mixed() fits mixed models using lme4::lmer() and computes p-values for all fixed effects using either Kenward-Roger or Satterthwaite approximation for degrees of freedom (LMM only), parametric bootstrap (LMMs and GLMMs), or likelihood ratio tests (LMMs and GLMMs). aov_ez(), aov_car(), and aov_4() allow specification of between, within (i.e., repeated-measures), or mixed (i.e., split-plot) ANOVAs for data in long format (i.e., one observation per row), automatically aggregating multiple observations per individual and cell of the design. (See the vignette AER for a package overview.) / GPL-2 | GPL-3Ĭonvenience functions for analyzing factorial experiments using ANOVA or mixed models. MIT file LICENSEĪnderson-Darling GoF test with p-value calculation based on Marsaglia’s 2004 paper Evaluating the Anderson-Darling Distribution / GPLįunctions, data sets, examples, demos, and vignettes for the book Christian Kleiber and Achim Zeileis (2008), Applied Econometrics with R, Springer-Verlag, New York. A good introduction to these two methods is in chapter 16 of Frank Harrel’s Regression Modeling Strategies in the Springer Series in Statistics.
Also included is the Additivity Variance Stabilization (AVAS) method which works better than ACE when correlation is low. it finds a set of transformed response variables that maximizes R^2 using smoothing functions. The first, Alternative Conditional Expectations (ACE), is an algorithm to find the fixed point of maximal correlation, i.e. Two nonparametric methods for multiple regression transform selection are provided.
Also provides functions ‘adrop’, ‘asub’, and ‘afill’ for manipulating, extracting and replacing data in arrays. Works with vectors, matrices, and higher-dimensional arrays.
This is a generalization of ‘cbind’ and ‘rbind’. Linux-32, linux-64, osx-64, win-32, win-64Ĭombine multidimensional arrays into a single array. A B C D E F G H I J K L M N O P Q R S T U V W X Y Z Misc ¶ NameĪ mutex package to ensure environment exclusivity between Anaconda R and MRO.
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