Sökning: "generalised mixed linear model"
Hittade 5 avhandlingar innehållade orden generalised mixed linear model.
1. Generalised linear models with clustered data
Sammanfattning : In situations where a large data set is partitioned into many relativelysmall clusters, and where the members within a cluster have some common unmeasured characteristics, the number of parameters requiring estimation tends to increase with sample size if a fixed effects model is applied. This fact causes the assumptions underlying asymptotic results to be violated. LÄS MER
2. Explicit Influence Analysis in Crossover Models
Sammanfattning : This dissertation develops influence diagnostics for crossover models. Mixed linear models and generalised mixed linear models are utilised to investigate continuous and count data from crossover studies, respectively. LÄS MER
3. Exploring Road Safety Deficiencies in Malaysia
Sammanfattning : The escalating number of road traffic crashes in Malaysia poses a critical concern. The underreporting of these crashes has been identified as a significant problem that obstructs the effectiveness and efficiency of road safety work. LÄS MER
4. Exploring the impact of virtual patient design : medical students' small group learning around medical error
Sammanfattning : Background: The demands on medical and healthcare practitioners are continuously changing, with new technologies, treatments and regulatory guidelines emerging each year. One such example is increased focus on the impact of medical error, which although difficult to measure is generally acknowledged to be responsible for significant numbers of patient harms each year. LÄS MER
5. Home care communication : moving beyond the surface
Sammanfattning : Communication is an essential part of care and human interaction. While communication within care entails both task-focused and socio-emotional elements, nurses are sometimes perceived as too task-focused. When in need of care, older persons want to be perceived and treated as individuals – to feel involved. LÄS MER