如何估计 R 中的回归

问题描述 投票:0回答:0

我有以下数据集变量: enter image description here

我正在尝试复制“特许学校是否掠夺学生或耗尽资源?”的表 3 第 1 列? ” 作者 Thomas Dee 和 Helen Fu(EER,2004)可在此处.

我已经开发了一个回归模型,但即使我得到了正确的系数 (-0.026),我得到的标准误差仍然是错误的。我做错了什么或包含了错误的变量吗?

这是我使用的代码:

model <- lm_robust(pctwhite ~ locale  + elementary + yr99 + arizona + arizona*yr99 , data = mydata, se_type = "HC2")

summary(model)

电话: lm_robust(公式 = pctwhite ~ locale + elementary + yr99 + arizona + 亚利桑那 * yr99,数据 = mydata,se_type =“HC2”)

标准错误类型:HC2

系数: 估计标准。误差 t 值 Pr(>|t|) CI Lower CI Upper DF (拦截)0.3823461 0.01407 27.17453 3.789e-147 0.354759 0.409933 3355 locale2 0.0300987 0.01121 2.68403 7.310e-03 0.008112 0.052086 3355 locale3 0.0008367 0.01394 0.06002 9.521e-01 -0.026499 0.028172 3355 elementary1 -0.0153657 0.01042 -1.47461 1.404e-01 -0.035796 0.005065 3355 yr991 -0.0315218 0.01396 -2.25796 2.401e-02 -0.058893 -0.004150 3355 亚利桑那 0.1839495 0.01407 13.07578 3.818e-38 0.156367 0.211532 3355 yr991:亚利桑那 -0.0261615 0.01944 -1.34547 1.786e-01 -0.064285 0.011962 3355

