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logistic regression

Member Training: Multinomial Logistic Regression

by TAF Support  Leave a Comment

Multinomial logistic regression is an important type of categorical data analysis. Specifically, it’s used when your response variable is nominal: more than two categories and not ordered.
[Read more…] about Member Training: Multinomial Logistic Regression

Tagged With: categorical variable, logistic regression, Multinomial Logistic Regression

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  • Member Training: Explaining Logistic Regression Results to Non-Researchers

Guidelines for writing up three types of odds ratios

by Karen Grace-Martin  Leave a Comment

Odds ratios have a unique part to play in describing the effects of logistic regression models. But that doesn’t mean they’re easy to communicate to an audience who is likely to misinterpret them. So writing up your odds ratios has to be done with care. [Read more…] about Guidelines for writing up three types of odds ratios

Tagged With: binary predictor, logistic regression, multicategory predictor, numerical predictor, odds ratios

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Logistic Regression Analysis: Understanding Odds and Probability

by Karen Grace-Martin  3 Comments

Updated 11/22/2021

Probability and odds measure the same thing: the likelihood or propensity or possibility of a specific outcome.

People use the terms odds and probability interchangeably in casual usage, but that is unfortunate. It just creates confusion because they are not equivalent.

How Odds and Probability Differ

They measure the same thing on different scales. Imagine how confusing it would be if people used degrees Celsius and degrees Fahrenheit interchangeably. “It’s going to be 35 degrees today” could really make you dress the wrong way.

In measuring the likelihood of any outcome, we need to know [Read more…] about Logistic Regression Analysis: Understanding Odds and Probability

Tagged With: logistic regression, odds, odds ratio, probability

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Why Generalized Linear Models Have No Error Term

by Karen Grace-Martin  1 Comment

Even if you’ve never heard the term Generalized Linear Model, you may have run one. It’s a term for a family of models that includes logistic and Poisson regression, among others.

It’s a small leap to generalized linear models, if you already understand linear models. Many, many concepts are the same in both types of models.

But one thing that’s perplexing to many is why generalized linear models have no error term, like linear models do. [Read more…] about Why Generalized Linear Models Have No Error Term

Tagged With: error term, generalized linear model, generalized linear models, logistic regression, Poisson Regression

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Types of Study Designs in Health Research: The Evidence Hierarchy

by guest contributer  Leave a Comment

by Danielle Bodicoat

Statistics can tell us a lot about our data, but it’s also important to consider where the underlying data came from when interpreting results, whether they’re our own or somebody else’s.

Not all evidence is created equally, and we should place more trust in some types of evidence than others.

[Read more…] about Types of Study Designs in Health Research: The Evidence Hierarchy

Tagged With: evidence hierarchy, generalized linear model, logistic regression, Study design, Survival Analysis

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Member Training: Goodness of Fit Statistics

by TAF Support 


What are goodness of fit statistics? Is the definition the same for all types of statistical model? Do we run the same tests for all types of statistic model?

[Read more…] about Member Training: Goodness of Fit Statistics

Tagged With: count models, goodness of fit, linear regression, logistic regression, mixed model, Structural Equation Modeling

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  • Member Training: Using Excel to Graph Predicted Values from Regression Models
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  • Member Training: Types of Regression Models and When to Use Them
  • Member Training: Generalized Linear Models

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