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Modern Peloponnese Modeling Roman-Medieval Era

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Feb 9th, 2026 (edited)
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  1. right = c('Australian.DG','Russia_MA1_UP.SG','Turkey_Central_Boncuklu_PPN.AG','Italy_Epigravettian.AG','BPgroup.AG','Southern_Illyrian_Cluster.AG','Greece_Aidonia_LBA.AG','Bulgaria_EIA.AG','Cetina_Cluster.AG','Turkey_Aegean_Mugla_Degirmendere_Ancient.AG','Turkey_Southeast_Batman_Ancient.AG','Turkey_Mediterranean_Isparta_BA.AG','Greece_Crete_HgCharalambos_EMBA.AG','Lebanon_MBA.SG','Lithuania_BA.AG')
  2.  
  3. left = c('Ten_Pel_Rom','Albania_Shtike_Medieval.AG','Poland_Viking.SG')
  4.  
  5. Southern_Illyrian_Cluster.AG contains: I10379.AG, I10383.AG, I10387.AG, I10388.AG, I10390.AG, I13167.AG, I14688.AG, I16251.AG
  6.  
  7. Cetina_Cluster.AG contains: I5726.AG, I10384.AG, I10385.AG, I10389.AG, I13168.AG, I13169.AG, I13171.AG, I13172.AG, I13775.AG, I13778.AG, I14498.AG, I14500.AG, I14501.AG, I14690.AG, I14692.AG, I16253.AG, I16254.AG, I16256.AG, I17139.AG, I18414_d.AG, I22940.AG, I23904.AG, I23911.AG, I23995.AG, I23996.AG, I24639.AG, I26742.AG
  8.  
  9. BPgroup.AG contains: I22200.AG, I22202.AG, I22199.AG, I22201.AG, PG2004.AG
  10.  
  11. Ten_Pel_Rom contains: Ten_Pel_Rom_4, Ten_Pel_Rom_3, Ten_Pel_Rom_2, Ten_Pel_Rom_1
  12.  
  13. ---------------------------------------------------------------------------------------------------------------------------------------
  14.  
  15. Main runs with the static for the Peloponnese project:
  16.  
  17. These are the core analyses focusing on various target populations (e.g., Deep_Mani, Achaea, East_Taygetos) with a static component analysis using ancestral sources.
  18. The results include weights, standard errors (se), and Z-scores for each component (e.g., Ten_Pel_Rom, Albania_Shtike_Medieval.AG, Poland_Viking.SG).
  19. The corresponding popdrop table provides chi-squared tests and p-values to assess the fit of each model.
  20.  
  21. During testing with qpadm rotation, both "Amv_Epi_Hel" and "Ten_Pel_Hel" produced poorer results, with worse p-values and overall model metrics. These models resulted in lower statistical significance and higher error rates, which made them unsuitable for the Peloponnese project.
  22. In contrast, both Albania_Bardhoc_PostMedieval.AG (excluding the outlier I14685.AG) and Albania_Shtike_Medieval.AG were considered. Among these, Albania_Shtike_Medieval.AG consistently outperformed Albania_Bardhoc_PostMedieval.AG in the majority of Peloponnese populations, leading to its selection as the preferred model.
  23.  
  24. ---------------------------------------------------------------------------------------------------------------------------------------
  25.  
  26. Main Pelop Model Three Ways:
  27.  
  28.  
  29. > results$weights
  30. # A tibble: 3 × 5
  31. target left weight se z
  32. <chr> <chr> <dbl> <dbl> <dbl>
  33. 1 Deep_Mani Ten_Pel_Rom 0.620 0.0485 12.8
  34. 2 Deep_Mani Albania_Shtike_Medieval.AG 0.241 0.0646 3.74
  35. 3 Deep_Mani Poland_Viking.SG 0.138 0.0271 5.11
  36. > results$popdrop
  37. # A tibble: 7 × 14
  38. pat wt dof chisq p f4rank Ten_Pel_Rom Albania_Shtike_Medieval.AG Poland_Viking.SG feasible best dofdiff chisqdiff p_nested
  39. <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <lgl> <lgl> <dbl> <dbl> <dbl>
  40. 1 000 0 12 5.47 9.41e- 1 2 0.620 0.241 0.138 TRUE NA NA NA NA
  41. 2 001 1 13 25.7 1.84e- 2 1 0.478 0.522 NA TRUE TRUE 0 5.92 0
  42. 3 010 1 13 19.8 9.96e- 2 1 0.798 NA 0.202 TRUE TRUE 0 -25.5 1
  43. 4 100 1 13 45.3 1.83e- 5 1 NA 1.09 -0.0900 FALSE TRUE NA NA NA
  44. 5 011 2 14 98.4 9.78e- 15 0 1 NA NA TRUE NA NA NA NA
  45. 6 101 2 14 49.3 7.97e- 6 0 NA 1 NA TRUE NA NA NA NA
  46. 7 110 2 14 1051. 1.66e-215 0 NA NA 1 TRUE NA NA NA NA
  47.  
