Within- herd FMDV analysis
Erin Gorsich
July 19, 2017
Sensitivity Results for Duration of Infection
Note: For base and Var 1 models, I define duration of infection as the time any animal is infectious. For Var2 models, I define duration of infection as the time any animal is either in the C or I stage.
Histograms: all parameters together
Baseruns
Variation 1: (duration I only)
Variation 2 blood: (duration I or C )
Variation 2 nasal: (duration I or C )
Variation 2 probang: (duration I or C)
Scatterplots for herdsizes of 10000 head and infection seeded with 100 head
Baseruns Density Dependent
Baseruns Frequency Dependent
Var 1 DD
Var 1 FD
Var 2b DD
Var 2b FD
Var 2n DD
Var 2n FD
Var 2o DD
Var 2o FD
Clay’s sensitivity method
For report, we should put the axes on the same scale and add some threashold where the coefficeint is biologically relevant.
Dataset
Base run DD
##
## Call:
## lm(formula = full.model.1, data = df)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.64201 -0.21249 0.00259 0.16880 1.51072
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 1.834e-02 2.364e-03 7.758 9.21e-15 ***
## size 6.661e-01 2.540e-03 262.226 < 2e-16 ***
## seed 2.071e-02 2.712e-03 7.636 2.37e-14 ***
## V1 -5.112e-03 2.239e-03 -2.283 0.0225 *
## V2 -5.792e-01 2.239e-03 -258.656 < 2e-16 ***
## V3 -3.894e-01 2.239e-03 -173.903 < 2e-16 ***
## size:seed 7.717e-02 3.306e-03 23.341 < 2e-16 ***
## size:V1 4.013e-04 2.301e-03 0.174 0.8615
## size:V2 -1.573e-01 2.301e-03 -68.384 < 2e-16 ***
## size:V3 -2.020e-03 2.301e-03 -0.878 0.3799
## seed:V1 -7.068e-05 2.301e-03 -0.031 0.9755
## seed:V2 -1.942e-03 2.301e-03 -0.844 0.3987
## seed:V3 6.264e-04 2.301e-03 0.272 0.7854
## V1:V2 -3.715e-04 2.220e-03 -0.167 0.8671
## V1:V3 2.108e-03 2.231e-03 0.945 0.3447
## V2:V3 4.709e-02 2.230e-03 21.118 < 2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.2742 on 14984 degrees of freedom
## Multiple R-squared: 0.9249, Adjusted R-squared: 0.9248
## F-statistic: 1.23e+04 on 15 and 14984 DF, p-value: < 2.2e-16
##
## Call:
## lm(formula = full.model.1, data = df)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.77009 -0.19945 -0.00964 0.17697 1.63884
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.0152575 0.0024604 6.201 5.75e-10 ***
## size 0.5871473 0.0026435 222.113 < 2e-16 ***
## seed 0.0139518 0.0028220 4.944 7.74e-07 ***
## V1 -0.0044044 0.0023306 -1.890 0.058799 .
## V2 -0.6330918 0.0023303 -271.678 < 2e-16 ***
## V3 -0.4203738 0.0023305 -180.377 < 2e-16 ***
## size:seed 0.0638179 0.0034407 18.548 < 2e-16 ***
## size:V1 0.0004084 0.0023941 0.171 0.864534
## size:V2 -0.1411391 0.0023942 -58.951 < 2e-16 ***
## size:V3 0.0010652 0.0023942 0.445 0.656406
## seed:V1 0.0004855 0.0023941 0.203 0.839299
## seed:V2 0.0023273 0.0023942 0.972 0.331023
## seed:V3 -0.0086036 0.0023942 -3.593 0.000327 ***
## V1:V2 -0.0012038 0.0023107 -0.521 0.602402
## V1:V3 0.0002124 0.0023220 0.091 0.927119
## V2:V3 0.0475908 0.0023206 20.508 < 2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.2853 on 14984 degrees of freedom
## Multiple R-squared: 0.9187, Adjusted R-squared: 0.9186
## F-statistic: 1.128e+04 on 15 and 14984 DF, p-value: < 2.2e-16Base run FD
##
## Call:
## lm(formula = full.model.1, data = df)
##
## Residuals:
## Min 1Q Median 3Q Max
## -4.5820 -0.2260 -0.0238 0.1632 8.8999
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.0091192 0.0041576 2.193 0.02830 *
