取样大小对不同因果推理问题强度估计的影响研究

The Influence of Sample Size on Causal-Strength Judgments of Different Contingency

使用纸笔测验探讨表格集中呈现信息条件下取样大小对单一因果关系强度推理的影响，并比较五种模型：△P、效力PC、SS效力、Support和χ2的预测与实验数据的相关。结果显示：（1）取样大小对不同的问题有不同的影响，高取样在△P=0时导致了低估汁值，在0〈｜△P｜=PPC时没有效果，在｜△P｜〈PPC时有不一致的效果，4倍取样比2倍取样有更明显的取样大小效应；（2）取样大小效应更一致地出现在PPC与｜△P｜不相等且PPC值较高的问题中；（3）虽然Suppoa模型和ss效力模型都能预测取样大小因素在所有问题上的作用方式，但取样大小效应并不如因果支持模型所预测的那么强大，在两种因果方向条件下SS效力模型都能最好地预测被试的反应。

Participant＇s judgment on causal strength can vary with sample size of contingency. Griffiths ＆ Tenenbaum （2005） show that sample size can affect participant＇s judgment on contingency with △P = 0. But Lu et al. （2008） found that sample size has an effect on contingency with △P 〉 0 in the opposite direction, and high power - PC can offset low sample size. Then, what is the effect of sample size on contingencies with different △P and Power- PC？ The research conducted an experiment to investigate whether participant＇s cansal judgment of seven contingencies vary with sample size. Contingency was presented on a booklet with a table format, and participants gave their causal - strength judgments under each contingency. Results show that sample size factor has different effects on different contingencies ： high sample size leads to low estimate on contingency with AP = 0, but has no effect on contingency with 0 〈 ｜△P ｜ = power - PC, but leads to a high estimate on contingency with ｜ △P ｜ 〈 power - PC = 1. Four times sample has more effect than two times sample. It seems that sample size effect is apt to emerge from the contingencies with ｜ △P ｜ 〈 power - PC. Meanwhile, a comparison of predictions of five models, △P, power - PC, SS, Support and χ2, was conducted. Results indicated that support and ）（2 model gave some predictions contradicting participants＇judgment, including lower predict on contingency with ｜ △P ｜ = . 33 and power - PC = . 50 than contingency with ｜ △P ｜ = . 33 and power - PC --- . 33, and lower predict on contingency with ｜ △P ｜ . 33 and power - PC = 1 than contingency with ｜ △P ｜ = power - PC = . 67. Support and SS model could predict sample size effect on each contingency, but the effectiveness of sample size was not so powerful as the prediction of the support model, while SS was the best model to predict the participants＂ performance in two kinds of causal direction.