GAMLj Suite for Linear Models

General, Mixed, Generalized, and Generalized Mixed Models

Version 3.6.0

Estimates a General Linear Model, Mixed Linear Models, Generalized Linear Models and Generalized Mixed Models with categorical and/or continuous variables, with options to facilitate estimation of interactions, simple slopes, simple effects, post-hoc etc.

Continuous and categorical independent and dependent variables F-test and parameter estimates
Confidence intervals Moderation made easy
Simple slopes analysis Simple effects
Polynomial effects Post-hoc analysis
Contrasts analysis Plots up to three-way interactions
Automatic selection of best estimation methods and degrees of freedom selection Type III estimation

# Docs

More information can be found at GAMLj page

# Install in jamovi

Please install jamovi and run it. Select the jamovi modules library and install GAMLj from there

Version 3

GAMLj has undergone a major upgrading with version 3.*. The upgrading made version 3 not compatible with previous versions of the module, meaning
that analyses that are done with previous versions cannot be opened with version 3. If you need to open and work with analyses done with GAMLj version < 3.0.0, you can install GAMLj legacy from the jamovi library. It will not interfere with GAMLj3.

From GitHub

In your R script (or Rstudio) simply issue


devtools::install_github("gamlj/gamlj")

From source

You will first need to download jamovi.

You can clone this repository and compile the module within R with

library(jmvtools)
jmvtools::install()

Previous Version (GAMLj 2.6.6 or below)

If you want to install the latest previous version of the module (Version 2.6.6) in R, run this:

devtools::install_github("gamlj/gamlj",ref="Version.2.6.6")

Programmatic name

paste(paste(LETTERS[c(7,1,13,12)],collapse =""),paste(letters[10]),sep="")
<center>
<img width="300" src="https://gamlj.github.io/commons/pics/ui.png" class="img-responsive" alt="">
</center>
<br>
Estimates a General Linear Model, Mixed Linear Models, Generalized Linear Models and Generalized Mixed Models with categorial and/or continuous variables, with options to facilitate estimation of interactions, simple slopes, simple effects, post-hoc etc.
* Continuous and categorical independent and dependent variables
* F-test and parameter estimates
* Confidence intervals
* Moderation made easy
* Simple slopes analysis
* Simple effects
* Polynomial effects
* post-hoc analysis
* Plots up to three-way interactions
* Automatic selection of best estimation methods and degrees of freedom selection
* Type III estimation
More informations can be found at [GAMLj page](https://gamlj.github.io/)
# Install in jamovi
Please install [jamovi](https://www.jamovi.org/download.html) and run it. Select the jamovi modules library and install GAMLj from there
<center>
<img width="600" src="https://gamlj.github.io/glm/install.png" class="img-responsive" alt="">
</center>
# Version 3
GAMLj has undergone a major upgrading with version 3.*. The upgrading made version 3 not compatible with previous versions of the module, meaning
that analyses that are done with previous versions cannot be opened with version 3. If you need to open and work with analyses done with GAMLj version < 3.0.0, you can install GAMLj legacy from the jamovi library. It will not interfere with GAMLj3.
## From GitHub
In your R script (or Rstudio) simply issue

devtools::install_github(“gamlj/gamlj”)


## From source
You will first need to download [jamovi](https://www.jamovi.org/download.html). 
You can clone this repository and compile the module within R with

library(jmvtools)

jmvtools::install()


# Previous Version (GAMLj 2.6.6 or below)
If you want to install the latest previous version of the module (Version 2.6.6) in R, run this:

devtools::install_github(“gamlj/gamlj”,ref=”Version.2.6.6”)


# Programmatic name

paste(paste(LETTERS[c(7,1,13,12)],collapse =””),paste(letters[10]),sep=””)

Estimates a General Linear Model, Mixed Linear Models, Generalized Linear Models and Generalized Mixed Models with categorial and/or continuous variables, with options to facilitate estimation of interactions, simple slopes, simple effects, post-hoc etc.

Continuous and categorical independent and dependent variables F-test and parameter estimates
Confidence intervals Moderation made easy
Simple slopes analysis Simple effects
Polynomial effects post-hoc analysis
Plots up to three-way interactions Automatic selection of best estimation methods and degrees of freedom selection
* Type III estimation

More informations can be found at GAMLj page

# Install in jamovi

Please install jamovi and run it. Select the jamovi modules library and install GAMLj from there