## size 0.6112822 0.0044670 136.845 < 2e-16 ***
## seed -0.0197660 0.0047687 -4.145 3.42e-05 ***
## V1 -0.1648596 0.0039382 -41.861 < 2e-16 ***
## V2 -0.4993635 0.0039378 -126.813 < 2e-16 ***
## V3 -0.3211822 0.0039382 -81.556 < 2e-16 ***
## size:seed 0.0373123 0.0058142 6.417 1.43e-10 ***
## size:V1 -0.0625920 0.0040456 -15.472 < 2e-16 ***
## size:V2 -0.1343139 0.0040457 -33.199 < 2e-16 ***
## size:V3 0.0120380 0.0040458 2.975 0.00293 **
## seed:V1 0.0126363 0.0040456 3.124 0.00179 **
## seed:V2 -0.0012588 0.0040457 -0.311 0.75569
## seed:V3 0.0068420 0.0040458 1.691 0.09083 .
## V1:V2 0.0004039 0.0039047 0.103 0.91762
## V1:V3 0.0095695 0.0039237 2.439 0.01474 *
## V2:V3 0.0356709 0.0039215 9.096 < 2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.4822 on 14984 degrees of freedom
## Multiple R-squared: 0.7677, Adjusted R-squared: 0.7675
## F-statistic: 3302 on 15 and 14984 DF, p-value: < 2.2e-16
##
## Call:
## lm(formula = full.model.1, data = df)
##
## Residuals:
## Min 1Q Median 3Q Max
## -3.4368 -0.2755 -0.0741 0.1499 8.2290
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.004647 0.005347 0.869 0.38477
## size 0.473832 0.005745 82.480 < 2e-16 ***
## seed -0.049140 0.006133 -8.012 1.21e-15 ***
## V1 -0.254528 0.005065 -50.254 < 2e-16 ***
## V2 -0.467662 0.005064 -92.346 < 2e-16 ***
## V3 -0.293129 0.005065 -57.877 < 2e-16 ***
## size:seed 0.020464 0.007477 2.737 0.00621 **
## size:V1 -0.054528 0.005203 -10.480 < 2e-16 ***
## size:V2 -0.106690 0.005203 -20.505 < 2e-16 ***
## size:V3 0.017034 0.005203 3.274 0.00106 **
## seed:V1 0.044763 0.005203 8.604 < 2e-16 ***
## seed:V2 -0.002016 0.005203 -0.387 0.69845
## seed:V3 -0.005505 0.005203 -1.058 0.29003
## V1:V2 -0.026255 0.005022 -5.228 1.73e-07 ***
## V1:V3 -0.014659 0.005046 -2.905 0.00368 **
## V2:V3 0.022045 0.005043 4.371 1.24e-05 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.6201 on 14984 degrees of freedom
## Multiple R-squared: 0.6158, Adjusted R-squared: 0.6155
## F-statistic: 1601 on 15 and 14984 DF, p-value: < 2.2e-16Var1 DD
##
## Call:
## lm(formula = full.model.1, data = df)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.67967 -0.21945 0.00226 0.17656 1.61735
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.0173899 0.0024604 7.068 1.64e-12 ***
## size 0.6808540 0.0026421 257.697 < 2e-16 ***
## seed 0.0240075 0.0028205 8.512 < 2e-16 ***
## V1 -0.0017472 0.0023323 -0.749 0.4538
## V2 -0.5166783 0.0023315 -221.608 < 2e-16 ***
## V3 -0.0672410 0.0023298 -28.861 < 2e-16 ***
## V4 -0.4374955 0.0023306 -187.720 < 2e-16 ***
## size:seed 0.0755108 0.0034389 21.958 < 2e-16 ***
## size:V1 0.0010574 0.0023938 0.442 0.6587
## size:V2 -0.1328319 0.0023943 -55.479 < 2e-16 ***
## size:V3 -0.0022827 0.0023933 -0.954 0.3402
## size:V4 -0.0044436 0.0023928 -1.857 0.0633 .
## seed:V1 0.0005934 0.0023938 0.248 0.8042
## seed:V2 -0.0042939 0.0023943 -1.793 0.0729 .
## seed:V3 -0.0033937 0.0023933 -1.418 0.1562
## seed:V4 0.0010182 0.0023928 0.426 0.6705
## V1:V2 0.0048711 0.0023357 2.085 0.0370 *
## V1:V3 -0.0045766 0.0023076 -1.983 0.0474 *
## V1:V4 -0.0008721 0.0023121 -0.377 0.7060
## V2:V3 0.0006890 0.0023005 0.299 0.7646
## V2:V4 0.0484986 0.0022945 21.136 < 2e-16 ***
## V3:V4 0.0133119 0.0023051 5.775 7.85e-09 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.2852 on 14978 degrees of freedom
## Multiple R-squared: 0.9188, Adjusted R-squared: 0.9187
## F-statistic: 8068 on 21 and 14978 DF, p-value: < 2.2e-16
##
## Call:
## lm(formula = full.model.1, data = df)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.83399 -0.21670 -0.01237 0.18840 1.54594
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.016697 0.002645 6.314 2.80e-10 ***
## size 0.596445 0.002840 210.028 < 2e-16 ***
## seed -0.009811 0.003032 -3.236 0.00121 **
## V1 -0.001165 0.002507 -0.465 0.64225
## V2 -0.634977 0.002506 -253.381 < 2e-16 ***
## V3 -0.206584 0.002504 -82.495 < 2e-16 ***
## V4 -0.320462 0.002505 -127.928 < 2e-16 ***
## size:seed 0.068001 0.003696 18.397 < 2e-16 ***
## size:V1 0.002833 0.002573 1.101 0.27081
## size:V2 -0.118970 0.002573 -46.229 < 2e-16 ***
## size:V3 0.004655 0.002572 1.810 0.07038 .
## size:V4 -0.004548 0.002572 -1.768 0.07700 .
## seed:V1 -0.001198 0.002573 -0.466 0.64154
## seed:V2 -0.004691 0.002573 -1.823 0.06834 .
## seed:V3 0.007434 0.002572 2.890 0.00386 **
## seed:V4 -0.007449 0.002572 -2.896 0.00378 **
## V1:V2 0.004200 0.002511 1.673 0.09435 .
## V1:V3 -0.004967 0.002480 -2.002 0.04525 *
## V1:V4 -0.003604 0.002485 -1.450 0.14706
## V2:V3 0.025155 0.002473 10.173 < 2e-16 ***
## V2:V4 0.019458 0.002466 7.890 3.24e-15 ***
## V3:V4 -0.045615 0.002478 -18.410 < 2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.3065 on 14978 degrees of freedom
## Multiple R-squared: 0.9062, Adjusted R-squared: 0.906
## F-statistic: 6888 on 21 and 14978 DF, p-value: < 2.2e-16
##
## Call:
## lm(formula = full.model.1, data = df)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.80982 -0.21621 -0.04308 0.14569 2.79259
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) -0.0009018 0.0031331 -0.288 0.7735
