Abstract. We developed a locative fiction application called nan0sphere and deployed it on the UCLA campus. This application presents an interactive narrative to users working in a group as they move around the campus. Based on each user's current location, previously visited locations, actions taken, and on the similar attributes of other users in the same group, the story will develop in different ways. Group members are encouraged by the story to move independently, with their individual actions and progress affecting the narrative and the overall group experience. Eight different locations on campus are involved in this story. Groups consist of four participants, and the complete story unfolds through the actions of all four group members. The supporting system could be used to create other similar types of locative literature, possibly augmented with multimedia, for other purposes and in other locations. We will discuss benefits and challenges of group interactions in locative fiction, infrastructure required to support such applications, issues of determining user locations, and our experiences using the application.
Examples of British Library digitisation projectsPercentage of time spent on activity Activity project A project B project C management 7% 7% 2% s e l e c t i o n 4 % 0 % 3 % preparation 4% 1% 4% digitisation 12% 41% 42% metadata 4% 51% 25% i p r 0 % 0 % 2 4 % Project A Selection was high, because it required very specialised selection by an expert. Metadata was low, because it was derived from existing records.
Project BNo selection was required, but metadata creation took twice as long.Project C IPR checking was significantly time-consuming and a manual process.
Background: It has long been advised to account for baseline covariates in the analysis of confirmatory randomised trials, with the main statistical justifications being that this increases power and, when a randomisation scheme balanced covariates, permits a valid estimate of experimental error. There are various methods available to account for covariates.
Methods:We consider how, at the point of writing a statistical analysis plan, to choose between three broad approaches: direct adjustment, standardisation and inverse-probability-of-treatment weighting (IPTW), which are in our view the most promising methods. Using the GetTested trial, a randomised trial designed to assess the effectiveness of an electonic STI (sexually transmitted infection) testing and results service, we illustrate how a method might be chosen in advance and show some of the anticipated issues in action.
Results:The choice of approach is not straightforward, particularly with models for binary outcome measures, where we focus most of our attention. We compare the properties of the three broad approaches in terms of the quantity they target (estimand), how a method performs under model misspecification, convergence issues, handling designed balance, precision of estimators, estimation of standard errors, and finally clarify some issues around handling of missing data.
Conclusions:We conclude that no single approach is always best and explain why the choice will depend on the trial context but encourage trialists to consider the three methods more routinely.
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