´╗┐´╗┐ GESIS Training Courses
user_jsdisabled
Search

Scientific Coordination

Dr.
Sebastian E. Wenz
Tel: +49 221 47694-159

Administrative Coordination

Angelika Ruf
Tel: +49 221 47694-162

Week 3: Using Simulation Studies to Evaluate Statistical Methods

About
Location:
Online via Zoom
 
General Topics:
Course Level:
Format:
Software used:
Duration:
Language:
Fees:
Students: 500 €
Academics: 750 €
Commercial: 1500 €
 
Keywords
Additional links
Lecturer(s): Dr. Tim Morris, Dr. Matteo Quartagno

About the lecturer - Dr. Tim Morris

About the lecturer - Dr. Matteo Quartagno

Course description

Simulation studies are computer experiments that generate data by pseudo-random sampling. The aim of a simulation study is 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 five-day course 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 participants. The course is 'bilingual', with computer code to support R and Stata users, with one lecturer expert in each.


Target group

Participants who will find the course useful:
  • 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 participants will:
  • Understand the rationale for simulation studies and their limitations
  • Appreciate the importance of careful planning
  • Have the tools to write and debug simple simulation studies in R or Stata
  • Know how to analyse simulation studies
  • Present methods and results for publication
  •  
     
    Organisational Structure of the Course:
    Each morning and afternoon will involve a lecture followed by a practical session.
     
    Lectures will be interactive, and we welcome participants asking questions or discussing examples they have seen.
     
    Practical sessions will be a mix of discussion-based and computer-based. One of the main practical tasks will be for participants to design, code, execute, analyse and report back on a simple simulation study which we will introduce. We will ask participants to work in small groups to work together on ideas and to critique each other's. The lecturers will be on-hand to facilitate discussions, to discuss participants' more general questions and for individual consultation during these sessions. Participants are invited to send examples of simulation studies that are published or that they are working on, to be discussed during the lectures.


    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:
    None. GESIS will provide participants with access to the statistical software package used in the course (i.e., Stata and/or R). Participants may also use their own laptop, if Stata (version 15 or later) or R (version 4.1.0 or later) are installed.