## size 0.0019351 0.0033645 0.575 0.5652
## seed -0.0019836 0.0035918 -0.552 0.5808
## V1 0.0001062 0.0029701 0.036 0.9715
## V2 -0.3311349 0.0029690 -111.531 < 2e-16 ***
## V3 0.6064725 0.0029668 204.418 < 2e-16 ***
## V4 -0.6080937 0.0029678 -204.896 < 2e-16 ***
## size:seed 0.0017106 0.0043792 0.391 0.6961
## size:V1 0.0024104 0.0030483 0.791 0.4291
## size:V2 0.0066915 0.0030489 2.195 0.0282 *
## size:V3 -0.0013421 0.0030477 -0.440 0.6597
## size:V4 -0.0131665 0.0030471 -4.321 1.56e-05 ***
## seed:V1 0.0006734 0.0030483 0.221 0.8252
## seed:V2 0.0026772 0.0030489 0.878 0.3799
## seed:V3 -0.0003043 0.0030477 -0.100 0.9205
## seed:V4 0.0004371 0.0030471 0.143 0.8859
## V1:V2 0.0054658 0.0029743 1.838 0.0661 .
## V1:V3 -0.0043692 0.0029385 -1.487 0.1371
## V1:V4 -0.0036457 0.0029443 -1.238 0.2157
## V2:V3 -0.1111495 0.0029295 -37.942 < 2e-16 ***
## V2:V4 0.0323967 0.0029219 11.087 < 2e-16 ***
## V3:V4 -0.0941938 0.0029354 -32.089 < 2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.3632 on 14978 degrees of freedom
## Multiple R-squared: 0.8683, Adjusted R-squared: 0.8681
## F-statistic: 4702 on 21 and 14978 DF, p-value: < 2.2e-16Var1 FD
##
## Call:
## lm(formula = full.model.1, data = df)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.45609 -0.26920 0.03059 0.22718 0.41074
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 5.657e-03 2.509e-03 2.255 0.0242 *
## size 9.370e-01 2.694e-03 347.794 < 2e-16 ***
## seed -8.878e-02 2.876e-03 -30.868 < 2e-16 ***
## V1 4.599e-16 2.378e-03 0.000 1.0000
## V2 2.014e-16 2.377e-03 0.000 1.0000
## V3 2.743e-17 2.376e-03 0.000 1.0000
## V4 2.308e-16 2.376e-03 0.000 1.0000
## size:seed 2.464e-02 3.507e-03 7.028 2.19e-12 ***
## size:V1 8.178e-16 2.441e-03 0.000 1.0000
## size:V2 3.985e-16 2.441e-03 0.000 1.0000
## size:V3 -2.224e-17 2.440e-03 0.000 1.0000
## size:V4 3.510e-16 2.440e-03 0.000 1.0000
## seed:V1 2.632e-16 2.441e-03 0.000 1.0000
## seed:V2 1.134e-16 2.441e-03 0.000 1.0000
## seed:V3 -1.710e-17 2.440e-03 0.000 1.0000
## seed:V4 1.388e-16 2.440e-03 0.000 1.0000
## V1:V2 2.228e-16 2.382e-03 0.000 1.0000
## V1:V3 9.890e-17 2.353e-03 0.000 1.0000
## V1:V4 6.839e-17 2.358e-03 0.000 1.0000
## V2:V3 7.277e-17 2.346e-03 0.000 1.0000
## V2:V4 2.450e-16 2.340e-03 0.000 1.0000
## V3:V4 1.750e-17 2.350e-03 0.000 1.0000
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.2908 on 14978 degrees of freedom
## Multiple R-squared: 0.9156, Adjusted R-squared: 0.9154
## F-statistic: 7733 on 21 and 14978 DF, p-value: < 2.2e-16
##
## Call:
## lm(formula = full.model.1, data = df)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.7048 -0.2283 0.0365 0.1422 0.7353
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) -1.575e-02 2.791e-03 -5.644 1.69e-08 ***
## size 8.452e-01 2.997e-03 282.022 < 2e-16 ***
## seed -2.554e-01 3.199e-03 -79.818 < 2e-16 ***
## V1 4.030e-15 2.646e-03 0.000 1
## V2 -6.191e-17 2.645e-03 0.000 1
## V3 7.952e-16 2.643e-03 0.000 1
## V4 3.097e-15 2.644e-03 0.000 1
## size:seed -6.862e-02 3.901e-03 -17.591 < 2e-16 ***
## size:V1 7.457e-15 2.715e-03 0.000 1
## size:V2 1.424e-18 2.716e-03 0.000 1
## size:V3 1.323e-15 2.715e-03 0.000 1
## size:V4 5.717e-15 2.714e-03 0.000 1
## seed:V1 2.249e-15 2.715e-03 0.000 1
## seed:V2 -2.340e-17 2.716e-03 0.000 1
## seed:V3 4.103e-16 2.715e-03 0.000 1
## seed:V4 1.698e-15 2.714e-03 0.000 1
## V1:V2 5.672e-16 2.649e-03 0.000 1
## V1:V3 -6.984e-16 2.617e-03 0.000 1
## V1:V4 -3.626e-15 2.623e-03 0.000 1
## V2:V3 1.666e-16 2.609e-03 0.000 1
## V2:V4 6.167e-16 2.603e-03 0.000 1
## V3:V4 -8.727e-16 2.615e-03 0.000 1
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.3235 on 14978 degrees of freedom
## Multiple R-squared: 0.8955, Adjusted R-squared: 0.8954
## F-statistic: 6112 on 21 and 14978 DF, p-value: < 2.2e-16Var2b DD
##
## Call:
## lm(formula = full.model.1, data = df)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.7896 -0.2404 -0.0013 0.2062 1.2407
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.0191786 0.0027516 6.970 3.30e-12 ***
