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jamovi Resources
Getting Started
Import Data & Types
Modules & R Code
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Correlations
General, Mixed and Generalized Models
OLS Regression
Non-Linear Regression
Interaction-Moderation
Indirect and Mediation Effects
ANOVA
Linear Mix Models
Logistic Regression
Statistical Power
EFA and PCA
Analytic Resources
Home
Foundational Concepts
Critical Thinking
AI and Gen AI
Analytics Overview
Data and Data Collection
Variables Types
Data Management
Descriptive Statistics
MCT
Variability
Visualizing Data
Hypothesis Testing
CLT
Confidence Intervals
Issues with NHST
Inferential Errors and Power
Effect Size
Missing Data
Correlations and Regression
Correlations
Linear Regression
Relative Importance Analysis
Non-Linear Regression
Interaction-Moderation
Indirect-Mediation
Maximum Likelihood Estimation
Generalized Linear Models
Logistic Regression
ROC, Sensitive, and Specificity
ANOVA
Between Groups ANOVA
Within Subjects ANOVA
Mixed Model ANOVA
ANCOVA
EFA and PCA
Linear Mixed Model
Cross Validation
R Resources
Getting Started in R and RStudio
Directories, Scripts, and Code
Packages and Libraries
SWIRL- Get Started
Dataframes and Types of Data
Importing Data
Generative AI and R
Getting to Know Your Data
Numeric Summaries
Descriptive Visuals
Pie Chart
Bar Chart
Histogram
Box Plot
Automated Exploration
Data Wrangling
Adding Labels
Renaming Variables
Missing Data
Data Recodes
Row Functions
Concatenate
Lag Functions
Reshaping Data
Subsetting
Group Functions
Merging Data
Dates and Times
Duplicate and Unique Cases
Missing Data
Correlations
OLS Regression
Non-Linear Regression
Interactions and Moderation
Indirect and Mediation Effects
PROCESS packages
ANOVA
Statistical Power
Dimension Reduction
Relative Importance Analysis
GZLM
Logistic Regression
Linear Mix Models
Cross Validation
jamovi Resources
Getting Started
Import Data & Types
Modules & R Code
Wrangling Data
Data Exploration
Correlations
General, Mixed and Generalized Models
OLS Regression
Non-Linear Regression
Interaction-Moderation
Indirect and Mediation Effects
ANOVA
Linear Mix Models
Logistic Regression
Statistical Power
EFA and PCA
More
Home
Foundational Concepts
Critical Thinking
AI and Gen AI
Analytics Overview
Data and Data Collection
Variables Types
Data Management
Descriptive Statistics
MCT
Variability
Visualizing Data
Hypothesis Testing
CLT
Confidence Intervals
Issues with NHST
Inferential Errors and Power
Effect Size
Missing Data
Correlations and Regression
Correlations
Linear Regression
Relative Importance Analysis
Non-Linear Regression
Interaction-Moderation
Indirect-Mediation
Maximum Likelihood Estimation
Generalized Linear Models
Logistic Regression
ROC, Sensitive, and Specificity
ANOVA
Between Groups ANOVA
Within Subjects ANOVA
Mixed Model ANOVA
ANCOVA
EFA and PCA
Linear Mixed Model
Cross Validation
R Resources
Getting Started in R and RStudio
Directories, Scripts, and Code
Packages and Libraries
SWIRL- Get Started
Dataframes and Types of Data
Importing Data
Generative AI and R
Getting to Know Your Data
Numeric Summaries
Descriptive Visuals
Pie Chart
Bar Chart
Histogram
Box Plot
Automated Exploration
Data Wrangling
Adding Labels
Renaming Variables
Missing Data
Data Recodes
Row Functions
Concatenate
Lag Functions
Reshaping Data
Subsetting
Group Functions
Merging Data
Dates and Times
Duplicate and Unique Cases
Missing Data
Correlations
OLS Regression
Non-Linear Regression
Interactions and Moderation
Indirect and Mediation Effects
PROCESS packages
ANOVA
Statistical Power
Dimension Reduction
Relative Importance Analysis
GZLM
Logistic Regression
Linear Mix Models
Cross Validation
jamovi Resources
Getting Started
Import Data & Types
Modules & R Code
Wrangling Data
Data Exploration
Correlations
General, Mixed and Generalized Models
OLS Regression
Non-Linear Regression
Interaction-Moderation
Indirect and Mediation Effects
ANOVA
Linear Mix Models
Logistic Regression
Statistical Power
EFA and PCA
General, Mixed, and Generalized Models
Marcello Gallucci & Jonathon Love
Introducing GAMLj: GLM, LME and GZLMs in jamovi
Marcello Gallucci
A brand new GAMLj
General Analyses for the Linear Model in Jamovi
General Linear Model
Chapter
2.2
:
Simple
Regression with the GLM
Chapter 2.3: Multiple Regression with the GLM
Chapter 2.
15
:
Assumptions checks
Chapter 2.16 Violations Remedies
Details: GLM effect size indices
GAMLj in R
Multiple regression, moderated regression, and simple slopes
Marcello Gallucci
GAMLj
Moderated Regression
Chapter 2.
4
:
Continuous IVs and interaction
Chapter 2.
5
:
Moderation=interaction
Chapter 2.
6
:
Simple Slopes
Chapter 2.16 Violations Remedies
Analysis of Variance (Categorical IVs)
Marcello Gallucci
Chapter 2.
7
:
Categorical IVs
Chapter 2.
8
:
Post-hoc tests
Chapter 2.
9
:
Cohen’s d
Chapter 2.
10
:
Estimated marginal means
Chapter 2.15: Assumptions checks
Chapter 2.16 Violations Remedies
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