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bayesian

Member Training: Generalized Linear Models

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In this webinar, we will provide an overview of generalized linear models. You may already be using them (perhaps without knowing it!).
For example, logistic regression is a type of generalized linear model that many people are already familiar with. Alternatively, maybe you’re not using them yet and you are just beginning to understand when they might be useful to you.
[Read more…] about Member Training: Generalized Linear Models

Tagged With: bayesian, distribution, error distribution, generalized linear models, GLM, linear model, linear regression, link function, logistic regression, maximum likelihood, mixed model, Poisson Regression

Related Posts

  • Member Training: Types of Regression Models and When to Use Them
  • Count Models: Understanding the Log Link Function
  • Member Training: A Predictive Modeling Primer: Regression and Beyond
  • The Difference Between Link Functions and Data Transformations

Member Training: A Gentle Introduction to Bayesian Data Analysis

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P-values are the fundamental tools used in most inferential data analyses [Read more…] about Member Training: A Gentle Introduction to Bayesian Data Analysis

Tagged With: analysis, bayesian, data, p-value, webinar

Related Posts

  • Member Training: Generalized Linear Models
  • Member Training: Analysis of Ordinal Variables–Options Beyond Nonparametrics
  • January Member Training: A Gentle Introduction To Random Slopes In Multilevel Models
  • September Member Training: Inference and p-values and Statistical Significance, Oh My!

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This Month’s Statistically Speaking Live Training

  • February Member Training: Choosing the Best Statistical Analysis

Upcoming Workshops

  • Logistic Regression for Binary, Ordinal, and Multinomial Outcomes (May 2021)
  • Introduction to Generalized Linear Mixed Models (May 2021)

Read Our Book



Data Analysis with SPSS
(4th Edition)

by Stephen Sweet and
Karen Grace-Martin

Statistical Resources by Topic

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  • Effect Size Statistics, Power, and Sample Size Calculations
  • Analysis of Variance and Covariance
  • Linear Regression
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  • Logistic Regression
  • Missing Data
  • Mixed and Multilevel Models
  • Principal Component Analysis and Factor Analysis
  • Structural Equation Modeling
  • Survival Analysis and Event History Analysis
  • Data Analysis Practice and Skills
  • R
  • SPSS
  • Stata

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