## size 0.7216257 0.0029536 244.322 < 2e-16 ***
## seed 0.0164280 0.0031531 5.210 1.91e-07 ***
## V1 -0.0059435 0.0026065 -2.280 0.02261 *
## V2 -0.6057970 0.0026077 -232.313 < 2e-16 ***
## V3 -0.1654399 0.0026060 -63.485 < 2e-16 ***
## V4 -0.1138885 0.0026064 -43.696 < 2e-16 ***
## size:seed 0.0897467 0.0038444 23.345 < 2e-16 ***
## size:V1 0.0009153 0.0026763 0.342 0.73236
## size:V2 -0.0811626 0.0026772 -30.316 < 2e-16 ***
## size:V3 -0.0120565 0.0026763 -4.505 6.69e-06 ***
## size:V4 -0.0231301 0.0026756 -8.645 < 2e-16 ***
## seed:V1 0.0005598 0.0026763 0.209 0.83433
## seed:V2 -0.0005234 0.0026772 -0.195 0.84502
## seed:V3 0.0004307 0.0026763 0.161 0.87216
## seed:V4 -0.0016649 0.0026756 -0.622 0.53378
## V1:V2 0.0063878 0.0025768 2.479 0.01319 *
## V1:V3 -0.0002714 0.0025943 -0.105 0.91668
## V1:V4 -0.0005978 0.0026059 -0.229 0.81855
## V2:V3 -0.0283731 0.0025911 -10.950 < 2e-16 ***
## V2:V4 -0.0219895 0.0025516 -8.618 < 2e-16 ***
## V3:V4 -0.0081797 0.0025723 -3.180 0.00148 **
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.3188 on 14978 degrees of freedom
## Multiple R-squared: 0.8985, Adjusted R-squared: 0.8984
## F-statistic: 6314 on 21 and 14978 DF, p-value: < 2.2e-16
##
## Call:
## lm(formula = full.model.1, data = df)
##
## Residuals:
## Min 1Q Median 3Q Max
## -1.0802 -0.2652 -0.0209 0.2359 1.6378
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 1.471e-02 3.206e-03 4.588 4.50e-06 ***
## size 5.981e-01 3.442e-03 173.794 < 2e-16 ***
## seed 1.019e-02 3.674e-03 2.773 0.00557 **
## V1 -4.749e-03 3.037e-03 -1.564 0.11792
## V2 -6.975e-01 3.039e-03 -229.558 < 2e-16 ***
## V3 -1.588e-01 3.037e-03 -52.284 < 2e-16 ***
## V4 -1.034e-01 3.037e-03 -34.052 < 2e-16 ***
## size:seed 7.308e-02 4.480e-03 16.314 < 2e-16 ***
## size:V1 -1.404e-03 3.119e-03 -0.450 0.65267
## size:V2 -8.090e-02 3.120e-03 -25.932 < 2e-16 ***
## size:V3 -1.168e-02 3.119e-03 -3.747 0.00018 ***
## size:V4 -1.787e-02 3.118e-03 -5.731 1.02e-08 ***
## seed:V1 -2.494e-03 3.119e-03 -0.800 0.42382
## seed:V2 -3.474e-03 3.120e-03 -1.114 0.26550
## seed:V3 -3.475e-03 3.119e-03 -1.114 0.26523
## seed:V4 -1.033e-03 3.118e-03 -0.331 0.74045
## V1:V2 8.530e-03 3.003e-03 2.841 0.00451 **
## V1:V3 2.488e-05 3.023e-03 0.008 0.99343
## V1:V4 -1.706e-03 3.037e-03 -0.562 0.57431
## V2:V3 -4.322e-02 3.019e-03 -14.315 < 2e-16 ***
## V2:V4 -3.339e-02 2.973e-03 -11.230 < 2e-16 ***
## V3:V4 -8.596e-03 2.997e-03 -2.868 0.00414 **
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.3715 on 14978 degrees of freedom
## Multiple R-squared: 0.8622, Adjusted R-squared: 0.862
## F-statistic: 4462 on 21 and 14978 DF, p-value: < 2.2e-16Var2b FD
##
## Call:
## lm(formula = full.model.1, data = df)
##
## Residuals:
## Min 1Q Median 3Q Max
## -3.6569 -0.2470 -0.0350 0.1687 19.0973
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.009552 0.004527 2.110 0.03489 *
## size 0.611848 0.004859 125.910 < 2e-16 ***
## seed -0.049877 0.005188 -9.615 < 2e-16 ***
## V1 -0.165255 0.004288 -38.536 < 2e-16 ***
## V2 -0.526479 0.004290 -122.714 < 2e-16 ***
## V3 -0.152415 0.004287 -35.549 < 2e-16 ***
## V4 -0.083966 0.004288 -19.581 < 2e-16 ***
## size:seed 0.049319 0.006325 7.797 6.73e-15 ***
## size:V1 -0.013583 0.004403 -3.085 0.00204 **
## size:V2 -0.071204 0.004405 -16.165 < 2e-16 ***
## size:V3 -0.014116 0.004403 -3.206 0.00135 **
## size:V4 -0.012579 0.004402 -2.858 0.00428 **
## seed:V1 0.043936 0.004403 9.978 < 2e-16 ***
## seed:V2 0.003905 0.004405 0.887 0.37533
## seed:V3 0.001930 0.004403 0.438 0.66118
## seed:V4 -0.001822 0.004402 -0.414 0.67901
## V1:V2 0.032253 0.004239 7.608 2.95e-14 ***
## V1:V3 0.025981 0.004268 6.087 1.18e-09 ***
## V1:V4 -0.019633 0.004287 -4.579 4.71e-06 ***
## V2:V3 -0.009568 0.004263 -2.244 0.02482 *
## V2:V4 -0.004597 0.004198 -1.095 0.27353
## V3:V4 -0.021985 0.004232 -5.195 2.08e-07 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.5245 on 14978 degrees of freedom
## Multiple R-squared: 0.7252, Adjusted R-squared: 0.7249
## F-statistic: 1883 on 21 and 14978 DF, p-value: < 2.2e-16
##
## Call:
## lm(formula = full.model.1, data = df)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.9872 -0.2663 -0.0509 0.1739 15.1995
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.0073116 0.0056469 1.295 0.19541
