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ANOVA

April Member Training: Statistical Contrasts

by TAF Support


Statistical contrasts are a tool for testing specific hypotheses and model effects, particularly comparing specific group means.

[Read more…] about April Member Training: Statistical Contrasts

Tagged With: ANOVA, General Linear Model, group comparisons, statistical contrasts

Related Posts

  • Member Training: Hierarchical Regressions
  • The General Linear Model, Analysis of Covariance, and How ANOVA and Linear Regression Really are the Same Model Wearing Different Clothes
  • March Member Training: Goodness of Fit Statistics
  • Member Training: The Anatomy of an ANOVA Table

What are Sums of Squares?

by Jeff Meyer Leave a Comment

A key part of the output in any linear model is the ANOVA table. It has many names in different software procedures, but every regression or ANOVA model has a table with Sums of Squares, degrees of freedom, mean squares, and F tests. Many of us were trained to skip over this table, but

[Read more…] about What are Sums of Squares?

Tagged With: ANOVA, linear regression, sum of squares

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  • Why ANOVA is Really a Linear Regression, Despite the Difference in Notation
  • Member Training: Using Excel to Graph Predicted Values from Regression Models
  • 7 Practical Guidelines for Accurate Statistical Model Building

When Unequal Sample Sizes Are and Are NOT a Problem in ANOVA

by Karen Grace-Martin 219 Comments

Updated Dec 18, 2020 to add more detail

In your statistics class, your professor made a big deal about unequal sample sizes in one-way Analysis of Variance (ANOVA) for two reasons.

1. Because she was making you calculate everything by hand.  Sums of squares require a different formula* if sample sizes are unequal, but statistical software will automatically use the right formula. So we’re not too concerned. We’re definitely using software.

2. Nice properties in ANOVA such as the Grand Mean being the intercept in an effect-coded regression model don’t hold when data are unbalanced.  Instead of the grand mean, you need to use a weighted mean.  That’s not a big deal if you’re aware of it. [Read more…] about When Unequal Sample Sizes Are and Are NOT a Problem in ANOVA

Tagged With: analysis of variance, ANOVA, SPSS, Unequal sample sizes

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  • Same Statistical Models, Different (and Confusing) Output Terms
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Same Statistical Models, Different (and Confusing) Output Terms

by Jeff Meyer Leave a Comment

Learning how to analyze data can be frustrating at times. Why do statistical software companies have to add to our confusion?

I do not have a good answer to that question. What I will do is show examples. In upcoming blog posts, I will explain what each output means and how they are used in a model.

We will focus on ANOVA and linear regression models using SPSS and Stata software. As you will see, the biggest differences are not across software, but across procedures in the same software.

[Read more…] about Same Statistical Models, Different (and Confusing) Output Terms

Tagged With: ANOVA, between groups, categorical predictor, linear regression, oneway, residuals, software, SPSS, SPSS output, Stata, Stata output, Statistical Software, within groups

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Member Training: The Anatomy of an ANOVA Table

by Jeff Meyer

Our analysis of linear regression focuses on parameter estimates, z-scores, p-values and confidence levels. Rarely in regression do we see a discussion of the estimates and F statistics given in the ANOVA table above the coefficients and p-values.

And yet, they tell you a lot about your model and your data. Understanding the parts of the table and what they tell you is important for anyone running any regression or ANOVA model.

[Read more…] about Member Training: The Anatomy of an ANOVA Table

Tagged With: ANOVA, estimate, estimation, F test, R-squared, residuals, sum of squares, tables, types

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Member Training: Elements of Experimental Design

by Karen Grace-Martin

Whether or not you run experiments, there are elements of experimental design that affect how you need to analyze many types of studies.

The most fundamental of these are replication, randomization, and blocking. These key design elements come up in studies under all sorts of names: trials, replicates, multi-level nesting, repeated measures. Any data set that requires mixed or multilevel models has some of these design elements. [Read more…] about Member Training: Elements of Experimental Design

Tagged With: ANOVA, blocking, Crossed factors, Crossover Design, Latin squares, multilevel model, nested models, Regression, Repeated Measures, replication

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  • Member Training: Interactions in ANOVA and Regression Models, Part 2

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