Различные результаты в Stata и R с одним и тем же кодом anova - PullRequest
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Различные результаты в Stata и R с одним и тем же кодом anova

0 голосов
/ 28 мая 2019

У меня есть некоторый код Stata, и я хочу повторить результаты в R .Однако даже с одним и тем же набором данных и, как мне кажется, одним и тем же кодом, я получаю в R результаты, отличные от результатов в Stata.Я думаю, это может быть потому, что Stata делает порядок регрессии отличным от введенного.

Нужен ли мне точно такой же порядок, как в Stata, чтобы получить те же результаты, и как я могу это сделать?

Я изменил все переменные на факторы и попробовал еще раз, но проблема все еще существует.

Я заметил, что когда я изменяю порядок объясняющих переменных, я получаю разные результаты, но я не нахожу "правильный порядок" для репликации результатов Stata.

Код Stata: 

. anova testm2 c.testm1 i.hptreat c.cortm1 c.cortm2 i.female if inelig == 0 & anyoutv1 == 0     

Number of obs =39    R-squared =0.7048 
Root MSE= 16.0144    Adj R-squared =0.6601 

 Source | Partial SS         df         MS        F    Prob>F
---------------------------------------------------------------
  Model |  20209.281          5   4041.8563     15.76  0.0000
 testm1 |  3516.6527          1   3516.6527     13.71  0.0008   
 hptreat|  1183.5007          1   1183.5007      4.61  0.0391
 cortm1 |  8.5753841          1   8.5753841      0.03  0.8560
 cortm2 |  2810.9353          1   2810.9353     10.96  0.0023
 female |  2557.3444          1   2557.3444      9.97  0.0034
Residual|  8463.2532         33   256.46222  
----------------------------------------------------------------
  Total |  28672.535         38   754.54038

R код: 

FosseTest<-aov(testm2~testm1+hptreat+cortm1+cortm2+female,data=X2data)
summary(FosseTest) 

            Df Sum Sq Mean Sq F value   Pr(>F)    
testm1       1  15121   15121  58.962 7.68e-09 ***
hptreat      1    524     524   2.043  0.16228    
cortm1       1     23      23   0.089  0.76715    
cortm2       1   1984    1984   7.735  0.00888 ** 
female       1   2557    2557   9.972  0.00339 ** 
Residuals   33   8463     256                     
---
Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1

Вы видите, что я получаю совершенно разные значения в репликации.

в наборе данных X2d IУже подмножество значений для if inelig == 0 & anyoutv1 == 0

для восстановления данных: 

