Solved – Repeated Measures ANOVA and the Bonferroni post hoc test different results of significantly

anovabonferronipost-hocr

I am doing an Repeated Measures ANOVA and the Bonferroni post hoc test for my data using R project. The ANOVA gives a significantly difference between the data but not the Bonferroni post hoc test.

> anova(aov2)
            numDF denDF   F-value p-value
(Intercept)     1  1366 110.51125  <.0001
time            5  1366   9.84684  <.0001

while 

> pairwise.t.test(x=table.metric2$value, g=table.metric2$time, p.adj="bonf")

        Pairwise comparisons using t tests with pooled SD 

data:  table.metric2$value and table.metric2$time 

    Su1 Su2 Su3 Su4 Su5
Su2 1   -   -   -   -  
Su3 1   1   -   -   -  
Su4 1   1   1   -   -  
Su5 1   1   1   1   -  
Su6 1   1   1   1   1  

P value adjustment method: bonferroni

These are my data with the code used

plot <- c(rep(1:275))

Su1 <- c(13.5584,0.0000,2.0710,0.4826,1.2761,1.6690,3.5188, 13.7578,0.0000,0.0000,0.0004,0.0000,0.0000,0.0000,4.4634,3.0151,2.1719,5.2861,4.9651,0.7908,0.0000,0.0000,0.0000,0.0000,
0.0000,5.2749,5.4706,4.4416,3.2166,0.0000,0.1929,0.0000,0.0000,0.0000,0.0000,0.0000,4.6765,1.7761,4.3579,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,
0.0000,6.1794,2.4194,1.4319,0.0000,0.0327,0.0000,0.4633,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0018,0.0000,0.0000,
0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,
0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.5425,0.5274,2.0883,0.6024,0.0000,0.0018,0.0000,0.0000,0.0015,0.0012,0.0000,0.0000,0.0000,
0.4560,2.1256,0.0295,0.0328,0.0000,1.6447,0.0428,0.0067,0.0058,0.0000,0.0000,0.0000,0.0001,0.3317,0.2898,3.5134,0.1539,0.0199,0.0000,0.0494,0.1159,2.0976,0.0644,0.9730,
0.0010,0.5074,0.0003,0.0000,0.1188,1.8818,0.0000,0.1213,0.3585,7.3932,0.5492,0.0045,0.9879,0.0010,0.7625,0.1695,0.1211,0.3164,2.6750,3.8926,0.0000,3.4626,0.0000,5.8339,
6.7315,0.0244,4.8770,2.6237,2.3700,0.5338,0.0215,3.2196,1.9811,3.3825,3.3929,1.5426,0.9165, 10.6561,3.2154,4.1531,5.3381,3.9432,4.8675,0.0047,0.0026,0.2058,1.8509,0.3697,
0.3131,0.0707,4.7908,6.4087, 10.3670,5.7662,4.0460,3.2571,9.1767,0.0116,0.0908,0.0053,0.1480,0.9063,5.4331,5.7945, 14.4097,6.9635,7.0637,0.1064,9.9095, 11.8432, 10.0234,0.0000,
0.0491,5.0472,5.3094,5.1657, 14.3944,7.6244,0.0034,1.4953, 14.7658,6.1775,7.1567,0.0296,0.0911,3.5552,4.9543,3.1200,1.9774,0.0000,4.1663,0.0000,2.3672,0.0638,1.8952,4.1948,
6.4229, 10.7573,0.0008,1.3818,6.0011,3.6791,9.7816,1.5203,0.8616,1.5483,5.4174,2.7070,2.1627,0.0000,1.7360,3.7292,2.4638,7.4498,4.2343,6.8263,3.2410,0.0001,0.0001,9.7424,
4.2861,2.9912,0.4316, 11.6082,2.0138,0.0002,1.8783,0.9934,0.2983,1.4013,0.1429)

