qualval: Test for qualitative interactions from estimation

In QualInt: Test for Qualitative Interactions

Description

Test for qualitative interactions between treatment effects and patient subgroups from the estimated treatment effect and its standard error directly. Output all the results related with qualitative interaction tests as a "qualint" object, just like the "qualint" function. Two common tests for qualitative interactions are included: IBGA and LRT, among which IBGA is the default. Users need to input the estiamted treatment effect and its standard erro themselves, therefore could accommodate any types of responses.

Usage

qualval(effect, se, test = c("IBGA", "LRT"), alpha = 0.05,
  plotout = FALSE)

Arguments

effect	treatment effects. A numeric vector as the estimated (for pvalue) or designed (for power) treatment effects for different patient subgroups.
se	standard error of estimated treatmen effects. A numeric vector as the standard error for the estimated treatment effects.
test	testing method. Choose either "IBGA" (interval based graphical approach) or "LRT" (Gail Simon likelihood ratio test).
alpha	significance level. The type I error for qualitative interaction tesing. The default is 0.05.
plotout	whether output the plot or not for test = "IBGA". There is no plot output for test = "LRT".

Details

This function is a more generalized version of qualint in the sense that it could be used for any types of responses. However, comepared to qualint, the user needs to input the estimated (for pvalue) or designed (for power ) treatment effects and its standard error by themselves to use this function. It gives more freedom and allows users to choose the method they prefer before testing for qualitative interactions.

Value

An object with S3 class "qualint".

call	the call that produces this object.
n	the sample size for each treatment in each subgroup.
type	response type.
alpha	significance level for the test.
treatment	treatment factors.
reference	reference treatment used for the comparison.
nsbp	the number of patient subgroups.
subgroup	subgroup factors.
scale	the scale type for treatment effects (see above).
effect	estimated treatment effects.
se	standard error of treatment effects estimators.
LowerCI	the lower limit of the confidence interval.
UpperCI	the upper limit of the confidence interval.
test	testing method used here, either "IBGA" or "LRT".
index	the testing index used only for test = "IBGA".
cvalue	the critical value used only for test = "LRT".
LowerTI	the lower limit of the testing interval used when test = "IBGA".
UpperTI	the upper limit of the testing interval used when test = "IBGA".
pvalue	the pvalue for qualitative interactions.
power	the power based on the observed data.
nobs	the number of subjects.
missing	the indexes of subjects with missing values.

Author(s)

Lixi Yu, Eun-Young Suh, Guohua (James) Pan
Maintainer: Lixi Yu [e-mail]

References

Gail and Simon (1985), Testing for qualitative interactions between treatment effects and patient subsets, Biometrics, 41, 361-372.

Pan and Wolfe (1993), Tests for generalized problems of detecting qualitative interaction, Technical Report No. 526, Department of Statistics, The Ohio State University.

Pan and Wolfe (1997), Test for qualitative interaction of clinical significance, Statistics in Medicine, 16, 1645-1652.

See Also

print.qualint, coef.qualint, plot.qualint, qualint

Examples

test9 <- qualval(effect = c(1.0, 0.5, -2.0), se = c(0.86, 0.64, 0.32))
print(test9)
plot(test9)

QualInt documentation built on May 1, 2019, 11 p.m.