How to interpret odds ratios as probability or chance? [duplicate]

Im working on a panel data set and have difficulties to understand the odds ratio of a fixed effect logit model. I prepared an cross sectional exapmle. I suppose the interpretation is identical:

 data(cars)
attach(cars)

summary(fit)

Coefficients:
Estimate Std. Error z value Pr(>|z|)
(Intercept)  1.581e+00  2.811e-01   5.623 1.88e-08 ***
Mileage     -1.189e-05  9.428e-06  -1.261 0.207205
Price       -2.734e-05  7.564e-06  -3.614 0.000301 ***

require(MASS)

exp(cbind(coef(fit), confint(fit))) ## for odds ratios

2.5 %    97.5 %
(Intercept) 4.8578575 2.8174158 8.4927615
Mileage     0.9999881 0.9999695 1.0000065
Price       0.9999727 0.9999577 0.9999874


How can I interpret odds ratios as an increase/decrease in chance or probability?

marked as duplicate by Xi'an, Andy, Tim♦, 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(); } ); }); }); Jul 17 '15 at 8:16

• @ Maarten Buis. Thank you for the asnwer. In terms of the example. That means that the odds of having a load car decreases by (0.9999881/0.9999727) ? – Googme Jul 17 '15 at 8:14