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Logistic Regression Notes

# O e ri i i i 1 2 k ei where oi is the observed

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Unformatted text preview: imilar way as in logistic regression. o −e ri = i√ i , i = 1, 2, . . . , K ei where oi is the observed value and ei is the expected frequency. ei computed as nπi ˆ Compared with oi = yi . Similar to ideas in a one-way contingency tables Chi-square statistic: applies if each category has a unique set of covariates K 2 ri2 X= i =1 UNM Odds ratio Suppose we have a covariate X , where X = 0 factor is absent and X = 1 factor is present. Since πj log = β0j + β1j X ; j = 2, . . . , K π1 If πjp (πja ) is the response probability associated to factor present (absent). For X = 0, πj log = β0j π1 and for X = 1, log πj π1 = β0j + β1j UNM Odds ratio for exposure for response j ORj...
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