ensayo | trat | hibrido | rep | l_tot | l_ch | l_med | l_gde | e_inf | e_med | e_sup | nlb_score | date | inoc | ddinoc | score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
1 - 2023 | DDD | MR | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 2023-03-08 | 2023-01-26 | 41 days | FALSE |
1 - 2023 | DDD | MR | 2 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 2023-03-08 | 2023-01-26 | 41 days | FALSE |
1 - 2023 | DDD | MR | 3 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 2023-03-08 | 2023-01-26 | 41 days | FALSE |
1 - 2023 | DDD | MR | 4 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 2023-03-08 | 2023-01-26 | 41 days | FALSE |
1 - 2023 | DDD | MR | 5 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 2023-03-08 | 2023-01-26 | 41 days | FALSE |
1 - 2023 | DDD | MR | 6 | 2 | 0 | 0 | 2 | 2 | 0 | 0 | 0 | 2023-03-08 | 2023-01-26 | 41 days | FALSE |
Análisis
Muestra de primeras lineas del dataset
Tamaño de lesión
Mosaico de datos
datos originales: Primer eval sin el Bco, ultima todos 0
- Calculo de AUC
2023
Analysis of Deviance Table (Type III tests)
Response: auc_manchas
LR Chisq Df Pr(>Chisq)
trat 80.794 3 < 2.2e-16 ***
lesion_size 27.524 2 1.055e-06 ***
hibrido 4.217 1 0.04001 *
rep 1.070 1 0.30097
trat:lesion_size 47.012 6 1.861e-08 ***
trat:hibrido 47.423 3 2.826e-10 ***
lesion_size:hibrido 24.869 2 3.979e-06 ***
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1trat:lesion_size
lesion_size = ch, hibrido = MR:
trat response SE df asymp.LCL asymp.UCL .group
JJJ 41.966 14.271 Inf 21.550 81.724 1
TTS 6.172 2.215 Inf 3.055 12.469 2
BLCO 1.609 0.667 Inf 0.714 3.627 3
DDD 0.572 0.278 Inf 0.221 1.484 3
lesion_size = med, hibrido = MR:
trat response SE df asymp.LCL asymp.UCL .group
JJJ 17.054 5.839 Inf 8.717 33.365 1
BLCO 7.410 2.664 Inf 3.662 14.991 12
TTS 4.558 1.658 Inf 2.235 9.297 2
DDD 0.462 0.230 Inf 0.174 1.227 3
lesion_size = gde, hibrido = MR:
trat response SE df asymp.LCL asymp.UCL .group
JJJ 12.993 4.533 Inf 6.558 25.743 1
DDD 0.496 0.246 Inf 0.187 1.313 2
BLCO 0.495 0.245 Inf 0.188 1.306 2
TTS 0.302 0.157 Inf 0.109 0.836 2
lesion_size = ch, hibrido = S:
trat response SE df asymp.LCL asymp.UCL .group
TTS 92.794 31.830 Inf 47.375 181.759 1
JJJ 77.424 26.240 Inf 39.847 150.439 1
DDD 1.964 0.802 Inf 0.882 4.373 2
BLCO 0.590 0.281 Inf 0.232 1.499 2
lesion_size = med, hibrido = S:
trat response SE df asymp.LCL asymp.UCL .group
TTS 292.301 99.899 Inf 149.596 571.139 1
JJJ 134.207 45.255 Inf 69.302 259.899 1
BLCO 11.587 4.106 Inf 5.785 23.206 2
DDD 6.762 2.508 Inf 3.268 13.990 2
lesion_size = gde, hibrido = S:
trat response SE df asymp.LCL asymp.UCL .group
JJJ 251.303 85.711 Inf 128.790 490.359 1
TTS 47.663 17.007 Inf 23.684 95.919 2
DDD 17.831 6.429 Inf 8.796 36.149 2
BLCO 1.904 0.780 Inf 0.853 4.249 3
Confidence level used: 0.95
Intervals are back-transformed from the log scale
P value adjustment: tukey method for comparing a family of 4 estimates
Tests are performed on the log scale
significance level used: alpha = 0.05
NOTE: If two or more means share the same grouping symbol,
then we cannot show them to be different.
But we also did not show them to be the same. 2024
Analysis of Deviance Table (Type III tests)
Response: auc_manchas
LR Chisq Df Pr(>Chisq)
trat 24.106 2 5.828e-06 ***
lesion_size 117.052 2 < 2.2e-16 ***
hibrido 32.902 1 9.694e-09 ***
rep 3.650 1 0.05606 .
trat:lesion_size 5.904 4 0.20646
trat:hibrido 20.772 2 3.087e-05 ***
lesion_size:hibrido 3.253 2 0.19660
trat:lesion_size:hibrido 7.788 4 0.09968 .