Su2 <- c(10.4361,0.0000,2.3346,0.5769,1.3392,1.5908,3.5759, 13.3183,0.0005,0.0000,0.0019,0.0000,0.0000,0.0000,4.4862,3.0418,2.3991,5.4263,4.9456,0.6907,0.0000,0.0007,0.0000,0.0000,
0.0000,5.1065,5.1748,4.2888,3.3633,0.0000,0.1791,0.0000,0.0000,0.0000,0.0000,0.0000,5.3485,1.9216,4.2880,0.0000,0.0001,0.0001,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,
0.0000,6.3664,2.2888,1.4636,0.0000,0.0282,0.0000,0.5838,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0013,0.0000,0.0000,
0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0002,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,
0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.6240,0.6401,1.9324,0.6263,0.0000,0.0020,0.0000,0.0001,0.0039,0.0018,0.0000,0.0000,0.0000,
0.4321,1.9815,0.0528,0.0350,0.0000,1.6519,0.0328,0.0153,0.0171,0.0000,0.0000,0.0000,0.0000,0.3966,0.2957,3.4653,0.1473,0.0038,0.0000,0.0774,0.1180,2.2780,0.0611,0.9490,
0.0024,0.8337,0.0000,0.0000,0.1531,1.9778,0.0000,0.1171,0.3485,7.2378,0.7476,0.0028,1.2072,0.0015,0.7425,0.1352,0.1908,0.3092,2.3735,3.9768,0.0000,3.8786,0.0000,6.5420,
6.8490,0.0256,5.8268,2.7856,2.4640,0.6399,0.0215,5.3411,1.7939,3.3401,3.2942,1.4990,0.9264, 10.6864,3.3749,4.7978,5.2929,3.8639,5.3890,0.0027,0.0486,0.2105,1.8514,0.3526,
0.3146,0.0950,4.8061,6.2244, 10.1131,5.8538,3.8861,4.4240,9.5952,0.0255,0.0533,0.0085,0.1742,1.0188,7.7153,5.4663,14.6060,6.8725,6.7284,0.0841, 10.2016, 11.3384,9.8938,0.0000,
0.0749,5.0774,7.2876,5.2040, 14.7609,7.7862,0.0005,1.4099, 14.8639,6.8801,7.2587,0.0125,0.0513,3.1338,7.1539,3.1733,1.9729,0.0000,4.5081,0.0000,2.1572,0.0452,1.8866,8.0198,
9.7868, 10.8746,0.0000,1.5011,6.0825,3.6705,9.9171,1.7091,0.8267,1.4186,6.4235,2.9303,1.9019,0.0000,1.5869,4.4028,2.4186,7.7739,4.6728,8.7722,3.9859,0.0001,0.0001, 10.1583,
5.4758,2.8977,0.9716, 11.5342,2.6111,0.0000,1.7497,1.0041,0.3273,1.1953,0.2289)

Su3 <- c(12.5808,0.0000,2.7244,0.1119,1.2633,0.9702,2.4513,2.4419,0.0014,0.0000,0.0000,0.0000,0.0019,0.0105,3.5392,2.4033,2.1847,5.5912,4.8628,0.9449,0.0000,0.0000,0.0000,0.0000,
0.0000,4.2928,5.0754,3.4644,2.8663,0.0066,0.0043,0.0000,0.0000,0.0000,0.0000,0.0000,3.5292,1.4846,4.6333,0.0000,0.0003,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,
0.0000,7.0110,2.7508,2.0824,0.0001,0.0001,0.0000,0.0770,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0023,0.0000,0.0000,
0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,
0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.4546,0.1491,2.2391,0.4464,0.0000,0.0007,0.0000,0.0000,0.0000,0.0238,0.0000,0.0000,0.0000,
0.5663,1.5734,0.0247,0.0259,0.0000,0.6823,0.0101,0.0000,0.1171,0.0000,0.0000,0.0000,0.0000,0.1110,0.0960,2.2888,0.1338,0.0000,0.0000,0.0294,0.1273,2.3082,0.0081,0.6343,
0.0021,0.1690,0.0000,0.0000,0.3456,1.7644,0.0000,0.0175,0.1027,9.8583,0.5133,0.0002,0.8704,0.0000,0.0850,0.1183,0.0949,0.0369,2.8741,1.0065,0.0000,4.6330,0.0000,7.7170,
7.7201,0.0038,3.7342,2.6457,1.6262,0.2836,0.0008,2.2052,2.6186,3.1951,5.4121,0.5787,1.4276, 12.5830,5.0891,3.7475,4.8317,0.3612,5.0634,0.0001,0.0002,0.2396,2.8372,0.5667,
0.0024,0.0396,4.4980,6.6203,11.8869,7.5642,4.4144,1.1202,7.8870,0.0214,0.0323,0.0000,0.1492,1.0881,3.4938,6.4025, 13.7996,5.3475,7.2365,0.4289, 10.5106, 12.1750,7.8348,0.0000,
0.0104,0.0126,4.7145,3.5840,11.1274,7.1017,0.4464,1.3384, 14.9060,4.1969,7.7008,0.0214,0.0022,2.6731,1.7724,3.0937,1.3026,1.1184,1.0817,0.0000,1.6675,0.0879,1.6432,4.3482,
3.5927,3.3646,0.0000,1.2088,2.6632,2.6712, 10.0635,6.1788,0.9486,0.8011,2.5326,5.1218,0.1574,0.0000,1.7523,5.2613,2.8762,6.7293,7.9969,3.7011,1.9242,0.0002,0.0000,6.8359,
3.4735,4.8440,1.0125,4.3772,1.9227,0.0034,1.0078,2.7654,0.0246,0.4001,0.2570)

