Advanced Categorical Data Analysis in Prevention Science
Author:
Publisher
Springer Science and Business Media LLC
Subject
Public Health, Environmental and Occupational Health
Link
https://link.springer.com/content/pdf/10.1007/s11121-022-01485-y.pdf
Reference34 articles.
1. Agresti, A. (2013). Categorical data analysis (3rd ed). Wiley.
2. Bonifay, W., & Depaoli, S. (2023). Model evaluation in the presence of categorical data: Bayesian model checking as an alternative to traditional methods. Prevention Science. https://doi.org/10.1007/s11121-021-01293-w
3. Bray, B. C., Layland, E. K., Stull, S. W., Vasilenko, S. A., & Lanza, S. T. (2023). Estimating the effects of a complex, multidimensional moderator: An example of latent class moderation to examine differential intervention effects of substance use services. Prevention Science. https://doi.org/10.1007/s11121-022-01448-3
4. Cai, L., Chung, S. W., & Lee, T. (2023). Incremental model fit assessment in the case of categorical data: Tucker-Lewis index for item response theory modeling. Prevention Science. https://doi.org/10.1007/s11121-021-01253-4
5. de la Torre, J., van der Ark, L. A., & Rossi, G. (2018). Analysis of clinical data from a cognitive diagnosis modeling framework. Measurement and Evaluation in Counseling and Development, 51(4), 281–296. https://doi.org/10.1080/07481756.2017.1327286
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