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@Misc{ordinal-pkg,
title = {ordinal---Regression Models for Ordinal Data },
author = {R. H. B. Christensen},
year = {2018},
note = {R package version 2018.8-25},
url = {http://www.cran.r-project.org/package=ordinal/},
}
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author = {Alexandra Kuznetsova and Per Brockhoff and Rune Christensen},
title = {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}
}
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}
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address = {Cary, NC},
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url = {https://support.sas.com/documentation/cdl/en/statugestimable/61763/PDF/default/statugestimable.pdf},
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@Manual{SAS,
title = {\proglang{SAS/STAT} \textregistered 9.22 User's Guide},
author = {\proglang{SAS} Institute Inc.},
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address = {Cary, NC},
year = {2010},
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title = {ucminf: General-Purpose Unconstrained Non-Linear Optimization},
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url = {https://CRAN.R-project.org/package=ucminf},
}
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author = {William H Greene and David A Hensher},
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}
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author = "Williams, R.",
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}
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author="Rabe-Hesketh, Sophia
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day="01",
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number="2",
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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{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 = {2018},
url = {https://www.R-project.org/},
}
@Article{brms,
title = {{brms}: An {R} Package for {Bayesian} Multilevel Models Using {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 = {rms: Regression Modeling Strategies},
author = {Frank E {Harrell Jr}},
year = {2018},
note = {R package version 5.1-2},
url = {https://CRAN.R-project.org/package=rms},
}
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author = {William N. Venables and Brian D. Ripley},
title = {Modern Applied Statistics with \proglang{S}},
edition = {4th},
year = {2002},
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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},
}
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