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  1. > summary(modelo.spmi)
  2. (Call:) glm(formula = count ~ -1 + W:Y + wi %in% W:Y + yj %in% W:Y, family = poisson(link = log),
  3. data = model.data)
  4. (Deviance Residuals: ) Min 1Q Median 3Q Max
  5. -11.7301 -2.2157 -0.0019 2.4841 9.7258
  6. (Coefficients:)
  7. Estimate RS SE z value Pr(>|z|)
  8. WansMRCV1.1:YansMRCV2.1 2.1702784 0.1218212 17.815 < 2e-16 ***
  9. WansMRCV1.2:YansMRCV2.1 5.2388368 0.0549085 95.410 < 2e-16 ***
  10. WansMRCV1.3:YansMRCV2.1 5.6394053 0.0520939 108.255 < 2e-16 ***
  11. WansMRCV1.4:YansMRCV2.1 5.1730511 0.0540114 95.777 < 2e-16 ***
  12. WansMRCV1.1:YansMRCV2.2 3.8316044 0.1047455 36.580 < 2e-16 ***
  13. WansMRCV1.2:YansMRCV2.2 6.9001627 0.0237448 290.597 < 2e-16 ***
  14. WansMRCV1.3:YansMRCV2.2 7.3007312 0.0202752 360.081 < 2e-16 ***
  15. WansMRCV1.4:YansMRCV2.2 6.8343770 0.0242338 282.019 < 2e-16 ***
  16. WansMRCV1.1:YansMRCV2.3 0.6605192 0.1602399 4.122 0.0000375 ***
  17. WansMRCV1.2:YansMRCV2.3 3.7290776 0.1143503 32.611 < 2e-16 ***
  18. WansMRCV1.3:YansMRCV2.3 4.1296461 0.1128318 36.600 < 2e-16 ***
  19. WansMRCV1.4:YansMRCV2.3 3.6632918 0.1142630 32.060 < 2e-16 ***
  20. WansMRCV1.1:YansMRCV2.4 3.0204051 0.1095504 27.571 < 2e-16 ***
  21. WansMRCV1.2:YansMRCV2.4 6.0889635 0.0359033 169.594 < 2e-16 ***
  22. WansMRCV1.3:YansMRCV2.4 6.4895320 0.0317723 204.251 < 2e-16 ***
  23. WansMRCV1.4:YansMRCV2.4 6.0231778 0.0367882 163.726 < 2e-16 ***
  24. WansMRCV1.1:YansMRCV2.1:wi 3.6710586 0.1055755 34.772 < 2e-16 ***
  25. WansMRCV1.2:YansMRCV2.1:wi -0.1356270 0.0329243 -4.119 0.0000380 ***
  26. WansMRCV1.3:YansMRCV2.1:wi -1.3668502 0.0408233 -33.482 < 2e-16 ***
  27. WansMRCV1.4:YansMRCV2.1:wi 0.0005395 0.0328487 0.016 0.987
  28. WansMRCV1.1:YansMRCV2.2:wi 3.6710586 0.1055755 34.772 < 2e-16 ***
  29. WansMRCV1.2:YansMRCV2.2:wi -0.1356270 0.0329243 -4.119 0.0000380 ***
  30. WansMRCV1.3:YansMRCV2.2:wi -1.3668502 0.0408233 -33.482 < 2e-16 ***
  31. WansMRCV1.4:YansMRCV2.2:wi 0.0005395 0.0328487 0.016 0.987
  32. WansMRCV1.1:YansMRCV2.3:wi 3.6710586 0.1055755 34.772 < 2e-16 ***
  33. WansMRCV1.2:YansMRCV2.3:wi -0.1356270 0.0329243 -4.119 0.0000380 ***
  34. WansMRCV1.3:YansMRCV2.3:wi -1.3668502 0.0408233 -33.482 < 2e-16 ***
  35. WansMRCV1.4:YansMRCV2.3:wi 0.0005395 0.0328487 0.016 0.987
  36. WansMRCV1.1:YansMRCV2.4:wi 3.6710586 0.1055755 34.772 < 2e-16 ***
  37. WansMRCV1.2:YansMRCV2.4:wi -0.1356270 0.0329243 -4.119 0.0000380 ***
  38. WansMRCV1.3:YansMRCV2.4:wi -1.3668502 0.0408233 -33.482 < 2e-16 ***
  39. WansMRCV1.4:YansMRCV2.4:wi 0.0005395 0.0328487 0.016 0.987
  40. WansMRCV1.1:YansMRCV2.1:yj 2.2514409 0.0559555 40.236 < 2e-16 ***
  41. WansMRCV1.2:YansMRCV2.1:yj 2.2514409 0.0559555 40.236 < 2e-16 ***
  42. WansMRCV1.3:YansMRCV2.1:yj 2.2514409 0.0559555 40.236 < 2e-16 ***
  43. WansMRCV1.4:YansMRCV2.1:yj 2.2514409 0.0559555 40.236 < 2e-16 ***
  44. WansMRCV1.1:YansMRCV2.2:yj -0.0059347 0.0328489 -0.181 0.857
  45. WansMRCV1.2:YansMRCV2.2:yj -0.0059347 0.0328489 -0.181 0.857
  46. WansMRCV1.3:YansMRCV2.2:yj -0.0059347 0.0328489 -0.181 0.857
  47. WansMRCV1.4:YansMRCV2.2:yj -0.0059347 0.0328489 -0.181 0.857
  48. WansMRCV1.1:YansMRCV2.3:yj 3.8400036 0.1144381 33.555 < 2e-16 ***