## size 0.4496813 0.0060613 74.188 < 2e-16 ***
## seed -0.0528226 0.0064708 -8.163 3.52e-16 ***
## V1 -0.1653061 0.0053490 -30.904 < 2e-16 ***
## V2 -0.5491412 0.0053515 -102.615 < 2e-16 ***
## V3 -0.1380156 0.0053479 -25.807 < 2e-16 ***
## V4 -0.0591625 0.0053488 -11.061 < 2e-16 ***
## size:seed 0.0403288 0.0078895 5.112 3.23e-07 ***
## size:V1 0.0009456 0.0054922 0.172 0.86331
## size:V2 -0.0592175 0.0054942 -10.778 < 2e-16 ***
## size:V3 -0.0084604 0.0054924 -1.540 0.12348
## size:V4 -0.0116665 0.0054909 -2.125 0.03363 *
## seed:V1 0.0463306 0.0054922 8.436 < 2e-16 ***
## seed:V2 0.0053076 0.0054942 0.966 0.33404
## seed:V3 0.0034996 0.0054924 0.637 0.52403
## seed:V4 -0.0033387 0.0054909 -0.608 0.54317
## V1:V2 0.0295239 0.0052881 5.583 2.40e-08 ***
## V1:V3 0.0352096 0.0053240 6.613 3.88e-11 ***
## V1:V4 -0.0343795 0.0053479 -6.429 1.33e-10 ***
## V2:V3 -0.0166293 0.0053174 -3.127 0.00177 **
## V2:V4 -0.0022352 0.0052364 -0.427 0.66949
## V3:V4 -0.0299385 0.0052789 -5.671 1.44e-08 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.6543 on 14978 degrees of freedom
## Multiple R-squared: 0.5725, Adjusted R-squared: 0.5719
## F-statistic: 955.2 on 21 and 14978 DF, p-value: < 2.2e-16Var2n DD
##
## Call:
## lm(formula = full.model.1, data = df)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.7896 -0.2404 -0.0013 0.2062 1.2407
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.0191786 0.0027516 6.970 3.30e-12 ***
## size 0.7216257 0.0029536 244.322 < 2e-16 ***
## seed 0.0164280 0.0031531 5.210 1.91e-07 ***
## V1 -0.0059435 0.0026065 -2.280 0.02261 *
## V2 -0.6057970 0.0026077 -232.313 < 2e-16 ***
## V3 -0.1654399 0.0026060 -63.485 < 2e-16 ***
## V4 -0.1138885 0.0026064 -43.696 < 2e-16 ***
## size:seed 0.0897467 0.0038444 23.345 < 2e-16 ***
## size:V1 0.0009153 0.0026763 0.342 0.73236
## size:V2 -0.0811626 0.0026772 -30.316 < 2e-16 ***
## size:V3 -0.0120565 0.0026763 -4.505 6.69e-06 ***
## size:V4 -0.0231301 0.0026756 -8.645 < 2e-16 ***
## seed:V1 0.0005598 0.0026763 0.209 0.83433
## seed:V2 -0.0005234 0.0026772 -0.195 0.84502
## seed:V3 0.0004307 0.0026763 0.161 0.87216
## seed:V4 -0.0016649 0.0026756 -0.622 0.53378
## V1:V2 0.0063878 0.0025768 2.479 0.01319 *
## V1:V3 -0.0002714 0.0025943 -0.105 0.91668
## V1:V4 -0.0005978 0.0026059 -0.229 0.81855
## V2:V3 -0.0283731 0.0025911 -10.950 < 2e-16 ***
## V2:V4 -0.0219895 0.0025516 -8.618 < 2e-16 ***
## V3:V4 -0.0081797 0.0025723 -3.180 0.00148 **
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.3188 on 14978 degrees of freedom
## Multiple R-squared: 0.8985, Adjusted R-squared: 0.8984
## F-statistic: 6314 on 21 and 14978 DF, p-value: < 2.2e-16
##
## Call:
## lm(formula = full.model.1, data = df)
##
## Residuals:
## Min 1Q Median 3Q Max
## -1.0802 -0.2652 -0.0209 0.2359 1.6378
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 1.471e-02 3.206e-03 4.588 4.50e-06 ***
## size 5.981e-01 3.442e-03 173.794 < 2e-16 ***
## seed 1.019e-02 3.674e-03 2.773 0.00557 **
## V1 -4.749e-03 3.037e-03 -1.564 0.11792
## V2 -6.975e-01 3.039e-03 -229.558 < 2e-16 ***
## V3 -1.588e-01 3.037e-03 -52.284 < 2e-16 ***
## V4 -1.034e-01 3.037e-03 -34.052 < 2e-16 ***
## size:seed 7.308e-02 4.480e-03 16.314 < 2e-16 ***
## size:V1 -1.404e-03 3.119e-03 -0.450 0.65267
## size:V2 -8.090e-02 3.120e-03 -25.932 < 2e-16 ***
## size:V3 -1.168e-02 3.119e-03 -3.747 0.00018 ***
## size:V4 -1.787e-02 3.118e-03 -5.731 1.02e-08 ***
## seed:V1 -2.494e-03 3.119e-03 -0.800 0.42382
## seed:V2 -3.474e-03 3.120e-03 -1.114 0.26550
## seed:V3 -3.475e-03 3.119e-03 -1.114 0.26523
## seed:V4 -1.033e-03 3.118e-03 -0.331 0.74045
## V1:V2 8.530e-03 3.003e-03 2.841 0.00451 **
## V1:V3 2.488e-05 3.023e-03 0.008 0.99343
## V1:V4 -1.706e-03 3.037e-03 -0.562 0.57431
## V2:V3 -4.322e-02 3.019e-03 -14.315 < 2e-16 ***
## V2:V4 -3.339e-02 2.973e-03 -11.230 < 2e-16 ***
## V3:V4 -8.596e-03 2.997e-03 -2.868 0.00414 **
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.3715 on 14978 degrees of freedom
## Multiple R-squared: 0.8622, Adjusted R-squared: 0.862
## F-statistic: 4462 on 21 and 14978 DF, p-value: < 2.2e-16Var2n FD
##
## Call:
## lm(formula = full.model.1, data = df)
##
## Residuals:
## Min 1Q Median 3Q Max
## -3.6569 -0.2470 -0.0350 0.1687 19.0973
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.009552 0.004527 2.110 0.03489 *
