# Need help determining sample size for logistic regression [duplicate]

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I need help determining the sample size necessary for a logistic regression (binary DV) with two continuous predictors and also the sample size necessary if I use three continuous predictors.

## marked as duplicate by user20160, mkt - Reinstate Monica, kjetil b halvorsen, Peter Flom - Reinstate Monica♦ regression StackExchange.ready(function() { if (StackExchange.options.isMobile) return; $('.dupe-hammer-message-hover:not(.hover-bound)').each(function() { var$hover = $(this).addClass('hover-bound'),$msg = $hover.siblings('.dupe-hammer-message');$hover.hover( function() { $hover.showInfoMessage('', { messageElement:$msg.clone().show(), transient: false, position: { my: 'bottom left', at: 'top center', offsetTop: -7 }, dismissable: false, relativeToBody: true }); }, function() { StackExchange.helpers.removeMessages(); } ); }); }); Sep 1 '18 at 11:53

tl;dr For a binary response model (e.g. logistic regression) you need about 15*(# of non-intercept parameters) successes or failures (whichever is less). Estimating a simple linear effect of a continuous predictor takes a single parameter. So in your case you need $\textrm{min}(\textrm{successes},\textrm{failures}) > 30$ (for 2 predictors) or $>45$ (for 3 predictors).
in many situations a fitted regression model is likely to be reliable when the number of predictors ... $p$ is less than $m/10$ or $m/20$, where $m$ is the "limiting sample size" given in Table 4.1