  48. > results$weights
  49. # A tibble: 3 × 5
  50. target left weight se z
  51. <chr> <chr> <dbl> <dbl> <dbl>
  52. 1 Achaea Ten_Pel_Rom 0.447 0.0542 8.25
  53. 2 Achaea Albania_Shtike_Medieval.AG 0.316 0.0717 4.41
  54. 3 Achaea Poland_Viking.SG 0.237 0.0266 8.89
  55. > results$popdrop
  56. # A tibble: 7 × 14
  57. pat wt dof chisq p f4rank Ten_Pel_Rom Albania_Shtike_Medieval.AG Poland_Viking.SG feasible best dofdiff chisqdiff p_nested
  58. <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <lgl> <lgl> <dbl> <dbl> <dbl>
  59. 1 000 0 12 9.68 6.44e- 1 2 0.447 0.316 0.237 TRUE NA NA NA NA
  60. 2 001 1 13 38.2 2.65e- 4 1 0.0488 0.951 NA TRUE TRUE 0 3.94 0
  61. 3 010 1 13 34.3 1.09e- 3 1 0.687 NA 0.313 TRUE TRUE 0 -1.28 1
  62. 4 100 1 13 35.6 6.91e- 4 1 NA 0.913 0.0872 TRUE TRUE NA NA NA
  63. 5 011 2 14 233. 8.44e- 42 0 1 NA NA TRUE NA NA NA NA
  64. 6 101 2 14 39.4 3.21e- 4 0 NA 1 NA TRUE NA NA NA NA
  65. 7 110 2 14 848. 6.78e-172 0 NA NA 1 TRUE NA NA NA NA
  66.  
  67. > results$weights
  68. # A tibble: 3 × 5
  69. target left weight se z
  70. <chr> <chr> <dbl> <dbl> <dbl>
  71. 1 East_Taygetos Ten_Pel_Rom 0.499 0.0482 10.4
  72. 2 East_Taygetos Albania_Shtike_Medieval.AG 0.285 0.0637 4.47
  73. 3 East_Taygetos Poland_Viking.SG 0.216 0.0256 8.42
  74. > results$popdrop
  75. # A tibble: 7 × 14
  76. pat wt dof chisq p f4rank Ten_Pel_Rom Albania_Shtike_Medieval.AG Poland_Viking.SG feasible best dofdiff chisqdiff p_nested
  77. <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <lgl> <lgl> <dbl> <dbl> <dbl>
  78. 1 000 0 12 5.74 9.29e- 1 2 0.499 0.285 0.216 TRUE NA NA NA NA
  79. 2 001 1 13 36.2 5.58e- 4 1 0.154 0.846 NA TRUE TRUE 0 8.59 0
  80. 3 010 1 13 27.6 1.03e- 2 1 0.713 NA 0.287 TRUE TRUE 0 -10.1 1
  81. 4 100 1 13 37.7 3.21e- 4 1 NA 0.956 0.0438 TRUE TRUE NA NA NA
  82. 5 011 2 14 189. 9.89e- 33 0 1 NA NA TRUE NA NA NA NA
  83. 6 101 2 14 39.0 3.67e- 4 0 NA 1 NA TRUE NA NA NA NA
  84. 7 110 2 14 877. 4.03e-178 0 NA NA 1 TRUE NA NA NA NA
  85.  
