Stata as a numerical tool for scientific thought experiments: A tutorial with worked examples
Theresa Wimberley
Department of Economics and Business
National Centre for Register-Based Research
Aarhus University
Aarhus, Denmark
[email protected]
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Erik Parner
Department of Public Health
Biostatistics
Aarhus University
Aarhus, Denmark
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Henrik Stovring
Department of Public Health
Biostatistics
Aarhus University
Aarhus, Denmark
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Abstract. Thought experiments based on simulation can be used to explain the
impact of the chosen study design, statistical analysis strategy, or the sensitivity
of results to fellow researchers. In this article, we demonstrate with two examples
how to implement quantitative thought experiments in Stata. The first example
uses a large-sample approach to study the impact on the estimated effect size of
dichotomizing an exposure variable at different values. The second example uses
simulations of datasets of realistic size to illustrate the necessity of using sampling
fractions as inverse probability weights in statistical analysis for protection against
bias in a complex sampling design. We also give a brief outline of the general steps
needed for implementing quantitative thought experiments in Stata. We demonstrate
how Stata provides programming facilities for conveniently implementing
such thought experiments, with the advantage of saving researchers time, speculation,
and debate as well as improving communication in interdisciplinary research
groups.
View all articles by these authors:
Theresa Wimberley, Erik Parner, Henrik Stovring
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quantitative thought experiments, simulations
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