
Detect outliers for small-plot trial analysis
outlier_summary.RdProvides a summary of the outliers present in the asreml model. Gives context to the outliers by showing the responses for the same factor combinations as the outliers
Value
NULL
Prints:
The number of outliers.
A table of the outliers, if any.
A table of relevant context to some factor combinations, if there are outliers.
Examples
library(asreml)
model <- asreml(
fixed = weight ~ littersize + Dose + Sex + Dose:Sex,
random = ~idv(Dam),
residual = ~units,
data = rats
)
outlier_summary(model)
#> ! No aom = T, updating model
#>
#> ── Outliers detected: 2 ────────────────────────────────────────────────────────
#> Dose Sex littersize Dam weight units combined_trt residuals
#> 56 C F 13 5 5.02 56 13_C_F -4.020632
#> 66 C F 9 6 3.68 66 9_C_F -7.877422
#>
#> ── Data table ──
#>
#> Dose Sex littersize Dam weight units combined_trt residuals
#> 56 C F 13 5 5.02 56 13_C_F -4.0206317
#> 53 C F 13 5 7.16 53 13_C_F 1.4705108
#> 55 C F 13 5 7.14 55 13_C_F 1.4191918
#> 57 C F 13 5 6.04 57 13_C_F -1.4033581
#> 54 C F 13 5 7.09 54 13_C_F 1.2908940
#> 129 C F 13 10 5.92 129 13_C_F -1.0564320
#> 126 C F 13 10 6.67 126 13_C_F 0.8629802
#> 128 C F 13 10 6.53 128 13_C_F 0.5046899
#> 130 C F 13 10 6.52 130 13_C_F 0.4790978
#> 125 C F 13 10 6.44 125 13_C_F 0.2743605
#> 131 C F 13 10 6.44 131 13_C_F 0.2743605
#> 127 C F 13 10 6.43 127 13_C_F 0.2487683
#> 66 C F 9 6 3.68 66 9_C_F -7.8774217
#> 64 C F 9 6 7.26 64 9_C_F 1.4570300
#> 65 C F 9 6 6.58 65 9_C_F -0.3159943