Su4 <-  c(NA,0.0001,NA,0.3616,0.2848,1.5804,3.2575,6.9722,0.0000,0.0053,0.0001,0.0000,0.0002,0.0000,4.9185,3.6967,1.9675,7.7624,4.0516,0.7658,0.0001,0.0018,0.0000,0.0000,
0.0000,5.4964,5.2645,5.0756,1.9665,0.0011,0.3481,0.0001,0.0000,0.0000,0.0000,0.0000,4.6501,1.6375,1.1133,0.0016,0.0063,0.0007,0.0000,0.0001,0.0008,0.0000,0.0000,0.0000,
0.0000,5.9308,2.0694,0.3611,0.0035,0.0126,0.0000,0.4887,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0001,0.0000,0.0000,
0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0002,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,
0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.6246,0.4996,1.2273,0.5902,0.0000,0.0016,0.0000,0.0000,0.0004,0.0010,0.0000,0.0000,0.0000,
0.4431,1.6631,0.0234,0.0230,0.0000,1.4833,0.0134,0.0321,0.0283,0.0000,0.0000,0.0000,0.0000,0.2446,0.1740,3.4582,0.0757,0.0092,0.0000,0.0202,0.1099,2.1932,0.0565,0.9499,
0.0176,0.2146,0.0001,0.0000,0.1009,1.8096,0.0000,0.0413,0.2970,7.6015,0.4349,0.0121,0.8901,0.0024,0.4629,0.0843,0.0934,0.2790,2.5034,3.0369,0.0000,4.1673,0.0000,6.2014,
5.6363,0.0211,5.2860,2.7722,1.7316,0.3452,0.0099,2.6113,1.8183,3.2228,3.1208,1.4761,0.9326,9.7211,4.4282,4.0727,5.1978,3.3293,5.8666,0.0013,0.0413,0.0958,1.3760,0.2844,
0.1587,0.0197,3.4947,6.2988, 10.5278,5.6255,3.7482,4.0839,9.5720,0.0113,0.0060,0.0005,0.2592,1.1092,6.5303,5.7979, 15.0240,6.6722,7.0578,0.0507,9.6608, 12.2310,7.6133,0.0002,
0.0147,4.6729,4.1950,5.4444, 13.3876,8.7654,0.0001,1.3864, 15.5325,5.2633,9.7407,0.0160,0.0069,3.3050,7.6701,2.8048,1.1736,0.0000,4.8370,0.0000,1.4801,0.0014,1.3862,7.8413,
3.9453,11.0588,0.0000,1.7270,6.0988,4.2754, 10.7927,1.1768,0.6381,0.1779,6.2290,2.9297,0.4520,0.0012,0.9822,6.6041,2.8147,6.9679,3.5493,9.5997,4.5469,0.0007,0.0004,6.7922,
5.2609,2.4192,0.0459, 10.4127,3.9877,0.0000,1.1876,0.8595,0.5107,0.8049,0.1749)