## size 0.611848 0.004859 125.910 < 2e-16 ***
## seed -0.049877 0.005188 -9.615 < 2e-16 ***
## V1 -0.165255 0.004288 -38.536 < 2e-16 ***
## V2 -0.526479 0.004290 -122.714 < 2e-16 ***
## V3 -0.152415 0.004287 -35.549 < 2e-16 ***
## V4 -0.083966 0.004288 -19.581 < 2e-16 ***
## size:seed 0.049319 0.006325 7.797 6.73e-15 ***
## size:V1 -0.013583 0.004403 -3.085 0.00204 **
## size:V2 -0.071204 0.004405 -16.165 < 2e-16 ***
## size:V3 -0.014116 0.004403 -3.206 0.00135 **
## size:V4 -0.012579 0.004402 -2.858 0.00428 **
## seed:V1 0.043936 0.004403 9.978 < 2e-16 ***
## seed:V2 0.003905 0.004405 0.887 0.37533
## seed:V3 0.001930 0.004403 0.438 0.66118
## seed:V4 -0.001822 0.004402 -0.414 0.67901
## V1:V2 0.032253 0.004239 7.608 2.95e-14 ***
## V1:V3 0.025981 0.004268 6.087 1.18e-09 ***
## V1:V4 -0.019633 0.004287 -4.579 4.71e-06 ***
## V2:V3 -0.009568 0.004263 -2.244 0.02482 *
## V2:V4 -0.004597 0.004198 -1.095 0.27353
## V3:V4 -0.021985 0.004232 -5.195 2.08e-07 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.5245 on 14978 degrees of freedom
## Multiple R-squared: 0.7252, Adjusted R-squared: 0.7249
## F-statistic: 1883 on 21 and 14978 DF, p-value: < 2.2e-16
##
## Call:
## lm(formula = full.model.1, data = df)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.9872 -0.2663 -0.0509 0.1739 15.1995
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.0073116 0.0056469 1.295 0.19541
## size 0.4496813 0.0060613 74.188 < 2e-16 ***
## seed -0.0528226 0.0064708 -8.163 3.52e-16 ***
## V1 -0.1653061 0.0053490 -30.904 < 2e-16 ***
## V2 -0.5491412 0.0053515 -102.615 < 2e-16 ***
## V3 -0.1380156 0.0053479 -25.807 < 2e-16 ***
## V4 -0.0591625 0.0053488 -11.061 < 2e-16 ***
## size:seed 0.0403288 0.0078895 5.112 3.23e-07 ***
## size:V1 0.0009456 0.0054922 0.172 0.86331
## size:V2 -0.0592175 0.0054942 -10.778 < 2e-16 ***
## size:V3 -0.0084604 0.0054924 -1.540 0.12348
## size:V4 -0.0116665 0.0054909 -2.125 0.03363 *
## seed:V1 0.0463306 0.0054922 8.436 < 2e-16 ***
## seed:V2 0.0053076 0.0054942 0.966 0.33404
## seed:V3 0.0034996 0.0054924 0.637 0.52403
## seed:V4 -0.0033387 0.0054909 -0.608 0.54317
## V1:V2 0.0295239 0.0052881 5.583 2.40e-08 ***
## V1:V3 0.0352096 0.0053240 6.613 3.88e-11 ***
## V1:V4 -0.0343795 0.0053479 -6.429 1.33e-10 ***
## V2:V3 -0.0166293 0.0053174 -3.127 0.00177 **
## V2:V4 -0.0022352 0.0052364 -0.427 0.66949
## V3:V4 -0.0299385 0.0052789 -5.671 1.44e-08 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.6543 on 14978 degrees of freedom
## Multiple R-squared: 0.5725, Adjusted R-squared: 0.5719
## F-statistic: 955.2 on 21 and 14978 DF, p-value: < 2.2e-16Var2o DD
##
## Call:
## lm(formula = full.model.1, data = df)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.64792 -0.26891 0.05404 0.22697 0.81265
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 2.605e-02 2.489e-03 10.464 <2e-16 ***
## size 8.745e-01 2.672e-03 327.267 <2e-16 ***
## seed 5.475e-02 2.853e-03 19.193 <2e-16 ***
## V1 -1.305e-03 2.358e-03 -0.553 0.580
## V2 -4.024e-02 2.359e-03 -17.058 <2e-16 ***
## V3 -3.901e-01 2.358e-03 -165.466 <2e-16 ***
## V4 -2.365e-01 2.358e-03 -100.318 <2e-16 ***
## size:seed 1.161e-01 3.478e-03 33.379 <2e-16 ***
## size:V1 7.087e-06 2.421e-03 0.003 0.998
## size:V2 1.709e-03 2.422e-03 0.706 0.480
## size:V3 -5.500e-02 2.421e-03 -22.716 <2e-16 ***
## size:V4 -6.221e-02 2.421e-03 -25.701 <2e-16 ***
## seed:V1 -2.652e-04 2.421e-03 -0.110 0.913
## seed:V2 3.607e-03 2.422e-03 1.489 0.136
## seed:V3 -7.943e-04 2.421e-03 -0.328 0.743
## seed:V4 -1.269e-03 2.421e-03 -0.524 0.600
## V1:V2 3.431e-03 2.331e-03 1.472 0.141
## V1:V3 1.042e-03 2.347e-03 0.444 0.657
## V1:V4 3.709e-04 2.358e-03 0.157 0.875
## V2:V3 -2.539e-03 2.344e-03 -1.083 0.279
## V2:V4 -4.308e-04 2.308e-03 -0.187 0.852
## V3:V4 -2.456e-02 2.327e-03 -10.551 <2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.2884 on 14978 degrees of freedom
## Multiple R-squared: 0.9169, Adjusted R-squared: 0.9168
## F-statistic: 7872 on 21 and 14978 DF, p-value: < 2.2e-16
##
## Call:
## lm(formula = full.model.1, data = df)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.92171 -0.26017 0.00719 0.23676 1.37169
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.0201724 0.0028533 7.070 1.62e-12 ***
