vlm_app(
launch.browser = TRUE
)\[ \newcommand{\vy}{\mathbf{y}} \newcommand{\vx}{\mathbf{x}} \newcommand{\vb}{\mathbf{b}} \newcommand{\ve}{\mathbf{e}} \newcommand{\vone}{\mathbf{1}} \newcommand{\vbeta}{\boldsymbol{\beta}} \newcommand{\vmu}{\boldsymbol{\mu}} \newcommand{\mX}{\mathbf{X}} \newcommand{\mZ}{\mathbf{Z}} \newcommand{\mV}{\mathbf{V}} \newcommand{\mI}{\mathbf{I}} \newcommand{\mJ}{\mathbf{J}} \newcommand{\mSigma}{\boldsymbol{\Sigma}} \newcommand{\vg}{\mathbf{g}} \newcommand{\vc}{\mathbf{c}} \newcommand{\vz}{\mathbf{z}} \newcommand{\vlambda}{\boldsymbol{\lambda}} \newcommand{\mA}{\mathbf{A}} \newcommand{\mB}{\mathbf{B}} \newcommand{\mK}{\mathbf{K}} \newcommand{\mD}{\mathbf{D}} \newcommand{\mL}{\mathbf{L}} \newcommand{\mQ}{\mathbf{Q}} \newcommand{\vu}{\mathbf{u}} \newcommand{\vr}{\mathbf{r}} \newcommand{\vl}{\mathbf{l}} \newcommand{\vk}{\mathbf{k}} \newcommand{\vtheta}{\boldsymbol{\theta}} \newcommand{\mG}{\mathbf{G}} \newcommand{\mR}{\mathbf{R}} \newcommand{\mP}{\mathbf{P}} \newcommand{\mC}{\mathbf{C}} \newcommand{\mH}{\mathbf{H}} \newcommand{\mW}{\mathbf{W}} \newcommand{\mPhi}{\boldsymbol{\Phi}} \newcommand{\E}{\mathrm{E}} \newcommand{\Var}{\mathrm{Var}} \newcommand{\Cov}{\mathrm{Cov}} \newcommand{\tr}{\operatorname{tr}} \]
1 Abstract
vlm_app() opens a point-and-click application in the web browser. It needs the packages shiny, bslib and DT. Every example of the book loads with one click, and every result comes with a plain-language interpretation, the printed output, tables to copy or download, plots and the R code that repeats the analysis.
2 Pages
- Data: the ten data sets of the book or a CSV file.
- Model: fixed effects, random variance components, random coefficients per subject, a residual structure, estimation method, denominator degrees of freedom and test type. Load an example of the book fills every field for one of the 17 analyses of the book.
- Means: least-squares means and their differences with Tukey, Bonferroni or Sidak adjustment.
-
Estimates: estimates and contrasts typed as in SAS, one per line, for example
Samorin mean: intercept 1 Drug 0 1 dose 0.5 0.5 Drug:dose 0 0 0.5 0.5. - Random effects: best linear unbiased predictions.
- Expected mean squares: the analysis of variance of PROC GLM with a RANDOM statement.
- Compare: independent, compound symmetry, AR(1) and random coefficient structures for the fixed effects of the Model page.
3 Deployment
vlm_app_object() returns the application object, for example for a file app.R on a server: library(VetResearchLMM); vlm_app_object().