Critical Appraisal Checklist for Statistical Methods

[R_cubed]

@llynn

Given the complexity of quality its hard to imagine that a checklist is not essential if the goal is to render a very high quality study

I view a scientific experiment (broadly defined) as a communication channel in the information theoretic sense with 3 components: sender (ie. state of nature), channel (design and actual conduct of data collection) and receiver (data analysis after collection is complete).

A checklist can be useful for the producer of the data (ie. experimenter); a checklist is not as useful for the reader, for all of the reasons Greenland mentions.

I merely request “quality” be thought of in a more quantitative fashion vs the “threshold science” approach I interpret “quality checklists” to be.

[Raj]

@s_doi

They come in two flavors - risk of bias checklists and quality assessment checklists. These should not be confused with reporting checklists which have nothing to do with critical appraisal.

Agree with this comment. The original post was intended to start by recognizing this, and then inquiring about availability of any process (checklist or otherwise) to assess choices made in statistical analysis of biomedical papers (i.e. why did methods use t.test I stead of ancova, etc).

The closest to this is the list of common mistakes to avoid, which has it’s own thread on data methods.