Revisiting Tobin's 1950 study of food expenditure
重新分析托宾1950年的食品支出研究，强调图形在数据发现和沟通中的力量，并讨论数据挖掘和贝叶斯敏感性分析在解决过度参数化问题中的优劣。
This re-analysis of Tobin's (1950) study makes three points: 1. Graphs are a powerful device for discovery and for communication, and can reveal much of the information in the data. 2. Squeezing out the more subtle multivariate messages requires some solution to the usual overparameterization problem. Data-mining is still the treatment of choice for this crippling disease, but it is more akin to leeches than to anti-biotics. A Bayesian sensitivity analysis is an alternative, but it isn't a perfect cure either. 3. Clear identification of the issues can help keep the enterprise from wandering off in technically amusing but largely irrelevant directions. © 1997 John Wiley & Sons, Ltd.