title: “LIAK coor prov 15” author: “Marcelo Araya-Salas” date: “01/31/2015” output: html_document
#Statistical analysis
## [1] 10000
##One bird at ST another at LT/shuf “at Colony”-“away from Colony”
## [1] "is ST/LT more common?"
## S num.p p.value p.adj
## 1 106.4738 25 5.82597e-06 5.82597e-06
## [1] "is ST/LT less common?"
## S num.p p.value p.adj
## 1 32.50986 25 0.9737815 0.9737815
##One bird at colony/shuf “at Colony”-“away from Colony”
## [1] "is ST/LT more common?"
## S num.p p.value p.adj
## 1 2.63516 25 1 1
## [1] "is ST/LT less common?"
## S num.p p.value p.adj
## 1 219.8366 25 0 0
##2 birds at the colony colony/shuf “at Colony”-“away from Colony”
## [1] "is 2 birds more common?"
## S num.p p.value p.adj
## 1 218.9393 25 0 0
## [1] "is 2 birds less common?"
## S num.p p.value p.adj
## 1 2.614887 25 1 1
##Males vs female effort
## [1] "is short trip duration diff between males and females?"
## [1] "Settings: unique SS "
## Component 1 :
## Df R Sum Sq R Mean Sq Iter Pr(Prob)
## res2$sex 1 7995 7994.6 10000 0.1005
## res2$pair 24 78040 3251.6 5000 0.1316
## Residuals 140 308751 2205.4
## [1] "is long trip duration diff between males and females?"
## [1] "Settings: unique SS "
## Component 1 :
## Df R Sum Sq R Mean Sq Iter Pr(Prob)
## res2$sex 1 27459 27459.2 10000 8.494e-05 ***
## res2$pair 24 40218 1675.8 2112 0.464
## Residuals 140 237676 1697.7
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## [1] "are number of feedings different between male and female?"
## [1] "Settings: unique SS "
## Df Sum Sq Mean Sq F value Pr(>F)
## res3$sex 1 19.6 19.572 3.059 0.0825 .
## res2$pair 24 198.4 8.268 1.292 0.1800
## Residuals 140 895.9 6.399
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## Component 1 :
## Df R Sum Sq R Mean Sq Iter Pr(Prob)
## res2$sex 1 27459 27459.2 10000 0.1427
## res2$pair 24 40218 1675.8 2112 0.4640
## Residuals 140 237676 1697.7
##Distribution of feedings tru time
## [1] "is variation higher?"
## S num.p p.value p.adj
## 1 44.96631 25 0.6750941 0.6750941
## [1] "is variation low?"
## S num.p p.value p.adj
## 1 118.9791 25 1.495144e-07 1.495144e-07
##Association to chick age
## [1] "Settings: unique SS : numeric variables centered"
## [1] "coordination vs chick age blocked by nest"
## Component 1 :
## Df R Sum Sq R Mean Sq Iter Pr(Prob)
## coorage$chick.age 1 2.7092 2.70920 10000 0.005988 **
## coorage$nest 22 7.4074 0.33670 5000 0.400200
## Residuals 29 8.7992 0.30342
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## [1] "Settings: unique SS "
## [1] "coordination vs watch blocked by nest"
## Component 1 :
## Df R Sum Sq R Mean Sq Iter Pr(Prob)
## coorage$p2 2 2.7440 1.37199 10000 0.02248 *
## coorage$nest 22 7.2558 0.32981 3806 0.43090
## Residuals 28 8.7644 0.31301
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##Association between trip duration, sex and chick age
## [1] "female.LT.duration"
## [1] "Settings: unique SS : numeric variables centered"
## Df Sum Sq Mean Sq F value Pr(>F)
## cooragetpd$chick.age 1 1224 1223.8 1.013 0.323
## cooragetpd$pair.x 22 6753 306.9 0.254 0.999
## Residuals 27 32612 1207.9
## 2 observations deleted due to missingness
## [1] "XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX"
## [1] "female.ST.duration"
## [1] "Settings: unique SS : numeric variables centered"
## Df Sum Sq Mean Sq F value Pr(>F)
## cooragetpd$chick.age 1 0.1 0.131 0.018 0.894808
## cooragetpd$pair.x 22 590.4 26.837 3.664 0.000967 ***
## Residuals 26 190.4 7.324
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 3 observations deleted due to missingness
## [1] "XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX"
## [1] "male.LT.duration"
## [1] "Settings: unique SS : numeric variables centered"
## Df Sum Sq Mean Sq F value Pr(>F)
## cooragetpd$chick.age 1 1080 1080.0 2.094 0.159
## cooragetpd$pair.x 22 8775 398.9 0.773 0.730
## Residuals 29 14957 515.8
## [1] "XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX"
## [1] "male.ST.duration"
## [1] "Settings: unique SS : numeric variables centered"
## Df Sum Sq Mean Sq F value Pr(>F)
## cooragetpd$chick.age 1 1.74 1.739 0.239 0.6285
## cooragetpd$pair.x 22 278.65 12.666 1.744 0.0825 .
## Residuals 28 203.40 7.264
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 1 observation deleted due to missingness
## [1] "XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX"
## [1] "female.LT.duration"
## [1] "Settings: unique SS : numeric variables centered"
## Df Sum Sq Mean Sq F value Pr(>F)
## cooragetpd$coorLTST 1 102 101.6 0.081 0.778
## cooragetpd$pair.x 22 6936 315.3 0.252 0.999
## Residuals 27 33734 1249.4
## 2 observations deleted due to missingness
## [1] "XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX"
## [1] "female.ST.duration"
## [1] "Settings: unique SS : numeric variables centered"
## Df Sum Sq Mean Sq F value Pr(>F)
## cooragetpd$coorLTST 1 7.8 7.782 1.107 0.302397
## cooragetpd$pair.x 22 589.5 26.794 3.812 0.000713 ***
## Residuals 26 182.8 7.029
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 3 observations deleted due to missingness
## [1] "XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX"
## [1] "male.LT.duration"
## [1] "Settings: unique SS : numeric variables centered"
## Df Sum Sq Mean Sq F value Pr(>F)
## cooragetpd$coorLTST 1 685 684.8 1.294 0.265
## cooragetpd$pair.x 22 7433 337.9 0.638 0.860
## Residuals 29 15353 529.4
## [1] "XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX"
## [1] "male.ST.duration"
## [1] "Settings: unique SS : numeric variables centered"
## Df Sum Sq Mean Sq F value Pr(>F)
## cooragetpd$coorLTST 1 10.13 10.128 1.454 0.2379
## cooragetpd$pair.x 22 297.24 13.511 1.940 0.0493 *
## Residuals 28 195.01 6.965
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 1 observation deleted due to missingness
## [1] "XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX"
##Variation of coordination among pairs
##Association between feeding distr and coordination
## [1] "Settings: unique SS : numeric variables centered"
## Component 1 :
## Df R Sum Sq R Mean Sq Iter Pr(Prob)
## feedcoor$coorLTST 1 1.5190 1.51902 5000 <2e-16 ***
## feedcoor$pair 24 1.1910 0.04962 5000 0.3502
## Residuals 57 2.4455 0.04290
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##Association to chick condition
## [1] "X14.16.mass vs variation.in.distrib.feeds.in.time"
## [1] "Settings: unique SS : numeric variables centered"
## Df Sum Sq Mean Sq F value Pr(>F)
## dat[, j] 1 119 118.83 2.064 0.185
## dat$pair 22 4147 188.51 3.275 0.035 *
## Residuals 9 518 57.56
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 7 observations deleted due to missingness
## [1] "Settings: unique SS : numeric variables centered"
## Df Sum Sq Mean Sq F value Pr(>F)
## dat[, j] 1 105 104.93 1.903 0.2050
## dat$pair 22 4223 191.95 3.482 0.0369 *
## dat$total.feedings 1 77 77.01 1.397 0.2712
## Residuals 8 441 55.13
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 7 observations deleted due to missingness