  49. WansMRCV1.2:YansMRCV2.3:yj 3.8400036 0.1144381 33.555 < 2e-16 ***
  50. WansMRCV1.3:YansMRCV2.3:yj 3.8400036 0.1144381 33.555 < 2e-16 ***
  51. WansMRCV1.4:YansMRCV2.3:yj 3.8400036 0.1144381 33.555 < 2e-16 ***
  52. WansMRCV1.1:YansMRCV2.4:yj 1.2492980 0.0394684 31.653 < 2e-16 ***
  53. WansMRCV1.2:YansMRCV2.4:yj 1.2492980 0.0394684 31.653 < 2e-16 ***
  54. WansMRCV1.3:YansMRCV2.4:yj 1.2492980 0.0394684 31.653 < 2e-16 ***
  55. WansMRCV1.4:YansMRCV2.4:yj 1.2492980 0.0394684 31.653 < 2e-16 ***
  56. (Dispersion parameter for poisson family taken to be 1)
  57. Null deviance: 749049.38 Residual deviance: 794.31
  58. Number of Fisher Scoring iterations: 5
  59. > summary(modelo.homogeneo)
  60. (Call:) glm(formula = count ~ -1 + W:Y + wi %in% W:Y + yj %in% W:Y +
  61. wi:yj, family = poisson(link = log), data = model.data)
  62. (Deviance Residuals:) Min 1Q Median 3Q Max
  63. -6.8445 -0.8966 -0.0044 0.7488 5.3983
  64. (Coefficients:)
  65. Estimate RS SE z value Pr(>|z|)
  66. WansMRCV1.1:YansMRCV2.1 2.72652 0.12347 22.083 < 2e-16 ***
  67. WansMRCV1.2:YansMRCV2.1 5.47463 0.05448 100.483 < 2e-16 ***
  68. WansMRCV1.3:YansMRCV2.1 5.73638 0.05167 111.029 < 2e-16 ***
  69. WansMRCV1.4:YansMRCV2.1 5.42800 0.05400 100.509 < 2e-16 ***
  70. WansMRCV1.1:YansMRCV2.2 4.10140 0.10444 39.271 < 2e-16 ***
  71. WansMRCV1.2:YansMRCV2.2 7.04144 0.02177 323.432 < 2e-16 ***
  72. WansMRCV1.3:YansMRCV2.2 7.36421 0.01864 395.161 < 2e-16 ***
  73. WansMRCV1.4:YansMRCV2.2 6.98522 0.02220 314.649 < 2e-16 ***
  74. WansMRCV1.1:YansMRCV2.3 1.27841 0.16479 7.758 8.66e-15 ***
  75. WansMRCV1.2:YansMRCV2.3 3.97980 0.11525 34.531 < 2e-16 ***
  76. WansMRCV1.3:YansMRCV2.3 4.23149 0.11303 37.436 < 2e-16 ***
  77. WansMRCV1.4:YansMRCV2.3 3.93492 0.11539 34.100 < 2e-16 ***
  78. WansMRCV1.1:YansMRCV2.4 3.47815 0.10965 31.721 < 2e-16 ***
  79. WansMRCV1.2:YansMRCV2.4 6.29738 0.03411 184.601 < 2e-16 ***
  80. WansMRCV1.3:YansMRCV2.4 6.57732 0.03090 212.851 < 2e-16 ***
  81. WansMRCV1.4:YansMRCV2.4 6.24771 0.03483 179.379 < 2e-16 ***
  82. wi:yj 0.65891 0.03569 18.463 < 2e-16 ***
  83. WansMRCV1.1:YansMRCV2.1:wi 3.09570 0.11002 28.138 < 2e-16 ***
  84. WansMRCV1.2:YansMRCV2.1:wi -0.73460 0.04626 -15.881 < 2e-16 ***
  85. WansMRCV1.3:YansMRCV2.1:wi -1.97380 0.05196 -37.986 < 2e-16 ***
  86. WansMRCV1.4:YansMRCV2.1:wi -0.59724 0.04579 -13.044 < 2e-16 ***
  87. WansMRCV1.1:YansMRCV2.2:wi 3.39335 0.10686 31.754 < 2e-16 ***
  88. WansMRCV1.2:YansMRCV2.2:wi -0.46779 0.03823 -12.238 < 2e-16 ***
  89. WansMRCV1.3:YansMRCV2.2:wi -1.72753 0.04512 -38.286 < 2e-16 ***
  90. WansMRCV1.4:YansMRCV2.2:wi -0.32790 0.03775 -8.686 < 2e-16 ***
  91. WansMRCV1.1:YansMRCV2.3:wi 3.03117 0.11170 27.138 < 2e-16 ***
  92. WansMRCV1.2:YansMRCV2.3:wi -0.78140 0.04802 -16.272 < 2e-16 ***
  93. WansMRCV1.3:YansMRCV2.3:wi -2.01445 0.05314 -37.908 < 2e-16 ***
  94. WansMRCV1.4:YansMRCV2.3:wi -0.64495 0.04742 -13.600 < 2e-16 ***
  95. WansMRCV1.1:YansMRCV2.4:wi 3.19842 0.10877 29.406 < 2e-16 ***
  96. WansMRCV1.2:YansMRCV2.4:wi -0.65245 0.04382 -14.890 < 2e-16 ***
  97. WansMRCV1.3:YansMRCV2.4:wi -1.90088 0.05060 -37.569 < 2e-16 ***
  98. WansMRCV1.4:YansMRCV2.4:wi -0.51380 0.04304 -11.939 < 2e-16 ***