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1comparaciones multiples
lesion_size = ch, hibrido = MR:
trat response SE df asymp.LCL asymp.UCL .group
BLCO 17.42 4.534 Inf 10.4632 29 1
TTS 10.08 2.689 Inf 5.9721 17 1
DDD 2.20 0.700 Inf 1.1831 4 2
lesion_size = med, hibrido = MR:
trat response SE df asymp.LCL asymp.UCL .group
TTS 0.73 0.307 Inf 0.3204 2 1
BLCO 0.24 0.153 Inf 0.0687 1 1
DDD 0.00 0.000 Inf 0.0000 Inf 1
lesion_size = gde, hibrido = MR:
trat response SE df asymp.LCL asymp.UCL .group
DDD 0.00 0.000 Inf 0.0000 Inf 1
TTS 0.00 0.000 Inf 0.0000 Inf 1
BLCO 0.00 0.000 Inf 0.0000 Inf 1
lesion_size = ch, hibrido = S:
trat response SE df asymp.LCL asymp.UCL .group
DDD 241.12 60.629 Inf 147.3011 395 1
TTS 178.86 45.016 Inf 109.2105 293 1
BLCO 164.77 41.485 Inf 100.5967 270 1
lesion_size = med, hibrido = S:
trat response SE df asymp.LCL asymp.UCL .group
DDD 116.00 29.261 Inf 70.7523 190 1
TTS 16.76 4.368 Inf 10.0583 28 2
BLCO 8.50 2.292 Inf 5.0086 14 2
lesion_size = gde, hibrido = S:
trat response SE df asymp.LCL asymp.UCL .group
DDD 5.83 1.620 Inf 3.3826 10 1
BLCO 0.00 0.000 Inf 0.0000 Inf 1
TTS 0.00 0.000 Inf 0.0000 Inf 1
Confidence level used: 0.95
Intervals are back-transformed from the log scale
P value adjustment: tukey method for comparing a family of 3 estimates
Tests are performed on the log scale
significance level used: alpha = 0.05
NOTE: If two or more means share the same grouping symbol,
then we cannot show them to be different.
But we also did not show them to be the same. Posición en el canopeo
2023
Analysis of Deviance Table (Type III tests)
Response: auc_manchas
LR Chisq Df Pr(>Chisq)
trat 42.897 3 2.588e-09 ***
lesion_pos 20.755 2 3.113e-05 ***
hibrido 0.173 1 0.67777
rep 1.947 1 0.16293
trat:lesion_pos 6.007 6 0.42238
trat:hibrido 7.831 3 0.04963 *
lesion_pos:hibrido 5.246 2 0.07257 .
trat:lesion_pos:hibrido 1.112 6 0.98100
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1trat:lesion_size:hibrido
lesion_pos = inf, hibrido = MR:
trat response SE df asymp.LCL asymp.UCL .group
JJJ 91.368 38.922 Inf 39.645 211 1
TTS 8.236 3.641 Inf 3.463 20 2
BLCO 3.934 1.812 Inf 1.595 10 2
DDD 2.913 1.377 Inf 1.154 7 2
lesion_pos = med, hibrido = MR:
trat response SE df asymp.LCL asymp.UCL .group
JJJ 17.983 7.779 Inf 7.703 42 1
TTS 7.614 3.377 Inf 3.193 18 1
BLCO 5.274 2.382 Inf 2.176 13 12
DDD 0.859 0.490 Inf 0.280 3 2
lesion_pos = sup, hibrido = MR:
trat response SE df asymp.LCL asymp.UCL .group
BLCO 0.000 0.000 Inf 0.000 Inf 1
DDD 0.000 0.000 Inf 0.000 Inf 1
JJJ 0.000 0.000 Inf 0.000 Inf 1
TTS 0.000 0.000 Inf 0.000 Inf 1
lesion_pos = inf, hibrido = S:
trat response SE df asymp.LCL asymp.UCL .group
JJJ 364.728 154.926 Inf 158.637 839 1
TTS 116.003 49.376 Inf 50.369 267 12
DDD 26.216 11.273 Inf 11.286 61 2
BLCO 5.143 2.326 Inf 2.119 12 3
lesion_pos = med, hibrido = S:
trat response SE df asymp.LCL asymp.UCL .group
TTS 345.326 146.692 Inf 150.191 794 1
JJJ 212.636 90.384 Inf 92.432 489 1
DDD 9.062 3.992 Inf 3.822 21 2
BLCO 8.438 3.727 Inf 3.551 20 2
lesion_pos = sup, hibrido = S:
trat response SE df asymp.LCL asymp.UCL .group
TTS 52.602 22.419 Inf 22.815 121 1
JJJ 18.240 7.815 Inf 7.876 42 1
BLCO 0.966 0.535 Inf 0.326 3 2
DDD 0.000 0.000 Inf 0.000 Inf 12
Confidence level used: 0.95
Intervals are back-transformed from the log scale
P value adjustment: tukey method for comparing a family of 4 estimates
Tests are performed on the log scale
significance level used: alpha = 0.05
NOTE: If two or more means share the same grouping symbol,
then we cannot show them to be different.