## [1] "XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX"
## [1] "X14.16.mass vs AVERAGE.coordination.of.LT-ST"
## [1] "Settings: unique SS : numeric variables centered"
## Df Sum Sq Mean Sq F value Pr(>F)
## dat[, j] 1 21 20.95 0.306 0.5936
## dat$pair 22 4044 183.80 2.686 0.0638 .
## Residuals 9 616 68.44
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 7 observations deleted due to missingness
## [1] "Settings: unique SS : numeric variables centered"
## Df Sum Sq Mean Sq F value Pr(>F)
## dat[, j] 1 13 13.05 0.196 0.6697
## dat$pair 22 4127 187.57 2.816 0.0669 .
## dat$total.feedings 1 83 83.01 1.246 0.2967
## Residuals 8 533 66.61
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 7 observations deleted due to missingness
## [1] "XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX"
## [1] "X14.16.mass vs MAX.coordination.of.LT-ST"
## [1] "Settings: unique SS : numeric variables centered"
## Df Sum Sq Mean Sq F value Pr(>F)
## dat[, j] 1 0 0.44 0.006 0.9385
## dat$pair 22 4029 183.15 2.590 0.0708 .
## Residuals 9 636 70.71
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 7 observations deleted due to missingness
## [1] "Settings: unique SS : numeric variables centered"
## Df Sum Sq Mean Sq F value Pr(>F)
## dat[, j] 1 0 0.25 0.004 0.9530
## dat$pair 22 4120 187.26 2.745 0.0716 .
## dat$total.feedings 1 91 90.72 1.330 0.2821
## Residuals 8 546 68.21
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 7 observations deleted due to missingness
## [1] "XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX"
## [1] "X14.16.mass vs MIN.variation.in..distrib.feeds.in.time"
## [1] "Settings: unique SS : numeric variables centered"
## Df Sum Sq Mean Sq F value Pr(>F)
## dat[, j] 1 105 105.0 1.777 0.2153
## dat$pair 22 3931 178.7 3.024 0.0448 *
## Residuals 9 532 59.1
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 7 observations deleted due to missingness
## [1] "Settings: unique SS : numeric variables centered"
## Df Sum Sq Mean Sq F value Pr(>F)
## dat[, j] 1 82 81.82 1.410 0.269
## dat$pair 22 3998 181.73 3.132 0.050 *
## dat$total.feedings 1 68 67.73 1.167 0.311
## Residuals 8 464 58.02
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 7 observations deleted due to missingness
## [1] "XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX"
## [1] "X14.16.mass vs total.feedings"
## [1] "Settings: unique SS : numeric variables centered"
## Df Sum Sq Mean Sq F value Pr(>F)
## dat[, j] 1 91 90.91 1.499 0.2520
## dat$pair 22 4127 187.59 3.092 0.0419 *
## Residuals 9 546 60.66
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 7 observations deleted due to missingness
## [1] "Settings: unique SS : numeric variables centered"
## Df Sum Sq Mean Sq F value Pr(>F)
## dat[, j] 1 91 90.91 1.499 0.2520
## dat$pair 22 4127 187.59 3.092 0.0419 *
## Residuals 9 546 60.66
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 7 observations deleted due to missingness
## [1] "XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX"
## [1] "X14.16.mass vs feedings.by.male"
## [1] "Settings: unique SS : numeric variables centered"
## Df Sum Sq Mean Sq F value Pr(>F)
## dat[, j] 1 15 14.90 0.216 0.6535
## dat$pair 22 3905 177.51 2.569 0.0725 .
## Residuals 9 622 69.11
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 7 observations deleted due to missingness
## [1] "Settings: unique SS : numeric variables centered"
## Df Sum Sq Mean Sq F value Pr(>F)
## dat[, j] 1 5 4.83 0.071 0.7960
## dat$pair 22 3895 177.03 2.617 0.0813 .
## dat$total.feedings 1 81 80.84 1.195 0.3061
## Residuals 8 541 67.64
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 7 observations deleted due to missingness
## [1] "XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX"
## [1] "X14.16.mass vs feedings.by.females"
## [1] "Settings: unique SS : numeric variables centered"
## Df Sum Sq Mean Sq F value Pr(>F)
## dat[, j] 1 91 90.55 1.492 0.2530
## dat$pair 22 4051 184.11 3.033 0.0444 *
## Residuals 9 546 60.70
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 7 observations deleted due to missingness