  86. > results$weights
  87. # A tibble: 3 × 5
  88. target left weight se z
  89. <chr> <chr> <dbl> <dbl> <dbl>
  90. 1 Argolis Ten_Pel_Rom 0.419 0.0579 7.24
  91. 2 Argolis Albania_Shtike_Medieval.AG 0.379 0.0758 5.00
  92. 3 Argolis Poland_Viking.SG 0.203 0.0286 7.09
  93. > results$popdrop
  94. # A tibble: 7 × 14
  95. pat wt dof chisq p f4rank Ten_Pel_Rom Albania_Shtike_Medieval.AG Poland_Viking.SG feasible best dofdiff chisqdiff p_nested
  96. <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <lgl> <lgl> <dbl> <dbl> <dbl>
  97. 1 000 0 12 12.9 3.80e- 1 2 0.419 0.379 0.203 TRUE NA NA NA NA
  98. 2 001 1 13 35.0 8.57e- 4 1 0.102 0.898 NA TRUE TRUE 0 -11.4 1
  99. 3 010 1 13 46.3 1.26e- 5 1 0.706 NA 0.294 TRUE TRUE 0 11.9 0
  100. 4 100 1 13 34.4 1.03e- 3 1 NA 0.931 0.0694 TRUE TRUE NA NA NA
  101. 5 011 2 14 210. 4.76e- 37 0 1 NA NA TRUE NA NA NA NA
  102. 6 101 2 14 36.8 8.02e- 4 0 NA 1 NA TRUE NA NA NA NA
  103. 7 110 2 14 845. 2.48e-171 0 NA NA 1 TRUE NA NA NA NA
  104.  
  105. > results$weights
  106. # A tibble: 3 × 5
  107. target left weight se z
  108. <chr> <chr> <dbl> <dbl> <dbl>
  109. 1 Arcadia Ten_Pel_Rom 0.452 0.0533 8.48
  110. 2 Arcadia Albania_Shtike_Medieval.AG 0.320 0.0704 4.55
  111. 3 Arcadia Poland_Viking.SG 0.228 0.0279 8.16
  112. > results$popdrop
  113. # A tibble: 7 × 14
  114. pat wt dof chisq p f4rank Ten_Pel_Rom Albania_Shtike_Medieval.AG Poland_Viking.SG feasible best dofdiff chisqdiff p_nested
  115. <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <lgl> <lgl> <dbl> <dbl> <dbl>
  116. 1 000 0 12 8.30 7.61e- 1 2 0.452 0.320 0.228 TRUE NA NA NA NA
  117. 2 001 1 13 36.5 5.03e- 4 1 0.0930 0.907 NA TRUE TRUE 0 3.14 0
  118. 3 010 1 13 33.3 1.53e- 3 1 0.694 NA 0.306 TRUE TRUE 0 -2.02 1
  119. 4 100 1 13 35.3 7.51e- 4 1 NA 0.920 0.0795 TRUE TRUE NA NA NA
  120. 5 011 2 14 201. 3.02e- 35 0 1 NA NA TRUE NA NA NA NA
  121. 6 101 2 14 38.3 4.64e- 4 0 NA 1 NA TRUE NA NA NA NA
  122. 7 110 2 14 812. 3.70e-164 0 NA NA 1 TRUE NA NA NA NA
  123.  
  124. > results$weights
  125. # A tibble: 3 × 5
  126. target left weight se z
  127. <chr> <chr> <dbl> <dbl> <dbl>
  128. 1 Elis Ten_Pel_Rom 0.463 0.0498 9.28
  129. 2 Elis Albania_Shtike_Medieval.AG 0.295 0.0652 4.53
  130. 3 Elis Poland_Viking.SG 0.242 0.0256 9.47
  131. > results$popdrop
  132. # A tibble: 7 × 14
  133. pat wt dof chisq p f4rank Ten_Pel_Rom Albania_Shtike_Medieval.AG Poland_Viking.SG feasible best dofdiff chisqdiff p_nested
  134. <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <lgl> <lgl> <dbl> <dbl> <dbl>
  135. 1 000 0 12 8.99 7.04e- 1 2 0.463 0.295 0.242 TRUE NA NA NA NA
  136. 2 001 1 13 39.1 1.90e- 4 1 0.0504 0.950 NA TRUE TRUE 0 7.08 0
  137. 3 010 1 13 32.1 2.35e- 3 1 0.688 NA 0.312 TRUE TRUE 0 -4.98 1
  138. 4 100 1 13 37.0 4.09e- 4 1 NA 0.917 0.0829 TRUE TRUE NA NA NA
  139. 5 011 2 14 218. 1.09e- 38 0 1 NA NA TRUE NA NA NA NA
  140. 6 101 2 14 40.2 2.40e- 4 0 NA 1 NA TRUE NA NA NA NA
  141. 7 110 2 14 828. 1.11e-167 0 NA NA 1 TRUE NA NA NA NA
  142.  