## size 0.8182892 0.0030627 267.180 < 2e-16 ***
## seed 0.0599909 0.0032696 18.348 < 2e-16 ***
## V1 0.0009132 0.0027028 0.338 0.73545
## V2 -0.0403634 0.0027040 -14.927 < 2e-16 ***
## V3 -0.4527314 0.0027022 -167.540 < 2e-16 ***
## V4 -0.2517639 0.0027026 -93.154 < 2e-16 ***
## size:seed 0.0917989 0.0039864 23.028 < 2e-16 ***
## size:V1 -0.0022883 0.0027751 -0.825 0.40962
## size:V2 0.0053234 0.0027761 1.918 0.05519 .
## size:V3 -0.0480828 0.0027752 -17.326 < 2e-16 ***
## size:V4 -0.0661479 0.0027745 -23.842 < 2e-16 ***
## seed:V1 -0.0032970 0.0027751 -1.188 0.23483
## seed:V2 0.0088427 0.0027761 3.185 0.00145 **
## seed:V3 -0.0032614 0.0027752 -1.175 0.23993
## seed:V4 -0.0073291 0.0027745 -2.642 0.00826 **
## V1:V2 0.0017700 0.0026720 0.662 0.50769
## V1:V3 0.0024471 0.0026901 0.910 0.36302
## V1:V4 -0.0023670 0.0027022 -0.876 0.38108
## V2:V3 -0.0028374 0.0026868 -1.056 0.29096
## V2:V4 -0.0022735 0.0026458 -0.859 0.39020
## V3:V4 -0.0438039 0.0026673 -16.422 < 2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.3306 on 14978 degrees of freedom
## Multiple R-squared: 0.8909, Adjusted R-squared: 0.8907
## F-statistic: 5822 on 21 and 14978 DF, p-value: < 2.2e-16Var2o FD
##
## Call:
## lm(formula = full.model.1, data = df)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.6822 -0.2761 0.0414 0.2196 6.1798
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.0231042 0.0028503 8.106 5.63e-16 ***
## size 0.8535617 0.0030595 278.992 < 2e-16 ***
## seed 0.0284813 0.0032661 8.720 < 2e-16 ***
## V1 -0.0589125 0.0026999 -21.820 < 2e-16 ***
## V2 -0.0508927 0.0027012 -18.841 < 2e-16 ***
## V3 -0.3839776 0.0026994 -142.248 < 2e-16 ***
## V4 -0.2246853 0.0026998 -83.223 < 2e-16 ***
## size:seed 0.1036888 0.0039822 26.038 < 2e-16 ***
## size:V1 -0.0007503 0.0027722 -0.271 0.786658
## size:V2 0.0010226 0.0027732 0.369 0.712321
## size:V3 -0.0522021 0.0027723 -18.830 < 2e-16 ***
## size:V4 -0.0588215 0.0027715 -21.223 < 2e-16 ***
## seed:V1 0.0182755 0.0027722 6.592 4.47e-11 ***
## seed:V2 0.0056371 0.0027732 2.033 0.042098 *
## seed:V3 0.0007225 0.0027723 0.261 0.794395
## seed:V4 -0.0015289 0.0027715 -0.552 0.581204
## V1:V2 0.0090777 0.0026691 3.401 0.000673 ***
## V1:V3 0.0099382 0.0026873 3.698 0.000218 ***
## V1:V4 -0.0108288 0.0026993 -4.012 6.06e-05 ***
## V2:V3 0.0004178 0.0026840 0.156 0.876300
## V2:V4 0.0047573 0.0026430 1.800 0.071892 .
## V3:V4 -0.0301194 0.0026645 -11.304 < 2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.3302 on 14978 degrees of freedom
## Multiple R-squared: 0.8911, Adjusted R-squared: 0.8909
## F-statistic: 5836 on 21 and 14978 DF, p-value: < 2.2e-16
##
## Call:
## lm(formula = full.model.1, data = df)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.8993 -0.2716 -0.0033 0.2265 10.6228
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.017467 0.003512 4.973 6.66e-07 ***
## size 0.785233 0.003770 208.282 < 2e-16 ***
## seed 0.037066 0.004025 9.210 < 2e-16 ***
## V1 -0.063573 0.003327 -19.108 < 2e-16 ***
## V2 -0.043986 0.003329 -13.215 < 2e-16 ***
## V3 -0.438340 0.003326 -131.779 < 2e-16 ***
## V4 -0.229977 0.003327 -69.128 < 2e-16 ***
## size:seed 0.079560 0.004907 16.213 < 2e-16 ***
## size:V1 0.003807 0.003416 1.114 0.265115
## size:V2 0.001446 0.003417 0.423 0.672287
## size:V3 -0.049665 0.003416 -14.538 < 2e-16 ***
## size:V4 -0.062563 0.003415 -18.319 < 2e-16 ***
## seed:V1 0.021395 0.003416 6.263 3.88e-10 ***
## seed:V2 0.007564 0.003417 2.213 0.026888 *
## seed:V3 -0.002231 0.003416 -0.653 0.513775
## seed:V4 -0.009726 0.003415 -2.848 0.004409 **
## V1:V2 0.006568 0.003289 1.997 0.045861 *
## V1:V3 0.012083 0.003311 3.649 0.000264 ***
## V1:V4 -0.020166 0.003326 -6.063 1.37e-09 ***
## V2:V3 0.001361 0.003307 0.411 0.680761
## V2:V4 0.007897 0.003257 2.425 0.015335 *
## V3:V4 -0.048814 0.003283 -14.867 < 2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.407 on 14978 degrees of freedom
## Multiple R-squared: 0.8346, Adjusted R-squared: 0.8344
## F-statistic: 3600 on 21 and 14978 DF, p-value: < 2.2e-16Length I and not C for Var 2 models
Var2b
##
## Call:
## lm(formula = full.model.1, data = df)
##
## Residuals:
## Min 1Q Median 3Q Max
## -1.2815 -0.1040 0.0155 0.0784 23.9920
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.006406 0.008485 0.755 0.450311