## [1] "Settings: unique SS : numeric variables centered"
## Df Sum Sq Mean Sq F value Pr(>F)
## dat[, j] 1 5 4.83 0.071 0.7960
## dat$pair 22 3895 177.03 2.617 0.0813 .
## dat$total.feedings 1 5 5.19 0.077 0.7889
## Residuals 8 541 67.64
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 7 observations deleted due to missingness
## [1] "XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX"
## [1] "Peak.mass vs variation.in.distrib.feeds.in.time"
## [1] "Settings: unique SS : numeric variables centered"
## Df Sum Sq Mean Sq F value Pr(>F)
## dat[, j] 1 13.5 13.46 0.161 0.695
## dat$pair 23 2283.7 99.29 1.190 0.382
## Residuals 13 1084.9 83.46
## 2 observations deleted due to missingness
## [1] "Settings: unique SS : numeric variables centered"
## Df Sum Sq Mean Sq F value Pr(>F)
## dat[, j] 1 32.6 32.58 0.372 0.554
## dat$pair 23 2245.9 97.65 1.113 0.438
## dat$total.feedings 1 32.5 32.51 0.371 0.554
## Residuals 12 1052.4 87.70
## 2 observations deleted due to missingness
## [1] "XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX"
## [1] "Peak.mass vs AVERAGE.coordination.of.LT-ST"
## [1] "Settings: unique SS : numeric variables centered"
## Df Sum Sq Mean Sq F value Pr(>F)
## dat[, j] 1 79 79.04 1.008 0.334
## dat$pair 23 2190 95.24 1.215 0.367
## Residuals 13 1019 78.41
## 2 observations deleted due to missingness
## [1] "Settings: unique SS : numeric variables centered"
## Df Sum Sq Mean Sq F value Pr(>F)
## dat[, j] 1 68.4 68.41 0.807 0.387
## dat$pair 23 2162.1 94.01 1.110 0.441
## dat$total.feedings 1 2.7 2.74 0.032 0.860
## Residuals 12 1016.6 84.72
## 2 observations deleted due to missingness
## [1] "XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX"
## [1] "Peak.mass vs MAX.coordination.of.LT-ST"
## [1] "Settings: unique SS : numeric variables centered"
## Df Sum Sq Mean Sq F value Pr(>F)
## dat[, j] 1 23.6 23.56 0.285 0.602
## dat$pair 23 2252.2 97.92 1.184 0.385
## Residuals 13 1074.8 82.68
## 2 observations deleted due to missingness
## [1] "Settings: unique SS : numeric variables centered"
## Df Sum Sq Mean Sq F value Pr(>F)
## dat[, j] 1 19.4 19.36 0.218 0.649
## dat$pair 23 2209.9 96.08 1.082 0.460
## dat$total.feedings 1 9.2 9.18 0.103 0.753
## Residuals 12 1065.6 88.80
## 2 observations deleted due to missingness
## [1] "XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX"
## [1] "Peak.mass vs MIN.variation.in..distrib.feeds.in.time"
## [1] "Settings: unique SS : numeric variables centered"
## Df Sum Sq Mean Sq F value Pr(>F)
## dat[, j] 1 6.2 6.21 0.074 0.79
## dat$pair 23 2275.3 98.92 1.177 0.39
## Residuals 13 1092.2 84.01
## 2 observations deleted due to missingness
## [1] "Settings: unique SS : numeric variables centered"
## Df Sum Sq Mean Sq F value Pr(>F)
## dat[, j] 1 21.9 21.89 0.247 0.628
## dat$pair 23 2231.5 97.02 1.095 0.451
## dat$total.feedings 1 29.1 29.06 0.328 0.577
## Residuals 12 1063.1 88.59
## 2 observations deleted due to missingness
## [1] "XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX"
## [1] "Peak.mass vs total.feedings"
## [1] "Settings: unique SS : numeric variables centered"
## Df Sum Sq Mean Sq F value Pr(>F)
## dat[, j] 1 13.4 13.38 0.160 0.695
## dat$pair 23 2217.5 96.41 1.155 0.404
## Residuals 13 1085.0 83.46
## 2 observations deleted due to missingness
## [1] "Settings: unique SS : numeric variables centered"
## Df Sum Sq Mean Sq F value Pr(>F)
## dat[, j] 1 13.4 13.38 0.160 0.695
## dat$pair 23 2217.5 96.41 1.155 0.404
## Residuals 13 1085.0 83.46
## 2 observations deleted due to missingness
## [1] "XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX"
## [1] "Peak.mass vs feedings.by.male"
## [1] "Settings: unique SS : numeric variables centered"
## Df Sum Sq Mean Sq F value Pr(>F)
## dat[, j] 1 35 34.97 0.428 0.525
## dat$pair 23 2237 97.24 1.189 0.383
## Residuals 13 1063 81.80
## 2 observations deleted due to missingness
## [1] "Settings: unique SS : numeric variables centered"
## Df Sum Sq Mean Sq F value Pr(>F)
## dat[, j] 1 22.7 22.70 0.256 0.622
## dat$pair 23 2227.6 96.85 1.094 0.452
## dat$total.feedings 1 1.1 1.11 0.013 0.913
## Residuals 12 1062.3 88.53
## 2 observations deleted due to missingness
## [1] "XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX"
## [1] "Peak.mass vs feedings.by.females"
## [1] "Settings: unique SS : numeric variables centered"
## Df Sum Sq Mean Sq F value Pr(>F)
## dat[, j] 1 0.7 0.73 0.009 0.927
## dat$pair 23 2252.6 97.94 1.160 0.401
## Residuals 13 1097.7 84.44
## 2 observations deleted due to missingness
## [1] "Settings: unique SS : numeric variables centered"
## Df Sum Sq Mean Sq F value Pr(>F)
## dat[, j] 1 22.7 22.70 0.256 0.622
## dat$pair 23 2227.6 96.85 1.094 0.452
## dat$total.feedings 1 35.4 35.35 0.399 0.539
## Residuals 12 1062.3 88.53
## 2 observations deleted due to missingness
## [1] "XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX"
## [1] "Fled.mass vs variation.in.distrib.feeds.in.time"
## [1] "Settings: unique SS : numeric variables centered"
## Df Sum Sq Mean Sq F value Pr(>F)
## dat[, j] 1 28.3 28.26 0.631 0.4437
## dat$pair 22 2079.2 94.51 2.112 0.0999 .
## Residuals 11 492.3 44.76
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 5 observations deleted due to missingness
## [1] "Settings: unique SS : numeric variables centered"
## Df Sum Sq Mean Sq F value Pr(>F)
## dat[, j] 1 84.9 84.88 2.237 0.1656
## dat$pair 22 1911.2 86.87 2.290 0.0878 .
## dat$total.feedings 1 113.0 112.97 2.978 0.1151
## Residuals 10 379.4 37.94
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 5 observations deleted due to missingness