  143. > results$weights
  144. # A tibble: 3 × 5
  145. target left weight se z
  146. <chr> <chr> <dbl> <dbl> <dbl>
  147. 1 Corinthia Ten_Pel_Rom 0.439 0.0527 8.33
  148. 2 Corinthia Albania_Shtike_Medieval.AG 0.338 0.0706 4.78
  149. 3 Corinthia Poland_Viking.SG 0.223 0.0280 7.99
  150. > results$popdrop
  151. # A tibble: 7 × 14
  152. pat wt dof chisq p f4rank Ten_Pel_Rom Albania_Shtike_Medieval.AG Poland_Viking.SG feasible best dofdiff chisqdiff p_nested
  153. <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <lgl> <lgl> <dbl> <dbl> <dbl>
  154. 1 000 0 12 6.63 8.81e- 1 2 0.439 0.338 0.223 TRUE NA NA NA NA
  155. 2 001 1 13 33.8 1.29e- 3 1 0.0875 0.913 NA TRUE TRUE 0 -0.381 1
  156. 3 010 1 13 34.2 1.13e- 3 1 0.688 NA 0.312 TRUE TRUE 0 2.24 0
  157. 4 100 1 13 31.9 2.45e- 3 1 NA 0.916 0.0840 TRUE TRUE NA NA NA
  158. 5 011 2 14 215. 4.69e- 38 0 1 NA NA TRUE NA NA NA NA
  159. 6 101 2 14 35.3 1.35e- 3 0 NA 1 NA TRUE NA NA NA NA
  160. 7 110 2 14 822. 2.19e-166 0 NA NA 1 TRUE NA NA NA NA
  161.  
  162. > results$weights
  163. # A tibble: 3 × 5
  164. target left weight se z
  165. <chr> <chr> <dbl> <dbl> <dbl>
  166. 1 Laconia Ten_Pel_Rom 0.487 0.0521 9.35
  167. 2 Laconia Albania_Shtike_Medieval.AG 0.303 0.0698 4.35
  168. 3 Laconia Poland_Viking.SG 0.209 0.0270 7.76
  169. > results$popdrop
  170. # A tibble: 7 × 14
  171. pat wt dof chisq p f4rank Ten_Pel_Rom Albania_Shtike_Medieval.AG Poland_Viking.SG feasible best dofdiff chisqdiff p_nested
  172. <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <lgl> <lgl> <dbl> <dbl> <dbl>
  173. 1 000 0 12 9.50 6.60e- 1 2 0.487 0.303 0.209 TRUE NA NA NA NA
  174. 2 001 1 13 35.9 6.14e- 4 1 0.158 0.842 NA TRUE TRUE 0 3.02 0
  175. 3 010 1 13 32.9 1.77e- 3 1 0.714 NA 0.286 TRUE TRUE 0 -4.91 1
  176. 4 100 1 13 37.8 3.10e- 4 1 NA 0.960 0.0404 TRUE TRUE NA NA NA
  177. 5 011 2 14 196. 4.34e- 34 0 1 NA NA TRUE NA NA NA NA
  178. 6 101 2 14 39.0 3.64e- 4 0 NA 1 NA TRUE NA NA NA NA
  179. 7 110 2 14 907. 1.37e-184 0 NA NA 1 TRUE NA NA NA NA
  180.  
  181. > results$weights
  182. # A tibble: 3 × 5
  183. target left weight se z
  184. <chr> <chr> <dbl> <dbl> <dbl>
  185. 1 Messenia Ten_Pel_Rom 0.433 0.0529 8.20
  186. 2 Messenia Albania_Shtike_Medieval.AG 0.339 0.0712 4.76
  187. 3 Messenia Poland_Viking.SG 0.228 0.0283 8.05
  188. > results$popdrop
  189. # A tibble: 7 × 14
  190. pat wt dof chisq p f4rank Ten_Pel_Rom Albania_Shtike_Medieval.AG Poland_Viking.SG feasible best dofdiff chisqdiff p_nested
  191. <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <lgl> <lgl> <dbl> <dbl> <dbl>
  192. 1 000 0 12 9.32 6.75e- 1 2 0.433 0.339 0.228 TRUE NA NA NA NA
  193. 2 001 1 13 35.6 6.93e- 4 1 0.0687 0.931 NA TRUE TRUE 0 -2.84 1
  194. 3 010 1 13 38.4 2.49e- 4 1 0.689 NA 0.311 TRUE TRUE 0 4.54 0
  195. 4 100 1 13 33.9 1.26e- 3 1 NA 0.916 0.0844 TRUE TRUE NA NA NA
  196. 5 011 2 14 228. 1.18e- 40 0 1 NA NA TRUE NA NA NA NA
  197. 6 101 2 14 37.1 7.04e- 4 0 NA 1 NA TRUE NA NA NA NA
  198. 7 110 2 14 860. 1.47e-174 0 NA NA 1 TRUE NA NA NA NA
  199.  
