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Review: Applied Logistic RegressionUser Review - Steven Peterson - Goodreads
Logistic regression is a very handy statistical tool. It does not demand much of the data (no need for variables to be normally distributed). Also, it can be used with dichotomous dependent variables ... Read full review
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95 percent confidence analysis assess benign breast disease best subsets binary Chapter clinical coded computed confidence interval constant continuous covariates correlation covariance matrix covariate patterns data set degrees-of-freedom denote design variables diagnostic statistics discussed distribution equation estimated coefficients estimated logistic probability estimated odds ratios estimated probability estimated standard errors example fitted model fitted values fractional polynomial goodness-of-fit Hosmer independent variable interaction interpretation interval estimates Lemeshow likelihood function likelihood ratio test linear regression log odds log-likelihood logistic model logistic regression model low birth weight main effects mammography maximum likelihood estimates methods model containing model fit model in Table NDRGTX observed obtained outcome variable p-value parameters plot population average model previous drug treatments RACE results of fitting sample Score test Section selection shown in Table significance slope coefficients SMOKE standard errors STATA step stepwise stratum subjects tion univariable variance versus Wald statistics Wald test zero
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Douglas E Jorenby, Scott J Leischow, Mitchell A Nides, Stephen I Rennard, J Andrew Johnston ... - 1999 - New England Journal of Medicine
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