The following review is for a paper that is currently published in the Scientific Research Publishing's Open Journal of Statistics (link omitted intentionally). I accepted the responsibility to review it, found it unfit for publication, and returned a review less than a month later only to find that the paper had already been published as is.
I won't be reviewing for this journal or this publishing house again. To ask for my review, get my assent, and not wait a reasonable time (a month, really?), for the review before going ahead and publishing is disrespectful of my time. It also smacks of predatory journal behaviour.
I won't be reviewing for this journal or this publishing house again. To ask for my review, get my assent, and not wait a reasonable time (a month, really?), for the review before going ahead and publishing is disrespectful of my time. It also smacks of predatory journal behaviour.
Was there another peer reviewer and were they qualified to perform the review? Read my review, and the paper, and judge for yourself.
Review for ‘Has Tom Brady Passed His Prime?’, Paul M. Sommers, submitted to the Open Journal of Statistics 2018.
Review by Jack Davis.
The subject matter of this paper is interesting, especially
in the context of Brady’s recently published book about maintaining peak
performance over a long period.
The statistical content of this paper consists of the formulae
for the sample mean, standard deviation, and coefficient of variation, followed
by three sets of t-tests on seven variables.
In all tables, a t-test is appropriate for at most four of
the seven variables. The other three,
completion percentage, touchdowns per game, and intercepts per game, deserve
different statistical tests.
Completion percentage is a proportion and it needs a
proportion test, a 2x2 chi-squared test, or an odds ratio test in order to see
a difference between the two proportions, not a t-test.
Touchdowns and intercepts are rare count events. They follow
a Poisson distribution much more closely than a normal distribution. A much
more appropriate test for equality of touchdown and interception rates is the
Likelihood Ratio Test.
In Table 2, how were the years chosen for the
before-and-after comparison?
In Table 3, are there significant differences between the coefficients of variation?
Rather than just comparing years, why not do a regression analysis of the trends in each of these variables over time? With plots of these statistics over time, we could see if there is a decline in recent years. Finally, allowances should be made for multiple testing.
Finally, the title has a grammar error. It should read
either “Has Tom Brady Passed his Prime” or “Is Tom Brady Past his Prime” but
not “has . . . passed”.
With more statistical details and rigour, this could be an
excellent manuscript. However, in its current state, it feels incomplete and not
ready for publication.
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