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\title{Methods for function anova in package "bild"}
\description{ Compute an analysis deviance table for two fitted model objects. }

\S4method{anova}{bild}(object, ..., test = TRUE, correct = FALSE)
  \item{object}{an object of class \code{\link[=bild-class]{bild}}.}
  \item{...}{an object of class \code{\link[=bild-class]{bild}}.}
  \item{test}{an optional logical value controlling whether likelihood ratio tests 
  should be used to compare the fitted models represented by \code{object} and by \code{y}. The default is TRUE. }  
  \item{correct}{an optional logical value controlling whether the p-value of the likelihood ratio test 
  must be corrected. The default is FALSE.}  
\code{correct} = TRUE is used to test the presence of a random intercept term and the solution proposed by Self and Liang (1987) is adopted 
only to the p-value. }

The comparison between two models by anova will only be valid if they are fitted to the same dataset.}

\item{\code{signature(object = "ANY")}:}{Generic function.}
\item{\code{signature(object="bild")}:}{Anova for \code{\link{bild}} object.} 

\references{Self, Steven G. and Liang, Kung-Yee (1987). Asymptotic properties of maximum likelihood estimators and likelihood 
ratio tests under nonstandard conditions. \emph{Journal of the American Statistical Association}, 82, 605-610. }


#####  data= locust

locust1 <- bild(move~(time+I(time^2))*feed*sex, data=locust, aggregate=feed, start=NULL, dependence="MC1")

locust2 <- bild(move~(time+I(time^2))*feed, data=locust, aggregate=feed, start=NULL, dependence="MC1")


locust3 <- bild(move~(time+I(time^2))*feed, data=locust, aggregate=feed, start=NULL, dependence="MC2")


#####  data= muscatine

# we decompose the time effect in orthogonal components
muscatine$time1 <- c(-1, 0, 1)
muscatine$time2 <- c(1, -2, 1)

musc1 <- bild(obese ~ time1 , data = muscatine, time = "time1", dependence = "MC1")

musc1r <- bild(obese ~ time1 , data = muscatine, time = "time1", dependence = "MC1R")



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