Background:Statistical analysis in palliative and end-of-life care research can be problematic due to high levels of missing data, attrition and response shift as disease progresses. Aim:To develop recommendations about managing missing data, attrition and response shift in palliative and end-of-life care research data. Design:We used the MORECare Transparent Expert Consultation approach to conduct a consultation workshop with experts in statistical methods in palliative and end-of-life care research. Following presentations and discussion, nominal group techniques were used to produce recommendations about attrition, missing data and response shift. These were rated online by experts and analysed using descriptive statistics for consensus ...
BACKGROUND: Missing data can introduce bias and reduce the power, precision and generalisability of ...
Background: Missing data can introduce bias and reduce the power, precision and generalisability of ...
Background: Missing data can introduce bias and reduce the power, precision and generalisability of ...
Background:Statistical analysis in palliative and end-of-life care research can be problematic due t...
Background:Statistical analysis in palliative and end-of-life care research can be problematic due t...
Background: Statistical analysis in palliative and end-of-life care research can be problematic due ...
Aims: To identify agreed best practice for statistical methods in palliative and end of life (P&EoLC...
BACKGROUND: Palliative care trials have higher rates of attrition. The MORECare guidance recommends ...
There are several methodological challenges when conducting randomised controlled trials in palliati...
There are several methodological challenges when conducting randomised controlled trials in palliati...
There are several methodological challenges when conducting randomised controlled trials in palliati...
There are several methodological challenges when conducting randomised controlled trials in palliati...
Background:: Missing data can introduce bias and reduce the power, precision and generalisability of...
Background: Missing data can introduce bias and reduce the power, precision and generalisability of ...
Background:: Missing data can introduce bias and reduce the power, precision and generalisability of...
BACKGROUND: Missing data can introduce bias and reduce the power, precision and generalisability of ...
Background: Missing data can introduce bias and reduce the power, precision and generalisability of ...
Background: Missing data can introduce bias and reduce the power, precision and generalisability of ...
Background:Statistical analysis in palliative and end-of-life care research can be problematic due t...
Background:Statistical analysis in palliative and end-of-life care research can be problematic due t...
Background: Statistical analysis in palliative and end-of-life care research can be problematic due ...
Aims: To identify agreed best practice for statistical methods in palliative and end of life (P&EoLC...
BACKGROUND: Palliative care trials have higher rates of attrition. The MORECare guidance recommends ...
There are several methodological challenges when conducting randomised controlled trials in palliati...
There are several methodological challenges when conducting randomised controlled trials in palliati...
There are several methodological challenges when conducting randomised controlled trials in palliati...
There are several methodological challenges when conducting randomised controlled trials in palliati...
Background:: Missing data can introduce bias and reduce the power, precision and generalisability of...
Background: Missing data can introduce bias and reduce the power, precision and generalisability of ...
Background:: Missing data can introduce bias and reduce the power, precision and generalisability of...
BACKGROUND: Missing data can introduce bias and reduce the power, precision and generalisability of ...
Background: Missing data can introduce bias and reduce the power, precision and generalisability of ...
Background: Missing data can introduce bias and reduce the power, precision and generalisability of ...