1. As this is a statistical, rather than an R issue, you would do better posting on a statistical help site like stats.stackexchange.com (although some generous soul here may respond).
2. You would also probably do better consulting with a local statistical resource if available, as it is difficult to explain such issues remotely. Cheers, Bert On Mon, May 7, 2012 at 10:05 AM, lincoln <misen...@hotmail.com> wrote: > Hi all, > > I can't find the error in the binomial GLM I have done. I want to use that > because there are more than one explanatory variables (all categorical) and > a binary response variable. > This is how my data set looks like: >> str(data) > 'data.frame': 1004 obs. of 5 variables: > $ site : int 0 0 0 0 0 0 0 0 0 0 ... > $ sex : Factor w/ 2 levels "0","1": NA NA NA NA 1 NA NA NA NA NA ... > $ age : Factor w/ 2 levels "0","1": 1 1 1 1 1 1 1 1 1 1 ... > $ cohort: Factor w/ 11 levels "1996","2000",..: 11 11 11 11 11 11 11 11 11 > 11 ... > $ birth : Factor w/ 3 levels "5","6","7": 3 3 2 2 2 2 2 2 2 2 ... > > I know that, particularly for one level of variable "cohort" (2004 value), > it should be a strong effect of variable "cohort" on variable "site" so I do > a Chi square test that confirms the null hypothesis there is a difference in > sites on the way "cohort" is distributed: > >> (chisq.test(data$site,data$cohort)) > > Pearson's Chi-squared test > > data: data$site and data$cohort > X-squared = 82.6016, df = 10, *p-value = 1.549e-13* > > Mensajes de aviso perdidos > In chisq.test(data$site, data$cohort) : > Chi-squared approximation may be incorrect > > > > > After that, I have tried to use a binomial GLM with all the explanatory > variables but I couldn't find any significance of any variable, neither > cohort, and for this reason I tried to use only cohort as predictor and I > get this: > > >> BinomialGlm <- glm(site ~ cohort, data=data,binomial) >> summary(BinomialGlm) > > Call: > glm(formula = site ~ cohort, family = binomial, data = data) > > Deviance Residuals: > Min 1Q Median 3Q Max > -1.9239 -0.9365 -0.9365 1.3584 1.6651 > > Coefficients: > Estimate Std. Error z value Pr(>|z|) > (Intercept) -12.57 324.74 -0.039 0.969 > cohort2000 11.47 324.75 0.035 0.972 > cohort2001 13.82 324.74 0.043 0.966 > cohort2002 12.97 324.74 0.040 0.968 > cohort2003 13.66 324.74 0.042 0.966 > *cohort2004 14.25 324.74 0.044 0.965* > cohort2006 12.21 324.74 0.038 0.970 > cohort2007 11.81 324.74 0.036 0.971 > cohort2008 12.41 324.74 0.038 0.970 > cohort2009 12.15 324.74 0.037 0.970 > cohort2010 11.97 324.74 0.037 0.971 > > (Dispersion parameter for binomial family taken to be 1) > > Null deviance: 1369.3 on 1003 degrees of freedom > Residual deviance: 1283.7 on 993 degrees of freedom > AIC: 1305.7 > > Number of Fisher Scoring iterations: 11 > > > > > I tired to use simple GLM (gaussian family) and I get results that are more > logicals: > >> GaussGlm <- glm(site ~ cohort, data=data) >> summary(GaussGlm) > > Call: > glm(formula = site ~ cohort, data = data) > > Deviance Residuals: > Min 1Q Median 3Q Max > -0.8429 -0.3550 -0.3550 0.6025 0.7500 > > Coefficients: > Estimate Std. Error t value Pr(>|t|) > (Intercept) 5.740e-14 4.762e-01 0.000 1.0000 > cohort2000 2.500e-01 5.324e-01 0.470 0.6388 > cohort2001 7.778e-01 5.020e-01 1.549 0.1216 > cohort2002 6.000e-01 4.880e-01 1.230 0.2192 > cohort2003 7.500e-01 4.861e-01 1.543 0.1231 > *cohort2004 8.429e-01 4.796e-01 1.757 0.0792 .* > cohort2006 4.118e-01 4.832e-01 0.852 0.3943 > cohort2007 3.204e-01 4.785e-01 0.670 0.5033 > cohort2008 4.600e-01 4.786e-01 0.961 0.3367 > cohort2009 3.975e-01 4.772e-01 0.833 0.4051 > cohort2010 3.550e-01 4.768e-01 0.745 0.4567 > --- > Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1 > > (Dispersion parameter for gaussian family taken to be 0.2267955) > > Null deviance: 245.40 on 1003 degrees of freedom > Residual deviance: 225.21 on 993 degrees of freedom > AIC: 1372.5 > > Number of Fisher Scoring iterations: 2 > > > > What is going on? Any suggestion/commentary? > > -- > View this message in context: > http://r.789695.n4.nabble.com/Can-t-find-the-error-in-a-Binomial-GLM-I-am-doing-please-help-tp4615340.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. -- Bert Gunter Genentech Nonclinical Biostatistics Internal Contact Info: Phone: 467-7374 Website: http://pharmadevelopment.roche.com/index/pdb/pdb-functional-groups/pdb-biostatistics/pdb-ncb-home.htm ______________________________________________ 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.
