinal Regression in
      High-dimensional Data Settings},
    author = {Kellie J. Archer and Jiayi Hou and Qing Zhou and Kyle
      Ferber and John G. Layne and Amanda Elswick Gentry},
    journal = {Cancer Informatics},
    year = {2014},
    volume = {13},
    pages = {187-195},
    url = {http://www.la-press.com/article.php?article_id=4569},
    doi = {10.4137/CIN.S20806}
  }

@Manual{oglmx,
    title = {\pkg{oglmx}: Estimation of Ordered Generalized Linear Models},
    author = {Nathan Carroll},
    year = {2018},
    note = {R package version 3.0.0.0},
    url = {https://CRAN.R-project.org/package=oglmx},
}  

@Article{mvord,
    title = {\pkg{mvord}: An \proglang{R} Package for Fitting Multivariate Ordinal
      Regression Models},
    author = {Rainer Hirk and Kurt Hornik and Laura Vana},
    journal = {Journal of Statistical Software},
    year = {2020},
    volume = {93},
    number = {4},
    pages = {1--41},
    doi = {10.18637/jss.v093.i04},
  }

 @Manual{CUB,
    title = {\pkg{CUB}: A Class of Mixture Models for Ordinal Data},
    author = {Maria Iannario and Domenico Piccolo and Rosaria Simone},
    year = {2020},
    note = {R package version 1.1.4},
    url = {https://CRAN.R-project.org/package=CUB},
  }
  
@Article{MCMCpack,
    title = {\pkg{MCMCpack}: Markov Chain Monte Carlo in \proglang{R}},
    author = {Andrew D. Martin and Kevin M. Quinn and Jong Hee Park},
    journal = {Journal of Statistical Software},
    year = {2011},
    volume = {42},
    number = {9},
    pages = {22},
    url = {http://www.jstatsoft.org/v42/i09/},
    doi = {10.18637/jss.v042.i09},
  }
  
@Article{decarlo98,
  author = 	 {Lawrence T DeCarlo},
  title = 	 {{Signal Detection Theory and Generalized Linear Models}},
  journal = 	 {Psychological Methods},
  year = 	 1998,
  volume = 	 3,
  number = 	 2,
  doi = {10.1037/1082-989X.3.2.186},
  pages = 	 {185-205}}
  
@Article{christensen11,
  author = 	 {Rune Haubo Bojesen Christensen and Graham Cleaver
                  and Per Bruun Brockhoff},
  title = 	 {{Statistical and Thurstonian Models for the A-not A
                  Protocol with and without Sureness}},
  journal = 	 {Food Quality and Preference},
  year = 	 2011,
  pages =        {542-549},
  volume =       {22},
  doi = {10.1016/j.foodqual.2011.03.003}}

@Book{macmillan05,
  author =	 {Neil A Macmillan and C Douglas Creelman},
  title = 	 {Detection Theory, A User's Guide},
  publisher = 	 {Lawrence Elbaum Associates, Publishers},
  year = 	 2005,
  edition =	 {2nd},
  ISBN = {978-0805842319}
}
  
@article{kuznetsova17,
   author = {Alexandra Kuznetsova and Per Brockhoff and Rune Christensen},
   title = {\pkg{lmerTest} Package: Tests in Linear Mixed Effects Models},
   journal = {Journal of Statistical Software, Articles},
   volume = {82},
   number = {13},
   year = {2017},
   keywords = {denominator degree of freedom, Satterthwaite's approximation, ANOVA, R, linear mixed effects models, lme4},
   abstract = {One of the frequent questions by users of the mixed model function lmer of the lme4 package has been: How can I get p values for the F and t tests for objects returned by lmer? The lmerTest package extends the 'lmerMod' class of the lme4 package, by overloading the anova and summary functions by providing p values for tests for fixed effects. We have implemented the Satterthwaite's method for approximating degrees of freedom for the t and F tests. We have also implemented the construction of Type I - III ANOVA tables. Furthermore, one may also obtain the summary as well as the anova table using the Kenward-Roger approximation for denominator degrees of freedom (based on the KRmodcomp function from the pbkrtest package). Some other convenient mixed model analysis tools such as a step method, that performs backward elimination of nonsignificant effects  -  both random and fixed, calculation of population means and multiple comparison tests together with plot facilities are provided by the package as well.},
   issn = {1548-7660},
   pages = {1--26},
   doi = {10.18637/jss.v082.i13},
   url = {https://www.jstatsoft.org/v082/i13}
}

