Non-Randomised and Quasi-Experimental Designs


Often, random allocation of the intervention under study is not possible and in such cases the primary challenge for investigators is to control confounding.

Members of the Centre for Evaluation organised a multi-disciplinary symposium in London in 2006 to discuss barriers to randomisation, review the issues, and identify practical solutions. The following two papers summarise the arguments presented, drawing on examples from high- and low-income countries:

Alternatives to randomisation in the evaluation of public health interventions: design challenges and solutions
Bonell CP, Hargreaves J, Cousens S, Ross D, Hayes R, Petticrew M, Kirkwood BR. Alternatives to randomisation in the evaluation of public health interventions: design challenges and solutions. Journal of Epidemiology and Community Health. 2011 Jul 1;65(7):582-7.

Alternatives to randomisation in the evaluation of public-health interventions: statistical analysis and causal inference
Cousens S, Hargreaves J, Bonell C, Armstrong B, Thomas J, Kirkwood BR, Hayes R. Alternatives to randomisation in the evaluation of public-health interventions: statistical analysis and causal inference. Journal of epidemiology and community health. 2009 Aug 6:jech-2008.

 

Some methodological approaches beyond stratification and regression to address confounding in quasi-experimental or non-randomised designs are highlighted on this page:

Difference in Differences

Regression Discontinuity

Interrupted Time Series

Synthetic Controls

We also highlight:

Researchers at LSHTM with Experitse in These Methods

Within the Centre for Evaluation at LSHTM, this type of work is carried out in close collaboration with the LSHTM Centre for Statistical Methodology, in particular the Causal Inference, Missing Data, and Time Series Regression Analysis groups, as well as LSHTM’s MARCH (Maternal Adolescent Reproductive and Child Health) Centre.

 

Craig and colleagues from the UK Medical Research Council have introduced new guidance on the use of some of these methods, and others, under the umbrella term of natural experiments:

Using natural experiments to evaluate population health interventions: new Medical Research Council guidance
Craig P, Cooper C, Gunnell D, Haw S, Lawson K, Macintyre S, Ogilvie D, Petticrew M, Reeves B, Sutton M, Thompson S. Using natural experiments to evaluate population health interventions: new Medical Research Council guidance. Journal of epidemiology and community health. 2012 May 10:jech-2011.