|Significance testing for the coefficients of Quasi binomial or the quasi Poisson regression||R Documentation|
Significance testing for the coefficients of Quasi binomial or the quasi Poisson regression.
anova_propreg(mod, poia = NULL) anova_qpois.reg(mod, poia = NULL)
An object as returned by the "prop.reg" or the "qpois.reg" function.
If you want to test the significance of a single coefficient this must be a number. In this case, the "prop.reg" or the "qpois.reg" function contains this information. If you want more coefficients to be testes simultaneously, e.g. for a categorical predictor, then this must contain the positions of the coefficients. If you want to see if all coefficients are zero, like an overall F-test, leave this NULL.
Even though the name of this function starts with anova it is not an ANOVA type significance testing, but a Wald type.
A vector with three elements, the test statistic value, its associated p-value and the relevant degrees of freedom.
R implementation and documentation: Michail Tsagris <email@example.com> and Manos Papadakis <firstname.lastname@example.org>.
Papke L. E. & Wooldridge J. (1996). Econometric methods for fractional response variables with an application to 401(K) plan participation rates. Journal of Applied Econometrics, 11(6): 619-632.
McCullagh, Peter, and John A. Nelder. Generalized linear models. CRC press, USA, 2nd edition, 1989.
prop.reg, qpois.reg, univglms, score.glms, logistic_only
y <- rbeta(1000, 1, 4) x <- matrix(rnorm(1000 * 3), ncol = 3) a <- prop.reg(y, x) ## all coefficients are tested res<-anova_propreg(a) ## the first predictor variable is tested res<-anova_propreg(a, 2) a ## this information is already included in the model output ## the first and the second predictor variables are tested res<-anova_propreg(a, 2:3)
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