But we also did not show them to be the same. 2024
Analysis of Deviance Table (Type III tests)
Response: auc_manchas
LR Chisq Df Pr(>Chisq)
trat 42.897 3 2.588e-09 ***
lesion_pos 20.755 2 3.113e-05 ***
hibrido 0.173 1 0.67777
rep 1.947 1 0.16293
trat:lesion_pos 6.007 6 0.42238
trat:hibrido 7.831 3 0.04963 *
lesion_pos:hibrido 5.246 2 0.07257 .
trat:lesion_pos:hibrido 1.112 6 0.98100
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1trat:lesion_size:hibrido
lesion_pos = inf, hibrido = MR:
trat response SE df asymp.LCL asymp.UCL .group
BLCO 12.41 3.101 Inf 7.601 20 1
TTS 5.74 1.523 Inf 3.416 10 1
DDD 2.22 0.678 Inf 1.220 4 2
lesion_pos = med, hibrido = MR:
trat response SE df asymp.LCL asymp.UCL .group
TTS 3.90 1.084 Inf 2.264 7 1
BLCO 3.77 1.052 Inf 2.182 7 1
DDD 0.00 0.000 Inf 0.000 Inf 1
lesion_pos = sup, hibrido = MR:
trat response SE df asymp.LCL asymp.UCL .group
BLCO 1.47 0.492 Inf 0.760 3 1
TTS 1.23 0.433 Inf 0.619 2 1
DDD 0.00 0.000 Inf 0.000 Inf 1
lesion_pos = inf, hibrido = S:
trat response SE df asymp.LCL asymp.UCL .group
DDD 203.90 48.318 Inf 128.151 324 1
BLCO 98.77 23.496 Inf 61.963 157 12
TTS 81.80 19.489 Inf 51.281 130 2
lesion_pos = med, hibrido = S:
trat response SE df asymp.LCL asymp.UCL .group
DDD 132.54 31.469 Inf 83.227 211 1
TTS 70.73 16.874 Inf 44.308 113 1
BLCO 61.57 14.712 Inf 38.543 98 1
lesion_pos = sup, hibrido = S:
trat response SE df asymp.LCL asymp.UCL .group
TTS 41.93 10.075 Inf 26.181 67 1
DDD 23.01 5.608 Inf 14.275 37 12
BLCO 12.81 3.197 Inf 7.856 21 2
Confidence level used: 0.95
Intervals are back-transformed from the log scale
P value adjustment: tukey method for comparing a family of 3 estimates
Tests are performed on the log scale
significance level used: alpha = 0.05
NOTE: If two or more means share the same grouping symbol,
then we cannot show them to be different.
But we also did not show them to be the same. Score
2023
trat = DDD:
model term df1 df2 F.ratio Chisq p.value
hibrido 1 Inf 0.092 0.092 0.7620
trat = JJJ:
model term df1 df2 F.ratio Chisq p.value
hibrido 1 Inf 7.913 7.913 0.0049
trat = TTS:
model term df1 df2 F.ratio Chisq p.value
hibrido 1 Inf 18.167 18.167 <.0001hibrido = MR:
model term df1 df2 F.ratio Chisq p.value
trat 2 Inf 1.048 2.096 0.3507
hibrido = S:
model term df1 df2 F.ratio Chisq p.value
trat 2 Inf 8.261 16.522 0.0003hibrido = MR:
trat emmean SE df asymp.LCL asymp.UCL .group
JJJ -2.742 0.861 Inf -4.429 -1.06 1
DDD -3.948 0.922 Inf -5.756 -2.14 1
TTS -4.134 0.965 Inf -6.025 -2.24 1
hibrido = S:
trat emmean SE df asymp.LCL asymp.UCL .group
TTS 1.848 0.803 Inf 0.274 3.42 1
JJJ 0.455 0.732 Inf -0.979 1.89 1
DDD -3.650 0.937 Inf -5.487 -1.81 2
Confidence level used: 0.95
P value adjustment: tukey method for comparing a family of 3 estimates
significance level used: alpha = 0.05
NOTE: If two or more means share the same grouping symbol,
then we cannot show them to be different.
But we also did not show them to be the same. 2024
hibrido = MR:
model term df1 df2 F.ratio Chisq p.value
trat 1 Inf 0.000 0.00 0.9984
hibrido = S:
model term df1 df2 F.ratio Chisq p.value
trat 1 Inf 0.920 0.92 0.3376hibrido = MR:
trat emmean SE df asymp.LCL asymp.UCL .group
DDD -5.396 1.393 Inf -8.126 -2.67 1
TTS -5.399 1.394 Inf -8.131 -2.67 1
hibrido = S:
trat emmean SE df asymp.LCL asymp.UCL .group
TTS 0.992 0.633 Inf -0.247 2.23 1
DDD 0.255 0.564 Inf -0.850 1.36 1
Confidence level used: 0.95
significance level used: alpha = 0.05
NOTE: If two or more means share the same grouping symbol,
then we cannot show them to be different.
But we also did not show them to be the same.