@Article{cox95,
  author = 	 {Christopher Cox},
  title = 	 {Location-Scale Cumulative Odds Models for Ordinal
  Data: A Generalized Non-Linear Model Approach},
  journal = 	 {Statistics in Medicine},
  year = 	 1995,
  volume =	 14,
  doi = {10.1002/sim.4780141105},
  pages =	 {1191-1203},
}

@Book{elden04,
  author = 	 {Lars Eld\'en and Linde Wittmeyer-Koch and Hans Bruun
                  Nielsen},
  title = 	 {Introduction to Numerical Computation --- Analysis
                  and \proglang{MATLAB} Illustrations},
  publisher = 	 {Studentlitteratur},
  ISBN = {978-9144037271},
  year = 	 2004}

@Article{farewell77,
  author = 	 {Vernon T Farewell and R L Prentice},
  title = 	 {A Study of Distributional Shape in Life Testing},
  journal = 	 {{Technometrics}},
  year = 	 1977,
  volume = 	 19,
  doi = {10.2307/1268257},
  pages = 	 {69-77}}

@Article{genter85,
  author = 	 {Frederic C Genter and Vernon T Farewell},
  title = 	 {Goodness-of-Link Testing in Ordinal Regression
                  Models},
  journal = 	 {{The Canadian Journal of Statistics}},
  year = 	 1985,
  volume = 	 13,
  number = 	 1,
  doi = {10.2307/3315165},
  pages = 	 {37-44},
}

@Article{aranda-ordaz83,
  author = 	 {Francisco J Aranda-Ordaz},
  title = 	 {An Extension of the Proportional-Hazards Model for
                  Grouped Data},
  journal = 	 {Biometrics},
  year = 	 1983,
  volume = 	 39,
  doi = {10.2307/2530811},
  pages = 	 {109-117}}

@Article{peterson90,
  author = 	 {Bercedis Peterson and Frank E {Harrell Jr.}},
  title = 	 {Partial Proportional Odds Models for Ordinal
  Response Variables},
  journal = 	 {Applied Statistics},
  year = 	 1990,
  volume =	 39,
  doi = {10.2307/2347760},
  pages =	 {205-217}
}

@Article{peterson92,
  author = 	 {Bercedis Peterson and Frank E {Harrell Jr.}},
  title = 	 {Proportional Odds Model},
  journal = 	 {Biometrics},
  year = 	 1992,
  month =	 {March},
  note =	 {Letters to the Editor}
}


@Book{brazzale07,
  author =	 {A R Brazzale and A C Davison and N Reid},
  title = 	 {Applied Asymptotics---Case Studies in Small-Sample
  Statistics},
  ISBN = {9780521847032},
  publisher = 	 {Cambridge University Press},
  year = 	 2007}


@Book{pawitan01,
  author =	 {Yudi Pawitan},
  title = 	 {{In All Likelihood---Statistical Modelling and
  Inference Using Likelihood}},
  publisher = 	 {Oxford University Press},
  ISBN = {978-0198507659},
  year = 	 2001
}

@Article{efron78,
  author = 	 {Bradley Efron and David V Hinkley},
  title = 	 {{Assessing the Accuracy of the Maximum Likelihood
                  Estimator: Observed versus Expected Fisher Information}},
  journal = 	 {Biometrika},
  year = 	 1978,
  volume = 	 65,
  number = 	 3,
  doi = {10.1093/biomet/65.3.457},
  pages = 	 {457-487},
}

