# What is the minimum number of “cases” for minority class to perform logistic regression? [duplicate]

I have 6 out of 167 cases of cancer in the dependent variable. I would evaluate if three independent variables predicted the cancer. Are 6 cases enough? Is there a rule to determine this? Is there difference if the indipendent variables is nominal or numeric?

## marked as duplicate by Tim♦, Sycorax, gung♦ 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(); } ); }); }); Aug 29 '16 at 15:45

• What does "enough" mean? If I were to say "enough" then I would personally say "given prevalence x, how many samples do I need for the Jeffreys prior on the rate to be within the range x-r to x+r. Here is what a decent tool gives for your samples. (epitools.ausvet.com.au/…) – EngrStudent Aug 29 '16 at 14:36
• 6 "Yes"s and 3 DVs will almost certainly produce complete separation in the data (which often manifests as huge coefficient estimates and standard errors). The rule of thumb usually says 5 or 10 cases per DV (depending on who you ask). – not_bonferroni Aug 29 '16 at 14:36
• What do you mean by "6 out of 167"? Is is that 6 patients had cancer diagnosed ? – Tim Aug 29 '16 at 14:36
• – David R Aug 29 '16 at 14:42

Also you may get some warnings from R, glm, if you have perfect separably data, so you may consider adding regularization.