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-rw-r--r--man/anova.saem.mmkin.Rd3
-rw-r--r--man/logLik.saem.mmkin.Rd4
-rw-r--r--man/saem.Rd16
3 files changed, 19 insertions, 4 deletions
diff --git a/man/anova.saem.mmkin.Rd b/man/anova.saem.mmkin.Rd
index 8f9cb241..ab6022bc 100644
--- a/man/anova.saem.mmkin.Rd
+++ b/man/anova.saem.mmkin.Rd
@@ -31,5 +31,6 @@ only be done for nested models.}
an "anova" data frame; the traditional (S3) result of anova()
}
\description{
-Anova method for saem.mmkin objects
+Generate an anova object. The method to calculate the BIC is that from
+the saemix package. As in other prominent anova methods, models are sorted
}
diff --git a/man/logLik.saem.mmkin.Rd b/man/logLik.saem.mmkin.Rd
index 8ea3426f..603f4607 100644
--- a/man/logLik.saem.mmkin.Rd
+++ b/man/logLik.saem.mmkin.Rd
@@ -7,6 +7,10 @@
\method{logLik}{saem.mmkin}(object, ..., method = c("lin", "is", "gq"))
}
\arguments{
+\item{object}{The fitted \link{saem.mmkin} object}
+
+\item{\dots}{Passed to \link[saemix:logLik]{saemix::logLik.SaemixObject}}
+
\item{method}{Passed to \link[saemix:logLik]{saemix::logLik.SaemixObject}}
}
\description{
diff --git a/man/saem.Rd b/man/saem.Rd
index 2b9199dd..d7b04691 100644
--- a/man/saem.Rd
+++ b/man/saem.Rd
@@ -82,6 +82,13 @@ automatic choice is not desired}
default, uncorrelated random effects are specified for all degradation
parameters.}
+\item{covariates}{A data frame with covariate data for use in
+'covariate_models', with dataset names as row names.}
+
+\item{covariate_models}{A list containing linear model formulas with one explanatory
+variable, i.e. of the type 'parameter ~ covariate'. Covariates must be available
+in the 'covariates' data frame.}
+
\item{no_random_effect}{Character vector of degradation parameters for
which there should be no variability over the groups. Only used
if the covariance model is not explicitly specified.}
@@ -142,10 +149,13 @@ f_mmkin_parent <- mmkin(c("SFO", "FOMC", "DFOP"), ds, quiet = TRUE)
f_saem_sfo <- saem(f_mmkin_parent["SFO", ])
f_saem_fomc <- saem(f_mmkin_parent["FOMC", ])
f_saem_dfop <- saem(f_mmkin_parent["DFOP", ])
+anova(f_saem_sfo, f_saem_fomc, f_saem_dfop)
+anova(f_saem_sfo, f_saem_dfop, test = TRUE)
illparms(f_saem_dfop)
-update(f_saem_dfop, covariance.model = diag(c(1, 1, 1, 0)))
-AIC(f_saem_dfop)
+f_saem_dfop_red <- update(f_saem_dfop, no_random_effect = "g_qlogis")
+anova(f_saem_dfop, f_saem_dfop_red, test = TRUE)
+anova(f_saem_sfo, f_saem_fomc, f_saem_dfop)
# The returned saem.mmkin object contains an SaemixObject, therefore we can use
# functions from saemix
library(saemix)
@@ -157,7 +167,7 @@ plot(f_saem_fomc$so, plot.type = "vpc")
f_mmkin_parent_tc <- update(f_mmkin_parent, error_model = "tc")
f_saem_fomc_tc <- saem(f_mmkin_parent_tc["FOMC", ])
-compare.saemix(f_saem_fomc$so, f_saem_fomc_tc$so)
+anova(f_saem_fomc, f_saem_fomc_tc, test = TRUE)
sfo_sfo <- mkinmod(parent = mkinsub("SFO", "A1"),
A1 = mkinsub("SFO"))

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