Library of Webinar Titles in Statistically Speaking
- A Gentle Introduction To Random Slopes In Multilevel Models
- Missing Data
- Preparing to Use (and Interpret) a Linear Regression Model
- Using Open Data in Research: Opportunities and Challenges
- Inference and p-values and Statistical Significance, Oh My!
- Explaining Logistic Regression Results to Non-Researchers
- A Guide to Latent Variable Models
- Data Cleaning
- Seven Fundamental Tests for Categorical Data
- Practical Suggestions for Improving Your Scatterplots
- Confusing Statistical Terms
- A Gentle Introduction to Multilevel Models
- The Anatomy of an ANOVA Table
- How to Avoid Some Common Graphical Mistakes
- Practical Advice for Establishing Reliability and Validity
- Reporting Structural Equation Modeling Results
- Interpretation of Effect Size Statistics
- Elements of Experimental Design
- Writing Up Statistical Results: Basic Concepts and Best Practices
- A Predictive Modeling Primer: Regression and Beyond
- Multiple Imputation for Missing Data
- Non-Parametric Analyses
- Determining Levels of Measurement: What Lies Beneath the Surface
- What’s the Best Statistical Package for You?
- Model Building Approaches
- Those Darn Ratios!
- Meta-analysis
- Latent Growth Curve Analysis
- Generalized Linear Models
- Power Analysis and Sample Size Determination Using Simulation
- Logistic Regression for Count and Proportion Data
- The Fundamentals of Sample Size Calculations
- Adjustments for Multiple Testing? When and How to Handle Multiplicity
- Tests of Equivalence and Non-Inferiority
- Using Transformations to Improve Your Linear Regression Model
- Marginal Means, Your New Best Friend
- A Primer on Exponents & Logarithms for the Data Analyst
- Model Fit Statistics in Structural Equation Modeling
- A Data Analyst’s Guide to Methods and Tools for Reproducible Research
- A Quick Introduction to Weighting in Complex Samples
- Quantile Regression: Going Beyond the Mean
- Making Sense of Statistical Distributions
- The Multi-Faceted World of Residuals
- Mediated Moderation and Moderated Mediation: What’s the Difference?
- Crossed and Nested Factors
- Segmented Regression
- Statistical Rules of Thumb
- Confirmatory Factor Analysis
- Communicating Statistical Results to Non-Statisticians
- A Gentle Introduction to Generalized Linear Mixed Models – Part 2
- The LASSO Regression Model
- A Gentle Introduction to Generalized Linear Mixed Models
- Cox Regression
- Small Sample Statistics
- Working with Truncated and Censored Data
- Zero Inflated Models
- Communicating Statistical Results: When to Use Tables vs Graphs to Tell the Data’s Story
- An Introduction to Kaplan-Meier Curves
- Inter-Rater Reliability
- (Just About) Everything You Need To Know Before Starting a Survey
- Analysis of Ordinal Variables — Options Beyond Nonparametrics
- A Gentle Introduction to Propensity Score Adjustments and Analysis
- Mixture Models in Longitudinal Data Analysis
- Correspondence Analysis
- Smoothing
- Latent Class Analysis
- An Overview of Effect Size Statistics and Why They Are So Important
- A Gentle Introduction to Bayesian Data Analysis
- Transformations and Nonlinear Effects in Linear Models
- Confidence Intervals
- Count Models
- Probability Rules and Applications
- ANCOVA (Analysis of Covariance)
- Introduction to Time Series Analysis
- Matrix Algebra for Data Analysts: A Primer
- ROC Curves
- Resampling Techniques
- Dummy and Effect Coding
- Classification and Regression Trees
- Multiple Comparisons
- Cluster Analysis: Hierarchical and KMeans
- Introduction to Structural Equation Modeling
- Multicollinearity
- Discrete Time Event History Analysis
- Interactions in ANOVA and Regression Models, Part 2
- Interactions in ANOVA and Regression Models
- Complex Survey Sampling — An Overview
- Mediation
- Outliers and Influential Points
- Item Response Theory and Rasch Models
- Measures of Association: Beyond Pearson’s Correlation
- MANOVA
- Using Excel to Graph Predicted Values from Regression Models
- Hierarchical Regressions
- Exploratory Factor Analysis
- Types of Regression Models and When to Use Them