dput(X2data)
structure(list(id = c(29L, 30L, 31L, 32L, 34L, 35L, 36L, 37L, 
39L, 41L, 42L, 43L, 44L, 46L, 47L, 49L, 50L, 51L, 52L, 53L, 54L, 
55L, 57L, 58L, 59L, 60L, 61L, 62L, 64L, 65L, 66L, 67L, 68L, 69L, 
70L, 71L, 72L, 73L, 74L), inelig = structure(c(1L, 1L, 1L, 1L, 
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
1L, 1L, 1L), .Label = c("Analytic sample (keep)", "Ineligible (drop)"
), class = "factor"), ccydrop = c(0L, 0L, 0L, 0L, 1L, 0L, 0L, 
0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 1L, 0L, 0L, 0L, 0L, 0L, 0L, 
0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L
), cortm1v2 = c(0.003, 0.086, 0.047, 0.106, NA, 0.153, 0.086, 
0.005, 0.133, 0.036, 0.03, 0.015, 0.014, 0.111, 0.389, 0.298, 
0.4, 0.215, 0.062, 0.021, 0.075, 0.073, 0.033, 0.243, 0.126, 
0.147, 0.019, 0.048, 0.28, 0.052, 0.039, 0.105, 0.111, 0.133, 
0.065, 0.051, 0.143, 0.127, 0.095), cortm2v2 = c(0.025, 0.167, 
0.059, 0.112, 0.171, 0.183, 0.102, 0.018, 0.08, 0.015, 0.027, 
0.05, 0.025, 0.046, 0.085, 0.144, 0.155, 0.09, 0.057, 0.023, 
0.038, 0.205, 0.035, 0.198, 0.112, 0.211, 0.042, 0.142, 0.328, 
0.076, 0.067, 0.094, 0.245, 0.153, 0.115, 0.127, 0.257, 0.125, 
0.096), cdiffv2 = c(0.022, 0.081, 0.012, 0.006, NA, 0.03, 0.016, 
0.013, -0.053, -0.021, -0.003, 0.035, 0.011, -0.065, -0.304, 
-0.154, -0.245, -0.125, -0.005, 0.002, -0.037, 0.132, 0.002, 
-0.045, -0.014, 0.064, 0.023, 0.094, 0.048, 0.024, 0.028, -0.011, 
0.134, 0.02, 0.05, 0.076, 0.114, -0.002, 0.001), testm1v2 = c(38.72, 
32.77, 32.32, 17.99, 73.58, 80.69, 48.56, 21.92, 27.24, 40.93, 
31.73, 60.05, 38.04, 30.17, 59.07, 26.92, 25.41, 47.81, 63.02, 
34.49, 104.38, 38.08, 30.99, 35.23, 104.81, 49.33, 50.03, 11.65, 
143.57, 48.31, 90.37, 48.56, 41.67, 75.23, 60.56, 39.03, 18.16, 
37.9, 84.5), testm2v2 = c(62.37, 29.23, 27.51, 28.66, 44.67, 
105.48, 42.67, 15.01, 21.33, 10.87, 2.14, 44.53, 35.8, 10.43, 
47.54, 48.5, 38.98, 91.32, 52.94, 22.43, 58.68, 81.63, 34.79, 
38.57, 94.86, 50.83, 55.75, 45.33, 111.62, 65.15, 81.08, 50.08, 
44.86, 58.63, 85.85, 58.69, 16.35, 35.97, 99.08), tdiffv2 = c(23.65, 
-3.54, -4.81, 10.67, -28.91, 24.79, -5.89, -6.91, -5.91, -30.06, 
-29.59, -15.52, -2.24, -19.74, -11.53, 21.58, 13.57, 43.51, -10.08, 
-12.06, -45.7, 43.55, 3.8, 3.34, -9.95, 1.5, 5.72, 33.68, -31.95, 
16.84, -9.29000000000001, 1.52, 3.19, -16.6, 25.29, 19.66, -1.81, 
-1.93, 14.58), testoutv1 = structure(c(1L, 1L, 1L, 1L, 1L, 1L, 
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
1L), .Label = c("Not selected", "Selected"), class = "factor"), 
    cortoutv1 = structure(c(1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
    1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
    1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L
    ), .Label = c("Not selected", "Selected"), class = "factor"), 
    anyoutv1 = structure(c(1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
    1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
    1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L
    ), .Label = c("Not selected", "Selected"), class = "factor"), 
    testoutv2 = structure(c(1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
    1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
    1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L
    ), .Label = c("Not selected", "Selected"), class = "factor"), 
    cortoutv2 = structure(c(1L, 1L, 1L, 1L, 2L, 1L, 1L, 1L, 1L, 
