这篇博客探讨了Python中固定效应模型的回归结果，包括R方、组数、最小观察值等统计指标。结果显示，某些系数的P值不显著，如lncharge和lnletter。博主对如何处理不显著的P值提出了疑问。
Fixed-effects (within) regression Number of obs = 270
Group variable: district Number of groups = 30
R-sq: within = 0.3651 Obs per group: min = 9
between = 0.6362 avg = 9.0
overall = 0.5300 max = 9
F(8,232) = 16.68
corr(u_i, Xb) = -0.0605 Prob > F = 0.0000
------------------------------------------------------------------------------
lnpatent | Coef. Std. Err. t P>|t| [95% Conf. Interval]
-------------+----------------------------------------------------------------
lncharge | .0988603 .1861722 0.53 0.596 -.267944 .4656646
lnascale |
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