S3E14: Patrick & Greg’s New Year’s Balls Drop


Greg and Patrick, perched in a glass booth high above New York’s Times Square, ring in 2022 with the help of some friends by counting down quantitative New Year’s resolutions.

Along the way they also mention QPod catheters, Dr. Ruth Westheimer, groin height, yelling at NPR, Shimmer, O’Nuckles, intellectual gooses, European Quanterati, smoldering corpses, Dilbert, Dom Perignon, quant club, organ grinders, and non-contiguous sub-4-minute miles.

Additional Show Notes

Arend, M. G., & Schäfer, T. (2019). Statistical power in two-level models: A tutorial based on Monte Carlo simulation. Psychological Methods24, 1-19.

Cook, T. D., Campbell, D. T., & Shadish, W. (2002). Experimental and quasi-experimental designs for generalized causal inference. Boston, MA: Houghton Mifflin.

Hancock, G. R. (2001). Effect size, power, and sample size determination for structured means modeling and MIMIC approaches to between-groups hypothesis testing of means on a single latent construct. Psychometrika66, 373-388.

Hancock, G. R., & An, J. (2020). A closed-form alternative for estimating ω reliability under unidimensionality. Measurement: Interdisciplinary Research and Perspectives18, 1-14.

Hancock, G. R., & French, B. F. (2013). Power analysis in structural equation modeling. In G. R. Hancock & R. O. Mueller (Eds.), Structural equation modeling: A second course (2nd ed., pp. 117-159). Information Age.

Hancock, G. R., & Mueller, R. O. (2001). Rethinking construct reliability within latent variable systems. Structural equation modeling: Present and Future195, 216.

Hayes, A. F., & Coutts, J. J. (2020). Use omega rather than Cronbach’s alpha for estimating reliability. But…. Communication Methods and Measures14, 1-24.

McNeish, D. (2018). Thanks coefficient alpha, we’ll take it from here. Psychological Methods23, 412.

Muthén, L. K., & Muthén, B. O. (2002). How to use a Monte Carlo study to decide on sample size and determine power. Structural Equation Modeling9, 599-620.

Padilla, M. A., & Divers, J. (2016). A comparison of composite reliability estimators: coefficient omega confidence intervals in the current literature. Educational and Psychological Measurement, 76, 436–453.

Saris, W. E., & Satorra, A. (1988). Characteristics of structural equation models which affect the power of the likelihood ratio test. In Sociometric Research (pp. 220-236). Palgrave Macmillan, London.

Saris, W. E., Satorra, A., & Sörbom, D. (1987). The detection and correction of specification errors in structural equation models. Sociological Methodology, 105-129.

Satorra, A., & Saris, W. E. (1985). Power of the likelihood ratio test in covariance structure analysis. Psychometrika50(1), 83-90.

Thoemmes, F., MacKinnon, D. P., & Reiser, M. R. (2010). Power analysis for complex mediational designs using Monte Carlo methods. Structural Equation Modeling17(3), 510-534.


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