Description Usage Arguments Value Examples
View source: R/eefAnalytics_03_2017.r
srtFREQ
perfoms analysis of educational trials under the assumption of independent errors among pupils.
This can also be used with schools as fixed effects.
1 |
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. |
S3 object; a list consisting of
Beta
. Estimates and confidence intervals for the predictors specified in the model.
ES
. Hedges' g effect size for the intervention(s). If nBoot is not specified, the confidence intervals are 95
sigma2
. Residual variance.
Perm
. A vector containing permutated effect sizes under null hypothesis. It is produced only if nPerm
is specified.
Bootstrap
. A vector containing bootstrapped effect sizes. It is prduced only if nBoot
is specified.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 | 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)
}
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