Crime is a multi-billion-dollar business. Crime is also deeply embedded in our social, economic, political, religious and material worlds. But, surely it is wrong that, day after day, year after year, thousands of decisions are taken, millions of lives are disturbed and billions of dollars are being spent without robust evidence as to what is the best course of action for those involved in, affected by, or afflicted through crime. Experiments seek to offer hope, they seek to offer help and they seek to assist in making this world, our world, your world, a better place.
Fully loaded with questions and examples from across the world, with 27 sections, 44 tables and diagrams, 203 references and 260 pages, this book aims to:
share rich contemporary examples of experiments in crime that you can read, discuss, learn from, relate to and find out more about
give you insight and inspiration with respect to experiments in crime
introduce the language, terms, tips and traps of experiments in crime
empower you to become more confident, capable and curious about experiments in crime
inspire you to ask questions of experiments in crime and of the evidence they produce
encourage you to look at experimental and non experimental evidence
encourage you to look at real life data and how you can use it to help support and challenge experiments in crime
make you do something: think, talk, listen then act.
The 27 sections cover the following areas:
In the beginning
On everyday life
On the RCT family
On the advantages and limitations of evidence from an experiment
Barriers to doing an experiment in crime
Before you get involved in an experiment
On consent, concealment and blinding
On entry and exclusion
On recruitment
On random
On sampling
On the control group
On the baseline
On outcomes and endpoints
On bias
On piloting
Bullet proof, gold standard and assumption free?
On hierarchies of the evidence and other methods
On the cycle of evidence and publication
On the fate of ideas
On the business of reviews
On data, data presentation, dirty data and data monitoring
On statistics
On interim analysis
On the number needed to treat, intention to treat and protocol analysis
On checklists and integrity of an experiment
On ethics
