,
Andrea Spoto [aut],
Giulio Vidotto [aut],
Marcello Gallucci [aut]| Title: | Code and Obtain Customized Planned Comparisons with 'appRiori' |
|---|---|
| Description: | With 'appRiori' <doi:10.1177/25152459241293110>, users upload the research variables and the app guides them to the best set of comparisons fitting the hypotheses, for both main and interaction effects. Through a graphical explanation and empirical examples on reproducible data, it is shown that it is possible to understand both the logic behind the planned comparisons and the way to interpret them when a model is tested. |
| Authors: | Umberto Granziol [aut, cre],
Maximilian Rabe [aut] ,
Andrea Spoto [aut],
Giulio Vidotto [aut],
Marcello Gallucci [aut] |
| Maintainer: | Umberto Granziol <umberto.granziol@unipd.it> |
| License: | GPL (>= 3) |
| Version: | 0.0.6 |
| Built: | 2025-02-27 09:26:43 UTC |
| Source: | https://github.com/ugranziol/appriori |
This function runs the appRiori Shiny app.
appRiori(...)appRiori(...)
... |
Arguments passed on to |
No return value, called for side effects
## Not run: # Run the app with default settings library(appRiori) appRiori() ## End(Not run)## Not run: # Run the app with default settings library(appRiori) appRiori() ## End(Not run)
Extract the estimates and the inferential tests for a contrasts
defined by hypr
contrasts_summary(model, ...) ## Default S3 method: contrasts_summary(model, ...) ## S3 method for class 'merMod' contrasts_summary(model, ...) ## S3 method for class 'glmerMod' contrasts_summary(model, ...)contrasts_summary(model, ...) ## Default S3 method: contrasts_summary(model, ...) ## S3 method for class 'merMod' contrasts_summary(model, ...) ## S3 method for class 'glmerMod' contrasts_summary(model, ...)
model |
|
... |
additional options (not used at the moment) |
A results table of class hypr_contrasts_results.
library(MASS) df<-MASS::anorexia df$Treat = factor(df$Treat) library ( hypr ) h <- hypr ( ~ 1/2 * CBT + 1/2 * FT - Cont , ~ CBT - FT , levels = c( "CBT" , "Cont" , "FT" )) contrasts(df$Treat,how.many=2)<-cmat(h) model = lm ( Prewt ~ Treat , data = df ) contrasts_summary ( model )library(MASS) df<-MASS::anorexia df$Treat = factor(df$Treat) library ( hypr ) h <- hypr ( ~ 1/2 * CBT + 1/2 * FT - Cont , ~ CBT - FT , levels = c( "CBT" , "Cont" , "FT" )) contrasts(df$Treat,how.many=2)<-cmat(h) model = lm ( Prewt ~ Treat , data = df ) contrasts_summary ( model )
Pretty print the estimates and the inferential tests for a contrasts
defined by hypr
## S3 method for class 'hypr_contrasts_results' print(x, ...)## S3 method for class 'hypr_contrasts_results' print(x, ...)
x |
an object of class |
... |
additional options (not used at the moment) |
A results table