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Wiss. Koordination

Alisa Remizova

Administrative Koordination

Noemi Hartung

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Using Simulation Studies to Evaluate Statistical Methods

About
Location:
Online via Zoom
General Topics:
Data Analysis, Computational Social Science
Course Level:
Advanced
Format:
Workshop
Software used:
Stata, R
Duration:
4 days
Language:
English
Fees:
Student: 220 €
Academic: 330 €
Commercial: 660 €
 
Keywords
Simulation studies,  Monte Carlo simulation, Simulation design
Additional links
Lecturer(s): Matteo Quartagno, Tra My Pham

About the lecturer - Matteo Quartagno

About the lecturer - Tra My Pham

Course description

Please note that this workshop will be held on November 19 - 20  and November 26 - 27 ! Please go to the schedule for more details.
Simulation studies are computer experiments that generate data by pseudo-random sampling. The aim is typically to understand the statistical properties of methods and to compare different methods. They are particularly useful when analytic results are not available. As such, simulation studies are a key tool for both methodological and applied quantitative researchers. To produce a meaningful simulation study, careful thought is required. This four-session workshop outlines the rationale for using simulation studies and offers guidance for design, execution, analysis, reporting, and presentation. The course will be practically focused: so concepts will be described in terms of examples, tested out, and there will be opportunities for critical discussion of published simulation studies or those being planned by you. The course is 'bilingual', with computer code to support R and Stata users, with one lecturer expert in each.
 
 
Organizational Structure of the Course
Each afternoon will involve a lecture followed by a practical session.
 
All lectures will be delivered 'live' and are interactive: we welcome you asking questions or discussing examples you have seen, and will stop for polls and discussions.
 
Practical sessions will be a mix of discussion-based and computer-based. One of the main practical tasks will be for you to design, code, execute, analyze and report back on a simple simulation study that we will introduce. We will ask you to work in small groups to work together and to critique each other's ideas. We will be on-hand to facilitate discussions, discuss your general questions and for individual consultation during these sessions. You are invited to send examples of simulation studies that are published or that you are working on, to be discussed during the lectures.
 


Target group

You will find the course useful if you are:
  • Methodological or applied quantitative researchers who need to evaluate the statistical properties of one or more methods.
  • PhD students using simulation studies.
  • Readers of methodology articles which evaluate methods by simulation.


Learning objectives

By the end of the course, youwill:
  • Understand the rationale for simulation studies, and their limitations.
  • Appreciate the importance of careful planning.
  • Have the knowledge to write and debug simple simulation studies in R or Stata.
  • Know how to analyze simulation studies.
  • Be able to present and critique methods and results of simulation studies to prepare for publication.


Prerequisites

Training in quantitative science.
Familiarity with R and/or Stata to the level of being able to:
  • run regression commands and access results,
  • use loops,
  • write a simple program (Stata) or function (R),
  • produce simple graphics.
 
 
Software requirements
You will need your own laptop with either Stata (version 15 or later) or R (version 4.3.0 or later) installed. If you need Stata, please let us know the latest two weeks in advance of the course start so that we can take care of it.


Schedule

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