On Jul 2, 2013, at 21:21 , Luciano La Sala wrote: > Hello everyone, > > I have a dataset which consists of "Pathology scores" (Absent, Mild, Severe) > as outcome variable, and two main effects: Age (two factors: twenty / thirty > days old) and Treatment Group (four factors: infected without ATB; infected > + ATB1; infected + ATB2; infected + ATB3). > > First I tried to fit an ordinal regression model, which seems more > appropriate given the characteristics of my dependent variable (ordinal). > However, the assumption of odds proportionality was severely violated > (graphically), which prompted me to use a multinomial model instead, using > the "nnet" package. > > > First I chose the outcome level that I need to use as baseline category: > > Data$Path <- relevel(Data$Path, ref = "Absent") > > Then, I needed to set baseline categories for the independent variables: > > Data$Age <- relevel(Data$Age, ref = "Twenty") > Data$Treat <- relevel(Data$Treat, ref = "infected without ATB") > > The model: > > test <- multinom(Path ~ Treat + Age, data = Data) > # weights: 18 (10 variable) > initial value 128.537638 > iter 10 value 80.623608 > final value 80.619911 > converged > >> summary1 <- summary(test1) >> summary1 > > Call: > multinom(formula = Jej_fact ~ Treat + Age, data = Data) > > Coefficients: > (Intercept) infected+ATB1 infected+ATB2 infected+ATB3 > AgeThirty > Moderate -2.238106 -1.1738540 -1.709608 -1.599301 > 2.684677 > Severe -1.544361 -0.8696531 -2.991307 -1.506709 > 1.810771 > > Std. Errors: > (Intercept) infected+ATB1 infected+ATB2 infected+ATB3 > AgeThirty > Moderate 0.7880046 0.8430368 0.7731359 0.7718480 > 0.8150993 > Severe 0.6110903 0.7574311 1.1486203 0.7504781 > 0.6607360 > > Residual Deviance: 161.2398 > AIC: 181.2398 > > For a while, I could not find a way to get the p-values for the model and > estimates when using nnet:multinom. Yesterday I came across a post where the > author put forward a similar issue regarding estimation of p-values for > coefficients > (http://stats.stackexchange.com/questions/9715/how-to-set-up-and-estimate-a- > multinomial-logit-model-in-r). > > There, one blogger suggested that getting p-values from the summary() result > of multinom() is pretty easy, by first getting the t values as follows: > > pt(abs(summary1$coefficients / summary1$standard.errors), df=nrow(Data)-10, > lower=FALSE) > > (Intercept) infected+ATB1 infected+ATB2 infected+ATB3 > AgeThirty > Moderate 0.002670340 0.08325396 0.014506395 0.02025858 > 0.0006587898 > Severe 0.006433581 0.12665278 0.005216581 0.02352202 > 0.0035612114 > > I AM NOT a statistician, so don't be baffled by a silly question! I this > procedure correct?
There's at least a factor of 2 missing for a two-tailed p value. It is usually a mistake to use the t-distribution for what is really a z-statistic; for aggregated data, it can be a very bad mistake. However, it's not really an R question, and you obviously know where to find stackexchange... (local, professional advice would be even better, though.) -- Peter Dalgaard, Professor, Center for Statistics, Copenhagen Business School Solbjerg Plads 3, 2000 Frederiksberg, Denmark Phone: (+45)38153501 Email: pd....@cbs.dk Priv: pda...@gmail.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.