  99. WansMRCV1.1:YansMRCV2.1:yj 1.61364 0.06884 23.441 < 2e-16 ***
  100. WansMRCV1.2:YansMRCV2.1:yj 1.98726 0.05864 33.889 < 2e-16 ***
  101. WansMRCV1.3:YansMRCV2.1:yj 2.14369 0.05670 37.810 < 2e-16 ***
  102. WansMRCV1.4:YansMRCV2.1:yj 1.96545 0.05950 33.032 < 2e-16 ***
  103. WansMRCV1.1:YansMRCV2.2:yj -0.64903 0.04871 -13.323 < 2e-16 ***
  104. WansMRCV1.2:YansMRCV2.2:yj -0.31284 0.03789 -8.257 2.22e-16 ***
  105. WansMRCV1.3:YansMRCV2.2:yj -0.13762 0.03347 -4.112 3.93e-05 ***
  106. WansMRCV1.4:YansMRCV2.2:yj -0.33564 0.03870 -8.674 < 2e-16 ***
  107. WansMRCV1.1:YansMRCV2.3:yj 3.20357 0.12457 25.717 < 2e-16 ***
  108. WansMRCV1.2:YansMRCV2.3:yj 3.58313 0.11678 30.683 < 2e-16 ***
  109. WansMRCV1.3:YansMRCV2.3:yj 3.73585 0.11518 32.435 < 2e-16 ***
  110. WansMRCV1.4:YansMRCV2.3:yj 3.56164 0.11719 30.392 < 2e-16 ***
  111. WansMRCV1.1:YansMRCV2.4:yj 0.60950 0.05270 11.565 < 2e-16 ***
  112. WansMRCV1.2:YansMRCV2.4:yj 0.97213 0.04222 23.027 < 2e-16 ***
  113. WansMRCV1.3:YansMRCV2.4:yj 1.13485 0.04044 28.064 < 2e-16 ***
  114. WansMRCV1.4:YansMRCV2.4:yj 0.94986 0.04258 22.309 < 2e-16 ***
  115. (Dispersion parameter for poisson family taken to be 1)
  116. Null deviance: 749049.38 Residual deviance: 234.34
  117. Number of Fisher Scoring iterations: 4
  118. > summary(modelo.wmain)
  119. (Call:) glm(formula = count ~ -1 + W:Y + wi %in% W:Y + yj %in% W:Y +
  120. wi:yj + wi:yj %in% W, family = poisson(link = log), data = model.data)
  121. (Deviance Residuals:) Min 1Q Median 3Q Max
  122. -4.7331 -0.8568 0.0058 0.8305 7.5585
  123. (Coefficients:)
  124. Estimate RS SE z value Pr(>|z|)
  125. WansMRCV1.1:YansMRCV2.1 3.09768 0.17924 17.283 < 2e-16 ***
  126. WansMRCV1.2:YansMRCV2.1 5.46537 0.05647 96.789 < 2e-16 ***
  127. WansMRCV1.3:YansMRCV2.1 5.76351 0.05161 111.678 < 2e-16 ***
  128. WansMRCV1.4:YansMRCV2.1 5.37055 0.05525 97.206 < 2e-16 ***
  129. WansMRCV1.1:YansMRCV2.2 4.24102 0.11201 37.862 < 2e-16 ***
  130. WansMRCV1.2:YansMRCV2.2 7.03534 0.02312 304.290 < 2e-16 ***
  131. WansMRCV1.3:YansMRCV2.2 7.38702 0.01902 388.302 < 2e-16 ***
  132. WansMRCV1.4:YansMRCV2.2 6.94902 0.02451 283.500 < 2e-16 ***
  133. WansMRCV1.1:YansMRCV2.3 1.71602 0.23234 7.386 1.52e-13 ***
  134. WansMRCV1.2:YansMRCV2.3 3.97017 0.11586 34.267 < 2e-16 ***
  135. WansMRCV1.3:YansMRCV2.3 4.25878 0.11294 37.707 < 2e-16 ***
  136. WansMRCV1.4:YansMRCV2.3 3.87465 0.11625 33.331 < 2e-16 ***
  137. WansMRCV1.1:YansMRCV2.4 3.75682 0.14197 26.462 < 2e-16 ***
  138. WansMRCV1.2:YansMRCV2.4 6.28890 0.03597 174.821 < 2e-16 ***
  139. WansMRCV1.3:YansMRCV2.4 6.60384 0.03045 216.859 < 2e-16 ***
  140. WansMRCV1.4:YansMRCV2.4 6.19588 0.03865 160.303 < 2e-16 ***
  141. wi:yj 1.14647 0.18652 6.147 7.92e-10 ***
  142. WansMRCV1.1:YansMRCV2.1:wi 2.70399 0.17636 15.332 < 2e-16 ***
  143. WansMRCV1.2:YansMRCV2.1:wi -0.70631 0.05770 -12.241 < 2e-16 ***
  144. WansMRCV1.3:YansMRCV2.1:wi -2.22156 0.08150 -27.259 < 2e-16 ***
  145. WansMRCV1.4:YansMRCV2.1:wi -0.44315 0.05801 -7.639 2.20e-14 ***
  146. WansMRCV1.1:YansMRCV2.2:wi 3.24868 0.11576 28.064 < 2e-16 ***
  147. WansMRCV1.2:YansMRCV2.2:wi -0.45204 0.04267 -10.593 < 2e-16 ***
  148. WansMRCV1.3:YansMRCV2.2:wi -1.88938 0.06228 -30.334 < 2e-16 ***