## [1] "XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX"
## [1] "Fled.mass vs AVERAGE.coordination.of.LT-ST"
## [1] "Settings: unique SS : numeric variables centered"
## Df Sum Sq Mean Sq F value Pr(>F)
## dat[, j] 1 3.4 3.35 0.071 0.794
## dat$pair 22 2124.7 96.58 2.054 0.108
## Residuals 11 517.2 47.02
## 5 observations deleted due to missingness
## [1] "Settings: unique SS : numeric variables centered"
## Df Sum Sq Mean Sq F value Pr(>F)
## dat[, j] 1 0.0 0.00 0.000 0.995
## dat$pair 22 1982.1 90.10 1.941 0.139
## dat$total.feedings 1 53.0 53.01 1.142 0.310
## Residuals 10 464.2 46.42
## 5 observations deleted due to missingness
## [1] "XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX"
## [1] "Fled.mass vs MAX.coordination.of.LT-ST"
## [1] "Settings: unique SS : numeric variables centered"
## Df Sum Sq Mean Sq F value Pr(>F)
## dat[, j] 1 15.6 15.61 0.340 0.572
## dat$pair 22 2126.5 96.66 2.105 0.101
## Residuals 11 505.0 45.91
## 5 observations deleted due to missingness
## [1] "Settings: unique SS : numeric variables centered"
## Df Sum Sq Mean Sq F value Pr(>F)
## dat[, j] 1 9.3 9.30 0.205 0.661
## dat$pair 22 2001.7 90.99 2.000 0.128
## dat$total.feedings 1 50.1 50.05 1.100 0.319
## Residuals 10 454.9 45.49
## 5 observations deleted due to missingness
## [1] "XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX"
## [1] "Fled.mass vs MIN.variation.in..distrib.feeds.in.time"
## [1] "Settings: unique SS : numeric variables centered"
## Df Sum Sq Mean Sq F value Pr(>F)
## dat[, j] 1 10.7 10.75 0.232 0.640
## dat$pair 22 2035.1 92.50 1.996 0.118
## Residuals 11 509.9 46.35
## 5 observations deleted due to missingness
## [1] "Settings: unique SS : numeric variables centered"
## Df Sum Sq Mean Sq F value Pr(>F)
## dat[, j] 1 58.3 58.33 1.437 0.258
## dat$pair 22 1817.8 82.63 2.036 0.122
## dat$total.feedings 1 103.9 103.94 2.561 0.141
## Residuals 10 405.9 40.59
## 5 observations deleted due to missingness
## [1] "XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX"
## [1] "Fled.mass vs total.feedings"
## [1] "Settings: unique SS : numeric variables centered"
## Df Sum Sq Mean Sq F value Pr(>F)
## dat[, j] 1 56.4 56.36 1.335 0.2723
## dat$pair 22 1992.9 90.59 2.146 0.0951 .
## Residuals 11 464.2 42.20
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 5 observations deleted due to missingness
## [1] "Settings: unique SS : numeric variables centered"
## Df Sum Sq Mean Sq F value Pr(>F)
## dat[, j] 1 56.4 56.36 1.335 0.2723
## dat$pair 22 1992.9 90.59 2.146 0.0951 .
## Residuals 11 464.2 42.20
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 5 observations deleted due to missingness
## [1] "XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX"
## [1] "Fled.mass vs feedings.by.male"
## [1] "Settings: unique SS : numeric variables centered"
## Df Sum Sq Mean Sq F value Pr(>F)
## dat[, j] 1 3.2 3.23 0.069 0.798
## dat$pair 22 2105.1 95.69 2.034 0.111
## Residuals 11 517.4 47.03
## 5 observations deleted due to missingness
## [1] "Settings: unique SS : numeric variables centered"
## Df Sum Sq Mean Sq F value Pr(>F)
## dat[, j] 1 38.7 38.71 0.910 0.363
## dat$pair 22 1978.8 89.95 2.114 0.110
## dat$total.feedings 1 91.8 91.83 2.158 0.173
## Residuals 10 425.5 42.55
## 5 observations deleted due to missingness
## [1] "XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX"
## [1] "Fled.mass vs feedings.by.females"
## [1] "Settings: unique SS : numeric variables centered"
## Df Sum Sq Mean Sq F value Pr(>F)
## dat[, j] 1 90.1 90.13 2.303 0.1573
## dat$pair 22 1981.4 90.06 2.301 0.0768 .
## Residuals 11 430.5 39.13
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 5 observations deleted due to missingness
## [1] "Settings: unique SS : numeric variables centered"
## Df Sum Sq Mean Sq F value Pr(>F)
## dat[, j] 1 38.7 38.71 0.910 0.363
## dat$pair 22 1978.8 89.95 2.114 0.110
## dat$total.feedings 1 4.9 4.94 0.116 0.740
## Residuals 10 425.5 42.55
## 5 observations deleted due to missingness
## [1] "XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX"
## [1] "Rec.mass vs variation.in.distrib.feeds.in.time"
## [1] "Settings: unique SS : numeric variables centered"
## Df Sum Sq Mean Sq F value Pr(>F)
## dat[, j] 1 9.4 9.44 0.162 0.695
## dat$pair 22 1531.1 69.59 1.198 0.391
## Residuals 11 639.1 58.10
## 5 observations deleted due to missingness
## [1] "Settings: unique SS : numeric variables centered"
## Df Sum Sq Mean Sq F value Pr(>F)
## dat[, j] 1 1.3 1.30 0.021 0.888
## dat$pair 22 1504.4 68.38 1.098 0.460
## dat$total.feedings 1 16.3 16.33 0.262 0.620
## Residuals 10 622.8 62.28
## 5 observations deleted due to missingness
## [1] "XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX"
## [1] "Rec.mass vs AVERAGE.coordination.of.LT-ST"
## [1] "Settings: unique SS : numeric variables centered"
## Df Sum Sq Mean Sq F value Pr(>F)
## dat[, j] 1 1.8 1.83 0.031 0.863
## dat$pair 22 1522.0 69.18 1.177 0.403
## Residuals 11 646.8 58.80
## 5 observations deleted due to missingness
## [1] "Settings: unique SS : numeric variables centered"
## Df Sum Sq Mean Sq F value Pr(>F)
## dat[, j] 1 6.8 6.79 0.110 0.747
## dat$pair 22 1511.8 68.72 1.113 0.450
## dat$total.feedings 1 29.4 29.43 0.477 0.506
## Residuals 10 617.3 61.73
## 5 observations deleted due to missingness
## [1] "XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX"
## [1] "Rec.mass vs MAX.coordination.of.LT-ST"
## [1] "Settings: unique SS : numeric variables centered"
## Df Sum Sq Mean Sq F value Pr(>F)
## dat[, j] 1 19.2 19.18 0.335 0.574
## dat$pair 22 1582.7 71.94 1.257 0.357
## Residuals 11 629.4 57.22
## 5 observations deleted due to missingness
## [1] "Settings: unique SS : numeric variables centered"
## Df Sum Sq Mean Sq F value Pr(>F)
## dat[, j] 1 14.4 14.44 0.237 0.637
## dat$pair 22 1585.1 72.05 1.182 0.408
## dat$total.feedings 1 19.7 19.72 0.324 0.582
## Residuals 10 609.7 60.97
## 5 observations deleted due to missingness
## [1] "XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX"
## [1] "Rec.mass vs MIN.variation.in..distrib.feeds.in.time"
## [1] "Settings: unique SS : numeric variables centered"
## Df Sum Sq Mean Sq F value Pr(>F)
## dat[, j] 1 19.9 19.94 0.349 0.567
## dat$pair 22 1543.2 70.15 1.227 0.373
## Residuals 11 628.6 57.15
## 5 observations deleted due to missingness
