Assessment of Biostatistics Expertise Available to Biomedical Research Groups

The following scale is suggested for assessing the degree of biostatistical expertise that a lab or research group has available to them. If the group uses a lab member for their statistical design and analysis they can use this scale to roughly rate that person's level of expertise. If the group uses a statistician outside their group, than can "rate" that person. The highest applicable score should be chosen. In what follows, "full course" refers to a full semester or quarter course. "Statistics" refers to biostatistics or statistics.

Score DefinitionSorted ascending
1 1 or 2 full course in statistics
2 3+ full courses in statistics
5 4+ full courses in statistics with 5+ years of experience in statistical analysis
8 4+ graduate courses in statistics
9 4+ doctoral level courses in statistics
3 5+ full courses in statistics
10 PhD in quantitative psychology or econometrics with 5+ years of experience analyzing biomedical data
12 PhD in statistics
6 B.S. or B.A. in statistics
7 M.S or M.A. in economics, psychology, math, computer science, or related fields with 3+ years of experience in statistical analysis
11 Master's degree in statistics
4 minor in statistics with B.S. or B.A. in quantitative field
0 No formal statistics courses or no statistician in group

Basic Assessment of Reproducible Statistical Computing Practices

Select the highest applicable score. In what follows, "statistical package" refers to a software system or platform dedicated to statistical analysis or having high-level statistical functions, for example R, Stata, SAS, SPSS, Python. What doesn't qualify as "statistical package" is anything related to Excel or that requires the analyst to write low-level functions even for regression analysis (e.g., C, Fortran, Matlab). "Interactive" refers to point and click software, but not exclusively. "Script" refers to high-level statistical language commands, or to statistical programming code. For example, you can write scripts in R, Stata, SAS, SPSS, Python, and SQL.

Score Definition
0 Use Excel
1 Use Excel for inputting or manipulating some of the data but not for any statistical analysis or graphics
2 Use an interactive statistical package that does not have the capability of creating/saving scripts defining what you did
3 Use an interactive statistical package having the capability of saving scripts but not always turning on this option
4 Use an interactive statistical package and always saving the script the package developed
5 Always write your own analysis scripts
6 Generally embed analysis scripts inside reports and using literate programming techniques for maximum reproducibility
7 Same as 5 but in addition you script all data manipulation/management and do not let the data pass through Excel at any stage

If you selected category 5 or 6 above, this means that you did not copy and paste results into a report document.
Topic revision: r6 - 26 Apr 2013, JohnBock
 

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