srtFREQ: Analysis of Simple Randomised Education Trial using Linear...

Description Usage Arguments Value Examples

View source: R/eefAnalytics_03_2017.r

Description

srtFREQ perfoms analysis of educational trials under the assumption of independent errors among pupils. This can also be used with schools as fixed effects.

Usage

1
srtFREQ(formula, intervention, nBoot = NULL, nPerm = NULL, 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

nBoot

number of bootstraps required to generate bootstrap confidence interval. Default is NULL.

nPerm

number of permutations required to generate permutated p-value. Default is NULL.

data

data frame containing the data to be analysed.

Value

S3 object; a list consisting of

Examples

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if(interactive()){

data(mstData)

###################################################################
## Analysis of simple randomised trials using Hedges Effect Size ##
###################################################################

output1 <- srtFREQ(Posttest~ Intervention+Prettest,
		intervention="Intervention",data=mstData )
ES1 <- output1$ES
ES1

###################################################################
## Analysis of simple randomised trials using Hedges Effect Size ## 
## with Permutation p-value                                      ##
###################################################################

output2 <- srtFREQ(Posttest~ Intervention+Prettest,
		intervention="Intervention",nPerm=1000,data=mstData )

ES2 <- output2$ES
ES2


#### plot permutated values

plot(output2, group=1)



###################################################################
## Analysis of simple randomised trials using Hedges Effect Size ##
## with non-parametric bootstrap confidence intervals            ##
###################################################################

output3 <- srtFREQ(Posttest~ Intervention+Prettest,
		intervention="Intervention",nBoot=1000,data=mstData)

ES3 <- output3$ES
ES3

### plot bootstrapped values

plot(output3, group=1)

####################################################################
## Analysis of simple randomised trials using Hedges' effect size  ##
##  with schools as fixed effects                                  ##
####################################################################

output4 <- srtFREQ(Posttest~ Intervention+Prettest+as.factor(School),
		intervention="Intervention",data=mstData )

ES4 <- output4$ES
ES4

####################################################################
## Analysis of simple randomised trials using Hedges' effect size ##
## with schools as fixed effects and with permutation p-value     ##
####################################################################

output5 <- srtFREQ(Posttest~ Intervention+Prettest+as.factor(School),
		intervention="Intervention",nPerm=1000,data=mstData )

ES5 <- output5$ES
ES5

#### plot permutated values

plot(output5, group=1)

####################################################################
## Analysis of simple randomised trials using Hedges' effect size ##
## with schools as fixed effects and with permutation p-value      ##
####################################################################

output6 <- srtFREQ(Posttest~ Intervention+Prettest+as.factor(School),
		intervention="Intervention",nBoot=1000,data=mstData)

ES6 <- output6$ES
ES6 

### plot bootstrapped values

plot(output6, group=1)
}

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

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