  149. WansMRCV1.4:YansMRCV2.2:wi -0.24354 0.04225 -5.764 8.21e-09 ***
  150. WansMRCV1.1:YansMRCV2.3:wi 2.56671 0.20390 12.588 < 2e-16 ***
  151. WansMRCV1.2:YansMRCV2.3:wi -0.75105 0.06080 -12.352 < 2e-16 ***
  152. WansMRCV1.3:YansMRCV2.3:wi -2.27417 0.08413 -27.033 < 2e-16 ***
  153. WansMRCV1.4:YansMRCV2.3:wi -0.47899 0.06098 -7.854 4.00e-15 ***
  154. WansMRCV1.1:YansMRCV2.4:wi 2.90655 0.14626 19.872 < 2e-16 ***
  155. WansMRCV1.2:YansMRCV2.4:wi -0.62790 0.05303 -11.840 < 2e-16 ***
  156. WansMRCV1.3:YansMRCV2.4:wi -2.12566 0.07749 -27.431 < 2e-16 ***
  157. WansMRCV1.4:YansMRCV2.4:wi -0.38093 0.05246 -7.261 3.85e-13 ***
  158. WansMRCV1.1:YansMRCV2.1:yj 1.14872 0.19077 6.021 1.73e-09 ***
  159. WansMRCV1.2:YansMRCV2.1:yj 1.99778 0.06093 32.790 < 2e-16 ***
  160. WansMRCV1.3:YansMRCV2.1:yj 2.11333 0.05697 37.099 < 2e-16 ***
  161. WansMRCV1.4:YansMRCV2.1:yj 2.03070 0.06004 33.821 < 2e-16 ***
  162. WansMRCV1.1:YansMRCV2.2:yj -1.12658 0.18671 -6.034 1.60e-09 ***
  163. WansMRCV1.2:YansMRCV2.2:yj -0.29847 0.04178 -7.144 9.09e-13 ***
  164. WansMRCV1.3:YansMRCV2.2:yj -0.18726 0.03613 -5.183 2.18e-07 ***
  165. WansMRCV1.4:YansMRCV2.2:yj -0.25091 0.04253 -5.899 3.65e-09 ***
  166. WansMRCV1.1:YansMRCV2.3:yj 2.74341 0.21849 12.556 < 2e-16 ***
  167. WansMRCV1.2:YansMRCV2.3:yj 3.59303 0.11737 30.612 < 2e-16 ***
  168. WansMRCV1.3:YansMRCV2.3:yj 3.70790 0.11523 32.179 < 2e-16 ***
  169. WansMRCV1.4:YansMRCV2.3:yj 3.62358 0.11768 30.793 < 2e-16 ***
  170. WansMRCV1.1:YansMRCV2.4:yj 0.13883 0.18486 0.751 0.452662
  171. WansMRCV1.2:YansMRCV2.4:yj 0.98380 0.04489 21.914 < 2e-16 ***
  172. WansMRCV1.3:YansMRCV2.4:yj 1.09965 0.04047 27.171 < 2e-16 ***
  173. WansMRCV1.4:YansMRCV2.4:yj 1.02103 0.04685 21.793 < 2e-16 ***
  174. WansMRCV1.2:wi:yj -0.51848 0.18985 -2.731 0.006314 **
  175. WansMRCV1.3:wi:yj -0.22463 0.20060 -1.120 0.262805
  176. WansMRCV1.4:wi:yj -0.65683 0.19768 -3.323 0.000892 ***
  177. (Dispersion parameter for poisson family taken to be 1)
  178. Null deviance: 749049.38 Residual deviance: 189.23
  179. Number of Fisher Scoring iterations: 4
  180. > summary(modelo.ymain)
  181. (Call:) glm(formula = count ~ -1 + W:Y + wi %in% W:Y + yj %in% W:Y +
  182. wi:yj + wi:yj %in% Y, family = poisson(link = log), data = model.data)
  183. (Deviance Residuals:) Min 1Q Median 3Q Max
  184. -6.9147 -0.8710 0.0001 0.7893 4.7927
  185. (Coefficients:)
  186. Estimate RS SE z value Pr(>|z|)
  187. WansMRCV1.1:YansMRCV2.1 2.88025 0.13424 21.456 < 2e-16 ***
  188. WansMRCV1.2:YansMRCV2.1 5.52942 0.05530 99.986 < 2e-16 ***
  189. WansMRCV1.3:YansMRCV2.1 5.75711 0.05136 112.099 < 2e-16 ***
  190. WansMRCV1.4:YansMRCV2.1 5.48791 0.05538 99.103 < 2e-16 ***
  191. WansMRCV1.1:YansMRCV2.2 4.09840 0.10377 39.495 < 2e-16 ***
  192. WansMRCV1.2:YansMRCV2.2 7.03968 0.02232 315.463 < 2e-16 ***
  193. WansMRCV1.3:YansMRCV2.2 7.36341 0.01865 394.764 < 2e-16 ***
  194. WansMRCV1.4:YansMRCV2.2 6.98335 0.02286 305.527 < 2e-16 ***
  195. WansMRCV1.1:YansMRCV2.3 1.92531 0.22975 8.380 < 2e-16 ***
  196. WansMRCV1.2:YansMRCV2.3 4.15537 0.11768 35.310 < 2e-16 ***
  197. WansMRCV1.3:YansMRCV2.3 4.29397 0.11268 38.109 < 2e-16 ***
  198. WansMRCV1.4:YansMRCV2.3 4.12891 0.11896 34.709 < 2e-16 ***
