1. Constrained randomisation: some applications

2. Tanzania: background CRT of impact of adolescent sexual health intervention on knowledge, behaviour and biomedical outcomes Primary outcomes: HIV incidence and HSV2 prevalence 20 communities to be randomised to intervention and control arms Data on HIV and CT prevalence from community survey of young people

3. Stratification of communities

4. Constrained randomisation 3 strata: –High risk: 6 communities –Medium risk: 8 communities –Low risk: 6 communities 28,000 ways of allocating half the communities in each stratum to intervention arm

5. Balance criteria Mean HIV prevalence in I and C arms within 0.15% Mean CT prevalence in I and C arms within 0.2% One of two communities near gold mines allocated to each arm Even distribution of I and C in each of four districts

6. Results 953 out of 28,000 permutations satisfied the balance criteria One of these was randomly selected in an open meeting attended by senior Tanzanian officials

7. Map of study communities

8. Zimbabwe: background CRT of impact of adolescent sexual health intervention on knowledge, behaviour and biomedical outcomes 30 communities to be randomised to intervention and control arms No baseline data on HIV or other biomedical markers

9. Constrained randomisation 3 strata based on distanced to tarred road: –Stratum 1: 10 communities –Stratum 2: 12 communities –Stratum 3: 8 communities 16,299,360 ways of allocating half the communities in each stratum to intervention arm

10. Balance criteria Even distribution of I and C in each of seven districts Equal number of schools (40) in both arms Average sample size per community between 255 and 261 in each arm Gives 8,575 acceptable permutations One selected at random

11. Some issues How to decide on appropriate trade-off between degree of balance and number of accepted permutations? We have not assessed “validity” of these schemes using Larry’s matrix approach No account taken of constrained randomisation in analysis Should we be using permutation-based inference?