Do the calculators effectively balance complexity with usability?

Answer Explanations

• No (please explain)

  Expert 3
   The calculators are indeed user-friendly, particularly since they are made in Shiny, but they lack the necessary complexity. Important options are missing, which limits their usefulness. It would be much more user-friendly if they allowed for a range of inputs and provided a range of acceptable outputs. Additionally, the absence of options to select different outputs, such as Relative Risk versus Odds Ratio, is a significant limitation. 
• No (please explain)

  Expert 4
  Manual input in parameters should be allowed, for example calculator 4.
  
  
• Yes

  Expert 1
  Yes, I believe so. There is a lot of complexity in these calculations, but the layout and structure of the calculators makes them easy to use and understand.
• I cannot tell

  Expert 8
  This is always a tricky trade-off for premade calculators/models. It should be simple enough to be used, especially for those without very extensive expertise, but they should be complex/flexible enough to accommodate various study types and datasets.  
  
  For this aspect, I think it's crucial to make the code open source, e.g. on github, so that those who need more flexibility/complexity can still use it, modify it for their needs. In my team we previously did that for e.g. spline models to test nonlinearity. One can use a 'basic' easy to use version on a website, but in case of exceptions and complexities in the data, one can access the original R and Python code and modify it for their needs.
• Yes

  Expert 5
  I guess so - they are user friendly but limited to the most simple scenario of classical measurement error and only one independent variable.  Most often we are dealing with many independent variables, with their own measurement error and correlations with the primary exposure variables of interest.  This complicates these type of scenarios, but reflects the real world.  
  
  Ideally, these calculators could be expanded to reflect more complicated scenarios!
• Yes

  Expert 2
   The calculators effectively balance complexity with usability by providing a simplified and intuitive interface that allows users to engage with advanced statistical concepts without being overwhelmed.  By focusing on key metrics such as the intraclass correlation coefficient (ICC), sample size, and measurement error, the calculators deliver valuable insights without requiring users to manage overly complex parameters. The inclusion of clear instructions and examples enhances usability, guiding users through the process and ensuring they understand the results' implications.