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 Definition
0 No formal statistics courses or no statistician in group
1 1 or 2 full course in statistics
2 3+ full courses in statistics
3 5+ full courses in statistics
4 minor in statistics with B.S. or B.A. in quantitative field
5 4+ full courses in statistics with 5+ years of experience in statistical analysis
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
8 4+ graduate courses in statistics
9 4+ doctoral level courses in statistics
10 PhD in quantitative psychology or econometrics with 5+ years of experience analyzing biomedical data
11 Master's degree in statistics
12 PhD in statistics

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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