So-called type-III tests violate marginality, testingĮach term in the model after all of the others. Testing each term after all others, except ignoring the term's higher-order relatives Type-II tests are calculated according to the principle of marginality, The designations "type-II" and "type-III" are borrowed from SAS, but theĭefinitions used here do not correspond precisely to those employed by SAS. If you don't understand this issue, then you probably shouldn't use Anova for type-III tests. Type-II tests are invariant with respect to (full-rank) contrast coding. In a model that contains factors, numeric covariates, and interactions, main-effect tests for factors will be for differences over the origin. Orthogonal in the row-basis of the model, such as those produced by contr.sum, contr.poly, or contr.helmert, but not by the defaultĬeatment. Test.statistic=c("Chisq", "F"), vcov.=vcov(mod, complete=FALSE),īe careful of type-III tests: For a traditional multifactor ANOVA model with interactions, for example, these tests will normally only be sensible when using contrasts that, for different terms, are Test.statistic=c("Chisq", "F"), vcov.=vcov(mod, complete=FALSE), singular.ok. Vcov.=vcov(mod, complete=FALSE), singular.ok. Print(x, digits = max(getOption("digits") - 2L, 3L),Īs.ame(x, row.names, optional, by=c("response", "term"). Summary(object, test.statistic, univariate=object$repeated, Test.statistic=c("Pillai", "Wilks", "Hotelling-Lawley", "Roy").) Idata, idesign, icontrasts=c("contr.sum", "contr.poly"), imatrix, Vcov.=vcov(mod, complete=TRUE), singular.ok. Linear and generalized linear mixed-effects models. Wald chi-square tests are provided for fixed effects in Or Wald tests are provided for Cox models. Various test statistics are provided for multivariate Likelihood-ratio chisquare, Wald chisquare, or F-tests are calculated įor multinomial logit and proportional-odds logit models, likelihood-ratio Models, F-tests are calculated for generalized linear models, Models with a linear predictor and asymptotically normal coefficients (see details below). Lme in the nlme package, and (by the default method) for most Svyglm and svycoxph (in the survey package), rlm (in the MASS package), Package), coxph (in the survival package), Model objects produced by lm, glm, multinom Anova: Anova Tables for Various Statistical Models DescriptionĬalculates type-II or type-III analysis-of-variance tables for
0 Comments
Leave a Reply. |
AuthorWrite something about yourself. No need to be fancy, just an overview. ArchivesCategories |