Description Usage Arguments Value Examples
View source: R/eefAnalytics_03_2017.r
caceCRTBoot
performs exploratoty CACE analysis of cluster randomised education trials.
1 | caceCRTBoot(formula, random, intervention, compliance, nBoot, data)
|
formula |
the model to be analysed. It is of the form y ~ x1+x2+.... Where y is the outcome variable and Xs are the predictors. |
random |
a string variable specifying the "clustering variable" as contained in the data. See example below |
intervention |
a string variable specifying the "intervention variable" as appeared in the formula. See example below |
compliance |
a string variable specifying the "compliance variable" as contained in the data. The data must be in percentages ranging from 0 - 100. |
nBoot |
number of bootstraps required to generate bootstrap confidence interval. Default is NULL. |
data |
data frame containing the data to be analysed. |
S3 object; a list consisting of
CACE
. Estimates of CACE adjusted effect sizes based on pre-specified thresholds. Only produced for threshold with at least 50
Compliers
. Percentage of pupils that achieved a pre-specified threshold of compliance.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 | if(interactive()){
data(crtData)
######################## weighted ITT ##############################################
caceOutput<- caceCRTBoot(Posttest~ Prettest+ Intervention,
random="School",intervention="Intervention",
compliance = "Percentage_Attendance",nBoot=1000,data=crtData)
cace <- caceOutput$CACE
cace
Complier <- caceOutput$Compliers
Complier
### visualising CACE effect size
plot(caceOutput)
}
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