Goodness-of-fit tests for npde
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, which = "npde", ...)
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 |
which |
character string giving (used by printgoftest) |
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:
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.
data(theopp) data(simtheopp) #' # Calling autonpde with dataframes x<-autonpde(theopp,simtheopp,1,3,4,boolsave=FALSE) gof.test(x)
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