qualval: Test for qualitative interactions from estimation

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.

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".

Value

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.

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.

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.

Examples

Run this code

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

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