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I would like to apply logistic regression for my research. And before that, I want to calculate the minimum number of sample size, positive cases, and negative cases.

http://www.medcalc.org/manual/logistic_regression.php

I came across the above website, stating the below calculation.

"Sample size calculation for logistic regression is a complex problem, but based on the work of Peduzzi et al. (1996) the following guideline for a minimum number of cases to include in your study can be suggested. Let p be the smallest of the proportions of negative or positive cases in the population and k the number of covariates (the number of independent variables), then the minimum number of cases to include is:

N = 10 k / p For example: you have 3 covariates to include in the model and the proportion of positive cases in the population is 0.20 (20%). The minimum number of cases required is

N = 10 x 3 / 0.20 = 150

If the resulting number is less than 100 you should increase it to 100 as suggested by Long (1997)."

So, since my positive cases in the population is 7.4%=0.074; and I have 10 independent variables. Therefore the sample size needed N = 10 * 10 / 0.074 = 1352.

But how can I determine how many positive and negative cases do I need? Or does it mean I would need 1352*50% for positive and negative cases respectively?

What if my available sample include only 500 positive and 7500 negative cases? Would it be inappropriate to run logistic regression?

Thank you !

cyrusjan
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  • Try Googling "rare event logistic regression." Gary King may have done articles that will be helpful. – rolando2 Jan 30 '15 at 03:06
  • http://stats.stackexchange.com/questions/2988/sample-size-calculation-for-univariate-logistic-regression?rq=1 and http://stats.stackexchange.com/questions/22328/sample-size-for-unequal-groups-in-logistic-regression?rq=1 have some info. – rolando2 Jan 31 '15 at 03:27
  • Another dup: https://stats.stackexchange.com/questions/162294/multiple-logistic-regression-power-analysis/396681#396681 – kjetil b halvorsen Mar 11 '19 at 23:06

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