## [1] "Settings: unique SS : numeric variables centered"
## Df Sum Sq Mean Sq F value Pr(>F)
## dat[, j] 1 6.0 5.99 0.097 0.762
## dat$pair 22 1505.8 68.45 1.107 0.454
## dat$total.feedings 1 10.5 10.52 0.170 0.689
## Residuals 10 618.1 61.81
## 5 observations deleted due to missingness
## [1] "XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX"
## [1] "Rec.mass vs total.feedings"
## [1] "Settings: unique SS : numeric variables centered"
## Df Sum Sq Mean Sq F value Pr(>F)
## dat[, j] 1 24.5 24.47 0.431 0.525
## dat$pair 22 1571.1 71.41 1.259 0.356
## Residuals 11 624.1 56.74
## 5 observations deleted due to missingness
## [1] "Settings: unique SS : numeric variables centered"
## Df Sum Sq Mean Sq F value Pr(>F)
## dat[, j] 1 24.5 24.47 0.431 0.525
## dat$pair 22 1571.1 71.41 1.259 0.356
## Residuals 11 624.1 56.74
## 5 observations deleted due to missingness
## [1] "XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX"
## [1] "Rec.mass vs feedings.by.male"
## [1] "Settings: unique SS : numeric variables centered"
## Df Sum Sq Mean Sq F value Pr(>F)
## dat[, j] 1 0.1 0.08 0.001 0.971
## dat$pair 22 1550.0 70.46 1.195 0.392
## Residuals 11 648.5 58.95
## 5 observations deleted due to missingness
## [1] "Settings: unique SS : numeric variables centered"
## Df Sum Sq Mean Sq F value Pr(>F)
## dat[, j] 1 40.9 40.92 0.702 0.422
## dat$pair 22 1514.1 68.82 1.180 0.409
## dat$total.feedings 1 65.3 65.31 1.120 0.315
## Residuals 10 583.2 58.32
## 5 observations deleted due to missingness
## [1] "XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX"
## [1] "Rec.mass vs feedings.by.females"
## [1] "Settings: unique SS : numeric variables centered"
## Df Sum Sq Mean Sq F value Pr(>F)
## dat[, j] 1 53.0 52.99 0.979 0.344
## dat$pair 22 1527.3 69.42 1.282 0.343
## Residuals 11 595.6 54.14
## 5 observations deleted due to missingness
## [1] "Settings: unique SS : numeric variables centered"
## Df Sum Sq Mean Sq F value Pr(>F)
## dat[, j] 1 40.9 40.92 0.702 0.422
## dat$pair 22 1514.1 68.82 1.180 0.409
## dat$total.feedings 1 12.4 12.40 0.213 0.655
## Residuals 10 583.2 58.32
## 5 observations deleted due to missingness
## [1] "XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX"
## [1] "Peak.day vs variation.in.distrib.feeds.in.time"
## [1] "Settings: unique SS : numeric variables centered"
## Df Sum Sq Mean Sq F value Pr(>F)
## dat[, j] 1 7.42 7.419 0.694 0.422
## dat$pair 22 167.59 7.618 0.713 0.760
## Residuals 11 117.58 10.689
## 5 observations deleted due to missingness
## [1] "Settings: unique SS : numeric variables centered"
## Df Sum Sq Mean Sq F value Pr(>F)
## dat[, j] 1 4.31 4.314 0.370 0.557
## dat$pair 22 154.76 7.034 0.603 0.845
## dat$total.feedings 1 0.98 0.979 0.084 0.778
## Residuals 10 116.60 11.660
## 5 observations deleted due to missingness
## [1] "XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX"
## [1] "Peak.day vs AVERAGE.coordination.of.LT-ST"
## [1] "Settings: unique SS : numeric variables centered"
## Df Sum Sq Mean Sq F value Pr(>F)
## dat[, j] 1 13.55 13.549 1.337 0.272
## dat$pair 22 161.89 7.358 0.726 0.749
## Residuals 11 111.45 10.132
## 5 observations deleted due to missingness
## [1] "Settings: unique SS : numeric variables centered"
## Df Sum Sq Mean Sq F value Pr(>F)
## dat[, j] 1 18.37 18.370 1.791 0.210
## dat$pair 22 155.78 7.081 0.691 0.776
## dat$total.feedings 1 8.90 8.905 0.868 0.373
## Residuals 10 102.55 10.255
## 5 observations deleted due to missingness
## [1] "XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX"
## [1] "Peak.day vs MAX.coordination.of.LT-ST"
## [1] "Settings: unique SS : numeric variables centered"
## Df Sum Sq Mean Sq F value Pr(>F)
## dat[, j] 1 19.97 19.969 2.091 0.176
## dat$pair 22 165.57 7.526 0.788 0.696
## Residuals 11 105.03 9.548
## 5 observations deleted due to missingness
## [1] "Settings: unique SS : numeric variables centered"
## Df Sum Sq Mean Sq F value Pr(>F)
## dat[, j] 1 22.60 22.596 2.298 0.160
## dat$pair 22 160.24 7.284 0.741 0.734
## dat$total.feedings 1 6.71 6.711 0.683 0.428
## Residuals 10 98.32 9.832
## 5 observations deleted due to missingness
## [1] "XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX"
## [1] "Peak.day vs MIN.variation.in..distrib.feeds.in.time"
## [1] "Settings: unique SS : numeric variables centered"
## Df Sum Sq Mean Sq F value Pr(>F)
## dat[, j] 1 2.92 2.922 0.263 0.618
## dat$pair 22 178.22 8.101 0.730 0.746
## Residuals 11 122.08 11.098
## 5 observations deleted due to missingness
## [1] "Settings: unique SS : numeric variables centered"
## Df Sum Sq Mean Sq F value Pr(>F)
## dat[, j] 1 0.76 0.758 0.063 0.807
## dat$pair 22 171.57 7.799 0.649 0.809
## dat$total.feedings 1 1.92 1.920 0.160 0.698
## Residuals 10 120.16 12.016
## 5 observations deleted due to missingness
## [1] "XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX"
## [1] "Peak.day vs total.feedings"
## [1] "Settings: unique SS : numeric variables centered"
## Df Sum Sq Mean Sq F value Pr(>F)
## dat[, j] 1 4.08 4.084 0.372 0.555
## dat$pair 22 175.03 7.956 0.724 0.751
## Residuals 11 120.92 10.992
## 5 observations deleted due to missingness
## [1] "Settings: unique SS : numeric variables centered"
## Df Sum Sq Mean Sq F value Pr(>F)
## dat[, j] 1 4.08 4.084 0.372 0.555
## dat$pair 22 175.03 7.956 0.724 0.751
## Residuals 11 120.92 10.992
## 5 observations deleted due to missingness
## [1] "XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX"
## [1] "Peak.day vs feedings.by.male"
## [1] "Settings: unique SS : numeric variables centered"
## Df Sum Sq Mean Sq F value Pr(>F)
## dat[, j] 1 4.44 4.438 0.405 0.538
## dat$pair 22 179.82 8.173 0.746 0.732
## Residuals 11 120.56 10.960
## 5 observations deleted due to missingness
## [1] "Settings: unique SS : numeric variables centered"
## Df Sum Sq Mean Sq F value Pr(>F)
## dat[, j] 1 0.75 0.747 0.062 0.808
## dat$pair 22 175.13 7.960 0.662 0.798
## dat$total.feedings 1 0.39 0.393 0.033 0.860
## Residuals 10 120.17 12.017
## 5 observations deleted due to missingness
## [1] "XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX"
## [1] "Peak.day vs feedings.by.females"
## [1] "Settings: unique SS : numeric variables centered"
## Df Sum Sq Mean Sq F value Pr(>F)
## dat[, j] 1 2.03 2.026 0.181 0.679
## dat$pair 22 173.04 7.865 0.704 0.768
