Latent Class and Latent Transition Analysis: WithApplications in the Social, Behavioral, and Health Sciences / Edition 1

Hardcover (Print)
Used and New from Other Sellers
Used and New from Other Sellers
from $96.05
Usually ships in 1-2 business days
(Save 24%)
Other sellers (Hardcover)
  • All (9) from $96.05   
  • New (7) from $96.05   
  • Used (2) from $96.05   


A modern, comprehensive treatment of latent class and latent transition analysis for categorical data On a daily basis, researchers in the social, behavioral, and health sciences collect information and fit statistical models to the gathered empirical data with the goal of making significant advances in these fields. In many cases, it can be useful to identify latent, or unobserved, subgroups in a population, where individuals' subgroup membership is inferred from their responses on a set of observed variables. Latent Class and Latent Transition Analysis provides a comprehensive and unified introduction to this topic through one-of-a-kind, step-by-step presentations and coverage of theoretical, technical, and practical issues in categorical latent variable modeling for both cross-sectional and longitudinal data. The book begins with an introduction to latent class and latent transition analysis for categorical data. Subsequent chapters delve into more in-depth material, featuring:
• A complete treatment of longitudinal latent class models
• Focused coverage of the conceptual underpinnings of interpretation and evaluationof a latent class solution
• Use of parameter restrictions and detection of identification problems
• Advanced topics such as multi-group analysis and the modeling and interpretation of interactions between covariates The authors present the topic in a style that is accessible yet rigorous. Each method is presented with both a theoretical background and the practical information that is useful for any data analyst. Empirical examples showcase the real-world applications of the discussed concepts and models, and each chapter concludes with a "Points to Remember" section that contains a brief summary of key ideas. All of the analyses in the book are performed using Proc LCA and Proc LTA, the authors' own software packages that can be run within the SASr environment. A related Web site houses information on

Read More Show Less

Product Details

Meet the Author

Linda M. Collins, PhD, is Director of The Methodology Center and Professor of Human Development and Family Studies at The Pennsylvania State University. A Fellow of the American Psychological Association and the Association for Psychological Science, Dr. Collins has published numerous journal articles in her areas of research interest, which include experimental and non-experimental design and models for longitudinal data.

STEPHANIE T. LANZA, PhD, is Scientific Director and Senior Research Associate at The Methodology Center at The Pennsylvania State University. She currently focuses her research on latent class and latent transition analysis and their applications in the social, behavioral, and health sciences.

Read More Show Less

Table of Contents

List of Figures.

List of Tables.



Part I Fundamentals.

1. General Introduction.

1.1 Overview.

1.2 Conceptual foundation and brief history of the latent class model.

1.3 Why select a categorical latent variable approach?

1.4 Scope of this book.

1.5 Empirical example of LCA:  Adolescent delinquency.

1.6 Empirical example of LTA: Adolescent delinquency.

1.7 About this book.

1.8 The examples in this book.

1.9 Software.

1.10 Additional resources: The book’s web site.

1.11 Suggested supplemental readings.

1.12 Points to remember.

1.13 What’s next.

2. The latent class model.

2.1 Overview.

2.2 Empirical example: Pubertal development.

2.3 The role of item-response probabilities to label the latent classes in the pubertal development example.

2.4 Empirical example: Health risk behaviors.

2.5 LCA: Model and notation.

2.6 Suggested supplemental readings.

2.7 Points to remember.

2.8 What’s next.

3. The relation between the latent variable and its indicators.

3.1 Overview.

3.2 The latent class measurement model.

3.3 Homogeneity and latent class separation.

3.4 The precision with which the observed variables measure the latent variable.

3.5 Expressing the degree of uncertainty: Mean posterior probabilities and entropy.

3.6 Points to remember.

3.7 What’s next.

4. Parameter estimation and model selection.

4.1 Overview.

4.2 Maximum Likelihood estimation.

4.3 Model fit and model selection.

4.4 Finding the ML solution.

4.5 Empirical example of using many starting values.

4.6 Empirical examples of selecting the number of latent classes.

4.7 More about parameter restrictions.

4.8 Standard errors.

4.9 Suggested supplemental readings.

4.10 Points to remember.

4.11 What’s next.

Part II Advanced LCA.

