Estimating intervention effects in a complex multi-level smoking prevention study.
This paper illustrates how to estimate cumulative and non-cumulative treatment effects in a complex school-based smoking intervention study. The Instrumental Variable method is used to tackle non-compliance and measurement error for a range of treatment exposure measures (binary, ordinal and continuous) in the presence of clustering and dropout. The results are compared to more routine analyses. The empirical findings from this study provide little encouragement for believing that poorly resourced school-based interventions can bring about substantial long-lasting reductions in smoking behaviour but that novel components such as a computer game might have some short-term effect.
Falcaro
Milena
M
Biostatistics Group, School of Community-Based Medicine, University of Manchester, UK. milena.falcaro@manchester.ac.uk
Povey
Andrew C
AC
Fielder
Anne
A
Nahit
Elizabeth
E
Pickles
Andrew
A
D006801:Humans; D012574:Schools; D000074606:Smoking Prevention