  199. WansMRCV1.1:YansMRCV2.4 3.38307 0.11373 29.746 < 2e-16 ***
  200. WansMRCV1.2:YansMRCV2.4 6.25570 0.03683 169.867 < 2e-16 ***
  201. WansMRCV1.3:YansMRCV2.4 6.56036 0.03154 207.989 < 2e-16 ***
  202. WansMRCV1.4:YansMRCV2.4 6.20262 0.03779 164.151 < 2e-16 ***
  203. wi:yj 0.85461 0.07673 11.138 < 2e-16 ***
  204. WansMRCV1.1:YansMRCV2.1:wi 2.93442 0.12640 23.216 < 2e-16 ***
  205. WansMRCV1.2:YansMRCV2.1:wi -0.91426 0.07716 -11.848 < 2e-16 ***
  206. WansMRCV1.3:YansMRCV2.1:wi -2.15794 0.08196 -26.330 < 2e-16 ***
  207. WansMRCV1.4:YansMRCV2.1:wi -0.77615 0.07722 -10.052 < 2e-16 ***
  208. WansMRCV1.1:YansMRCV2.2:wi 3.39645 0.10618 31.988 < 2e-16 ***
  209. WansMRCV1.2:YansMRCV2.2:wi -0.46325 0.04042 -11.461 < 2e-16 ***
  210. WansMRCV1.3:YansMRCV2.2:wi -1.72222 0.04583 -37.577 < 2e-16 ***
  211. WansMRCV1.4:YansMRCV2.2:wi -0.32346 0.04004 -8.078 6.66e-16 ***
  212. WansMRCV1.1:YansMRCV2.3:wi 2.33938 0.21733 10.764 < 2e-16 ***
  213. WansMRCV1.2:YansMRCV2.3:wi -1.50040 0.19975 -7.512 5.84e-14 ***
  214. WansMRCV1.3:YansMRCV2.3:wi -2.73732 0.20171 -13.571 < 2e-16 ***
  215. WansMRCV1.4:YansMRCV2.3:wi -1.36324 0.20048 -6.800 1.05e-11 ***
  216. WansMRCV1.1:YansMRCV2.4:wi 3.29720 0.11257 29.292 < 2e-16 ***
  217. WansMRCV1.2:YansMRCV2.4:wi -0.53530 0.05474 -9.778 < 2e-16 ***
  218. WansMRCV1.3:YansMRCV2.4:wi -1.77723 0.06359 -27.950 < 2e-16 ***
  219. WansMRCV1.4:YansMRCV2.4:wi -0.39762 0.05353 -7.429 1.10e-13 ***
  220. WansMRCV1.1:YansMRCV2.1:yj 1.42626 0.09155 15.578 < 2e-16 ***
  221. WansMRCV1.2:YansMRCV2.1:yj 1.92473 0.06071 31.704 < 2e-16 ***
  222. WansMRCV1.3:YansMRCV2.1:yj 2.12050 0.05665 37.429 < 2e-16 ***
  223. WansMRCV1.4:YansMRCV2.1:yj 1.89685 0.06220 30.498 < 2e-16 ***
  224. WansMRCV1.1:YansMRCV2.2:yj -0.64031 0.05414 -11.827 < 2e-16 ***
  225. WansMRCV1.2:YansMRCV2.2:yj -0.30869 0.03932 -7.851 4.22e-15 ***
  226. WansMRCV1.3:YansMRCV2.2:yj -0.13589 0.03377 -4.024 5.72e-05 ***
  227. WansMRCV1.4:YansMRCV2.2:yj -0.33118 0.04032 -8.214 2.22e-16 ***
  228. WansMRCV1.1:YansMRCV2.3:yj 2.51902 0.21505 11.714 < 2e-16 ***
  229. WansMRCV1.2:YansMRCV2.3:yj 3.40222 0.12055 28.223 < 2e-16 ***
  230. WansMRCV1.3:YansMRCV2.3:yj 3.67183 0.11517 31.882 < 2e-16 ***
  231. WansMRCV1.4:YansMRCV2.3:yj 3.36156 0.12210 27.530 < 2e-16 ***
  232. WansMRCV1.1:YansMRCV2.4:yj 0.75271 0.06610 11.388 < 2e-16 ***
  233. WansMRCV1.2:YansMRCV2.4:yj 1.02914 0.04508 22.828 < 2e-16 ***
  234. WansMRCV1.3:YansMRCV2.4:yj 1.15721 0.04067 28.454 < 2e-16 ***
  235. WansMRCV1.4:YansMRCV2.4:yj 1.01185 0.04599 21.999 < 2e-16 ***
  236. YansMRCV2.2:wi:yj -0.20462 0.07815 -2.618 0.00884 **
  237. YansMRCV2.3:wi:yj 0.53465 0.19741 2.708 0.00676 **
  238. YansMRCV2.4:wi:yj -0.34365 0.08820 -3.896 9.76e-05 ***
  239. (Dispersion parameter for poisson family taken to be 1)
  240. Null deviance: 749049.38 Residual deviance: 198.14
  241. Number of Fisher Scoring iterations: 4
  242. > summary(modelo.wymain)
  243. (Call:) glm(formula = count ~ -1 + W:Y + wi %in% W:Y + yj %in% W:Y +
  244. wi:yj + wi:yj %in% W + wi:yj %in% Y, family = poisson(link = log),
  245. data = model.data)
  246. (Deviance Residuals:) Min 1Q Median 3Q Max
  247. -4.7156 -0.6245 0.0000 0.6513 6.4618
  248. (Coefficients:)
