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. Author manuscript; available in PMC: 2019 Aug 21.
Published in final edited form as: J Stat Educ. 2018 Aug 21;26(2):137–142. doi: 10.1080/10691898.2018.1484674

Table 1.

Original and revised wording for statistical competencies with results of surveys from Oster et al. (2015) and Enders et al. (2017). Modified wording is shown in bold text.

Rank Oster et al. (2015), unless otherwise
specified
Enders et al. (2017)
1 Assess sources of bias and variation in published studies and threats to study validity (bias) including problems with sampling, recruitment, randomization, and comparability of study groups Fundamental Assess sources of bias and variation in published studies and threats to study validity (bias) including problems with sampling, recruitment, randomization, and comparability of study groups [no change] Fundamental
2 Assess study designs for addressing a clinical or translational research question Fundamental Identify the strengths and limitations of
study designs for addressing a clinical or translational research question
Fundamental
3 Collaborate with biostatisticians in the design, conduct, and analyses of clinical and translational research [Not Assessed] Recognize limitation in statistical competency and realize when it would be best to involve a professional statistician Fundamental
4  Communicate research findings for scientific and lay audiences Fundamental Communicate research findings for scientific and lay audiences [no change] Fundamental
5 Assess the basic principles and practical importance of probability, random variation, systematic error, sampling error, measurement error, commonly used statistical probability distributions, hypothesis testing, type I and type II errors, and confidence limits Fundamental Understand the basic principles and practical importance of probability, random variation, commonly used statistical probability distributions, hypothesis testing, type I and type II errors, and confidence limits [shortened] Fundamental
6 Understand appropriate data quality and data management procedures Specialized Understand the value of data quality and data management Fundamental
7  Understand the reasons for performing research that is reproducible from data collection through publication of results Fundamental Understand the reasons for performing research that is reproducible from data collection through publication of results [no change] Fundamental
8 Assess the different measurement scales and the implications for selection of statistical methods to be used on the basis of these measurement scales Intermediate Distinguish between variable types (e.g., continuous, binary, categorical) and understand the implications for selection of appropriate statistical methods Fundamental
9  Assess results in light of multiple comparisons Intermediate Understand the potential misinterpretation of results in the presence of multiple comparisons Fundamental
10 Understand appropriate methods for data presentation, especially effective statistical graphs and tables Fundamental Understand appropriate methods for data presentation, especially effective statistical graphs and tables [no change] Fundamental
11 Assess size of the effect with a measure of precision Fundamental Evaluate size of the effect with a measure of precision Fundamental
12 Assess the study sample, including sampling methods, the amount and type of missing data, and the implications for generalizability Fundamental Understand issues relating to generalizability of a study, including sampling methods and the amount and type of missing data Fundamental
13 [Developed for this survey] Evaluate the impact of statistics on ethical research (e.g., an inadequate power calculation may mean it is unethical to ask subjects to consent to a study) and of ethics on statistical practice (e.g., collecting valid data from consenting subjects while maintaining privacy) Fundamental
14 Assess simple descriptive and inferential statistics that fit the study design chosen and answer research question Intermediate Compute descriptive and simple inferential statistics appropriate for the data and research question Fundamental
15 Understand how to determine sample size, power, and precision for comparisons of two independent samples with respect to continuous and binary outcomes Specialized Understand the components of sample size, power, and precision Fundamental
16 Understand statistical methods appropriate to address loss to followup Specialized Understand the need to address loss to followup Fundamental
17 Assess the concepts and implications of reliability and validity of study measurements and evaluate the reliability and validity of measures Fundamental Understand the concepts and bias implications of reliability and validity of study measurements and evaluate the reliability and validity of measures Fundamental
18 Assess the assumptions behind different statistical methods and their corresponding limitations and describe preferred methodologic alternatives to commonly used statistical methods when assumptions are not met Intermediate Evaluate potential violations of the assumptions behind common statistical methods Fundamental
19 Identify inferential methods appropriate for clustered, matched, paired, or longitudinal studies Intermediate Identify when clustered, matched, paired, or longitudinal statistical methods must be used Fundamental
20 Characterization of diagnostic testing, including sensitivity, specificity, and
ROC curves
Specialized Understand the concepts of sensitivity, specificity, positive and negative predictive value, and receiver operating characteristic curves Not Fundamental
21 Defend the significance of data and safety monitoring plans. [Wording from CTSA,
2011]
[Not Assessed] Understand the purpose of data and safety monitoring plans Not Fundamental
22 Identify adjusted inferential methods appropriate for the study design, including examination of interaction Intermediate Identify appropriate methods to address potential confounding and effect modification Not Fundamental
23  Understand the uses of meta-analytic methods Specialized Understand the purpose of meta-analysis and its place in the hierarchy of evidence Not Fundamental
24 Explain the uses, importance, and limitations of early stopping rules in clinical trials Specialized Understand the uses, importance, and limitations of early stopping rules in clinical trials Not Fundamental