Description Usage Arguments Value Examples
mstFREQ
performs analysis of multisite randomised education trials using a multilevel model under a frequentist setting.
1 |
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. |
S3 object; a list consisting of
Beta
: Estimates and confidence intervals for variables specified in the model.
ES
: Conditional Hedge's g effect size (ES) and its 95
covParm
: A list of variance decomposition into between cluster variance-covariance matrix (schools and school by intervention) and within cluster variance (Pupils). It also contains intra-cluster correlation (ICC).
SchEffects
: A vector of the estimated deviation of each school from the intercept and intervention slope.
Perm
: A "nPerm x 2w" matrix containing permutated effect sizes using residual variance and total 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 when nPerm
is specified.
Bootstrap
: A "nBoot x 2w" matrix containing the bootstrapped effect sizes using residual variance (Within) and total variance (Total). "w" denotes number of intervention. "w=1" for two arm trial and "w=2" for three arm trial excluding the control group. It is only prduced when nBoot
is specified.
Unconditional
: A list of unconditional effect sizes, covParm, Perm and Bootstrap obtained based on variances from the unconditional model (model with only the intercept as a fixed effect).
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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)
}
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