  249. Estimate RS SE z value Pr(>|z|)
  250. WansMRCV1.1:YansMRCV2.1 3.18876 0.17474 18.248 < 2e-16 ***
  251. WansMRCV1.2:YansMRCV2.1 5.52162 0.05684 97.145 < 2e-16 ***
  252. WansMRCV1.3:YansMRCV2.1 5.78124 0.05121 112.896 < 2e-16 ***
  253. WansMRCV1.4:YansMRCV2.1 5.43608 0.05662 96.015 < 2e-16 ***
  254. WansMRCV1.1:YansMRCV2.2 4.22198 0.11183 37.752 < 2e-16 ***
  255. WansMRCV1.2:YansMRCV2.2 7.03364 0.02377 295.936 < 2e-16 ***
  256. WansMRCV1.3:YansMRCV2.2 7.38720 0.01895 389.762 < 2e-16 ***
  257. WansMRCV1.4:YansMRCV2.2 6.94650 0.02541 273.430 < 2e-16 ***
  258. WansMRCV1.1:YansMRCV2.3 2.24187 0.24474 9.160 < 2e-16 ***
  259. WansMRCV1.2:YansMRCV2.3 4.14322 0.11744 35.279 < 2e-16 ***
  260. WansMRCV1.3:YansMRCV2.3 4.30690 0.11242 38.311 < 2e-16 ***
  261. WansMRCV1.4:YansMRCV2.3 4.08385 0.12014 33.993 < 2e-16 ***
  262. WansMRCV1.1:YansMRCV2.4 3.64184 0.14544 25.041 < 2e-16 ***
  263. WansMRCV1.2:YansMRCV2.4 6.24767 0.03888 160.702 < 2e-16 ***
  264. WansMRCV1.3:YansMRCV2.4 6.59092 0.03105 212.235 < 2e-16 ***
  265. WansMRCV1.4:YansMRCV2.4 6.14756 0.04195 146.552 < 2e-16 ***
  266. wi:yj 1.27530 0.18520 6.886 5.74e-12 ***
  267. WansMRCV1.1:YansMRCV2.1:wi 2.60651 0.17423 14.960 < 2e-16 ***
  268. WansMRCV1.2:YansMRCV2.1:wi -0.88727 0.08406 -10.555 < 2e-16 ***
  269. WansMRCV1.3:YansMRCV2.1:wi -2.41953 0.10513 -23.015 < 2e-16 ***
  270. WansMRCV1.4:YansMRCV2.1:wi -0.62017 0.08423 -7.363 1.80e-13 ***
  271. WansMRCV1.1:YansMRCV2.2:wi 3.26845 0.11546 28.309 < 2e-16 ***
  272. WansMRCV1.2:YansMRCV2.2:wi -0.44767 0.04512 -9.921 < 2e-16 ***
  273. WansMRCV1.3:YansMRCV2.2:wi -1.89075 0.06201 -30.489 < 2e-16 ***
  274. WansMRCV1.4:YansMRCV2.2:wi -0.23782 0.04499 -5.286 1.25e-07 ***
  275. WansMRCV1.1:YansMRCV2.3:wi 1.98627 0.24225 8.199 2.22e-16 ***
  276. WansMRCV1.2:YansMRCV2.3:wi -1.43552 0.18900 -7.596 3.06e-14 ***
  277. WansMRCV1.3:YansMRCV2.3:wi -2.97456 0.19753 -15.059 < 2e-16 ***
  278. WansMRCV1.4:YansMRCV2.3:wi -1.15928 0.19211 -6.034 1.60e-09 ***
  279. WansMRCV1.1:YansMRCV2.4:wi 3.02745 0.14880 20.346 < 2e-16 ***
  280. WansMRCV1.2:YansMRCV2.4:wi -0.51371 0.06269 -8.194 2.22e-16 ***
  281. WansMRCV1.3:YansMRCV2.4:wi -2.01060 0.09091 -22.117 < 2e-16 ***
  282. WansMRCV1.4:YansMRCV2.4:wi -0.26585 0.06111 -4.350 1.36e-05 ***
  283. WansMRCV1.1:YansMRCV2.1:yj 1.02694 0.18726 5.484 4.16e-08 ***
  284. WansMRCV1.2:YansMRCV2.1:yj 1.93366 0.06244 30.967 < 2e-16 ***
  285. WansMRCV1.3:YansMRCV2.1:yj 2.09344 0.05678 36.869 < 2e-16 ***
  286. WansMRCV1.4:YansMRCV2.1:yj 1.95623 0.06278 31.160 < 2e-16 ***
  287. WansMRCV1.1:YansMRCV2.2:yj -1.05098 0.18137 -5.795 6.84e-09 ***
  288. WansMRCV1.2:YansMRCV2.2:yj -0.29447 0.04339 -6.787 1.15e-11 ***
  289. WansMRCV1.3:YansMRCV2.2:yj -0.18765 0.03621 -5.183 2.19e-07 ***
  290. WansMRCV1.4:YansMRCV2.2:yj -0.24517 0.04454 -5.505 3.69e-08 ***
  291. WansMRCV1.1:YansMRCV2.3:yj 2.17201 0.24555 8.846 < 2e-16 ***
