![]() We used the number working or the prob(working). Probability of working by the probability of not working, we get the same result as we gotīefore, an odds of 2. For example, families that earn $10k have a probability of. In this example, when we increase income by 1 unit, the odds of the wife working ($1000) the odds of working increased by a factor of 2. Notice that when income increased by 1 unit The odds of working for those earning $12k by the odds of workingįor those earning $11k, we get 8 / 4 = 2. If we divide the odds for thoseĮarning $11k by the odds for those earning $10k, we get 4 / 2 = 2. Number Number not Oddsįor those earning $10k (2) with those earning $11k (4). Of the wife working at each level of inc, as shown below. The odds ratio, but let’s first start with looking at the odds That for every unit increase in inc, the odds of the wife working Predicting wifework from inc is 2 (in the right-most columnīut what does this mean? The definition of an odds ratio tells us Let’s run a logistic regression predicting wifeworkįrom inc. There are 2 wives who work and 1 who does not, for families earning $11,000 thereĪre 4 wives who work, and 1 who does not, and for families earning $12,000 thereĪre 8 wives who work, and 1 who does not. You might notice that for families earning $10,000, Below we have a data file with informationĪbout families containing the husband’s income (in thousands of dollars) rangingįrom 10,000 to 12,000, and whether the wife works, 1 if the wife does
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