Missing Data:

• Graham, J. W. (2009). Missing data analysis: Making it work in the real world. Annual Review of Psychology, 60, 549–576.
• Jorgensen, T. D., Forney, K. J., Hall, J. A., & Giles, S. M. (2018). Using modern methods for missing data analysis with the social relations model: A bridge to social network analysis. Social networks, 54, 26-40.
• Pampaka, M., Hutcheson, G., & Williams, J. (2016). Handling missing data: analysis of a challenging data set using multiple imputation. International Journal of Research & Method in Education, 39(1), 19-37.

Statistical Power Issues:

• Arend, M. G., & Schäfer, T. (2019). Statistical power in two-level models: A tutorial based on Monte Carlo simulation. Psychological Methods, 24(1), 1-19.
• Tein, J. Y., Coxe, S., & Cham, H. (2013). Statistical power to detect the correct number of classes in latent profile analysis. Structural Equation Modeling: A multidisciplinary journal, 20(4), 640-657.

Modeling Debates:

• Hooper, D., Coughlan, J., & Mullen, M. (2008). Structural equation modelling: Guidelines for determining model fit. Journal of Business Research Methods, 6, 52-60.
• Hayduk, L. A., & Littvay, L. (2012). Should researchers use single indicators, best indicators, or multiple indicators in structural equation models?. BMC Medical Research Methodology, 12(1), 159.
• Barrett P. (2007). Structural equation modelling: Adjudging model fit. Personality and Individual Differences, 42, 815–824.
• Hayduk LA, Cummings GG, Boadu K, Pazderka-Robinson H, Boulianne S (2007) Testing! Testing! One, two, three – Testing the theory in structural equation models! Personality and Individual Differences, 42, 841–850.
• McIntosh CN (2007) Rethinking fit assessment in structural equation modelling: A commentary and elaboration on Barrett. Personality and Individual Differences, 42, 859–867.
• Steiger, J. H. (2007). Understanding the limitations of global fit assessment in structural equation modeling. Personality and Individual differences, 42(5), 893-898.