srtfreq -- Effect Size calculation for Simple Randomised Trials

Syntax

srtfreq varlist [if] [in], intervention(interv_var) [options]

main

intervention() requires a factor variable identifying the intervention (arms) of the trial.

Model
seed(#) seed number; default is 1020252.

nperm(#) number of permutations; default is NULL.

nboot(#) number of bootstraps; default is NULL.

percentile percentile confidence interval for bootstrap.

basic basic confidence interval for bootstrap; default is percentile.

Reporting
noisily displays the calculation of conditional models.

nodot suppresses display of dots; default is one dot character every 10 replications.

paste attaches bootstrapped/permutated effect sizes on the existing dataset.

varlist and intervention() may contain factor-variable operators; see fvvarlist.

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.
The analysis produces Effect Size (ES) estimates for both conditional and unconditional model specifications in Simple Randomised Trials. It also allows for sensitivity analysis options such as permutations
and bootstraps.

Options

Model

seed(#) Sets seed number for permutations/bootstraps.

nperm(#) Specifies number of permutations required to generate permutated p-values; see Stored results.
If specified with paste, a list of generated variables attaches to the user's dataset containing the permutated effect sizes.

nboot(#) Specifies number of bootstraps required to generate the bootstrap confidence intervals.
If specified with paste, a list of generated variables attaches to the user's dataset containing the bootstrapped effect sizes.

percentile Specifies use of the percentile bootstrap confidence interval.

basic Specifies use of the basic (Hall's) bootstrap confidence interval; default is percentile.

Reporting

noisily Displays the permutated/bootstrapped conditional models' regression results as they occur.

nodot Suppresses display of dots indicating progress of permutations/bootstraps. Default is one dot character displayed for every block of 10 replications.

paste Attaches bootstrapped or permutated effect sizes to existing dataset if nperm (PermC/Unc_I#) or nboot (BootC/Unc_I#) has been specified,
where I# denotes number of interventions and C/Unc denotes Conditional/Unconditional estimates. Existing variables generated from previous use are replaced.

Examples

Setup:

. use mstData.dta

Simple model:

. srtfreq Posttest Prettest, int(Intervention)

Model using permutations including Schools as fixed effects with base level change:

. srtfreq Posttest Prettest i.School, int(ib(#2).Intervention) nperm(3000)

Model using permutations and bootstraps with three-arm intervention variable:

. srtfreq Posttest Prettest, int(Intervention2) nperm(3000) nboot(2000) noisily

Stored results

srtfreq stores the following in r():

Matrices

r(CondES) conditional Hedges’ g effect size and its 95% confidence intervals for the trial arm(s) in interv_var. If nboot is specified, CIs are replaced with bootstrapped CIs.

r(UncondES) unconditional effect size for the trial arm(s) in interv_var, obtained based on variance from the unconditional model (model with only the intercept as a fixed effect).

r(Beta) estimates and confidence intervals for variables specified in the model.

r(Sigma2) residual variance for conditional and unconditional models.

r(Pv) conditional and unconditional two-sided within and total effect size permutation p-values (available if nperm(#) has been selected).