## Residuals 11 122.97 11.179
## 5 observations deleted due to missingness
## [1] "Settings: unique SS : numeric variables centered"
## Df Sum Sq Mean Sq F value Pr(>F)
## dat[, j] 1 0.75 0.747 0.062 0.808
## dat$pair 22 175.13 7.960 0.662 0.798
## dat$total.feedings 1 2.80 2.805 0.233 0.639
## Residuals 10 120.17 12.017
## 5 observations deleted due to missingness
## [1] "XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX"
## [1] "Fled.day vs variation.in.distrib.feeds.in.time"
## [1] "Settings: unique SS : numeric variables centered"
## Df Sum Sq Mean Sq F value Pr(>F)
## dat[, j] 1 0.45 0.453 0.089 0.770
## dat$pair 23 130.38 5.669 1.116 0.431
## Residuals 13 66.05 5.081
## 2 observations deleted due to missingness
## [1] "Settings: unique SS : numeric variables centered"
## Df Sum Sq Mean Sq F value Pr(>F)
## dat[, j] 1 1.25 1.252 0.233 0.638
## dat$pair 23 131.83 5.732 1.065 0.472
## dat$total.feedings 1 1.49 1.486 0.276 0.609
## Residuals 12 64.56 5.380
## 2 observations deleted due to missingness
## [1] "XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX"
## [1] "Fled.day vs AVERAGE.coordination.of.LT-ST"
## [1] "Settings: unique SS : numeric variables centered"
## Df Sum Sq Mean Sq F value Pr(>F)
## dat[, j] 1 1.68 1.680 0.337 0.571
## dat$pair 23 131.22 5.705 1.144 0.412
## Residuals 13 64.82 4.986
## 2 observations deleted due to missingness
## [1] "Settings: unique SS : numeric variables centered"
## Df Sum Sq Mean Sq F value Pr(>F)
## dat[, j] 1 2.33 2.335 0.441 0.519
## dat$pair 23 132.53 5.762 1.089 0.455
## dat$total.feedings 1 1.34 1.341 0.254 0.624
## Residuals 12 63.48 5.290
## 2 observations deleted due to missingness
## [1] "XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX"
## [1] "Fled.day vs MAX.coordination.of.LT-ST"
## [1] "Settings: unique SS : numeric variables centered"
## Df Sum Sq Mean Sq F value Pr(>F)
## dat[, j] 1 1.75 1.753 0.352 0.563
## dat$pair 23 128.05 5.567 1.118 0.430
## Residuals 13 64.75 4.981
## 2 observations deleted due to missingness
## [1] "Settings: unique SS : numeric variables centered"
## Df Sum Sq Mean Sq F value Pr(>F)
## dat[, j] 1 2.10 2.100 0.396 0.541
## dat$pair 23 128.99 5.608 1.056 0.479
## dat$total.feedings 1 1.03 1.034 0.195 0.667
## Residuals 12 63.71 5.309
## 2 observations deleted due to missingness
## [1] "XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX"
## [1] "Fled.day vs MIN.variation.in..distrib.feeds.in.time"
## [1] "Settings: unique SS : numeric variables centered"
## Df Sum Sq Mean Sq F value Pr(>F)
## dat[, j] 1 0.58 0.582 0.115 0.740
## dat$pair 23 125.89 5.473 1.079 0.457
## Residuals 13 65.92 5.071
## 2 observations deleted due to missingness
## [1] "Settings: unique SS : numeric variables centered"
## Df Sum Sq Mean Sq F value Pr(>F)
## dat[, j] 1 1.64 1.645 0.308 0.589
## dat$pair 23 127.40 5.539 1.036 0.494
## dat$total.feedings 1 1.75 1.750 0.327 0.578
## Residuals 12 64.17 5.347
## 2 observations deleted due to missingness
## [1] "XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX"
## [1] "Fled.day vs total.feedings"
## [1] "Settings: unique SS : numeric variables centered"
## Df Sum Sq Mean Sq F value Pr(>F)
## dat[, j] 1 0.69 0.687 0.136 0.719
## dat$pair 23 131.03 5.697 1.125 0.425
## Residuals 13 65.81 5.063
## 2 observations deleted due to missingness
## [1] "Settings: unique SS : numeric variables centered"
## Df Sum Sq Mean Sq F value Pr(>F)
## dat[, j] 1 0.69 0.687 0.136 0.719
## dat$pair 23 131.03 5.697 1.125 0.425
## Residuals 13 65.81 5.063
## 2 observations deleted due to missingness
## [1] "XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX"
## [1] "Fled.day vs feedings.by.male"
## [1] "Settings: unique SS : numeric variables centered"
## Df Sum Sq Mean Sq F value Pr(>F)
## dat[, j] 1 0.08 0.079 0.015 0.903
## dat$pair 23 130.01 5.653 1.106 0.438
## Residuals 13 66.42 5.109
## 2 observations deleted due to missingness
## [1] "Settings: unique SS : numeric variables centered"
## Df Sum Sq Mean Sq F value Pr(>F)
## dat[, j] 1 0.24 0.242 0.044 0.837
## dat$pair 23 130.40 5.669 1.038 0.493
## dat$total.feedings 1 0.85 0.850 0.156 0.700
## Residuals 12 65.57 5.464
## 2 observations deleted due to missingness
## [1] "XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX"
## [1] "Fled.day vs feedings.by.females"
## [1] "Settings: unique SS : numeric variables centered"
## Df Sum Sq Mean Sq F value Pr(>F)
## dat[, j] 1 0.93 0.928 0.184 0.675
## dat$pair 23 130.93 5.692 1.129 0.422
## Residuals 13 65.57 5.044
## 2 observations deleted due to missingness
## [1] "Settings: unique SS : numeric variables centered"
## Df Sum Sq Mean Sq F value Pr(>F)
## dat[, j] 1 0.24 0.242 0.044 0.837
## dat$pair 23 130.40 5.669 1.038 0.493
## dat$total.feedings 1 0.00 0.001 0.000 0.993
## Residuals 12 65.57 5.464
## 2 observations deleted due to missingness
## [1] "XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX"
## [1] "SGR1 vs variation.in.distrib.feeds.in.time"
## [1] "Settings: unique SS : numeric variables centered"
## Df Sum Sq Mean Sq F value Pr(>F)
## dat[, j] 1 0.41 0.409 0.039 0.849
## dat$pair 20 90.65 4.532 0.427 0.942
## Residuals 8 85.01 10.626
## 10 observations deleted due to missingness
## [1] "Settings: unique SS : numeric variables centered"
## Df Sum Sq Mean Sq F value Pr(>F)
## dat[, j] 1 0.65 0.648 0.058 0.817
## dat$pair 20 92.33 4.617 0.412 0.943
## dat$total.feedings 1 6.55 6.548 0.584 0.470
## Residuals 7 78.46 11.209
## 10 observations deleted due to missingness
## [1] "XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX"
## [1] "SGR1 vs AVERAGE.coordination.of.LT-ST"
## [1] "Settings: unique SS : numeric variables centered"
## Df Sum Sq Mean Sq F value Pr(>F)
## dat[, j] 1 1.12 1.115 0.106 0.753
## dat$pair 20 93.19 4.660 0.442 0.934
## Residuals 8 84.30 10.538
## 10 observations deleted due to missingness
## [1] "Settings: unique SS : numeric variables centered"
## Df Sum Sq Mean Sq F value Pr(>F)
## dat[, j] 1 0.68 0.680 0.061 0.812
## dat$pair 20 95.14 4.757 0.425 0.937
## dat$total.feedings 1 5.87 5.874 0.524 0.492
## Residuals 7 78.43 11.204
## 10 observations deleted due to missingness
## [1] "XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX"
## [1] "SGR1 vs MAX.coordination.of.LT-ST"
## [1] "Settings: unique SS : numeric variables