Online Workshops
The Craft of Statistical Analysis Free Webinars
- Interpreting Linear Regression Coefficients: A Walk Through Output
- Four Critical Steps in Building Linear Regression Models
Statistically Speaking Member Trainings
- Multicollinearity
- Hierarchical Regressions
- Using Excel to Graph Predicted Values from Regression Models
- ANCOVA (Analysis of Covariance)
- Dummy and Effect Coding
- Transformations & Nonlinear Effects in Linear Models
- The Multi-Faceted World of Residuals
- Using Transformations to Improve Your Linear Regression Model
- Marginal Means, Your New Best Friend
- Segmented Regression
- Quantile Regression: Going Beyond the Mean
Articles at The Analysis Factor
- Should I Specify a Model Predictor as Categorical or Continuous?
- What Is Specification Error in Statistical Models?
- Steps to Take When Your Regression (or Other Statistical) Results Just Look…Wrong
- Understanding Interactions Between Categorical and Continuous Variables in Linear Regression
- The Distribution of Independent Variables in Regression Models
- Differences in Model Building Between Explanatory and Predictive Models
- Why ANOVA is Really a Linear Regression, Despite the Difference in Notation
- The Impact of Removing the Constant from a Regression Model: The Categorical Case
- When to leave insignificant effects in a model
- Model Building Strategies: Step Up and Top Down
- Five Common Relationships Among Three Variables in a Statistical Model
- Can a Regression Model with a Small R-squared Be Useful?
- Confusing Statistical Terms #5: Covariate
- Making Dummy Codes Easy to Keep Track of
- 3 Situations when it makes sense to Categorize a Continuous Predictor in a Regression Model
- Likert Scale Items as Predictor Variables in Regression
- Why ANOVA and Linear Regression are the Same Analysis
- Assessing the Fit of Regression Models
- Understanding Interaction Between Dummy Coded Categorical Variables in Linear Regression
Stata
- Incorporating Graphs in Regression Diagnostics with Stata
- Linear Regression in Stata: Missing Data and the Stories it Might Tell
- Using the Same Sample for Different Models in Stata
- Hierarchical Regression in Stata: An Easy Method to Compare Model Results
R
- Linear Models in R: Diagnosing Our Regression Model
- Linear Models in R: Plotting Regression Lines
- R Is Not So Hard! A Tutorial, Part 5: Fitting an Exponential Model
- R Is Not So Hard! A Tutorial, Part 4: Fitting a Quadratic Model
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