    1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
    1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L
    ), .Label = c("Not selected", "Selected"), class = "factor"), 
    anyoutv2 = structure(c(1L, 1L, 1L, 1L, 2L, 1L, 1L, 1L, 1L, 
    1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
    1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L
    ), .Label = c("Not selected", "Selected"), class = "factor"), 
    pose1rate = c(6L, 7L, 6L, 6L, 7L, 7L, 6L, 7L, 5L, 6L, 7L, 
    4L, 7L, 7L, 7L, 6L, 7L, 7L, 7L, 7L, 6L, 7L, 7L, 7L, 7L, 7L, 
    7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L), pose2rate = c(6L, 
    6L, 5L, 7L, 7L, 7L, 7L, 7L, 6L, 7L, 7L, 7L, 7L, 7L, 7L, 6L, 
    6L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 6L, 7L, 6L, 7L, 7L, 7L, 
    6L, 7L, 7L, 7L, 7L, 7L, 6L, 6L), poseratem = c(6, 6.5, 5.5, 
    6.5, 7, 7, 6.5, 7, 5.5, 6.5, 7, 5.5, 7, 7, 7, 6, 6.5, 7, 
    7, 7, 6.5, 7, 7, 7, 7, 6.5, 7, 6.5, 7, 7, 7, 6.5, 7, 7, 7, 
    7, 7, 6.5, 6.5), saldiff = c(24.30555556, 20.83333333, 29.16666667, 
    18.75, 23.61111111, 34.02777778, 18.05555556, 19.44444444, 
    21.52777778, 15.97222222, 22.91666667, 13.88888889, 22.22222222, 
    25, 22.22222222, 22.22222222, 18.05555556, 17.36111111, 22.22222222, 
    27.08333333, 20.83333333, 24.30555556, 22.22222222, 28.47222222, 
    24.30555556, 25, 27.77777778, 22.22222222, 15.97222222, 24.30555556, 
    21.52777778, 19.44444444, 15.97222222, 15.27777778, 15.97222222, 
    24.30555556, 19.44444444, 24.30555556, 15.27777778), sal2manip = c(19.80555556, 
    16.33333333, 24.66666667, 14.25, 19.11111111, 29.52777778, 
    13.55555556, 14.94444444, 17.02777778, 11.47222222, 18.41666667, 
    9.38888889, 17.72222222, 20.5, 17.72222222, 17.72222222, 
    13.55555556, 12.86111111, 17.72222222, 22.58333333, 16.33333333, 
    19.80555556, 17.72222222, 23.97222222, 19.80555556, 20.5, 
    23.27777778, 17.72222222, 11.47222222, 19.80555556, 17.02777778, 
    14.94444444, 11.47222222, 10.77777778, 11.47222222, 19.80555556, 
    14.94444444, 19.80555556, 10.77777778), hptreat = structure(c(2L, 
    1L, 2L, 1L, 1L, 2L, 1L, 2L, 2L, 2L, 1L, 2L, 1L, 1L, 2L, 2L, 
    1L, 2L, 1L, 2L, 1L, 2L, 2L, 1L, 2L, 1L, 2L, 1L, 1L, 2L, 1L, 
    2L, 1L, 2L, 1L, 2L, 1L, 2L, 1L), .Label = c("0", "1"), class = "factor"), 
    female = structure(c(1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 
    2L, 2L, 1L, 2L, 2L, 2L, 2L, 2L, 1L, 1L, 2L, 1L, 2L, 1L, 2L, 
    1L, 2L, 2L, 2L, 1L, 1L, 1L, 2L, 2L, 2L, 1L, 1L, 2L, 2L, 1L
    ), .Label = c("0", "1"), class = "factor"), age = c(19L, 
    20L, 20L, 18L, 21L, 20L, 18L, 21L, 35L, 20L, 18L, 20L, 20L, 
    18L, 20L, 25L, 18L, 23L, 21L, 19L, 20L, 20L, 30L, 19L, 22L, 
    18L, 19L, 22L, 19L, 20L, 28L, 28L, 19L, 19L, 20L, 25L, 20L, 
    25L, 23L), cort1a1 = c(0.004, 0.085, 0.049, 0.107, 0.486, 
    0.159, 0.088, 0.004, 0.138, 0.035, 0.03, 0.018, 0.017, 0.111, 
    0.39, 0.292, 0.396, 0.213, 0.065, 0.022, 0.074, 0.077, 0.035, 
    0.241, 0.126, 0.154, 0.021, 0.05, 0.296, 0.054, 0.04, 0.109, 
    0.114, 0.133, 0.063, 0.055, 0.149, 0.134, 0.098), cort1a2 = c(0.001, 
    0.086, 0.045, 0.105, 0.482, 0.147, 0.085, 0.005, 0.127, 0.037, 
    0.031, 0.013, 0.011, 0.111, 0.389, 0.304, 0.405, 0.218, 0.059, 
    0.02, 0.076, 0.069, 0.032, 0.246, 0.126, 0.141, 0.017, 0.046, 
    0.264, 0.051, 0.038, 0.101, 0.109, 0.133, 0.068, 0.048, 0.137, 
    0.12, 0.092), cort2a1 = c(0.027, 0.174, 0.056, 0.111, 0.175, 