centered"
## Df Sum Sq Mean Sq F value Pr(>F)
## dat[, j] 1 0.02 0.023 0.002 0.964
## dat$pair 20 92.15 4.607 0.432 0.939
## Residuals 8 85.40 10.674
## 10 observations deleted due to missingness
## [1] "Settings: unique SS : numeric variables centered"
## Df Sum Sq Mean Sq F value Pr(>F)
## dat[, j] 1 0.19 0.194 0.017 0.899
## dat$pair 20 94.55 4.727 0.419 0.940
## dat$total.feedings 1 6.48 6.481 0.575 0.473
## Residuals 7 78.91 11.274
## 10 observations deleted due to missingness
## [1] "XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX"
## [1] "SGR1 vs MIN.variation.in..distrib.feeds.in.time"
## [1] "Settings: unique SS : numeric variables centered"
## Df Sum Sq Mean Sq F value Pr(>F)
## dat[, j] 1 1.30 1.304 0.124 0.734
## dat$pair 20 91.15 4.558 0.433 0.938
## Residuals 8 84.11 10.514
## 10 observations deleted due to missingness
## [1] "Settings: unique SS : numeric variables centered"
## Df Sum Sq Mean Sq F value Pr(>F)
## dat[, j] 1 2.20 2.199 0.200 0.668
## dat$pair 20 93.32 4.666 0.425 0.937
## dat$total.feedings 1 7.20 7.205 0.656 0.445
## Residuals 7 76.91 10.987
## 10 observations deleted due to missingness
## [1] "XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX"
## [1] "SGR1 vs total.feedings"
## [1] "Settings: unique SS : numeric variables centered"
## Df Sum Sq Mean Sq F value Pr(>F)
## dat[, j] 1 6.31 6.309 0.638 0.447
## dat$pair 20 94.52 4.726 0.478 0.914
## Residuals 8 79.11 9.889
## 10 observations deleted due to missingness
## [1] "Settings: unique SS : numeric variables centered"
## Df Sum Sq Mean Sq F value Pr(>F)
## dat[, j] 1 6.31 6.309 0.638 0.447
## dat$pair 20 94.52 4.726 0.478 0.914
## Residuals 8 79.11 9.889
## 10 observations deleted due to missingness
## [1] "XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX"
## [1] "SGR1 vs feedings.by.male"
## [1] "Settings: unique SS : numeric variables centered"
## Df Sum Sq Mean Sq F value Pr(>F)
## dat[, j] 1 0.18 0.181 0.017 0.900
## dat$pair 20 92.02 4.601 0.432 0.939
## Residuals 8 85.24 10.655
## 10 observations deleted due to missingness
## [1] "Settings: unique SS : numeric variables centered"
## Df Sum Sq Mean Sq F value Pr(>F)
## dat[, j] 1 2.69 2.686 0.246 0.635
## dat$pair 20 91.58 4.579 0.419 0.940
## dat$total.feedings 1 8.82 8.815 0.807 0.399
## Residuals 7 76.42 10.918
## 10 observations deleted due to missingness
## [1] "XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX"
## [1] "SGR1 vs feedings.by.females"
## [1] "Settings: unique SS : numeric variables centered"
## Df Sum Sq Mean Sq F value Pr(>F)
## dat[, j] 1 8.63 8.631 0.899 0.371
## dat$pair 20 91.55 4.578 0.477 0.914
## Residuals 8 76.79 9.598
## 10 observations deleted due to missingness
## [1] "Settings: unique SS : numeric variables centered"
## Df Sum Sq Mean Sq F value Pr(>F)
## dat[, j] 1 2.69 2.686 0.246 0.635
## dat$pair 20 91.58 4.579 0.419 0.940
## dat$total.feedings 1 0.37 0.365 0.033 0.860
## Residuals 7 76.42 10.918
## 10 observations deleted due to missingness
## [1] "XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX"
## [1] "SGR2 vs variation.in.distrib.feeds.in.time"
## [1] "Settings: unique SS : numeric variables centered"
## Df Sum Sq Mean Sq F value Pr(>F)
## dat[, j] 1 2.83 2.835 0.997 0.340
## dat$pair 22 56.42 2.564 0.902 0.601
## Residuals 11 31.28 2.844
## 5 observations deleted due to missingness
## [1] "Settings: unique SS : numeric variables centered"
## Df Sum Sq Mean Sq F value Pr(>F)
## dat[, j] 1 5.14 5.143 1.830 0.206
## dat$pair 22 58.10 2.641 0.940 0.572
## dat$total.feedings 1 3.18 3.181 1.132 0.312
## Residuals 10 28.10 2.810
## 5 observations deleted due to missingness
## [1] "XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX"
## [1] "SGR2 vs AVERAGE.coordination.of.LT-ST"
## [1] "Settings: unique SS : numeric variables centered"
## Df Sum Sq Mean Sq F value Pr(>F)
## dat[, j] 1 0.95 0.9455 0.314 0.587
## dat$pair 22 56.10 2.5500 0.846 0.647
## Residuals 11 33.17 3.0158
## 5 observations deleted due to missingness
## [1] "Settings: unique SS : numeric variables centered"
## Df Sum Sq Mean Sq F value Pr(>F)
## dat[, j] 1 0.60 0.596 0.182 0.678
## dat$pair 22 55.94 2.543 0.779 0.702
## dat$total.feedings 1 0.52 0.524 0.160 0.697
## Residuals 10 32.65 3.265
## 5 observations deleted due to missingness
## [1] "XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX"
## [1] "SGR2 vs MAX.coordination.of.LT-ST"
## [1] "Settings: unique SS : numeric variables centered"
## Df Sum Sq Mean Sq F value Pr(>F)
## dat[, j] 1 6.21 6.213 2.449 0.146
## dat$pair 22 56.87 2.585 1.019 0.509
## Residuals 11 27.91 2.537
## 5 observations deleted due to missingness
## [1] "Settings: unique SS : numeric variables centered"
## Df Sum Sq Mean Sq F value Pr(>F)
## dat[, j] 1 5.74 5.740 2.087 0.179
## dat$pair 22 57.09 2.595 0.943 0.569
## dat$total.feedings 1 0.40 0.400 0.145 0.711
## Residuals 10 27.51 2.751
## 5 observations deleted due to missingness
## [1] "XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX"
## [1] "SGR2 vs MIN.variation.in..distrib.feeds.in.time"
## [1] "Settings: unique SS : numeric variables centered"
## Df Sum Sq Mean Sq F value Pr(>F)
## dat[, j] 1 0.91 0.9097 0.301 0.594
## dat$pair 22 51.96 2.3616 0.782 0.701
## Residuals 11 33.21 3.0191
## 5 observations deleted due to missingness
## [1] "Settings: unique SS : numeric variables centered"
## Df Sum Sq Mean Sq F value Pr(>F)
## dat[, j] 1 2.45 2.455 0.797 0.393
## dat$pair 22 51.90 2.359 0.766 0.713
## dat$total.feedings 1 2.42 2.418 0.785 0.396
## Residuals 10 30.79 3.079
## 5 observations deleted due to missingness
## [1] "XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX"
## [1] "SGR2 vs total.feedings"
## [1] "Settings: unique SS : numeric variables centered"
## Df Sum Sq Mean Sq F value Pr(>F)
## dat[, j] 1 0.87 0.8732 0.289 0.602
## dat$pair 22 55.38 2.5172 0.833 0.658
## Residuals 11 33.25 3.0224
## 5 observations deleted due to missingness
## [1] "Settings: unique SS : numeric variables centered"
## Df Sum Sq Mean Sq F value Pr(>F)
## dat[, j] 1 0.87 0.8732 0.289 0.602
## dat$pair 22 55.38 2.5172 0.833 0.658
## Residuals 11 33.25 3.0224
## 5 observations deleted due to missingness
## [1] "XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX"
## [1] "SGR2 vs feedings.by.male"
## [1] "Settings: unique