Generation of data with specific marginal risk difference

  • Kazem Mohammad Professor, Department of Epidemiology and Biostatistics, School of Public Health, Tehran University of Medical Sciences, Tehran, Iran
  • Mohammad Ali Mansournia Assistant Professor, Department of Epidemiology and Biostatistics, School of Public Health, Tehran University of Medical Sciences, Tehran, Iran
  • safoora gharibzadeh Department of Epidemiology and Biostatistics, School of Public Health, Tehran University of Medical Sciences, Tehran, Iran
Keywords: Data systems, Risk ratio, Causality, Computer simulation, Monte Carlo method

Abstract

Background & Aim: Simulation studies are important statistical tools to investigate the performance of statistical models in specific situations. For a binary outcome and exposure, one of the most important statistical measures will be the risk difference (RD). To assess the quality of estimators in estimating the effect of the exposure, a data set with a specific effect measure is require.Methods & Materials: Monte Carlo simulation can be helpful in situations when there is a proper data  generating  process.  In  this  paper,  another  technique  will  be  presented  to  generate  data  with specific marginal risk difference (MRD). Results: Convergence of simulation methods in the same scenario reached in a few iterations using the proposed method. Conclusion:  The  proposed  method  is  recommended  over  the  current  method  due  to  less  time consumption; this issue is important in studies with different scenarios. 

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Published
2018-07-11
How to Cite
1.
Mohammad K, Mansournia MA, gharibzadeh safoora. Generation of data with specific marginal risk difference. jbe. 3(3-4):76-2.
Section
Original Article(s)