2016 AAPM Annual Meeting
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Session Title: Statistical Failings That Keep Us All In The Dark
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?
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
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.
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:
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:
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.
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