Package: predictmeans 1.1.1

predictmeans: Predicted Means for Linear and Semiparametric Models

Providing functions to diagnose and make inferences from various linear models, such as those obtained from 'aov', 'lm', 'glm', 'gls', 'lme', 'lmer', 'glmmTMB' and 'semireg'. Inferences include predicted means and standard errors, contrasts, multiple comparisons, permutation tests, adjusted R-square and graphs.

Authors:Dongwen Luo, Siva Ganesh and John Koolaard

predictmeans_1.1.1.tar.gz
predictmeans_1.1.1.zip(r-4.5)predictmeans_1.1.1.zip(r-4.4)predictmeans_1.1.1.zip(r-4.3)
predictmeans_1.1.1.tgz(r-4.4-any)predictmeans_1.1.1.tgz(r-4.3-any)
predictmeans_1.1.1.tar.gz(r-4.5-noble)predictmeans_1.1.1.tar.gz(r-4.4-noble)
predictmeans_1.1.1.tgz(r-4.4-emscripten)predictmeans_1.1.1.tgz(r-4.3-emscripten)
predictmeans.pdf |predictmeans.html✨
predictmeans/json (API)

# Install 'predictmeans' in R:

install.packages('predictmeans', repos = c('https://dongwenluo.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/dongwenluo/predictmeans/issues

Datasets:

ATP - 'ATP' containing data
Clinical - 'Clinical' data
Drug - 'Drug' data

On CRAN:

20 exports 3.09 score 102 dependencies 2 dependents 14 mentions 151 scripts 1.4k downloads

Last updated 5 months agofrom:f9d9d03e6e. Checks:OK: 1 NOTE: 6. Indexed: yes.

Target	Result	Date
Doc / Vignettes	OK	Sep 08 2024
R-4.5-win	NOTE	Sep 08 2024
R-4.5-linux	NOTE	Sep 08 2024
R-4.4-win	NOTE	Sep 08 2024
R-4.4-mac	NOTE	Sep 08 2024
R-4.3-win	NOTE	Sep 08 2024
R-4.3-mac	NOTE	Sep 08 2024

Exports:ci_mcp contrastmeans CookD covariatemeans df_term Kmatrix permanova.lmer permindex permlmer permmodels PMplot predictmeans R2_glmm residplot se_ranef semipred semireg semireg_tmb smZ varcomp

Dependencies:abind askpass backports base64enc boot broom bslib cachem car carData cli colorspace cowplot cpp11 crosstalk curl data.table Deriv digest doBy dplyr evaluate fansi farver fastmap fontawesome fs generics ggplot2 glmmTMB glue gtable highr HRW htmltools htmlwidgets httr isoband jquerylib jsonlite KernSmooth knitr labeling later lattice lazyeval lifecycle lme4 lmeInfo lmerTest lmeSplines magrittr MASS Matrix MatrixModels memoise mgcv microbenchmark mime minqa modelr munsell nlme nloptr nnet numDeriv openssl pbkrtest pillar pkgconfig plotly plyr promises purrr quantreg R6 rappdirs RColorBrewer Rcpp RcppArmadillo RcppEigen rlang rmarkdown sass scales SparseM splines2 stringi stringr survival sys tibble tidyr tidyselect tinytex TMB utf8 vctrs viridisLite withr xfun yaml

Citation

Development and contributors

Readme and manuals

Help Manual

Help page	Topics
Predicted Means for Linear and Semiparametric Models	predictmeans-package
'ATP' containing data	ATP
Multiple Comparisons Based on the Confidence Intervals	ci_mcp
'Clinical' data	Clinical
Linear Contrast Tests for a Linear Model	contrastmeans
Calculates and plots Cook's distances for a Linear (Mixed) Model	CookD
Predicted Means of a Linear Model with Covariate Variable(s)	covariatemeans
Calculate degree of freedom of a modelterm (contrast) for a lmer model	df_term
'Drug' data	Drug
Matrix of Coefficients in a Linear Model	Kmatrix
Permutation ANOVA for 'lmer' Model	permanova.lmer
Permutation Index	permindex
Permutation Test of random or fixed effects for 'lmer' model.	permlmer
Permutation Test of Linear Model	permmodels
Level Plot of a Matrix of p-values.	PMplot
Predicted Means of a Linear Model	predictmeans
An adjusted coefficient of determination (R2) for generalized linear mixed models	R2_glmm
Diagnostic Plots for a Linear (Mixed) Model	residplot
Extract Standard Errors of Model Random Effects	se_ranef
Predicted Means of a Semi Paramatric Model with Covariate Variable(s)	semipred
Fitting Semi Parametric Models Using lme4 Ecosystem	semireg
Fitting Semi Parametric Models Using glmmTMB	semireg_tmb
Generate Sparse Matrix Z for penalized spline smoothing	smZ
Calculate SE and CI of variance components for 'lmer', 'glmer', 'lme', 'glmmTMB' model	varcomp