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Member Training: Reporting Structural Equation Modeling Results

by Jeff Meyer

The last, and sometimes hardest, step for running any statistical model is writing up results.

As with most other steps, this one is a bit more complicated for structural equation models than it is for simpler models like linear regression.

Any good statistical report includes enough information that someone else could replicate your results with your data.

[Read more…] about Member Training: Reporting Structural Equation Modeling Results

Tagged With: CFA, discriminant analysis, error term, factor loadings, Intercept, Latent Growth Curve Model, mean, mediation, parameter estimates, principal component analysis, reliability, reporting, SEM, Structural Equation Modeling

Related Posts

  • One of the Many Advantages to Running Confirmatory Factor Analysis with a Structural Equation Model
  • First Steps in Structural Equation Modeling: Confirmatory Factor Analysis
  • Member Training: Latent Growth Curve Models
  • Member Training: Confirmatory Factor Analysis

Correlated Errors in Confirmatory Factor Analysis

by Jeff Meyer 2 Comments

Latent constructs, such as liberalism or conservatism, are theoretical and cannot be measured directly.

But we can use a set of questions on a scale, called indicators, to represent the construct together by combining them into a latent factor.

Often prior research has determined which indicators represent the latent construct. Prudent researchers will run a confirmatory factor analysis (CFA) to ensure the same indicators work in their sample.

[Read more…] about Correlated Errors in Confirmatory Factor Analysis

Tagged With: Confirmatory Factor Analysis, error term, Factor Analysis, latent variable, Model Fit

Related Posts

  • One of the Many Advantages to Running Confirmatory Factor Analysis with a Structural Equation Model
  • Measurement Invariance and Multiple Group Analysis
  • Why Adding Values on a Scale Can Lead to Measurement Error
  • First Steps in Structural Equation Modeling: Confirmatory Factor Analysis

Link Functions and Errors in Logistic Regression

by Karen Grace-Martin 1 Comment

I recently held a free webinar in our The Craft of Statistical Analysis program about Binary, Ordinal, and Nominal Logistic Regression.

It was a record crowd and we didn’t get through everyone’s questions, so I’m answering some here on the site. They’re grouped by topic, and you will probably get more out of it if you watch the webinar recording. It’s free.

The following questions refer to this logistic regression model: [Read more…] about Link Functions and Errors in Logistic Regression

Tagged With: Binary Logistic Regression, error term, link function, logit, logit link

Related Posts

  • What is a Logit Function and Why Use Logistic Regression?
  • How to Decide Between Multinomial and Ordinal Logistic Regression Models
  • The Difference Between Logistic and Probit Regression
  • Logistic Regression Models for Multinomial and Ordinal Variables

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This Month’s Statistically Speaking Live Training

  • January Member Training: A Gentle Introduction To Random Slopes In Multilevel Models

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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