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siman.sthlp
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{smcl}
{* *! version 0.11 11oct2024}{...}
{vieweralsosee "simsum (if installed)" "simsum"}{...}
{viewerjumpto "Syntax" "siman##syntax"}{...}
{viewerjumpto "Description" "siman##description"}{...}
{viewerjumpto "Data and formats" "siman##formats"}{...}
{viewerjumpto "Examples" "siman##examples"}{...}
{viewerjumpto "Details" "siman##details"}{...}
{viewerjumpto "References" "siman##refs"}{...}
{viewerjumpto "Authors and updates" "siman##updates"}{...}
{title:Title}
{phang}
{bf:siman} {hline 2} Suite of commands for analysing the results of simulation studies and producing graphs
{title:Syntax}{marker syntax}
{p2colset 9 29 29 0}{...}
{pstd}Get started
{p2col:{bf:{help siman setup}}}Sets up the user’s raw simulation data (estimates data set) in the format required by siman
{pstd}Analyses
{p2col:{bf:{help siman analyse}}}Creates a performance measures data set from the estimates data set, and can hold both in memory
{pstd}Descriptive tables and figures
{p2col:{bf:{help siman describe}}}Describes the simulation data
{p2col:{bf:{help siman table}}}Tabulates the computed performance measures data
{pstd}Graphs of estimates data
{p2col:{bf:{help siman swarm}}}Swarm plot: plots the estimates or the standard errors against method
{p2col:{bf:{help siman scatter}}}Scatter plot: plots the estimates versus their standard errors
{p2col:{bf:{help siman comparemethodsscatter}}}Scatter compare methods plot: compares estimates and/or standard errors between methods on a set of scatterplots
{p2col:{bf:{help siman blandaltman}}}Bland-Altman plot: compares estimates between methods
by plotting the difference of the estimates against the mean of the estimates (or similarly for the standard errors), with a selected method as the comparator
{p2col:{bf:{help siman zipplot}}}Zip plot: shows all of the confidence intervals for each data-generating mechanism and analysis method
{pstd}Graphs of performance measures data
{p2col:{bf:{help siman lollyplot}}}Lollypop plot: compares various performance measure estimates between methods, with Monte Carlo 95% confidence intervals
{p2col:{bf:{help siman nestloop}}}Nested loop plot: compares a single performance measure between methods across a complex set of data generating mechanisms (e.g. a full factorial simulation study)
{pstd}Utilities
{p2col:{bf:siman which}}report the version number and date for each {cmd:siman} subcommand
{pstd}Subcommands may be abbreviated to 3 or more characters, and {cmd:comparemethodsscatter} may be abbreviated to {cmd:cms}.
{marker description}{...}
{title:Description}
{pstd}
{cmd:siman} is a suite of programs for importing estimates data, analysing the results of simulation studies and graphing the data.
{marker formats}{...}
{title:Data and formats}
{pstd}{cmd:siman} uses 2 data set types.
{pstd}An {bf:estimates data set} contains summaries of results from individual repetitions of a simulation experiment.
Such data may consist of, for example, parameter estimates, standard errors, degrees of freedom,
confidence intervals, p-values, and more.
They typically arise from multiple data generating mechanisms (DGMs) and multiple methods of analysis, and relate to multiple targets or estimands.
They are read in by {bf:{help siman setup}}.
{pstd}A {bf:performance measures data set}
is produced by {bf:{help siman analyse}} which calculates performance measures including Monte Carlo error,
for use with {bf:{help siman table}}, {bf:{help siman lollyplot}} and {bf:{help siman nestloop}}.
The performance measures data sety is usually appended to the estimates data set.
{marker examples}{...}
{title:Examples}
{pstd} An example estimates data set with 3 DGMs (MCAR, MAR, MNAR) and 3 methods (Full, CCA, MI) with 1000 repetitions named simpaper1.dta available on the {cmd: siman} GitHub repository {browse "https://github.com/UCL/siman/":here}.
{phang} Open the data set and set it up in {cmd:siman}
{phang}. {stata "use https://raw.githubusercontent.com/UCL/siman/master/testing/data/simpaper1.dta, clear"}
{phang}. {stata "siman setup, rep(repno) dgm(dgm) method(method) est(b) se(se) true(0)"}
{phang}Plot some descriptive graphs of the estimates data
{phang}. {stata "siman swarm"}
{phang}. {stata "siman scatter"}
{phang}. {stata "siman comparemethodsscatter if dgm == 3"}
{phang}. {stata "siman blandaltman if dgm == 3"}
{phang}. {stata "siman zipplot"}
{pstd}Create and graph performance measures
{phang}. {stata "siman analyse"}
{phang}. {stata "siman lollyplot, bygr(legend(pos(3)))"}
{title:Details}{marker details}
{pstd}{bf:{help siman analyse}} requires the additional program {bf:{help simsum}}.
{title:References}{marker refs}
{phang}{marker Morris++19}Morris TP, White IR, Crowther MJ.
Using simulation studies to evaluate statistical methods.
Statistics in Medicine 2019; 38: 2074-2102.
{browse "https://onlinelibrary.wiley.com/doi/10.1002/sim.8086"}
{title:Authors and updates}{marker updates}
{pstd}Ella Marley-Zagar, MRC Clinical Trials Unit at UCL, London, UK.
{pstd}Ian White, MRC Clinical Trials Unit at UCL, London, UK.
Email {browse "mailto:[email protected]":[email protected]}.
{pstd}Tim Morris, MRC Clinical Trials Unit at UCL, London, UK.
Email {browse "mailto:[email protected]":[email protected]}.
{title:See Also}
{pstd}{help simsum} (if installed)