    0.179, 0.103, 0.021, 0.079, 0.014, 0.028, 0.051, 0.024, 0.051, 
    0.083, 0.148, 0.156, 0.086, 0.062, 0.024, 0.038, 0.209, 0.036, 
    0.199, 0.114, 0.207, 0.041, 0.141, 0.333, 0.078, 0.065, 0.088, 
    0.238, 0.157, 0.119, 0.132, 0.268, 0.132, 0.099), cort2a2 = c(0.023, 
    0.161, 0.062, 0.113, 0.166, 0.188, 0.101, 0.016, 0.081, 0.015, 
    0.026, 0.049, 0.026, 0.041, 0.086, 0.139, 0.154, 0.093, 0.052, 
    0.022, 0.038, 0.202, 0.034, 0.198, 0.111, 0.215, 0.042, 0.142, 
    0.324, 0.075, 0.068, 0.101, 0.252, 0.149, 0.111, 0.123, 0.247, 
    0.118, 0.093), cortm1 = c(0.0024999999, 0.085500002, 0.046999998, 
    0.106, 0.484, 0.153, 0.086499996, 0.0044999998, 0.13249999, 
    0.035999998, 0.0305, 0.0155, 0.014, 0.111, 0.38949999, 0.29800001, 
    0.4005, 0.2155, 0.061999999, 0.021, 0.075000003, 0.072999999, 
    0.033500001, 0.24349999, 0.126, 0.14749999, 0.018999999, 
    0.048, 0.28, 0.052499998, 0.039000001, 0.105, 0.1115, 0.133, 
    0.065499999, 0.0515, 0.14300001, 0.127, 0.094999999), cortm2 = c(0.025, 
    0.1675, 0.059, 0.112, 0.1705, 0.18350001, 0.102, 0.0185, 
    0.079999998, 0.0145, 0.027000001, 0.050000001, 0.025, 0.046, 
    0.0845, 0.1435, 0.155, 0.089500003, 0.057, 0.023, 0.037999999, 
    0.20550001, 0.035, 0.19850001, 0.1125, 0.211, 0.041499998, 
    0.1415, 0.3285, 0.076499999, 0.066500001, 0.094499998, 0.245, 
    0.153, 0.115, 0.1275, 0.25749999, 0.125, 0.096000001), cdiff = c(0.022500001, 
    0.082000002, 0.012000002, 0.0060000047, -0.31349999, 0.03050001, 
    0.015500002, 0.014, -0.052499995, -0.021499999, -0.0034999996, 
    0.034500003, 0.011, -0.064999998, -0.30500001, -0.15450001, 
    -0.2455, -0.12599999, -0.004999999, 0.0020000003, -0.037000004, 
    0.13250001, 0.0014999993, -0.044999987, -0.013500005, 0.063500002, 
    0.022499999, 0.093499996, 0.048500001, 0.024, 0.0275, -0.010499999, 
    0.13350001, 0.019999996, 0.049500003, 0.075999998, 0.11449999, 
    -0.0020000041, 0.001000002), test1a1 = c(39.87, 33.22, 32.52, 
    19.74, 78.85, 83.51, 48.37, 22.31, 28.17, 41.44, 32.92, 61.4, 
    40.31, 30.36, 59.44, 27.52, 26.14, 46.75, 63.73, 34.03, 98.47, 
    36.62, 30.26, 37.15, 105.64, 47.99, 50.15, 11.33, 149.12, 
    48.57, 92.04, 51.22, 42.25, 77.07, 62.75, 38.8, 17.91, 40.28, 
    88.47), test1a2 = c(37.58, 32.32, 32.12, 16.25, 68.31, 77.88, 
    48.75, 21.53, 26.32, 40.42, 30.55, 58.7, 35.78, 29.97, 58.7, 
    26.32, 24.69, 48.87, 62.32, 34.95, 110.29, 39.53, 31.72, 
    33.32, 103.99, 50.67, 49.9, 11.97, 138.02, 48.05, 88.7, 45.89, 
    41.08, 73.39, 58.38, 39.25, 18.41, 35.53, 80.54), test2a1 = c(64.22, 
    29.43, 27.98, 28.17, 46.14, 105.92, 43.68, 16.41, 21.42, 
    11.35, 1.66, 44.17, 38.58, 11.11, 48.57, 48.31, 39.71, 92.04, 
    52.73, 22.3, 58.23, 82.01, 35.76, 39.59, 94.06, 50.52, 55.82, 
    45.91, 115.13, 67.59, 82.97, 49.89, 45.09, 57.86, 86.76, 
    58.83, 16.53, 36.7, 100.4), test2a2 = c(60.53, 29.04, 27.04, 
    29.14, 43.2, 105.05, 41.66, 13.62, 21.25, 10.39, 2.63, 44.9, 
    33.02, 9.75, 46.52, 48.7, 38.25, 90.59, 53.15, 22.57, 59.14, 
    81.24, 33.81, 37.55, 95.66, 51.14, 55.69, 44.74, 108.1, 62.71, 
    79.18, 50.27, 44.63, 59.39, 84.94, 58.55, 16.16, 35.24, 97.75
    ), testm1 = c(38.724998, 32.77, 32.32, 17.995001, 73.580002, 
    80.695, 48.560001, 21.92, 27.245001, 40.93, 31.735001, 60.049999, 
    38.044998, 30.165001, 59.07, 26.92, 25.415001, 47.810001, 
    63.025002, 34.490002, 104.38, 38.075001, 30.99, 35.235001, 
