Statistical analysis
death
REGRESSION
We used a frequentist approach, with a two sided 5% statistical significance level for hypothesis testing, providing estimates of between group differences and corresponding 95% confidence intervals. The primary analysis was done on an intention-to-treat basis (that is, participants were analysed within their allocated group, rather than by actual treatment received), with a per protocol analysis also completed for participants deemed to have received the PIP intervention as intended. We anticipated that the primary outcome would follow a Poisson distribution, but the data proved to best fit a negative binomial model, which we used instead. We estimated parameters by using a generalised estimating equation approach, to account for the clustered design, with an offset included for length of follow-up. Length of follow-up varied from participant to participant owing to death or dropout.The final primary outcome model included baseline fall rate, key prognostic variables (defined as baseline values of Drug Burden Index,We used a Cox proportional hazards regression model (time from consent to death or otherwise censored) for mortality analyses, in which we used robust sandwich estimates of standard errors to adjust for clustering within care homes. We used SAS v.9.4 for analyses. The trial was overseen by a Data Monitoring Committee and an over-arching Trial Steering Committee.