To quote the college, "candidates either knew this topic or knew nothing about it". We have all seen these graphs before, but when pushed to give specific definitions people tend to do poorly. Fortunately, there is not much to know.
The forest plot has appeared in many past paper questions:
Primary Exam:
Fellowship Exam:
The box-and-whisker plot has never appeared in any Part II papers, but made frequent appearances in Part I:
In brief summary, this is all the exam candidate is expected to know to satisfy the college demands:
Now, to revel in apocryphal detail:
The box and whisker plot is a way of graphically representing the "five number summary", or four parameters which demonstrate the central tendency of the data set.
Uses of this graph:
This thing was invented by John W. Tukey, the man also responsible for introducing the term "bit" to computers. He introduced the world to this concept in 1977, in his book "Exploratory Data Analysis." Tukey's original drawings had slightly different conventions (for instance, he extended the whiskers all the way to the extreme data points whereas modern box-and-whisker plots tend to extend the "whiskers" to the farthest points that are not outliers (i.e, that are within 3/2 times the interquartile range of the first and third quartiles). Other weird conventions exist, for instance whether to add dots or circles for every outlier data point, etc.
Judging by the college answer to Question 14 from the second paper of 2014, the examiners either don't know or don't care about such nonsense. Myles and Gin are the reference text, and offer only a bare minimum. On page 17 (Ch. 2, Descriptive statistics) they offer an unlabelled box and whisker plot of creatinine clearance as an example, and spend literally three lines on it (listing the five data points it represents). The rest of the brief section is wasted on highly specific and useful statements like "tables and diagrams are a convenient way of summarisizing data". One supposes we must be grateful for even these scraps; the forest plot is completely ignored by that entire textbook and the trainee who used textbooks exclusively will find themselves ill-prepared for the forest plot questions (of which there have now been four).
This thing is also more properly referred to as a "confidence interval plot", or - if Wikipedia is to be believed - a blobbogram. It is in essence a series of severely mutated box-and-whisker plots, stacked together and summarised in a manner which favours rapid assessment by persons well instructed in the interpretation of such graphics.
In summary, its properties are as follows:
From the college's lazy answer to Question 14 from the first paper of 2017, some candidates might get the impresison that occasionally it is ok to refer to this representation as a "Forrest plot". That would be an incorrect impression. It's a forest plot. Because it looks like a forest of lines. Forrest is the surname of Pat Forrest, a medical oncologist. A fellow medical oncologist joked about the plot being named after Forrest at some sort of provincial breast cancer meeting in 1990 (Lewis & Clarke; 2001). Idiotic terminological laxity had ensued from this. Let us maintain high standards in medical literature by eradicating it.
Methodological Expectations of Cochrane Intervention Reviews
Schriger, David L., et al. "Forest plots in reports of systematic reviews: a cross-sectional study reviewing current practice." International journal of epidemiology39.2 (2010): 421-429.
Lewis, Steff, and Mike Clarke. "Forest plots: trying to see the wood and the trees." Bmj 322.7300 (2001): 1479-1480.
Anzures‐Cabrera, Judith, and Julian Higgins. "Graphical displays for meta‐analysis: An overview with suggestions for practice." Research Synthesis Methods 1.1 (2010): 66-80.
Cochrane: "Considerations and recommendations for
figures in Cochrane reviews: graphs of statistical data" 4 December 2003 (updated 27 February 2008)
Reade, Michael C., et al. "Bench-to-bedside review: Avoiding pitfalls in critical care meta-analysis–funnel plots, risk estimates, types of heterogeneity, baseline risk and the ecologic fallacy." Critical Care 12.4 (2008): 220.
DerSimonian, Rebecca, and Nan Laird. "Meta-analysis in clinical trials."Controlled clinical trials 7.3 (1986): 177-188.
Biggerstaff, B. J., and R. L. Tweedie. "Incorporating variability in estimates of heterogeneity in the random effects model in meta-analysis." Statistics in medicine 16.7 (1997): 753-768.
The Cochrane Handbook: 9.5.4 "Incorporating heterogeneity into random-effects model"
Larsen, Russell D. "Box-and-whisker plots." J. Chem. Educ 62.4 (1985): 302.
Weisstein, Eric W. "Box-and-whisker plot." From MathWorld–A Wolfram Web Resource.[Cited 2006 June 7]. Available from: URL: http://mathwold. wolfram. com/Box-and-Whiskerplot (1999).
Tukey, J. W. "Box-and-Whisker plots, in: Exploratory Data Analysis." (1977).