@article{burridge81,
 title = {A Note on Maximum Likelihood Estimation for Regression
              Models Using Grouped Data}, 
 author = {Burridge, J.},
 journal = {Journal of the Royal Statistical Society B}, 
 volume = {43},
 number = {1},
 pages = {41-45},
 ISSN = {00359246},
 language = {English},
 year = {1981},
 publisher = {Blackwell Publishing for the Royal Statistical Society},
}

@article{pratt81,
 title = {Concavity of the Log Likelihood},
 author = {Pratt, John W.},
 journal = {Journal of the American Statistical Association},
 volume = {76},
 number = {373},
 pages = {103-106},
 ISSN = {01621459},
 language = {English},
 year = {1981},
 doi = {10.2307/2287052},
}

@Book{agresti10,
  author = 	 {Alan Agresti},
  title = 	 {Analysis of Ordinal Categorical Data},
  publisher = 	 {John Wiley \& Sons},
  year = 	 2010,
  edition = 	 {2nd},
  doi = {10.1002/9780470594001}
}

@Book{agresti02,
  author =	 {Alan Agresti},
  title = 	 {Categorical Data Analysis},
  publisher = 	 {John Wiley \& Sons},
  year = 	 2002,
  edition =	 {3rd},
  ISBN = {978-0470463635},
}

@Article{mccullagh80,
  author = 	 {Peter McCullagh},
  title = 	 {Regression Models for Ordinal Data},
  journal = 	 {Journal of the Royal Statistical Society B},
  year = 	 1980,
  volume =	 42,
  pages =	 {109-142}
}

@Article{randall89,
  author = 	 {J.H. Randall},
  title = 	 {The Analysis of Sensory Data by Generalised Linear Model},
  journal = 	 {Biometrical journal},
  year = 	 1989,
  volume =	 7,
  pages =	 {781-793},
  doi = {10.1002/bimj.4710310703},
}

@phdthesis{mythesis,
title = "Sensometrics: Thurstonian and Statistical Models",
author = "Christensen, Rune Haubo Bojesen",
year = "2012",
publisher = "Technical University of Denmark (DTU)",
school = "Technical University of Denmark (DTU)",
url = "http://orbit.dtu.dk/files/12270008/phd271_Rune_Haubo_net.pdf"
}

@Manual{SAStype,
    title = {The Four Types of Estimable Functions -- \proglang{SAS/STAT} \textregistered 9.22 User's Guide},
    author = {\proglang{SAS} Institute Inc.},
    organization = {\proglang{SAS} Institute Inc.},
    address = {Cary, NC},
    year = {2008},
    url = {https://support.sas.com/documentation/cdl/en/statugestimable/61763/PDF/default/statugestimable.pdf},
}

@Manual{SAS,
  title = {\proglang{SAS/STAT} \textregistered 9.22 User's Guide},
  author = {\proglang{SAS} Institute Inc.},
  organization = {\proglang{SAS} Institute Inc.},
  address = {Cary, NC},
  year = {2010},
  url = {https://support.sas.com/documentation/},
}



@Manual{ucminf,
    title = {\pkg{ucminf}: General-Purpose Unconstrained Non-Linear Optimization},
    author = {Hans Bruun Nielsen and Stig Bousgaard Mortensen},
    year = {2016},
    note = {\proglang{R} package version 1.1-4},
    url = {https://CRAN.R-project.org/package=ucminf},
}

@Book{fahrmeir01,
  author =	 {Ludwig Fahrmeir and Gerhard Tutz},
  title = 	 {Multivariate Statistical Modelling Based on
  Generalized Linear Models},
  publisher = 	 {Springer-Verlag},
  year = 	 2001,
  series =	 {Springer series in statistics},
  edition =	 {2nd}
}

@Book{greene10,
  author = 	 {William H Greene and David A Hensher},
  title = 	 {Modeling Ordered Choices: A Primer},
  publisher = 	 {Cambridge University Press},
  year = 	 2010}

@Book{mccullagh89,
  author = {Peter McCullagh and John A. Nelder},
  title = {Generalized Linear Models},
  edition = {2nd},
  year = {1989},
  publisher = {Chapman \& Hall},
  address = {London},
  doi = {10.1007/978-1-4899-3242-6},
}