SS : numeric variables centered"
## Df Sum Sq Mean Sq F value Pr(>F)
## dat[, j] 1 0.30 0.3046 0.099 0.759
## dat$pair 22 53.91 2.4505 0.797 0.688
## Residuals 11 33.81 3.0741
## 5 observations deleted due to missingness
## [1] "Settings: unique SS : numeric variables centered"
## Df Sum Sq Mean Sq F value Pr(>F)
## dat[, j] 1 3.95 3.954 1.350 0.272
## dat$pair 22 52.80 2.400 0.819 0.668
## dat$total.feedings 1 4.52 4.522 1.544 0.242
## Residuals 10 29.29 2.929
## 5 observations deleted due to missingness
## [1] "XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX"
## [1] "SGR2 vs feedings.by.females"
## [1] "Settings: unique SS : numeric variables centered"
## Df Sum Sq Mean Sq F value Pr(>F)
## dat[, j] 1 2.97 2.969 1.048 0.328
## dat$pair 22 53.20 2.418 0.854 0.640
## Residuals 11 31.15 2.832
## 5 observations deleted due to missingness
## [1] "Settings: unique SS : numeric variables centered"
## Df Sum Sq Mean Sq F value Pr(>F)
## dat[, j] 1 3.95 3.954 1.350 0.272
## dat$pair 22 52.80 2.400 0.819 0.668
## dat$total.feedings 1 1.86 1.858 0.634 0.444
## Residuals 10 29.29 2.929
## 5 observations deleted due to missingness
## [1] "XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX"
## [1] "Settings: unique SS "
## Component 1 :
## Df R Sum Sq R Mean Sq Iter Pr(Prob)
## dat$coorgroup1 1 9.656 9.6560 51 0.7059
## Residuals 15 128.508 8.5672
## [1] "Settings: unique SS "
## Component 1 :
## Df R Sum Sq R Mean Sq Iter Pr(Prob)
## dat$coorgroup1 1 2.617 2.6171 273 0.2711
## Residuals 19 73.008 3.8425
## [1] "Settings: unique SS "
## Component 1 :
## Df R Sum Sq R Mean Sq Iter Pr(Prob)
## dat$coorgroup1 1 0.25 0.248 51 0.9412
## Residuals 19 1956.64 102.981
##Association to parents morphology
## 'data.frame': 80 obs. of 8 variables:
## $ Sezon : int 2010 2009 2010 2010 2009 2010 2009 2010 2009 2010 ...
## $ Ring.no : int 41150 41158 41158 41161 41162 41162 41163 41163 41164 41164 ...
## $ Nest.season : Factor w/ 40 levels "M.F11.2009","M.F11.2010",..: 13 14 15 21 22 23 24 25 14 15 ...
## $ Sx : Factor w/ 2 levels "F","M": 2 1 1 2 1 1 1 1 2 2 ...
## $ Dt.body.mass: Factor w/ 19 levels "13 Jul 09","14 Jul 09",..: 15 2 12 9 1 9 3 12 1 11 ...
## $ Wing : int 121 125 125 NA 125 125 120 120 123 123 ...
## $ Thl : num 54.1 53.4 53.4 NA 53 53 52.2 52.2 52.3 52.3 ...
## $ Body.mass : int 164 170 NA NA 190 NA 163 NA 144 NA ...
## [1] "Settings: unique SS "
## Df Sum Sq Mean Sq F value Pr(>F)
## pair 23 3277 142.5 1.071 0.438
## Residuals 22 2928 133.1
## 4 observations deleted due to missingness
## [1] "Settings: unique SS "
## Df Sum Sq Mean Sq F value Pr(>F)
## pair 23 148.2 6.442 1.076 0.433
## Residuals 22 131.8 5.989
## 4 observations deleted due to missingness
## [1] "Settings: unique SS "
## Df Sum Sq Mean Sq F value Pr(>F)
## pair 23 6.26 0.2723 0.116 1
## Residuals 22 51.86 2.3571
## 4 observations deleted due to missingness
## [1] "X14.16.mass vs mean.Body.mass"
## [1] "XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX"
## [1] "X14.16.mass vs diff.Body.mass"
## [1] "XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX"
## [1] "Peak.mass vs mean.Body.mass"
## [1] "XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX"
## [1] "Peak.mass vs diff.Body.mass"
## [1] "XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX"
## [1] "Fled.mass vs mean.Body.mass"
## [1] "XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX"
## [1] "Fled.mass vs diff.Body.mass"
## [1] "XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX"
## [1] "Rec.mass vs mean.Body.mass"
## [1] "XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX"
## [1] "Rec.mass vs diff.Body.mass"
## [1] "XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX"
## [1] "Peak.day vs mean.Body.mass"
## [1] "XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX"
## [1] "Peak.day vs diff.Body.mass"
## [1] "XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX"
## [1] "Fled.day vs mean.Body.mass"
## [1] "XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX"
## [1] "Fled.day vs diff.Body.mass"
## [1] "XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX"
## [1] "SGR1 vs mean.Body.mass"
## [1] "XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX"
## [1] "SGR1 vs diff.Body.mass"
## [1] "XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX"
## [1] "SGR2 vs mean.Body.mass"
## [1] "XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX"
## [1] "SGR2 vs diff.Body.mass"
## [1] "XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX"
## [1] "variation.in.distrib.feeds.in.time vs mean.Body.mass"
## [1] "XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX"
## [1] "variation.in.distrib.feeds.in.time vs diff.Body.mass"
## [1] "XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX"
## [1] "AVERAGE.coordination.of.LT.ST vs mean.Body.mass"
## [1] "XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX"
## [1] "AVERAGE.coordination.of.LT.ST vs diff.Body.mass"
## [1] "XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX"
## [1] "MAX.coordination.of.LT.ST vs mean.Body.mass"
## [1] "XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX"
## [1] "MAX.coordination.of.LT.ST vs diff.Body.mass"
## [1] "XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX"
## [1] "MIN.variation.in..distrib.feeds.in.time vs mean.Body.mass"
## [1] "XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX"
## [1] "MIN.variation.in..distrib.feeds.in.time vs diff.Body.mass"
## [1] "XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX"
## [1] "total.feedings vs mean.Body.mass"
## [1] "XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX"
## [1] "total.feedings vs diff.Body.mass"
## [1] "XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX"
## [1] "feedings.by.male vs mean.Body.mass"
## [1] "XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX"
## [1] "feedings.by.male vs diff.Body.mass"
## [1] "XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX"
## [1] "feedings.by.females vs mean.Body.mass"
## [1] "XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX"
## [1] "feedings.by.females vs diff.Body.mass"
## [1] "XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX"
## [1] "Settings: unique SS "
## Component 1 :
## Df R Sum Sq R Mean Sq Iter Pr(Prob)
## dat$coorgroup1 1 9.656 9.6560 304 0.25
## Residuals 15 128.508 8.5672
