LPM and Logit Regressions of HS Honors on Left Hand 2D:4D and its Square.

Note: The numbers in brackets are robust standard errors; * Significant at 10%, ** 5%, *** 1% in OLS, LPM or Logit regressions; + p-value equal or less than 0.10 tolerance level in backward stepwise regressions, implying that the variable ought not to be removed from the model. Lmax (Lmin) is the value of left digit ratio that maximizes (minimizes) the dependent variable, equal to -b1/(2×b2), computed only for significant values in OLS and LPM regressions.

注释：括号内的数值为稳健标准误；* 表示在普通最小二乘（OLS, Ordinary Least Squares）、线性概率模型（LPM, Linear Probability Model）或Logit回归中显著性水平为10%，** 为5%，*** 为1%；+ 代表在向后逐步回归中p值小于等于0.10的容忍阈值，意味着该变量不应从模型中剔除。Lmax（Lmin）为使因变量实现最大化（最小化）的左手数字比例值，计算公式为 $-b_1/(2 imes b_2)$，且仅在普通最小二乘与线性概率模型回归的显著结果中进行计算。