  292. WansMRCV1.2:YansMRCV2.3:yj 3.41477 0.12022 28.405 < 2e-16 ***
  293. WansMRCV1.3:YansMRCV2.3:yj 3.65857 0.11498 31.820 < 2e-16 ***
  294. WansMRCV1.4:YansMRCV2.3:yj 3.40814 0.12296 27.718 < 2e-16 ***
  295. WansMRCV1.1:YansMRCV2.4:yj 0.34413 0.17739 1.940 0.05239 .
  296. WansMRCV1.2:YansMRCV2.4:yj 1.04002 0.04797 21.681 < 2e-16 ***
  297. WansMRCV1.3:YansMRCV2.4:yj 1.11683 0.04075 27.410 < 2e-16 ***
  298. WansMRCV1.4:YansMRCV2.4:yj 1.08620 0.05058 21.474 < 2e-16 ***
  299. WansMRCV1.2:wi:yj -0.45002 0.18075 -2.490 0.01278 *
  300. WansMRCV1.3:wi:yj -0.14543 0.19236 -0.756 0.44963
  301. WansMRCV1.4:wi:yj -0.59125 0.18878 -3.132 0.00174 **
  302. YansMRCV2.2:wi:yj -0.20588 0.07791 -2.643 0.00823 **
  303. YansMRCV2.3:wi:yj 0.49825 0.18373 2.712 0.00669 **
  304. YansMRCV2.4:wi:yj -0.34169 0.08759 -3.901 9.58e-05 ***
  305. (Dispersion parameter for poisson family taken to be 1)
  306. Null deviance: 749049.38 Residual deviance: 154.52
  307. Number of Fisher Scoring iterations: 4
  308. > summary(modelo.saturado)
  309. (Call:) glm(formula = count ~ -1 + W:Y + wi %in% W:Y + yj %in% W:Y +
  310. wi:yj + wi:yj %in% W + wi:yj %in% Y + wi:yj %in% W:Y, family = poisson(link = log),
  311. data = model.data)
  312. (Coefficients:)
  313. Estimate RS SE z value Pr(>|z|)
  314. WansMRCV1.1:YansMRCV2.1 3.58352 0.16586 21.606 < 2e-16 ***
  315. WansMRCV1.2:YansMRCV2.1 5.57595 0.05931 94.008 < 2e-16 ***
  316. WansMRCV1.3:YansMRCV2.1 5.78074 0.05307 108.922 < 2e-16 ***
  317. WansMRCV1.4:YansMRCV2.1 5.31812 0.06806 78.138 < 2e-16 ***
  318. WansMRCV1.1:YansMRCV2.2 4.00733 0.13384 29.942 < 2e-16 ***
  319. WansMRCV1.2:YansMRCV2.2 7.00579 0.02524 277.610 < 2e-16 ***
  320. WansMRCV1.3:YansMRCV2.2 7.42952 0.01799 412.935 < 2e-16 ***
  321. WansMRCV1.4:YansMRCV2.2 6.92166 0.02677 258.596 < 2e-16 ***
  322. WansMRCV1.1:YansMRCV2.3 2.39790 0.30106 7.965 1.55e-15 ***
  323. WansMRCV1.2:YansMRCV2.3 4.15888 0.12392 33.562 < 2e-16 ***
  324. WansMRCV1.3:YansMRCV2.3 4.31749 0.11430 37.775 < 2e-16 ***
  325. WansMRCV1.4:YansMRCV2.3 4.02535 0.13262 30.353 < 2e-16 ***
  326. WansMRCV1.1:YansMRCV2.4 3.63759 0.16139 22.539 < 2e-16 ***
  327. WansMRCV1.2:YansMRCV2.4 6.27852 0.04008 156.649 < 2e-16 ***
  328. WansMRCV1.3:YansMRCV2.4 6.48920 0.03536 183.543 < 2e-16 ***
  329. WansMRCV1.4:YansMRCV2.4 6.25767 0.04057 154.243 < 2e-16 ***
  330. wi:yj 1.90034 0.22157 8.577 < 2e-16 ***
  331. WansMRCV1.1:YansMRCV2.1:wi 2.17538 0.17588 12.369 < 2e-16 ***
  332. WansMRCV1.2:YansMRCV2.1:wi -1.08731 0.12257 -8.871 < 2e-16 ***
  333. WansMRCV1.3:YansMRCV2.1:wi -2.41345 0.19383 -12.452 < 2e-16 ***
  334. WansMRCV1.4:YansMRCV2.1:wi -0.31417 0.10777 -2.915 0.003553 **
  335. WansMRCV1.1:YansMRCV2.2:wi 3.49043 0.13688 25.500 < 2e-16 ***
  336. WansMRCV1.2:YansMRCV2.2:wi -0.37775 0.04722 -8.000 1.33e-15 ***
  337. WansMRCV1.3:YansMRCV2.2:wi -2.27047 0.07963 -28.513 < 2e-16 ***
  338. WansMRCV1.4:YansMRCV2.2:wi -0.18232 0.04658 -3.914 9.07e-05 ***
