Resource Bibliography

Covariates/Collinearity

Hyatt, C., Owens, M., Crowe, M., Carter, N., Lynam, D., Miller, J. (2020). The quandary of covarying: A brief review and empirical examination of covariate use in structural neuroimaging studies on psychological variables. Neuroimage. https://doi.org/10.1016/j.neuroimage.2019.116225

King, K., Littlefield, A., McCabe, C., Mills, K., Flournoy, J., Chassin, L. (2018). Longitudinal modeling in developmental neuroimaging research: Common challenges and solutions from developmental psychology. Developmental Cognitive Neuroscience. https://doi.org/10.1016/j.dcn.2017.11.009

Miller, G., Chapman, J. (2001). Misunderstanding analysis of covariance. Journal of Abnormal Psychology. https://doi.org/10.1037//0021-843x.110.1.40

Rashid, B., Calhoun, V. (2020). Towards a brain-based predictome of mental illness. Human Brain Mapping. https://doi.org/10.1002/hbm.25013

Effect Size

Dick, A.S., et al. (2020). Meaningful effects in the Adolescent Brain Cognitive Development Study. Unpublished Manuscript. https://apps1.seiservices.com/meaningfuleffects/documents/abcd_meaningful_effects.pdf

Ask an Expert: Estimation Statistics and Statistical Power (2020). Featured in: Foundations of Rigorous Neuroscience Research.

Bukszar, J., Van den Oord, E. (2010). Estimating effects sizes in genome-wide association studies. Behavioral Genetics. https://doi.org/10.1007/s10519-009-9321-9

Coe, R. (2002). It’s the effect size, stupid. What effect size is and why it is important. British Educational Research Association annual conference. http://www.leeds.ac.uk/educol/documents/00002182.htm

Correll, J., Mellinger, C., McClelland, G., Judd, C. (2020). Avoid Cohen’s ‘small’, ‘medium’, and ‘large’ for power analysis. Trends in Cognitive Sciences. https://doi.org/10.1016/j.tics.2019.12.009

Funder, D., Ozer, D. (2019). Evaluating effect size in psychological research: Sense and nonsense. Advances in Methods and Practices in Psychological Science. https://doi.org/10.1177/2515245919847202

Gelman, A., Weakliem, D. (2020). Of beauty, sex and power. American Scientist. https://doi.org/10.1511/2009.79.310

Khera, A. et al. (2019). Polygenic prediction of weight and obesity trajectories from birth to adulthood. Cell. https://doi.org/10.1016/j.cell.2019.03.028

Marek, S. et al. (2020). Towards reproducible brain-wide association studies. BioRxiv. https://doi.org/10.1101/2020.08.21.257758

Nelson, M., et al. (2015). The support of human genetic evidence for approved drug indications. Nature Genetics. https://doi.org/10.1038/ng.3314

Reddan, M., Lindquist, M., Wager, T. (2017). Effect size estimation in neuroimaging. JAMA Psychiatry. https://doi.org/10.1001/jamapsychiatry.2016.3356

Schafer, T., Schwarz, M. (2019). The meaningfulness of effect sizes in psychological research: Differences between sub-disciplines and the impact of potential biases. Frontiers in Psychology. https://doi.org/10.3389/fpsyg.2019.00813

Siontis, G., Ioannidis, J. (2011). Risk factors and interventions with statistically significant tiny effects. International Journal of Epidemiology. https://doi.org/10.1093/ije/dyr099

Sullivan, P.F. et al. (2018). Psychiatric genomics: An update and an agenda. The American Journal of Psychiatry. https://doi.org/10.1176/appi.ajp.2017.17030283

Exploratory, Confirmatory Analysis

Amrhein, V., Trafimow, D., Greenland, S. (2019). Inferential statistics as descriptive statistics: There is no replication crisis if we don’t expect replication. The American Statistician. https://doi.org/10.1080/00031305.2018.1543137

Chambers (2019). What’s next for registered reports? Nature. https://doi.org/10.1038/d41586-019-02674-6

Flournoy, J., Vijayakumar, N., Cheng, T., Cosme, D., Flannery, J., Pfeifer, J. (2020). Improving practices and inferences in developmental cognitive neuroscience. Developmental Cognitive Neuroscience. https://doi.org/10.1016/j.dcn.2020.100807

Hong, Y-W., Yoo, Y., Han, J., Wager, T., Woo, C-W (2019). False-positive neuroimaging: Undisclosed flexibility in testing spatial hypotheses allows presenting anything as a replicated finding. NeuroImage. https://doi.org/10.1016/j.neuroimage.2019.03.070

Kvarven, A., Stromland, E., Johannesson, M. (2019). Comparing meta-analyses and preregistered multiple-laboratory replication projects. Nature Human Behavior. https://doi.org/10.1038/s41562-019-0787-z

Poldrack, R., Huckins, G., Varoquaux, G. (2019). Establishment of best practices for evidence for prediction. A review. JAMA Psychiatry. https://doi.org/10.1001/jamapsychiatry.2019.3671