Su5 <- c(10.4824,0.0000,2.0018,0.2817,1.0086,1.1640,2.6718, 11.2732,0.0000,0.0000,0.0003,0.0000,0.0000,0.0000,5.1846,3.1089,1.6050,5.3045,5.1410,0.7458,0.0000,0.0000,0.0000,0.0000,
0.0000,5.8211,5.6094,4.2910,2.6412,0.0000,0.0404,0.0000,0.0000,0.0000,0.0000,0.0000,4.8222,1.7778,1.6938,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,
0.0000,5.3706,2.1161,0.5845,0.0000,0.0154,0.0000,0.6280,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0001,0.0000,0.0000,
0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,
0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.5967,0.6631,1.2776,0.8574,0.0000,0.0010,0.0000,0.0000,0.0016,0.0010,0.0000,0.0000,0.0000,
0.4013,1.7534,0.0341,0.0360,0.0000,1.8029,0.0163,0.0280,0.0541,0.0000,0.0000,0.0000,0.0000,0.2873,0.2288,3.3035,0.0943,0.0277,0.0000,0.0273,0.1230,1.1606,0.0553,0.9261,
0.0006,0.2793,0.0001,0.0000,0.0702,1.7861,0.0000,0.0441,0.6919,7.2771,0.4737,0.0001,0.9996,0.0028,0.7776,0.0760,0.2064,0.3322,2.1804,3.8545,0.0000,3.8377,0.0000,6.0567,
6.7315,0.0168,6.6603,2.2872,2.7505,0.6174,0.0235,2.5142,1.3832,3.0431,2.3944,1.4855,0.5978,9.6032,3.2907,3.7126,5.1397,3.7415,5.0454,0.0003,0.0361,0.0761,1.4128,0.3045,
0.4881,0.0392,3.8213,5.8874,9.9054,4.9779,3.2351,4.7589,9.2551,0.0108,0.0184,0.0086,0.1905,1.0657,8.1882,5.5578, 14.6536,7.3801,7.8668,0.0315,9.0087, 10.1677,9.6868,0.0001,
0.0797,5.6032,5.4432,5.9958, 15.4570,8.1095,0.0000,1.1854, 14.0602,5.9429,8.4364,0.0056,0.0163,4.0671,5.5083,3.2078,1.8711,0.0000,6.0628,0.0000,1.8110,0.0941,1.8252,8.3102,
9.3829,5.5418,0.0000,1.4030,8.6327,4.3226,9.3724,1.6725,1.0198,1.4480,6.7463,1.7035,1.3542,0.0000,1.4079,4.2148,2.6589,7.3225,4.6582,9.1156,4.0312,0.0000,0.0000,9.2176,
5.5112,2.1917,0.5516,9.7061,2.7556,0.0000,1.0919,1.0696,0.5361,1.0160,0.1019)

Su6 <- c(9.3294,0.0001,1.7365,0.2030,0.5796,0.3794,2.4745,0.0104,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,2.2045,2.8210,1.0607,4.9375,0.0892,1.1530,0.0000,0.0000,0.0000,0.0000,
0.0000,5.5562,5.9813,4.6396,3.0815,0.0000,0.1245,0.0000,0.0000,0.0000,0.0000,0.0000,4.4952,1.3822,5.3511,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,
0.0000,2.4023,0.3491,2.0235,0.0000,0.0469,0.0000,0.3316,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,
0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,
0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.5361,0.5083,2.4144,1.6541,0.0000,0.0009,0.0000,0.0000,0.0007,0.0084,0.0000,0.0000,0.0000,
0.7155,2.4862,2.8153,2.0548,0.0000,1.0062,0.1725,0.0028,0.0404,0.0000,0.0000,0.0000,0.0000,2.0952,1.8754,2.3209,0.1329,0.0025,0.0000,0.0134,0.1656,1.9201,0.0624,0.9148,
0.2393,1.8717,0.0000,0.0000,0.2733,1.3219,0.0000,0.0502,0.4294,6.5172,0.4368,0.0001,2.5930,0.0024,1.1465,0.0857,0.1336,0.1791,2.2427,1.7424,0.0000,4.5865,0.0000,7.4015,
5.1587,0.0953,1.9529,1.7191,2.6812,1.0850,0.0133,3.5750,1.3194,2.2280,2.7217,2.5155,0.6812, 10.1853,0.3850,4.3999,3.9028,1.5311,5.2335,0.0006,0.0359,0.2206,1.5833,0.1611,
0.2389,0.2579,4.7568,5.7652, 11.4255,3.1828,1.8413,3.6434,6.6662,0.0148,0.0166,0.0284,0.4646,1.2736,5.3859,6.2033, 14.0715,5.1563,7.2547,0.0163,9.8463,9.7350,7.7685,0.0015,
0.0694,2.4957,5.9204,3.0981, 13.9429,6.0630,0.0000,0.4167, 16.6025,8.0124,6.8630,0.0314,0.0453,5.1017,7.6560,2.2824,1.6168,0.0000,1.5369,0.0000,1.4277,0.1390,1.3599,5.5345,
7.0305,4.4969,0.0000,1.4448,3.2237,3.5196, 11.8150,1.1668,0.5838,1.5561,2.9927,1.8511,1.4603,0.0000,1.2046,1.1346,2.0005,7.2672,6.1411,3.1801,1.8131,0.0005,0.0000,4.1790,
3.8307,1.0645,NA,NA,0.0119,0.0001,1.1278,0.1273,0.0837,0.0863,0.6916)

