Raindrop Plots

In a variety of settings, it is desirable to display a collection of likelihoods over a common interval. One approach is simply to superimpose the likelihood curves. However, where there are more than a handful of curves, such displays are extremely difficult to decipher. An alternative is simply to display a point estimate with a confidence interval, corresponding to each likelihood. However, these may be inadequate when the likelihood is not approximately normal, as can occur with small sample sizes or nonlinear models. A second dimension is needed to gauge the relative plausibility of different parameter values. We introduce the raindrop plot, a shaded figure over the range of parameter values having log-likelihood greater than some cutoff, with height varying proportional to the difference between the log-likelihood and the cutoff. In the case of a normal likelihood, this produces a reflected parabola so that deviations from normality can be easily detected. An analogue of the raindrop plot can also be used to display estimated random effect distributions, posterior distributions, and predictive distributions.

[1]  Douglas M. Bates,et al.  Nonlinear Regression Analysis and Its Applications , 1988 .

[2]  B. Efron Empirical Bayes Methods for Combining Likelihoods , 1996 .

[3]  Steff Lewis,et al.  Forest plots: trying to see the wood and the trees , 2001, BMJ : British Medical Journal.

[4]  Jiun-Kae Jack Lee,et al.  A Versatile One-Dimensional Distribution Plot: The BLiP Plot , 1997 .

[5]  J. Hintze,et al.  Violin plots : A box plot-density trace synergism , 1998 .

[6]  G. Milliken Nonlinear Regression Analysis and Its Applications , 1990 .

[7]  Ransom A. Myers,et al.  Still more spawner-recruitment curves: the hockey stick and its generalizations , 2000 .

[8]  B. M. Hill,et al.  Bayesian Inference in Statistical Analysis , 1974 .

[9]  Issei Fujishiro,et al.  The elements of graphing data , 2005, The Visual Computer.

[10]  T C Chalmers,et al.  Endoscopic hemostasis. An effective therapy for bleeding peptic ulcers. , 1990, JAMA.

[11]  Chris Field,et al.  THE VARIABILITY AMONG POPULATIONS OF COHO SALMON IN THE MAXIMUM REPRODUCTIVE RATE AND DEPENSATION , 2003 .

[12]  Peter Green,et al.  Markov chain Monte Carlo in Practice , 1996 .

[13]  R. Gnanadesikan,et al.  Probability plotting methods for the analysis of data. , 1968, Biometrika.

[14]  Walter R. Gilks,et al.  A Language and Program for Complex Bayesian Modelling , 1994 .

[15]  H C Van Houwelingen,et al.  A bivariate approach to meta-analysis. , 1993, Statistics in medicine.

[16]  K. Balanda,et al.  Kurtosis: A Critical Review , 1988 .

[17]  Rob J Hyndman,et al.  Computing and Graphing Highest Density Regions , 1996 .

[18]  V. Vieland,et al.  Statistical Evidence: A Likelihood Paradigm , 1998 .

[19]  P. Lerman Fitting Segmented Regression Models by Grid Search , 1980 .

[20]  D. Bates,et al.  Nonlinear mixed effects models for repeated measures data. , 1990, Biometrics.