多个 R 平方:0.08509,调整后的 R 平方:0.08345 F 统计量:6 和 3355 DF 上的 54.4,p 值:< 2.2e-16 structure(list(countyfips = c("04001", "04001", "04001", "04001", "04001", "04001", "04001", "04001", "04001", "04001", "04001", "04001", "04001", "04001", "04001", "04001", "04001", "04001", "04001", "04001", "04001", "04001", "04001", "04001", "04001", "04001", "04001", "04001", "04001", "04001", "04001", "04001", "04001", "04001", "04001", "04001", "04001", "04001", "04001", "04001", "04001", "04001", "04001", "04001", "04001", "04001", "04001", "04001", "04001", "04001", "04001", "04001", "04001", "04001", "04001", "04001", "04001", "04001", "04001", "04001", "04001", "04001", "04001", "04001", "04003", "04003", "04003", "04003", "04003", "04003", "04003", "04003", "04003", "04003", "04003", "04003", "04003", "04003", "04003", "04003", "04003", "04003", "04003", "04003", "04003", "04003", "04003", "04003", "04003", "04003", "04003", "04003", "04003", "04003", "04003", "04003", "04003", "04003", "04003", "04003"), year = c(94, 94, 94, 94, 94, 94, 94, 94, 94, 94, 94, 94, 94, 94, 94, 94, 94, 94, 94, 94, 94, 94, 94, 94, 94, 94, 94, 94, 94, 94, 94, 94, 99, 99, 99, 99, 99, 99, 99, 99, 99, 99, 99, 99, 99, 99, 99, 99, 99, 99, 99, 99, 99, 99, 99, 99, 99, 99, 99, 99, 99, 99, 99, 99, 94, 94, 94, 94, 94, 94, 94, 94, 94, 94, 94, 94, 94, 94, 94, 94, 94, 94, 94, 94, 94, 94, 94, 94, 94, 94, 94, 94, 94, 94, 94, 94, 94, 94, 94, 94), schoolid = c("040002201354", "040063000019", "040194000135", "040194000136", "040194000137", "040194000138", "040194000140", "040194000145", "040194001488", "040219000154", "040329000251", "040329000252", "040329000253", "040329000254", "040486000376", "040674000572", "040674001043", "040674001142", "040687000141", "040687000142", "040687000143", "040713000617", "040713000618", "040713001044", "040713001484", "040808000702", "040808001049", "040808001105", "040943000967", "040943000968", "040943000969", "040943000970", "040002201354", "040063000019", "040194000135", "040194000136", "040194000137", "040194000138", "040194000140", "040194000145", "040194001488", "040219000154", "040329000251", "040329000252", "040329000253", "040329000254", "040486000376", "040674000572", "040674001043", "040674001142", "040687000141", "040687000142", "040687000143", "040713000617", "040713000618", "040713001044", "040713001484", "040808000702", "040808001049", "040808001105", "040943000967", "040943000968", "040943000969", "040943000970", "040075000039", "040087000046", "040111000060", "040111001120", "040114000061", "040118000063", "040118000064", "040118000066", "040133000072", "040133000073", "040146000076", "040146000077", "040146000078", "040146000080", "040146000081", "040146000213", "040146001050", "040146001051", "040146001356", "040213000152", "040249000183", "040253000184", "040253000185", "040253000186", "040253000187", "040253000190", "040253000191", "040253000192", "040253000193", "040253000194", "040253001291", "040276000204", "040315000244", "040315000245", "040315000247", "040492000377"), arizona = c(1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1), elementary = c("1", "1", "1", "1", "0", "0", "1", "1", "1", "1", "1", "0", "1", "0", "1", "1", "0", "0", "1", "0", "1", "0", "1", "0", "1", "1", "0", "1", "1", "0", "1", "0", "1", "1", "1", "1", "0", "0", "1", "1", "1", "1", "1", "0", "1", "0", "1", "1", "0", "0", "1", "0", "1", "0", "1", "0", "1", "1", "0", "1", "1", "0", "1", "0", "1", "1", "1", "1", "0", "0", "0", "1", "1", "0", "1", "1", "0", "1", "0", "0", "1", "1", "1", "1", "1", "1", "0", "1", "0", "1", "1", "1", "1", "0", "1", "1", "1", "0", "1", "1"), totalstud = c(50, 35, 715, 734, 1240, 562, 414, 512, 277, 197, 470, 705, 424, 512, 83, 585, 341, 298, 236, 285, 151, 485, 424, 582, 426, 339, 441, 459, 922, 782, 714, 801, 78, 37, 745, 705, 1189, 571, 406, 510, 247, 178, 408, 752, 513, 525, 145, 541, 299, 350, 267, 267, 187, 403, 328, 501, 354, 303, 385, 377, 460, 794, 630, 787, 9, 71, 432, 426, 448, 476, 521, 350, 76, 31, 459, 516, 864, 512, 2564, 815, 481, 443, 613, 54, 80, 306, 705, 260, 1402, 401, 182, 393, 391, 487, 15, 228, 657, 424, 581, 51), whitestud = c(45, 34, 15, 13, 17, 17, 6, 5, 7, 149, 11, 6, 7, 9, 0, 26, 11, 12, 1, 1, 0, 367, 338, 464, 353, 239, 321, 328, 9, 12, 8, 16, 69, 34, 13, 17, 10, 8, 5, 2, 7, 136, 7, 9, 8, 2, 0, 10, 5, 10, 2, 1, 0, 320, 254, 421, 277, 193, 264, 247, 1, 4, 2, 8, 7, 52, 307, 320, 326, 240, 276, 166, 23, 11, 290, 234, 569, 353, 1663, 513, 336, 300, 467, 41, 62, 16, 81, 15, 97, 53, 9, 3, 49, 10, 0, 124, 359, 195, 311, 37), fteteach = c(4, 2.5, 39, 41, 73, 34, 28, 27.5, 16.3, 12.9, 34, 40, 31, 33, 7.5, 37.6, 23.5, 20, 27, 26, 10, 26.8, 21, 30.2, 23.7, 17.8, 26.5, 25, 57, 45.5, 46, 54.5, 5, 2.5, 43, 46, 75, 37, 25, 30, 18, 14.2, 33.1, 39, 30, 34.2, 11.5, 27, 21.8, 23, 22, 21, 12, 20, 17, 28, 21, 20, 27.8, 20, 27, 46, 41.5, 43, 1, 6.3, 19, 19.3, 