View source: R/NpdeRes-methods.R
gof.test | R Documentation |
Performs test on the selected variable (which=one of npde, pd or npd) or on a numeric vector
gof.test(object, parametric = TRUE, ...)
printgoftest(object, ...)
object |
an object (currently has methods for types numeric, NpdeRes and NpdeObject) |
parametric |
a boolean. If TRUE (default), parametric tests are performed |
... |
additional arguments passed on to the function; special arguments are |
If object is an NpdeObject and an argument covsplit=TRUE is given in ..., in addition to the global descriptive statistics and tests, tests will be performed for each covariate in which.cov
. This argument can be set in ...; barring an explicit specification, the component which.cov
of the prefs slot for a NpdeObject object will be used. The default value is which.cov="all"
, which produces tests for each covariate in the dataset. Two additional dataframes will then be present:
descriptive statistics and test p-values split by covariate and by categories
p-values split by covariate; for each covariate, two tests are performed: the first test is a correlation test for continuous covariates and a Chi-square test for categorical covariates; the second test is defined using the p-values of the global tests split by each category, and appling a Bonferroni correction to obtain an overall p-value (see PDF documentation for details)
The p.value elements is a named vector with four components:
p-value for the mean test (Wilcoxon test if parametric=FALSE, Student test if parametric=TRUE)
p-value for the variance test (parametric=FALSE, Fisher test if parametric=TRUE)
p-value for the distribution test (Shapiro-test for normality (npd, npde)/Kolmogorove-Smirnov test for uniformity)
p-value for the global test (combination of the mean, variance and distribution tests with a Bonferroni correction)
The p-values are adjusted using a Bonferroni correction: the raw p-values of the 3 individual tests are multiplied by 3, and the p-value for the global test is equal to the minimum of the adjusted p-values.
A list with the following elements:
mean
standard error of the mean
variance
standard error on variance
kurtosis (see kurtosis
)
skewness (see skewness
)
p-values for several tests (see below)
K. Brendel, E. Comets, C. Laffont, C. Laveille, and F. Mentre. Metrics for external model evaluation with an application to the population pharmacokinetics of gliclazide. Pharmaceutical Research, 23:2036–49, 2006.
K. Brendel, E. Comets, C. Laffont, and F. Mentre. Evaluation of different tests based on observations for external model evaluation of population analyses. Journal of Pharmacokinetics and Pharmacodynamics, 37:49–65, 2010.
kurtosis
, skewness
data(theopp)
data(simtheopp)
#' # Calling autonpde with dataframes
x<-autonpde(theopp,simtheopp,1,3,4,boolsave=FALSE)
gof.test(x)
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