## size -0.038709 0.009108 -4.250 2.15e-05 ***
## seed -0.035347 0.009723 -3.635 0.000279 ***
## V1 -0.042922 0.008038 -5.340 9.42e-08 ***
## V2 -0.057785 0.008041 -7.186 6.99e-13 ***
## V3 -0.028207 0.008036 -3.510 0.000449 ***
## V4 0.028821 0.008037 3.586 0.000337 ***
## size:seed 0.036438 0.011855 3.074 0.002118 **
## size:V1 0.051580 0.008253 6.250 4.21e-10 ***
## size:V2 0.069408 0.008256 8.407 < 2e-16 ***
## size:V3 0.031685 0.008253 3.839 0.000124 ***
## size:V4 -0.038284 0.008251 -4.640 3.51e-06 ***
## seed:V1 0.051595 0.008253 6.252 4.17e-10 ***
## seed:V2 0.070212 0.008256 8.505 < 2e-16 ***
## seed:V3 0.032368 0.008253 3.922 8.82e-05 ***
## seed:V4 -0.040215 0.008251 -4.874 1.10e-06 ***
## V1:V2 0.052892 0.007946 6.656 2.90e-11 ***
## V1:V3 0.029522 0.008000 3.690 0.000225 ***
## V1:V4 -0.015340 0.008036 -1.909 0.056295 .
## V2:V3 0.031619 0.007990 3.957 7.62e-05 ***
## V2:V4 -0.036781 0.007868 -4.675 2.97e-06 ***
## V3:V4 -0.026664 0.007932 -3.361 0.000777 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.9831 on 14978 degrees of freedom
## Multiple R-squared: 0.03477, Adjusted R-squared: 0.03342
## F-statistic: 25.7 on 21 and 14978 DF, p-value: < 2.2e-16
##
## Call:
## lm(formula = full.model.1, data = df)
##
## Residuals:
## Min 1Q Median 3Q Max
## -2.2215 -0.3801 0.0192 0.2465 7.8683
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.024478 0.006313 3.878 0.000106 ***
## size -0.267113 0.006776 -39.421 < 2e-16 ***
## seed -0.310234 0.007234 -42.888 < 2e-16 ***
## V1 -0.271191 0.005980 -45.353 < 2e-16 ***
## V2 -0.223520 0.005982 -37.363 < 2e-16 ***
## V3 -0.063553 0.005978 -10.630 < 2e-16 ***
## V4 0.034944 0.005979 5.844 5.20e-09 ***
## size:seed 0.117958 0.008820 13.375 < 2e-16 ***
## size:V1 0.197536 0.006140 32.174 < 2e-16 ***
## size:V2 0.167890 0.006142 27.335 < 2e-16 ***
## size:V3 0.047594 0.006140 7.752 9.65e-15 ***
## size:V4 -0.024199 0.006138 -3.942 8.10e-05 ***
## seed:V1 0.256282 0.006140 41.742 < 2e-16 ***
## seed:V2 0.204824 0.006142 33.349 < 2e-16 ***
## seed:V3 0.056305 0.006140 9.170 < 2e-16 ***
## seed:V4 -0.028917 0.006138 -4.711 2.49e-06 ***
## V1:V2 0.083143 0.005911 14.065 < 2e-16 ***
## V1:V3 0.038400 0.005952 6.452 1.14e-10 ***
## V1:V4 -0.010799 0.005978 -1.806 0.070890 .
## V2:V3 0.025003 0.005944 4.206 2.61e-05 ***
## V2:V4 -0.021236 0.005854 -3.628 0.000287 ***
## V3:V4 -0.007430 0.005901 -1.259 0.208016
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.7314 on 14978 degrees of freedom
## Multiple R-squared: 0.4658, Adjusted R-squared: 0.465
## F-statistic: 621.9 on 21 and 14978 DF, p-value: < 2.2e-16Var2n
##
## Call:
## lm(formula = full.model.1, data = df)
##
## Residuals:
## Min 1Q Median 3Q Max
## -1.2815 -0.1040 0.0155 0.0784 23.9920
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.006406 0.008485 0.755 0.450311
## size -0.038709 0.009108 -4.250 2.15e-05 ***
## seed -0.035347 0.009723 -3.635 0.000279 ***
## V1 -0.042922 0.008038 -5.340 9.42e-08 ***
## V2 -0.057785 0.008041 -7.186 6.99e-13 ***
## V3 -0.028207 0.008036 -3.510 0.000449 ***
## V4 0.028821 0.008037 3.586 0.000337 ***
## size:seed 0.036438 0.011855 3.074 0.002118 **
## size:V1 0.051580 0.008253 6.250 4.21e-10 ***
## size:V2 0.069408 0.008256 8.407 < 2e-16 ***
## size:V3 0.031685 0.008253 3.839 0.000124 ***
## size:V4 -0.038284 0.008251 -4.640 3.51e-06 ***
## seed:V1 0.051595 0.008253 6.252 4.17e-10 ***
## seed:V2 0.070212 0.008256 8.505 < 2e-16 ***
## seed:V3 0.032368 0.008253 3.922 8.82e-05 ***
## seed:V4 -0.040215 0.008251 -4.874 1.10e-06 ***
## V1:V2 0.052892 0.007946 6.656 2.90e-11 ***
## V1:V3 0.029522 0.008000 3.690 0.000225 ***
## V1:V4 -0.015340 0.008036 -1.909 0.056295 .
## V2:V3 0.031619 0.007990 3.957 7.62e-05 ***
## V2:V4 -0.036781 0.007868 -4.675 2.97e-06 ***
## V3:V4 -0.026664 0.007932 -3.361 0.000777 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.9831 on 14978 degrees of freedom
## Multiple R-squared: 0.03477, Adjusted R-squared: 0.03342
## F-statistic: 25.7 on 21 and 14978 DF, p-value: < 2.2e-16