Education

Self assessment

The self-assessment section, along with targeted quizzes across the site, provides an interactive way for you to test and deepen your understanding of core epidemiology concepts and reinforce critical principles.

Latent class analysis

Test your knowledge of the principles of latent class analysis

1 / 10

Which of the following methods can be used to evaluate model fit in Latent Class Analysis when BIC and AIC provide conflicting recommendations?

2 / 10

How would you interpret a situation in which adding covariates to an LCA model changes the distribution of individuals across classes?

3 / 10

What is one advantage of using Latent Class Analysis over traditional clustering methods like k-means clustering?

4 / 10

In Latent Class Analysis, what does the conditional independence assumption imply?

5 / 10

If the entropy of an LCA model is low, what might this indicate about the model’s classification accuracy?

6 / 10

Which criterion is most often preferred for deciding on the number of classes in LCA models, especially when sample size is large?

7 / 10

In an LCA model with covariates, how do covariates impact the interpretation of the latent classes?

8 / 10

Which of the following assumptions is critical for conducting Latent Class Analysis?

9 / 10

In the context of LCA, what does entropy measure?

10 / 10

Which type of indicator variable is most appropriate for Latent Class Analysis?

Your score is

The average score is 40%

0%

Case Study Scenarios

The following are real-life epidemiology case scenarios where you can make decisions at each stage of an investigation (e.g., identifying study designs, selecting data collection methods, interpreting results).

Practice with Data

Latent class analysis

  • https://stats.oarc.ucla.edu/sas/dae/latent-class-analysis/
  • https://www.latentclassanalysis.com/code-repository/