My point was just that the situation in a cumulative link model is not much different from a binomial glm - the binomial glm is even a special case of the clm with only two response categories. And just like summary(glm(...., family=binomial)) reports z-values and computes p-values by using the normal distribution as reference, one can do the same in a cumulative link model by applying the same asymptotic arguments.
In both models the variance is determined implicitly by the mean, so a t-distribution is never involved. Cheers, Rune On 25 June 2012 11:05, Prof Brian Ripley <rip...@stats.ox.ac.uk> wrote: > On 25/06/2012 09:32, Rune Haubo wrote: >> >> According to standard likelihood theory these are actually not >> t-values, but z-values, i.e., they asymptotically follow a standard >> normal distribution under the null hypothesis. This means that you > > > Whose 'standard'? > > It is conventional to call a value of t-like statistic (i.e. a ratio of the > form value/standard error) a 't-value'. And that is nothing to do with > 'likelihood theory' (t statistics predate the term 'likelihood'!). > > The separate issue is whether a t statistic is even approximately > t-distributed (and if so, on what df?), and another is if it is > asymptotically normal. For the latter you have to say what you mean by > 'asymptotic': we have lost a lot of the context, but as this does not appear > to be IID univariate observations: > > - 'standard likelihood theory' is unlikely to apply. > > - standard asymptotics may well not be a good approximation (in regression > modelling, people tend to fit more complex models to large datasets, which > is often why a large dataset was collected). > > - even for IID observations the derivation of the t distribution assumes > normality. > > The difference between a t distribution and a normal distribution is > practically insignificant unless the df is small. And if the df is small, > one can rarely rely on the CLT for approximate normality .... > > >> could use pnorm instead of pt to get the p-values, but an easier >> solution is probably to use the clm-function (for Cumulative Link >> Models) from the ordinal package - here you get the p-values >> automatically. >> >> Cheers, >> Rune >> >> On 23 June 2012 07:02, Bert Gunter <gunter.ber...@gene.com> wrote: >>> >>> This advice is almost certainly false! >>> >>> A "t-statistic" can be calculated, but the distribution will not >>> necessarily be student's t nor will the "df" be those of the rse. See, >>> for >>> example, rlm() in MASS, where values of the t-statistic are given without >>> p >>> values. If Brian Ripley says that p values cannot be straightforwardly >>> calculated by pt(), then believe it! >>> >>> -- Bert >>> >>> On Fri, Jun 22, 2012 at 9:30 PM, Özgür Asar <oa...@metu.edu.tr> wrote: >>> >>>> Michael, >>>> >>>> Try >>>> >>>> ?pt >>>> >>>> Best >>>> Ozgur >>>> >>>> -- >>>> View this message in context: >>>> >>>> http://r.789695.n4.nabble.com/significance-level-p-for-t-value-in-package-zelig-tp4634252p4634271.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 >>> >>> [[alternative HTML version deleted]] >>> >>> >>> ______________________________________________ >>> 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. >>> >> >> >> > > > -- > Brian D. Ripley, rip...@stats.ox.ac.uk > Professor of Applied Statistics, http://www.stats.ox.ac.uk/~ripley/ > University of Oxford, Tel: +44 1865 272861 (self) > 1 South Parks Road, +44 1865 272866 (PA) > Oxford OX1 3TG, UK Fax: +44 1865 272595 > > > ______________________________________________ > 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. -- Rune Haubo Bojesen Christensen Ph.D. Student, M.Sc. Eng. Phone: (+45) 45 25 33 63 Mobile: (+45) 30 26 45 54 DTU Informatics, Section for Statistics Technical University of Denmark, Build. 305, Room 122, DK-2800 Kgs. Lyngby, Denmark ______________________________________________ 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.