  200. > results$weights
  201. # A tibble: 3 × 5
  202. target left weight se z
  203. <chr> <chr> <dbl> <dbl> <dbl>
  204. 1 West_Taygetos Ten_Pel_Rom 0.466 0.0507 9.20
  205. 2 West_Taygetos Albania_Shtike_Medieval.AG 0.254 0.0655 3.88
  206. 3 West_Taygetos Poland_Viking.SG 0.280 0.0254 11.0
  207. > results$popdrop
  208. # A tibble: 7 × 14
  209. pat wt dof chisq p f4rank Ten_Pel_Rom Albania_Shtike_Medieval.AG Poland_Viking.SG feasible best dofdiff chisqdiff p_nested
  210. <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <lgl> <lgl> <dbl> <dbl> <dbl>
  211. 1 000 0 12 8.64 7.33e- 1 2 0.466 0.254 0.280 TRUE NA NA NA NA
  212. 2 001 1 13 44.7 2.32e- 5 1 -0.0686 1.07 NA FALSE TRUE 0 18.8 0
  213. 3 010 1 13 25.9 1.76e- 2 1 0.658 NA 0.342 TRUE TRUE 0 -13.4 1
  214. 4 100 1 13 39.3 1.78e- 4 1 NA 0.876 0.124 TRUE TRUE NA NA NA
  215. 5 011 2 14 246. 2.03e- 44 0 1 NA NA TRUE NA NA NA NA
  216. 6 101 2 14 45.8 3.00e- 5 0 NA 1 NA TRUE NA NA NA NA
  217. 7 110 2 14 711. 1.12e-142 0 NA NA 1 TRUE NA NA NA NA
  218.  
  219. > results$weights
  220. # A tibble: 3 × 5
  221. target left weight se z
  222. <chr> <chr> <dbl> <dbl> <dbl>
  223. 1 South_Tsakonia Ten_Pel_Rom 0.506 0.0564 8.97
  224. 2 South_Tsakonia Albania_Shtike_Medieval.AG 0.318 0.0757 4.20
  225. 3 South_Tsakonia Poland_Viking.SG 0.176 0.0304 5.77
  226. > results$popdrop
  227. # A tibble: 7 × 14
  228. pat wt dof chisq p f4rank Ten_Pel_Rom Albania_Shtike_Medieval.AG Poland_Viking.SG feasible best dofdiff chisqdiff p_nested
  229. <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <lgl> <lgl> <dbl> <dbl> <dbl>
  230. 1 000 0 12 9.66 6.46e- 1 2 0.506 0.318 0.176 TRUE NA NA NA NA
  231. 2 001 1 13 30.5 4.04e- 3 1 0.274 0.726 NA TRUE TRUE 0 -1.21 1
  232. 3 010 1 13 31.7 2.68e- 3 1 0.745 NA 0.255 TRUE TRUE 0 -5.90 1
  233. 4 100 1 13 37.6 3.36e- 4 1 NA 1.00 0.000218 TRUE TRUE NA NA NA
  234. 5 011 2 14 154. 1.03e- 25 0 1 NA NA TRUE NA NA NA NA
  235. 6 101 2 14 38.2 4.89e- 4 0 NA 1 NA TRUE NA NA NA NA
  236. 7 110 2 14 851. 1.59e-172 0 NA NA 1 TRUE NA NA NA NA
  237.  
