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Sample Size Calculator (web)

Logistic Regression - Rule-of-thumb

Independent variable	Scale	Categories	Count

Total independent variables count (k):
Events (outcomes) per variable (EPV):
Choose a value between 5 and 20 (Peduzzi et al. 1996; Vittinghoff & McCulloch, 2007)
Proportion with outcome (p):
Expected dropout rate: %

Number of subjects with outcome, n₁ =
n₁ is the number of subjects in the smaller of the two outcome groups (i.e. Yes vs No), taking into account the intercept (n₁ = [k + 1] × EPV [Hosmer et al. 2013])
Sample size, n =
When p > 0.5, n = n₁/(1 - p)
Sample size (with 10% dropout), n_drop =

Tutorial:

A short tutorial on sample size calculation › Logistic regression

References for formula:

Hosmer, D. W., Lemeshow, S., & Sturdivant, R. X. (2013). Applied logistic regression (3rd ed.). New Jersey: John Wiley & Sons, Inc.

Peduzzi, P., Concato, J., Kemper, E., Holford, T. R., & Feinstein, A. R. (1996). A simulation study of the number of events per variable in logistic regression analysis. Journal of clinical epidemiology, 49(12), 1373-1379.

Vittinghoff, E., & McCulloch, C. E. (2007). Relaxing the rule of ten events per variable in logistic and Cox regression. American journal of epidemiology, 165(6), 710-718.

Suggested reference:

APA: Arifin, W. N. ( ). Sample size calculator (web). Retrieved from http://wnarifin.github.io

Vancouver: Arifin WN. Sample size calculator (web) [Internet]. [cited ]. Available from: http://wnarifin.github.io

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