LMMstar.options: Global options for LMMstar package

View source: R/LMMstar.options.R

LMMstar.optionsR Documentation

Global options for LMMstar package


Update or select global options for the LMMstar package.


LMMstar.options(..., reinitialise = FALSE)



options to be selected or updated


should all the global parameters be set to their default value


The options are:

  • backtransform.confint [logical]: should variance/covariance/correlation estimates be back-transformed when they are transformed on the log or atanh scale. Used by confint.

  • columns.anova [character vector]: columns to ouput when using anova with argument ci=TRUE.

  • columns.confint [character vector]: columns to ouput when using confint.

  • columns.summary [character vector]: columns to ouput when displaying the model coefficients using summary.

  • df [logical]: should approximate degrees of freedom be computed for Wald and F-tests. Used by lmm, anova, predict, and confint.

  • drop.X [logical]: should columns causing non-identifiability of the model coefficients be dropped from the design matrix. Used by lmm.

  • effects [character]: parameters relative to which estimates, score, information should be output.

  • min.df [integer]: minimum possible degree of freedom. Used by confint.

  • method.fit [character]: objective function when fitting the Linear Mixed Model (REML or ML). Used by lmm.

  • method.numDeriv [character]: type used to approximate the third derivative of the log-likelihood (when computing the degrees of freedom). Can be "simple" or "Richardson". See numDeriv::jacobian for more details. Used by lmm.

  • n.sampleCopula [integer]: number of samples used to compute confidence intervals and p-values adjusted for multiple comparisons via "single-step2". Used by confint.Wald_lmm.

  • optimizer [character]: method used to estimate the model parameters: can the nlme::gls ("gls") or an algorithm combine fisher scoring for the variance parameters and generalized least squares for the mean parameters ("FS").

  • param.optimizer [numeric vector]: default option for the FS optimization routine: maximum number of gradient descent iterations (n.iter), maximum acceptable score value (tol.score), maximum acceptable change in parameter value (tol.param).

  • precompute.moments [logical]: Should the cross terms between the residuals and design matrix be pre-computed. Useful when the number of subject is substantially larger than the number of mean paramters.

  • trace [logical]: Should the progress of the execution of the lmm function be displayed?

  • tranform.sigma, tranform.k, tranform.rho: transformation used to compute the confidence intervals/p-values for the variance and correlation parameters. See the detail section of the coef function for more information. Used by lmm, anova and confint.

  • type.information [character]: Should the expected or observed information ("expected" or "observed") be used to perform statistical inference? Used by lmm, anova and confint.


A list containing the default options.

LMMstar documentation built on Jan. 7, 2023, 1:20 a.m.