  238. > results$weights
  239. # A tibble: 3 × 5
  240. target left weight se z
  241. <chr> <chr> <dbl> <dbl> <dbl>
  242. 1 North_Tsakonia Ten_Pel_Rom 0.509 0.0567 8.99
  243. 2 North_Tsakonia Albania_Shtike_Medieval.AG 0.317 0.0737 4.30
  244. 3 North_Tsakonia Poland_Viking.SG 0.174 0.0295 5.89
  245. > results$popdrop
  246. # A tibble: 7 × 14
  247. pat wt dof chisq p f4rank Ten_Pel_Rom Albania_Shtike_Medieval.AG Poland_Viking.SG feasible best dofdiff chisqdiff p_nested
  248. <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <lgl> <lgl> <dbl> <dbl> <dbl>
  249. 1 000 0 12 7.32 8.36e- 1 2 0.509 0.317 0.174 TRUE NA NA NA NA
  250. 2 001 1 13 28.4 8.04e- 3 1 0.274 0.726 NA TRUE TRUE 0 -1.45 1
  251. 3 010 1 13 29.8 4.99e- 3 1 0.751 NA 0.249 TRUE TRUE 0 -5.68 1
  252. 4 100 1 13 35.5 7.09e- 4 1 NA 0.993 0.00708 TRUE TRUE NA NA NA
  253. 5 011 2 14 138. 1.61e- 22 0 1 NA NA TRUE NA NA NA NA
  254. 6 101 2 14 36.0 1.04e- 3 0 NA 1 NA TRUE NA NA NA NA
  255. 7 110 2 14 815. 7.40e-165 0 NA NA 1 TRUE NA NA NA NA
  256.  
  257. ---------------------------------------------------------------------------------------------------------------------------------------
  258.  
  259. Control Testing:
  260.  
  261. Control groups are essential for validating the model’s effectiveness. Albania_Bardhoc_PostMedieval.AG primarily derives from MDV Albanians, with negative weight from Roman Peloponnese and near-zero Slavic input, confirming its alignment with the MDV Albanians without external influence.
  262.  
  263. Similarly, Cretan.DG showed negative weight with MDV Albanian samples, indicating Arvanite ancestry is largely confined to the Peloponnese and does not affect the islands.
  264.  
  265. These results confirm the validity of the static, showing that it accurately reflects Peloponnese populations without overestimating external genetic influences.
  266. ---------------------------------------------------------------------------------------------------------------------------------------
  267.  
  268. Control Pops Model K-Ways:
  269.  
  270. Albania_Bardhoc_PostMedieval.AG 3-Way:
  271.  
  272. > results$weights
  273. # A tibble: 3 × 5
  274. target left weight se z
  275. <chr> <chr> <dbl> <dbl> <dbl>
  276. 1 Albania_Bardhoc_PostMedieval.AG Ten_Pel_Rom -0.0856 0.119 -0.722
  277. 2 Albania_Bardhoc_PostMedieval.AG Albania_Shtike_Medieval.AG 1.06 0.159 6.66
  278. 3 Albania_Bardhoc_PostMedieval.AG Poland_Viking.SG 0.0251 0.0668 0.375
  279. > results$popdrop
  280. # A tibble: 7 × 14
  281. pat wt dof chisq p f4rank Ten_Pel_Rom Albania_Shtike_Medieval.AG Poland_Viking.SG feasible best dofdiff chisqdiff p_nested
  282. <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <lgl> <lgl> <dbl> <dbl> <dbl>
  283. 1 000 0 12 8.76 7.23e- 1 2 -0.0856 1.06 0.0251 FALSE NA NA NA NA
  284. 2 001 1 13 9.72 7.17e- 1 1 -0.103 1.10 NA FALSE TRUE 0 -154. 1
  285. 3 010 1 13 164. 3.69e- 28 1 0.718 NA 0.282 TRUE TRUE 0 153. 0
  286. 4 100 1 13 10.8 6.30e- 1 1 NA 0.965 0.0352 TRUE TRUE NA NA NA
  287. 5 011 2 14 308. 3.08e- 57 0 1 NA NA TRUE NA NA NA NA
  288. 6 101 2 14 11.7 6.29e- 1 0 NA 1 NA TRUE NA NA NA NA
  289. 7 110 2 14 727. 3.67e-146 0 NA NA 1 TRUE NA NA NA NA
  290.  
  291. Albania_Bardhoc_PostMedieval.AG 2-Way:
  292.  
