Page Index - Private-Projects237/Statistics GitHub Wiki
139 page(s) in this GitHub Wiki:
- Home
- T-test
- Converting test statistics to effect sizes
- Regression
- Regression and Effect Size
- Logistic Regression
- Gamma Regression
- ANOVA
- Underlying Math
- Interpreting Outputs
- ANCOVA
- Effect Coding
- Estimated Marginal Means
- Plotting Main Effect and Estimated Marginal Means Follow-Up Tests (Asterisk Lines)
- Estimated Marginal Means of Linear Trends (Slopes)
- Mediation Analysis
- Meta-Analysis
- Path Analysis
- Linear Mixed Effects Models
- Quadratic Linear Mixed Effects Models
- Generalized Linear Mixed Effects Models
- Generalized Structural Equation Modeling (GSEM)
- Multivariate Mixed Effects Models
- Power Analyses
- Confirmatory Factor Analysis (CFA)
- Item Response Theory (ITR)
- Path Diagrams
- SEM
- Complex Models
- Categorical Exploratory Factor Analysis (EFA)
- Categorical Confirmatory Factory Analysis (CFA)
- ANCOVA Overview
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- Capturing Direct, Indirect, and Mediation Effects with Bayesian Statistics
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- Confirmatory Factor Analysis with Lavaan
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- Converting test statistics to Cohen's D
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- Converting test statistics to partial eta square from ANOVA
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- Converting test statistics to partial eta square from repeated measures ANOVA
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- Converting test statistics to partial eta squared and generalized eta squared
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- Effect Coding and Estimated Marginal Means in R
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- Effect Coding in R
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- Estimated Marginal Means from Custom Contrasts in R
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- Estimated Marginal Means in R
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- Estimated Marginal Means of Linear Trends in R
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- Estimating means and standard deviations
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- Exploring the Theta Estimate in the IRT model (2PL)
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- Extending the Linear Model with R: Chapter 2 Logistic Regression
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- Gamma Regression in R
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- Getting Started with Categorical Confirmation Factor Analysis
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- Getting Started with Categorical with Exploratory Factor Analysis (EFA) in Lavaan
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- GLMM Intro into Linear Mixed Effects Models
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- Graded Response Model (GRT)
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- GSEM for Path Analysis and Nested Logistic Regression
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- Hierarchical Categorical Confirmation Factor Analysis
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- Higher order factor model HolzingerSwineford1939
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- How to run a multi level meta analysis in R
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- Intermediate Path Analysis Examples in R
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- Interpreting the Outputs in a One‐Way Repeated Measures ANOVA
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- Intro into Generalized Linear Mixed Effects Models GLMM
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- Intro into Multivariate Mixed Models
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- Introduction into Heywood Cases and Consequences of Constraining
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- Introduction into Mediation Analysis
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- Introduction into Power Analysis for Linear Mixed‐Effects Models
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- Introduction into when to use Linear Mixed Effects Models
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- Introduction to Path Analysis Using Lavaan
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- Introduction to Power Analysis Using simr for Mixed Models
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- Invariant and Non‐Invariant categorical CFA
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- Linear Mixed Effects Models (Behavior Example)
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- Linear Mixed Effects Models (ERPs Example)
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- lme4: Mixed‐effects modeling in R
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- Logistic Regression Overview
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- Math Underlying a one‐way ANOVA
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- Math Underlying a one‐way repeated measures ANOVA
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- Math Underlying a two‐way ANOVA
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- Meta Analysis Fixed Effects vs Random Effects Models
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- Meta Analysis in R
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- Path Diagrams for some common types of statistical models
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- Plotting Asterisk Lines in Follow‐Up Tests
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- Quadratic Linear Mixed Effects Models
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- Regression and Effect Sizes
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- Regression Overview
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- Standard t‐test Overview
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- Testing for Moderation in a Meta Analysis
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- Testing the Capabilities of a Bayesian Generalized Non Linear Multivariate Multilevel Model in R
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- Two parameter IRT model (2PL)
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- Two parameter IRT model (2PL) with Missing Data
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