HI I use glm in R to do logistic regression. and treat both response and predictor as factor In my first try:
******************************************************************************* Call: glm(formula = as.factor(diagnostic) ~ as.factor(7161521) + as.factor(2281517), family = binomial()) Deviance Residuals: Min 1Q Median 3Q Max -1.5370 -1.0431 -0.9416 1.3065 1.4331 Coefficients: Estimate Std. Error z value Pr(>|z|) (Intercept) -0.58363 0.27948 -2.088 0.0368 * as.factor(7161521)2 1.39811 0.66618 2.099 0.0358 * as.factor(7161521)3 0.28192 0.83255 0.339 0.7349 as.factor(2281517)2 -1.11284 0.63692 -1.747 0.0806 . as.factor(2281517)3 -0.02286 0.80708 -0.028 0.9774 --- Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1 (Dispersion parameter for binomial family taken to be 1) Null deviance: 678.55 on 498 degrees of freedom Residual deviance: 671.20 on 494 degrees of freedom AIC: 681.2 Number of Fisher Scoring iterations: 4 ******************************************************************************* And I remodel it and *want no intercept*: ******************************************************************************* Call: glm(formula = as.factor(diagnostic) ~ as.factor(2281517) + as.factor(7161521) - 1, family = binomial()) Deviance Residuals: Min 1Q Median 3Q Max -1.5370 -1.0431 -0.9416 1.3065 1.4331 Coefficients: Estimate Std. Error z value Pr(>|z|) as.factor(2281517)1 -0.5836 0.2795 -2.088 0.0368 * as.factor(2281517)2 -1.6965 0.6751 -2.513 0.0120 * as.factor(2281517)3 -0.6065 0.8325 -0.728 0.4663 as.factor(7161521)2 1.3981 0.6662 2.099 0.0358 * as.factor(7161521)3 0.2819 0.8325 0.339 0.7349 --- Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1 (Dispersion parameter for binomial family taken to be 1) Null deviance: 691.76 on 499 degrees of freedom Residual deviance: 671.20 on 494 degrees of freedom AIC: 681.2 Number of Fisher Scoring iterations: 4 ******************************************************************************* *As show above in my second model it return no intercept but look this: Model1: (Intercept) -0.58363 0.27948 -2.088 0.0368 * Model2: as.factor(2281517)1 -0.5836 0.2795 -2.088 0.0368 ** They are exactly the same. Could you please tell me what happen? Thank you in advance -- View this message in context: http://r.789695.n4.nabble.com/logistic-regression-by-glm-tp4088471p4088471.html Sent from the R help mailing list archive at Nabble.com. ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
