caceSRTBoot: CACE Analysis of Simple Randomised Education Trials.

In eefAnalytics: Analysing Education Trials

Description

caceSRTBoot performs exploraty CACE analysis of simple randomised education trials.

Usage

caceSRTBoot(formula, intervention, compliance, nBoot, data)

Arguments

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.
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 non-parametric bootstraps. Default is NULL.
data	data frame containing the data to be analysed.

Value

S3 mcpi object; a list consisting of

• CACE. Estimates of CACE adjusted effect sizes based on pre-specified thresholds. Only produced for threshold with atleast 50

• Compliers Percentage of pupils that achieved a pre-specified threshold of compliance.

Examples

if(interactive()){

data(mstData)
############# weighted ITT ####################################
caceOutput3<- caceSRTBoot(Posttest~ Prettest+ Intervention,
			intervention="Intervention",
			compliance = "Percentage_Attendance",nBoot=1000,data=mstData)

cace <- caceOutput3$CACE
cace

Complier <- caceOutput3$Compliers
Complier 

### visualising CACE effect size

plot(caceOutput3)
}

Example output

Warning message:
no DISPLAY variable so Tk is not available 

eefAnalytics documentation built on May 31, 2017, 4:17 a.m.