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

In germaine86/eefAnalytics_v10: Robust Analytical Methods for Evaluating Educational Interventions using Randomised Controlled Trials Designs

Description

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

Usage

srtFREQ(formula, intervention, baseln, nBoot, nPerm, seed, data)

Arguments

formula	the model to be analysed is of the form y~x1+x2+.... Where y is the outcome variable and Xs are the independent variables.
intervention	a string variable specifying the "intervention variable" as appearing in the formula and the data. See example below.
baseln	A string variable allowing the user to specify the reference category for intervention variable. When not specified, the first level will be used as a reference.
nBoot	number of bootstraps required to generate bootstrap confidence intervals.
nPerm	number of permutations required to generate permutated p-value.
seed	seed required for bootstrapping and permutation procedure, if not provided default seed will be used.
data	data frame containing the data to be analysed.

Value

S3 object; a list consisting of

• Beta: Estimates and confidence intervals for the variables specified in the model.

• ES: Conditional Hedges'g effect size and its 95

• sigma2: Residual variance.

• Perm: A "nPerm x w" matrix containing permutated effect sizes using residual variance. "w" denotes number of intervention. "w=1" for two arm trial and "w=2" for three arm trial excluding the control group. It is produced only if nPerm is specified.

• Bootstrap: A "nBoot x w" matrix containing the bootstrapped effect sizes using residual variance. "w" denotes number of intervention. "w=1" for two arm trial and "w=2" for three arm trial excluding the control group. It is produced only if nBoot is specified.

• Unconditional: A list of unconditional effect size, sigma2, Perm and Bootstrap obtained based on variances from the unconditional model (model with only intercept as fixed effect).

Examples

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)
}

germaine86/eefAnalytics_v10 documentation built on Feb. 20, 2021, 12:13 a.m.