    104.815, 49.330002, 50.025002, 11.65, 143.57001, 48.310001, 
    90.370003, 48.555, 41.665001, 75.230003, 60.564999, 39.025002, 
    18.16, 37.904999, 84.504997), testm2 = c(62.375, 29.235001, 
    27.51, 28.655001, 44.669998, 105.485, 42.669998, 15.015, 
    21.334999, 10.87, 2.145, 44.535, 35.799999, 10.43, 47.544998, 
    48.505001, 38.98, 91.315002, 52.939999, 22.434999, 58.685001, 
    81.625, 34.785, 38.57, 94.860001, 50.830002, 55.755001, 45.325001, 
    111.615, 65.150002, 81.074997, 50.080002, 44.860001, 58.625, 
    85.849998, 58.689999, 16.344999, 35.970001, 99.074997), tdiff = c(23.650002, 
    -3.5349998, -4.8099995, 10.66, -28.910004, 24.790001, -5.8900032, 
    -6.9049997, -5.9100018, -30.060001, -29.59, -15.514999, -2.2449989, 
    -19.735001, -11.525002, 21.585001, 13.564999, 43.505001, 
    -10.085003, -12.055002, -45.694996, 43.549999, 3.7950001, 
    3.3349991, -9.9550018, 1.5, 5.7299995, 33.675003, -31.955009, 
    16.84, -9.2950058, 1.5250015, 3.1949997, -16.605003, 25.285, 
    19.664997, -1.8150005, -1.9349976, 14.57), feelpower = structure(c(2L, 
    3L, 1L, 2L, 1L, 2L, 3L, 3L, 3L, 3L, 3L, 4L, 3L, 1L, 2L, 1L, 
    1L, 2L, 2L, 2L, 1L, 2L, 1L, 1L, 1L, 2L, 2L, 2L, 3L, 4L, 3L, 
    4L, 3L, 1L, 3L, 4L, 2L, 2L, 3L), .Label = c("2", "3", "Not at all", 
    "Very much"), class = "factor"), incharge = structure(c(1L, 
    1L, 3L, 4L, 1L, 2L, 3L, 3L, 1L, 1L, 3L, 4L, 3L, 2L, 2L, 1L, 
    3L, 2L, 2L, 1L, 1L, 2L, 1L, 1L, 2L, 1L, 1L, 2L, 1L, 2L, 1L, 
    1L, 3L, 1L, 1L, 4L, 3L, 1L, 1L), .Label = c("2", "3", "Not at all", 
    "Very much"), class = "factor"), powm = structure(c(3L, 1L, 
    1L, 5L, 2L, 4L, 6L, 6L, 1L, 1L, 6L, 7L, 6L, 3L, 4L, 2L, 1L, 
    4L, 4L, 3L, 2L, 4L, 2L, 2L, 3L, 3L, 3L, 4L, 1L, 5L, 1L, 4L, 
    6L, 2L, 1L, 7L, 2L, 3L, 1L), .Label = c("1.5", "2", "2.5", 
    "3", "3.5", "Not at all", "Very much"), class = "factor"), 
    diceroll = structure(c(2L, 1L, 2L, 2L, 1L, 2L, 2L, 2L, 2L, 
    1L, 2L, 2L, 2L, 2L, 2L, 2L, 1L, 2L, 2L, 2L, 1L, 2L, 2L, 2L, 
    2L, 2L, 2L, 1L, 2L, 2L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 1L, 1L
    ), .Label = c("No", "Yes"), class = "factor")), row.names = c(2L, 
3L, 4L, 5L, 7L, 8L, 9L, 10L, 12L, 14L, 15L, 16L, 17L, 19L, 20L, 
22L, 23L, 24L, 25L, 26L, 27L, 28L, 30L, 31L, 32L, 33L, 34L, 35L, 
37L, 38L, 39L, 40L, 41L, 42L, 43L, 44L, 45L, 46L, 47L), class = "data.frame")

1 Ответ

1 голос
/ 28 мая 2019

Вы можете получить те же результаты в R, используя drop1(FosseTest, test = "F"). Это проверит эффект оставления одной из переменных за aov. 

drop1(FosseTest, test = "F")

# 
# Single term deletions
# 
# Model:
# testm2 ~ testm1 + hptreat + cortm1 + cortm2 + female
#         Df Sum of Sq     RSS    AIC F value    Pr(>F)    
# <none>                8463.3 221.82                      
# testm1   1    3516.7 11979.9 233.37 13.7122 0.0007751 ***
# hptreat  1    1183.5  9646.8 224.92  4.6147 0.0391333 *  
# cortm1   1       8.6  8471.8 219.86  0.0334 0.8560279    
# cortm2   1    2810.9 11274.2 231.00 10.9604 0.0022605 ** 
# female   1    2557.3 11020.6 230.11  9.9716 0.0033895 ** 
# ---
# Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1

summary(FosseTest) отображает последовательный эффект добавления переменных одна за другой.

Был другой способ получить доступ к этому, но на данный момент я не могу вспомнить ...

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