5. Multiple-group LCA.

5.1 Overview.

5.2 Introduction.

5.3 Multiple-group LCA: Model and notation.

5.4 Computing the number of parameters estimated.

5.5 Expressing group differences in the LCA model.

5.6 Measurement invariance.

5.7 Establishing whether the number of latent classes is identical across groups.

5.8 Establishing invariance of item-response probabilities across groups.

5.9 Interpretation when measurement invariance does not hold.

5.10 Strategies when measurement invariance does not hold.

5.11 Significant differences and important differences.

5.12 Testing equivalence of latent class prevalences across groups.

5.13 Suggested supplemental readings.

5.14 Points to remember.

5.15 What’s next.

6. LCA with Covariates.

6.1 Overview.

6.2 Empirical example: Positive health behaviors.

6.3 Preparing to conduct LCA with covariates.

6.4 LCA with covariates: Model and notation.

6.5 Hypothesis testing in LCA with covariates.

6.6 Interpretation of the intercepts and regression coefficients.

6.7 Empirical examples of LCA with a single covariate.

6.8 Empirical example of multiple covariates and interaction terms.

6.9 Multiple-group LCA with covariates: Model and notation.

6.10 Grouping variable or covariate?

6.11 Use of a Bayesian prior to stabilize estimation.

6.12 Binomial logistic regression.

6.13 Suggested supplemental readings.

6.14 Points to remember.

6.15 What’s next.

Part III Latent Class Models for Longitudinal Data.

7. RMLCA and LTA.

7.1 Overview.

7.2 RMLCA.

7.3 LTA.

7.4 LTA model parameters.

7.5 LTA: Model and notation.

7.6 Degrees of freedom associated with latent transition models.

7.7 Empirical example: Adolescent depression.

7.8 Empirical example: Dating and sexual risk behavior.

7.9 Interpreting what a latent transition model reveals about change.

7.10 Parameter restrictions in LTA.

7.11 Testing the hypotheses of measurement invariance across times.

7.12 Testing the hypotheses about change between times.

7.13 Relation between RMLCA and LTA.

7.14 Invariance of the transition probability matrix.

7.15 Suggested supplemental readings.

7.16 Points to remember.

7.17 What’s next.

8. Multiple-Group LTA and LTA with Covariates.

8.1 Overview.

8.2 LTA with a grouping variable.

8.3 Multiple-group LTA: Model and notation.

8.4 Computing the number of parameters estimated in multiple-group latent transition models.

8.5 Hypothesis tests concerning group differences: General consideration.

8.6 Overall hypothesis tests about group differences in LTA.

8.7 Testing the hypothesis of equality of latent status prevalences.

8.8 Testing the hypothesis of equality of transition probabilities.

8.9 Incorporating covariates in LTA.

8.10 LTA with covariates: Model and notation.

8.11 Hypothesis testing in LTA with covariates.

8.12 Including both a grouping variable and a covariate in LTA.

8.13 Binomial logistic regression.

8.14 The relation between multiple-group LTA and LTA with a covariate.

8.15 Suggested supplemental readings.

8.16 Points to remember.

Topic Index.

Author Index.

Read More Show Less

Customer Reviews

Be the first to write a review
( 0 )
Rating Distribution

5 Star


4 Star


3 Star


2 Star


1 Star


Your Rating:

Your Name: Create a Pen Name or

Barnes & Review Rules

Our reader reviews allow you to share your comments on titles you liked, or didn't, with others. By submitting an online review, you are representing to Barnes & that all information contained in your review is original and accurate in all respects, and that the submission of such content by you and the posting of such content by Barnes & does not and will not violate the rights of any third party. Please follow the rules below to help ensure that your review can be posted.

Reviews by Our Customers Under the Age of 13

We highly value and respect everyone's opinion concerning the titles we offer. However, we cannot allow persons under the age of 13 to have accounts at or to post customer reviews. Please see our Terms of Use for more details.

What to exclude from your review:

Please do not write about reviews, commentary, or information posted on the product page. If you see any errors in the information on the product page, please send us an email.

Reviews should not contain any of the following:

  • - HTML tags, profanity, obscenities, vulgarities, or comments that defame anyone
  • - Time-sensitive information such as tour dates, signings, lectures, etc.
  • - Single-word reviews. Other people will read your review to discover why you liked or didn't like the title. Be descriptive.
  • - Comments focusing on the author or that may ruin the ending for others
  • - Phone numbers, addresses, URLs
  • - Pricing and availability information or alternative ordering information
  • - Advertisements or commercial solicitation


  • - By submitting a review, you grant to Barnes & and its sublicensees the royalty-free, perpetual, irrevocable right and license to use the review in accordance with the Barnes & Terms of Use.
  • - Barnes & reserves the right not to post any review -- particularly those that do not follow the terms and conditions of these Rules. Barnes & also reserves the right to remove any review at any time without notice.
  • - See Terms of Use for other conditions and disclaimers.
Search for Products You'd Like to Recommend

Recommend other products that relate to your review. Just search for them below and share!

Create a Pen Name

Your Pen Name is your unique identity on It will appear on the reviews you write and other website activities. Your Pen Name cannot be edited, changed or deleted once submitted.

Your Pen Name can be any combination of alphanumeric characters (plus - and _), and must be at least two characters long.

Continue Anonymously

    If you find inappropriate content, please report it to Barnes & Noble
    Why is this product inappropriate?
    Comments (optional)