R: Predicted Means for Linear and Semiparametric Models

# Predicted Means for Linear and Semiparametric Models

## Documentation for package ‘predictmeans’ version 1.1.1

- DESCRIPTION file

## Help Pages

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