Question 1: Various publications have found a higher than expected incidence of p-values immediately below p=0.05 as compared to p-values immediately above p=0.05. Some possible reasons for this over-representation could include: |
Reference: | B. Ginsel, et al., The distribution of probability values in medical abstracts: an observational study., BMC Res Notes, Nov 26, 2015. |
Choice A: | Publication bias. |
Choice B: | Statistical fraud. |
Choice C: | Methodological errors (selective reporting, selective analyses, underpowered analysis). |
Choice D: | A and B. |
Choice E: | All of the above. |
Question 2: Which is the most appropriate definition of a p-value?
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Reference: | R.L. Wasserstein and N.A. Lazar, The ASA’s statement on p-values, context, process, and purpose, The American Statistician, accepted version published online 3/7/2016. |
Choice A: | A p-value is the probability that the null hypothesis is true |
Choice B: | A p-value is the probability under a specified statistical model that a statistic al summary of the would be equal to or more extreme than its observed value. |
Choice C: | A p-value is the probability that the result was a random coincidence |
Choice D: | A p-value is the probability the results will not hold up if the experiment is repeated |
Choice E: | All of the above. |
Question 3: Effect sizes are more important than p-values because: |
Reference: | Source: http://amstat.tandfonline.com/doi/abs/10.1080/00031305.2016.1154108
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Choice A: | They are unitless measures. |
Choice B: | They are sample independent. |
Choice C: | They tell you how practically meaningful your results are. |
Choice D: | They are unrelated to the p-value. |
Choice E: | C and D. |
Question 4: In non-mathematical terms, the problem of performing multiple comparisons without controlling for them is that it: |
Reference: | H. Motulsky, Intuitive Biostatistics: A nonmathematical guide to statistical thinking, Oxford Univ Press, (2014), pp. 183.
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Choice A: | Makes it difficult to detect cause from correlation among all of the predictors. |
Choice B: | Makes it less likely to achieve a p-value <= 0.05 among all of the predictors. |
Choice C: | Across all of the predictors, leads to an increased probability of erroneously finding a difference that is statistically significant when in fact all of the null hypotheses are true. |
Choice D: | Makes it more difficult to compile the analysis due to the number of results presented. |
Choice E: | Is difficult to achieve with currently available statistical software. |
Question 5: The reason censoring tick marks are important for the interpretation of a survival curve is:
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Reference: | J. T. Rich, et al., A Practical Guide to Understanding Kaplan-Meier Curves, Otolaryngol Head Neck Surg 143(3), 2010, 331-336. |
Choice A: | They represent the total fraction of subjects lost to followup at a given timepoint. |
Choice B: | They yield important information about the number of subjects remaining in the study (and thus the reliability of the curve) at each timepoint. |
Choice C: | They represent the timepoint when a subject reaches the specified event being analyzed. |
Choice D: | They represent fixed time intervals on the KM curve. |
Question 6: The best approach to missing data is:
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Reference: | http://www.valueinhealthjournal.com/article/S1098-3015(10)60635-3/references |
Choice A: | Last value carried forward. |
Choice B: | A sensitivity analysis of competing approaches. |
Choice C: | Simple imputation. |
Choice D: | Multiple imputation. |
Choice E: | Complete Cases. |