  339. WansMRCV1.1:YansMRCV2.3:wi 1.80680 0.32532 5.554 2.79e-08 ***
  340. WansMRCV1.2:YansMRCV2.3:wi -1.51983 0.29505 -5.151 2.59e-07 ***
  341. WansMRCV1.3:YansMRCV2.3:wi -3.21888 0.58878 -5.467 4.58e-08 ***
  342. WansMRCV1.4:YansMRCV2.3:wi -0.93431 0.25162 -3.713 0.000205 ***
  343. WansMRCV1.1:YansMRCV2.4:wi 3.03191 0.16609 18.255 < 2e-16 ***
  344. WansMRCV1.2:YansMRCV2.4:wi -0.59835 0.07273 -8.227 2.22e-16 ***
  345. WansMRCV1.3:YansMRCV2.4:wi -1.36524 0.08644 -15.794 < 2e-16 ***
  346. WansMRCV1.4:YansMRCV2.4:wi -0.54064 0.07215 -7.494 6.71e-14 ***
  347. WansMRCV1.1:YansMRCV2.1:yj 0.44183 0.21362 2.068 0.038614 *
  348. WansMRCV1.2:YansMRCV2.1:yj 1.87122 0.06611 28.303 < 2e-16 ***
  349. WansMRCV1.3:YansMRCV2.1:yj 2.09400 0.05888 35.565 < 2e-16 ***
  350. WansMRCV1.4:YansMRCV2.1:yj 2.08980 0.07422 28.157 < 2e-16 ***
  351. WansMRCV1.1:YansMRCV2.2:yj -0.39642 0.21262 -1.864 0.062266 .
  352. WansMRCV1.2:YansMRCV2.2:yj -0.23042 0.04526 -5.091 3.55e-07 ***
  353. WansMRCV1.3:YansMRCV2.2:yj -0.28354 0.03717 -7.628 2.38e-14 ***
  354. WansMRCV1.4:YansMRCV2.2:yj -0.18945 0.04667 -4.059 4.92e-05 ***
  355. WansMRCV1.1:YansMRCV2.3:yj 1.99655 0.32133 6.213 5.19e-10 ***
  356. WansMRCV1.2:YansMRCV2.3:yj 3.39859 0.12707 26.745 < 2e-16 ***
  357. WansMRCV1.3:YansMRCV2.3:yj 3.64771 0.11696 31.186 < 2e-16 ***
  358. WansMRCV1.4:YansMRCV2.3:yj 3.46852 0.13570 25.561 < 2e-16 ***
  359. WansMRCV1.1:YansMRCV2.4:yj 0.35140 0.21174 1.660 0.097002 .
  360. WansMRCV1.2:YansMRCV2.4:yj 0.99803 0.05067 19.696 < 2e-16 ***
  361. WansMRCV1.3:YansMRCV2.4:yj 1.24972 0.04422 28.262 < 2e-16 ***
  362. WansMRCV1.4:YansMRCV2.4:yj 0.93602 0.05164 18.125 < 2e-16 ***
  363. WansMRCV1.2:wi:yj -0.85835 0.24883 -3.450 0.000561 ***
  364. WansMRCV1.3:wi:yj -0.77684 0.29827 -2.604 0.009201 **
  365. WansMRCV1.4:wi:yj -1.55277 0.26191 -5.929 3.05e-09 ***
  366. YansMRCV2.2:wi:yj -1.50005 0.23512 -6.380 1.77e-10 ***
  367. YansMRCV2.3:wi:yj 0.07256 0.34857 0.208 0.835110
  368. YansMRCV2.4:wi:yj -0.97426 0.25674 -3.795 0.000148 ***
  369. WansMRCV1.2:YansMRCV2.2:wi:yj 0.93980 0.26272 3.577 0.000347 ***
  370. WansMRCV1.3:YansMRCV2.2:wi:yj 1.86233 0.31186 5.972 2.35e-09 ***
  371. WansMRCV1.4:YansMRCV2.2:wi:yj 1.51931 0.27143 5.597 2.18e-08 ***
  372. WansMRCV1.2:YansMRCV2.3:wi:yj 0.29440 0.44585 0.660 0.509063
  373. WansMRCV1.3:YansMRCV2.3:wi:yj 0.67769 0.75665 0.896 0.370438
  374. WansMRCV1.4:YansMRCV2.3:wi:yj 0.53347 0.46050 1.158 0.246677
  375. WansMRCV1.2:YansMRCV2.4:wi:yj 0.52299 0.28700 1.822 0.068420 .
  376. WansMRCV1.3:YansMRCV2.4:wi:yj -0.15131 0.33200 -0.456 0.648565
  377. WansMRCV1.4:YansMRCV2.4:wi:yj 1.31966 0.29869 4.418 9.95e-06 ***
  378. (Dispersion parameter for poisson family taken to be 1)
  379. Null deviance: 7.4905e+05 Residual deviance: 2.1034e-12
  380. Number of Fisher Scoring iterations: 3
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