20.1, 23.1, 28.2, 16.3, 7.5, 6.4, 25.3, 29.7, 49.5, 28.7, 125, 38.7, 26.7, 23.6, 29, 7.6, 4.3, 12, 32.5, 12, 73.4, 18, 6, 17, 18, 30, 1, 12, 29.8, 22.3, 25, 3.6), stud_teach_ratio = c(12.5, 14, 18.3333333333333, 17.9024390243902, 16.986301369863, 16.5294117647059, 14.7857142857143, 18.6181818181818, 16.9938650306749, 15.2713178294574, 13.8235294117647, 17.625, 13.6774193548387, 15.5151515151515, 11.0666666666667, 15.5585106382979, 14.5106382978723, 14.9, 8.74074074074074, 10.9615384615385, 15.1, 18.0970149253731, 20.1904761904762, 19.2715231788079, 17.9746835443038, 19.0449438202247, 16.6415094339623, 18.36, 16.1754385964912, 17.1868131868132, 15.5217391304348, 14.697247706422, 15.6, 14.8, 17.3255813953488, 15.3260869565217, 15.8533333333333, 15.4324324324324, 16.24, 17, 13.7222222222222, 12.5352112676056, 12.3262839879154, 19.2820512820513, 17.1, 15.3508771929825, 12.6086956521739, 20.037037037037, 13.7155963302752, 15.2173913043478, 12.1363636363636, 12.7142857142857, 15.5833333333333, 20.15, 19.2941176470588, 17.8928571428571, 16.8571428571429, 15.15, 13.8489208633094, 18.85, 17.037037037037, 17.2608695652174, 15.1807228915663, 18.3023255813954, 9, 11.2698412698413, 22.7368421052632, 22.0725388601036, 22.2885572139303, 20.6060606060606, 18.4751773049645, 21.4723926380368, 10.1333333333333, 4.84375, 18.1422924901186, 17.3737373737374, 17.4545454545454, 17.8397212543554, 20.512, 21.0594315245478, 18.0149812734082, 18.771186440678, 21.1379310344828, 7.10526315789474, 18.6046511627907, 25.5, 21.6923076923077, 21.6666666666667, 19.1008174386921, 22.2777777777778, 30.3333333333333, 23.1176470588235, 21.7222222222222, 16.2333333333333, 15, 19, 22.0469798657718, 19.0134529147982, 23.24, 14.1666666666667), pctwhite = c(0.9, 0.971428571428571, 0.020979020979021, 0.0177111716621253, 0.0137096774193548, 0.0302491103202847, 0.0144927536231884, 0.009765625, 0.0252707581227437, 0.756345177664975, 0.0234042553191489, 0.00851063829787234, 0.0165094339622642, 0.017578125, 0, 0.0444444444444445, 0.032258064516129, 0.0402684563758389, 0.00423728813559322, 0.00350877192982456, 0, 0.756701030927835, 0.797169811320755, 0.797250859106529, 0.828638497652582, 0.705014749262537, 0.727891156462585, 0.714596949891068, 0.00976138828633406, 0.0153452685421995, 0.0112044817927171, 0.0199750312109863, 0.884615384615385, 0.918918918918919, 0.0174496644295302, 0.024113475177305, 0.00841042893187553, 0.0140105078809107, 0.0123152709359606, 0.00392156862745098, 0.0283400809716599, 0.764044943820225, 0.017156862745098, 0.011968085106383, 0.0155945419103314, 0.00380952380952381, 0, 0.0184842883548983, 0.0167224080267558, 0.0285714285714286, 0.00749063670411985, 0.00374531835205993, 0, 0.794044665012407, 0.774390243902439, 0.840319361277445, 0.782485875706215, 0.636963696369637, 0.685714285714286, 0.655172413793103, 0.00217391304347826, 0.00503778337531486, 0.00317460317460318, 0.0101651842439644, 0.777777777777778, 0.732394366197183, 0.710648148148148, 0.751173708920188, 0.727678571428571, 0.504201680672269, 0.529750479846449, 0.474285714285714, 0.302631578947368, 0.354838709677419, 0.631808278867102, 0.453488372093023, 0.658564814814815, 0.689453125, 0.648595943837754, 0.629447852760736, 0.698544698544699, 0.677200902934537, 0.761827079934747, 0.759259259259259, 0.775, 0.0522875816993464, 0.114893617021277, 0.0576923076923077, 0.0691868758915835, 0.13216957605985, 0.0494505494505494, 0.00763358778625954, 0.125319693094629, 0.0205338809034908, 0, 0.543859649122807, 0.546423135464231, 0.459905660377359, 0.535283993115318, 0.725490196078431), locale = c("3", "3", "2", "2", "2", "2", "2", "2", "2", "3", "3", "3", "3", "3", "3", "3", "3", "3", "3", "3", "3", "3", "3", "3", "3", "2", "2", "2", "2", "2", "2", "2", "3", "3", "3", "3", "3", "3", "3", "3", "3", "3", "3", "3", "3", "3", "3", "3", "3", "3", "3", "3", "3", "2", "3", "2", "2", "2", "2", "2", "3", "3", "3", "3", "2", "3", "2", "2", "2", "2", "2", "2", "3", "3", "2", "2", "2", "2", "2", "2", "2", "2", "2", "3", "3", "2", "2", "2", "2", "2", "3", "2", "2", "2", "2", "3", "3", "3", "3", "3"), yr99 = c("0", "0", "0", "0", "0", "0", "0", "0", "0", "0", "0", "0", "0", "0", "0", "0", "0", "0", "0", "0", "0", "0", "0", "0", "0", "0", "0", "0", "0", "0", "0", "0", "1", "1", "1", "1", "1", "1", "1", "1", "1", "1", "1", "1", "1", "1", "1", "1", "1", "1", "1", "1", "1", "1", "1", "1", "1", "1", "1", "1", "1", "1", "1", "1", "0", "0", "0", "0", "0", "0", "0", "0", "0", "0", "0", "0", "0", "0", "0", "0", "0", "0", "0", "0", "0", "0", "0", "0", "0", "0", "0", "0", "0", "0", "0", "0", "0", "0", "0", "0"), arizonayr99 = c(0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0), fracwhite519 = c(NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA)), row.names = c(NA, -100L ), class = c("tbl_df", "tbl", "data.frame"))

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