@Manual{Stata,
  title = {\proglang{Stata} 15 Base Reference Manual},
  author = {{StataCorp}},
	publisher = "\proglang{Stata} Press",
	address = "College Station, TX",
  year = {2017},
  url = {https://www.stata.com/},
}

@article{oglm,
	author = "Williams, R.",
	title = "Fitting Heterogeneous Choice Models with \pkg{oglm}",
	journal = "Stata Journal",
	publisher = "\proglang{Stata} Press",
	address = "College Station, TX",
	volume = "10",
	number = "4",
	year = "2010",
	pages = "540-567(28)",
	url = "http://www.stata-journal.com/article.html?article=st0208"
}

@Article{gllamm,
author="Rabe-Hesketh, Sophia
and Skrondal, Anders
and Pickles, Andrew",
title="Generalized Multilevel Structural Equation Modeling",
journal="Psychometrika",
year="2004",
month="Jun",
day="01",
volume="69",
number="2",
pages="167--190",
issn="1860-0980",
doi="10.1007/BF02295939",
url="https://doi.org/10.1007/BF02295939"
}

@Manual{SPSS,
  title = {\proglang{IBM SPSS} Statistics for Windows, Version 25.0},
  author = {{IBM Corp.}},
  organization = {IBM Corp.},
  address = {Armonk, NY},
  year = {2017},
}

@manual{Matlab,
  author = {\proglang{Matlab}},
  address = {Natick, Massachusetts},
  organization = {The Mathworks, Inc.},
  title = {{\proglang{Matlab} version 9.8 (R2020a)}},
  year = {2020}
}

@phdthesis{mord,
  author       = {Fabian Pedregosa-Izquierdo}, 
  title        = {Feature Extraction and Supervised Learning on fMRI: From Practice to Theory},
  school       = {Université Pierre et Marie Curie},
  year         = 2015,
  address      = {Paris VI},
  url          = {https://pythonhosted.org/mord/}
}

@Manual{R,
  title = {\proglang{R}: {A} Language and Environment for Statistical Computing},
  author = {{\proglang{R} Core Team}},
  organization = {\proglang{R} Foundation for Statistical Computing},
  address = {Vienna, Austria},
  year = {2020},
  url = {https://www.R-project.org/},
}

@Article{brms,
  title = {\pkg{brms}: An \proglang{R} Package for {Bayesian} Multilevel Models Using \pkg{Stan}},
  author = {Paul-Christian Bürkner},
  journal = {Journal of Statistical Software},
  year = {2017},
  volume = {80},
  number = {1},
  pages = {1--28},
  doi = {10.18637/jss.v080.i01},
  encoding = {UTF-8},
}

@Manual{rms,
    title = {\pkg{rms}: Regression Modeling Strategies},
    author = {Frank E {Harrell Jr}},
    year = {2018},
    note = {\proglang{R} package version 5.1-2},
    url = {https://CRAN.R-project.org/package=rms},
  }

@Book{MASS,
  author = {William N. Venables and Brian D. Ripley},
  title = {Modern Applied Statistics with \proglang{S}},
  edition = {4th},
  year = {2002},
  pages = {495},
  publisher = {Springer-Verlag},
  address = {New York},
  doi = {10.1007/978-0-387-21706-2},
}

@Article{VGAM,
  author = {Thomas W. Yee},
  title = {The \pkg{VGAM} Package for Categorical Data Analysis},
  journal = {Journal of Statistical Software},
  year = {2010},
  volume = {32},
  number = {10},
  pages = {1--34},
  doi = {10.18637/jss.v032.i10},
}

@Article{Zeileis+Kleiber+Jackman:2008,
  author = {Achim Zeileis and Christian Kleiber and Simon Jackman},
  title = {Regression Models for Count Data in \proglang{R}},
  journal = {Journal of Statistical Software},
  year = {2008},
  volume = {27},
  number = {8},
  pages = {1--25},
  doi = {10.18637/jss.v027.i08},
}