table.metric <- data.frame(plot,Su1, Su2, Su3, Su4, Su5, Su6)
plot <- table.metric$plot
    table.metric$plot <- NULL
table.metric2 <- stack(table.metric)
plot.metrics = factor(rep(plot,6))
table.metric2[3] = plot.metrics
names(table.metric2) <- c("value", "time", "plot") 
aov2 <- lme(fixed= value~time, random=~1|plot, na.action=na.omit, data=table.metric2)
summary(aov2)
anova(aov2)
pairwise.t.test(x=table.metric2$value, g=table.metric2$time, p.adj="bonf")

Best Answer

Your t-tests are ignoring the repeated measures in the data. Use paired=TRUE. And just use the Bonferroni-Holm default adjustment; there should be no reason to use regular Bonferroni.

pairwise.t.test(x=table.metric2$value, g=table.metric2$time, paired=TRUE)
##  
##         Pairwise comparisons using paired t tests 
##  
## data:  table.metric2$value and table.metric2$time 
##  
##     Su1    Su2    Su3    Su4    Su5   
## Su2 0.0124 -      -      -      -     
## Su3 0.0241 0.0032 -      -      -     
## Su4 0.9299 0.0115 0.0953 -      -     
## Su5 0.9299 0.0087 0.0937 0.9299 -     
## Su6 0.0038 5e-05  0.9299 0.0186 0.0074
##  
## P value adjustment method: holm

But also see Peter Flom's excellent answer to a related question. These tests get at different things so will not always "agree." Better to decide which test is most appropriate for your question.

As mentioned in the comments, the mixed model assumes equal variance, but the pairwise paired t-tests do not. To get pairwise tests based on the model, which would keep this assumption, you can use the multcomp library, like this (output not shown).

library(multcomp)
summary(glht(aov2, linfct=mcp(time="Tukey")))

In this case, however, they give different results (if you define different as on different sides of the nominal 0.05 cutoff); this is because the variance of the differences between each pair are not equal, the standard deviations have a range of about 3.

ss <- summary(glht(aov2, linfct=mcp(time="Tukey")))
foo <- pairwise.t.test(x=table.metric2$value, g=table.metric2$time, 
                       paired=TRUE)
foo <- as.data.frame(as.table(foo$p.value))
foo <- foo[!is.na(foo$Freq),]
names(foo)[3] <- "pval.pairedt"
foo$pval.pairedt <- format.pval(foo$pval.pairedt, digits=3)
foo$pval.mixed <- format.pval(ss$test$pvalues, digits=3)
foo$Var1 <- factor(foo$Var1, levels=levels(table.metric2$time))
foo$Var2 <- factor(foo$Var2, levels=levels(table.metric2$time))
foo$diff.sd <- sapply(1:nrow(foo), function(i) {
    y1 <- table.metric2$value[table.metric2$time==foo$Var1[i]]
    y2 <- table.metric2$value[table.metric2$time==foo$Var2[i]]
    sd(y1-y2, na.rm=TRUE)
})
print(foo, row.names=FALSE)
## Var1 Var2 pval.pairedt pval.mixed   diff.sd
##  Su2  Su1      0.01239   0.727461 0.4963881
##  Su3  Su1      0.02409   0.008360 1.3264442
##  Su4  Su1      0.92986   0.962717 0.7934766
##  Su5  Su1      0.92986   0.999487 0.7164677
##  Su6  Su1      0.00383   0.000114 1.3635100
##  Su3  Su2      0.00316   2.21e-05 1.4763516
##  Su4  Su2      0.01150   0.227215 0.7914265
##  Su5  Su2      0.00867   0.512340 0.5840229
##  Su6  Su2     4.97e-05   4.83e-08 1.3861764
##  Su4  Su3      0.09527   0.102065 1.3110117
##  Su5  Su3      0.09366   0.024984 1.4534286
##  Su6  Su3      0.92986   0.896211 1.2320563
##  Su5  Su4      0.92986   0.996275 0.7751331
##  Su6  Su4      0.01860   0.003817 1.3068406
##  Su6  Su5      0.00743   0.000494 1.3654174
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