  293. > results$weights
  294. # A tibble: 2 × 5
  295. target left weight se z
  296. <chr> <chr> <dbl> <dbl> <dbl>
  297. 1 Albania_Bardhoc_PostMedieval.AG Albania_Shtike_Medieval.AG 0.960 0.0567 16.9
  298. 2 Albania_Bardhoc_PostMedieval.AG Poland_Viking.SG 0.0398 0.0567 0.702
  299. > results$popdrop
  300. # A tibble: 3 × 13
  301. pat wt dof chisq p f4rank Albania_Shtike_Medieval.AG Poland_Viking.SG feasible best dofdiff chisqdiff p_nested
  302. <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <lgl> <lgl> <dbl> <dbl> <dbl>
  303. 1 00 0 13 9.20 7.57e- 1 1 0.960 0.0398 TRUE NA NA NA NA
  304. 2 01 1 14 11.0 6.88e- 1 0 1 NA TRUE TRUE 0 -628. 1
  305. 3 10 1 14 639. 3.30e-127 0 NA 1 TRUE TRUE NA NA NA
  306.  
  307. Albania_Bardhoc_PostMedieval.AG 1-Way:
  308.  
  309. > results$weights
  310. # A tibble: 1 × 5
  311. target left weight se z
  312. <chr> <chr> <dbl> <dbl> <dbl>
  313. 1 Albania_Bardhoc_PostMedieval.AG Albania_Shtike_Medieval.AG 1 2.49e-14 4.02e13
  314. > results$popdrop
  315. # A tibble: 1 × 12
  316. pat wt dof chisq p f4rank Albania_Shtike_Medieval.AG feasible best dofdiff chisqdiff p_nested
  317. <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <lgl> <lgl> <dbl> <dbl> <dbl>
  318. 1 0 0 14 9.58 0.792 0 1 TRUE NA NA NA NA
  319.  
  320. Cretan.DG 3-Way:
  321.  
  322. > results$weights
  323. # A tibble: 3 × 5
  324. target left weight se z
  325. <chr> <chr> <dbl> <dbl> <dbl>
  326. 1 Cretan.DG Ten_Pel_Rom 0.821 0.0970 8.47
  327. 2 Cretan.DG Albania_Shtike_Medieval.AG -0.0310 0.120 -0.259
  328. 3 Cretan.DG Poland_Viking.SG 0.210 0.0494 4.25
  329. > results$popdrop
  330. # A tibble: 7 × 14
  331. pat wt dof chisq p f4rank Ten_Pel_Rom Albania_Shtike_Medieval.AG Poland_Viking.SG feasible best dofdiff chisqdiff p_nested
  332. <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <lgl> <lgl> <dbl> <dbl> <dbl>
  333. 1 000 0 12 12.0 4.45e- 1 2 0.821 -0.0310 0.210 FALSE NA NA NA NA
  334. 2 001 1 13 52.1 1.28e- 6 1 0.654 0.346 NA TRUE TRUE 0 38.6 0
  335. 3 010 1 13 13.6 4.05e- 1 1 0.800 NA 0.200 TRUE TRUE 0 -53.3 1
  336. 4 100 1 13 66.9 3.03e- 9 1 NA 1.13 -0.129 FALSE TRUE NA NA NA
  337. 5 011 2 14 71.4 1.08e- 9 0 1 NA NA TRUE NA NA NA NA
  338. 6 101 2 14 77.3 9.12e- 11 0 NA 1 NA TRUE NA NA NA NA
  339. 7 110 2 14 774. 3.40e-156 0 NA NA 1 TRUE NA NA NA NA
  340.  
  341. Cretan.DG 2-Way:
  342.  
  343. > results$weights
  344. # A tibble: 2 × 5
  345. target left weight se z
  346. <chr> <chr> <dbl> <dbl> <dbl>
  347. 1 Cretan.DG Ten_Pel_Rom 0.799 0.0383 20.9
  348. 2 Cretan.DG Poland_Viking.SG 0.201 0.0383 5.26
  349. > results$popdrop
  350. # A tibble: 3 × 13
  351. pat wt dof chisq p f4rank Ten_Pel_Rom Poland_Viking.SG feasible best dofdiff chisqdiff p_nested
  352. <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <lgl> <lgl> <dbl> <dbl> <dbl>
  353. 1 00 0 13 12.0 5.31e- 1 1 0.799 0.201 TRUE NA NA NA NA
  354. 2 01 1 14 67.1 6.44e- 9 0 1 NA TRUE TRUE 0 -629. 1
  355. 3 10 1 14 697. 1.43e-139 0 NA 1 TRUE TRUE NA NA NA
  356.  
  357.  
  358.  
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