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. 2012 Oct 8;7(10):e46319. doi: 10.1371/journal.pone.0046319

Table 10. LPM and Logit Regressions of Full Scholarship on Left Hand 2D:4D and its Square.

Moscow
Full Scholarship
Female Male
Explanatory Variables LPM Logit LPM Logit LPM Logit LPM Logit
Left Hand 2D:4D 2.126 10.931 0.184 −11.150 −49.158* + −259.535* + −46.485* + −277.004* +
(22.640) (117.828) (22.076) (132.991) (27.578) (144.446) (26.864) (151.403)
Square of Left Hand 2D:4D −1.130 −5.816 0.279 7.531 25.859* + 136.198* + 24.594* + 146.418* +
(11.350) (59.012) (11.146) (67.379) (13.882) (73.258) (13.520) (77.445)
Left Hand 2D:4D × Faculty (Law) −0.072 −1.482 0.457 2.986
(1.545) (8.750) (1.630) (9.372)
Left Hand 2D:4D × Faculty (Management) 1.885 8.420 0.189 3.741
(2.017) (9.321) (2.204) (10.426)
Left Hand 2D:4D × Faculty (Political Science) 0.699 + 2.775 + −0.578 −4.404
(1.668) (11.848) (2.415) (16.176)
Square of Left Hand 2D:4D × Faculty (Law) 0.138 1.868 −0.442 −2.959
(1.544) (8.807) (1.639) (9.553)
Square of Left Hand 2D:4D × Faculty (Management) −2.070 + −9.243 + −0.488 + −5.083 +
(2.011) (9.311) (2.230) (10.596)
Square of Left Hand 2D:4D × Faculty (Political Science) −0.564 −1.875 0.620 4.642
(1.670) (11.933) (2.431) (16.503)
Constant −0.248 −4.028 0.276 4.657 23.948* 123.967* 22.590* 131.488*
(11.285) (58.786) (10.954) (65.706) (13.685) (71.168) (13.342) (74.073)
R-squared (LPM) 0.000 0.072 0.022 0.087
Adjusted R-squared (LPM) 0.004 0.055 0.016 0.064
Pseudo R-squared (Logit) 0.000 0.062 0.019 0.069
Pseudo R-squared (Stepwise) 0.000 0.056 0.019 0.068
N 447 447 447 447 322 322 322 322
p-value(F) (LPM, Logit) 0.973 0.972 0.000 0.000 0.001 0.008 0.000 0.001
F-stat (LPM) 0.028 3.893 6.960 4.833
Lmin (LPM) 0.951 0.945 (Economics)

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.