mstFREQ: Analysis of Multisite Randomised Education Trials using...

Description Usage Arguments Value Examples

View source: R/mstFreq.R

Description

mstFREQ performs analysis of multisite randomised education trials using a multilevel model under a frequentist setting.

Usage

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mstFREQ(formula, random, intervention, baseln, nPerm, data, seed, nBoot)

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.

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 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.

nPerm

number of permutations required to generate permutated p-value.

data

data frame containing the data to be analysed.

seed

seed required for bootstrapping and permutation procedure, if not provided default seed will be used.

nBoot

number of bootstraps required to generate bootstrap confidence intervals.

Value

S3 object; a list consisting of

Examples

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if(interactive()){

data(mstData)

########################################################
## MLM analysis of multisite trials + 1.96SE ##
########################################################

output1 <- mstFREQ(Posttest~ Intervention+Prettest,random="School",
		intervention="Intervention",data=mstData)


### Fixed effects
beta <- output1$Beta
beta

### Effect size
ES1 <- output1$ES
ES1

## Covariance matrix
covParm <- output1$covParm
covParm

### plot random effects for schools

plot(output1)

###############################################
## MLM analysis of multisite trials          ##	 
## with bootstrap confidence intervals       ##
###############################################

output2 <- mstFREQ(Posttest~ Intervention+Prettest,random="School",
		intervention="Intervention",nBoot=1000,data=mstData)

tp <- output2$Bootstrap
### Effect size

ES2 <- output2$ES
ES2

### plot bootstrapped values 

plot(output2, group=1)

#######################################################################
## MLM analysis of mutltisite trials with permutation p-value##
#######################################################################

output3 <- mstFREQ(Posttest~ Intervention+Prettest,random="School",
		intervention="Intervention",nPerm=1000,data=mstData)

ES3 <- output3$ES
ES3

#### plot permutated values 

plot(output3, group=1)
}

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