Influence Diagnostics for MARS Models
influence_diagnostics.RdCompute case-level and grouped influence summaries using studentized residuals, leverage, and Cook's distance.
Value
A list with row-level influence diagnostics, grouped summaries, thresholds, and top influential rows.
Examples
# \donttest{
fit <- mars(
data = teacher_expectancy,
studyID = "study",
effectID = NULL,
sample_size = NULL,
formula = yi ~ 1,
variance = "vi",
varcov_type = "univariate",
structure = "univariate"
)
influence_diagnostics(fit, top_n = 5)
#> $structure
#> [1] "univariate"
#>
#> $influence
#> index fitted raw studentized leverage cooks_distance
#> 1 1 0.08370128 -0.05370128 -0.30137140 0.07748085 0.0076282176
#> 2 2 0.08370128 0.03629872 0.18682016 0.06597902 0.0024654527
#> 3 3 0.08370128 -0.22370128 -1.06582956 0.05708170 0.0687698934
#> 4 4 0.08370128 1.09629872 2.78234449 0.01688697 0.1329750145
#> 5 5 0.08370128 0.17629872 0.45167461 0.01720288 0.0035709903
#> 6 6 0.08370128 -0.14370128 -0.87858944 0.09064966 0.0769496905
#> 7 7 0.08370128 -0.10370128 -0.63402950 0.09064966 0.0400731836
#> 8 8 0.08370128 -0.40370128 -1.58893713 0.03967313 0.1043015704
#> 9 9 0.08370128 0.18629872 0.89787390 0.05833025 0.0499373993
#> 10 10 0.08370128 0.71629872 2.54603515 0.03259370 0.2184004330
#> 11 11 0.08370128 0.45629872 1.39265980 0.02423925 0.0481799030
#> 12 12 0.08370128 0.09629872 0.37526445 0.03892041 0.0057028630
#> 13 13 0.08370128 -0.10370128 -0.32850505 0.02606338 0.0028879136
#> 14 14 0.08370128 0.14629872 0.46205632 0.02591144 0.0056791442
#> 15 15 0.08370128 -0.26370128 -1.29521460 0.06044566 0.1079261528
#> 16 16 0.08370128 -0.14370128 -0.68466785 0.05708170 0.0283780594
#> 17 17 0.08370128 0.21629872 1.14877819 0.06996008 0.0992707047
#> 18 18 0.08370128 -0.01370128 -0.08673857 0.09655766 0.0008041015
#> 19 19 0.08370128 -0.15370128 -0.71314407 0.05429260 0.0291970100
#> influence_score flagged cluster
#> 1 0.08733967 FALSE 1
#> 2 0.04965333 FALSE 2
#> 3 0.26224014 FALSE 3
#> 4 0.36465739 TRUE 4
#> 5 0.05975776 FALSE 5
#> 6 0.27739807 FALSE 6
#> 7 0.20018288 FALSE 7
#> 8 0.32295754 FALSE 8
#> 9 0.22346677 FALSE 9
#> 10 0.46733332 TRUE 10
#> 11 0.21949921 FALSE 11
#> 12 0.07551730 FALSE 12
#> 13 0.05373931 FALSE 13
#> 14 0.07536010 FALSE 14
#> 15 0.32852116 FALSE 15
#> 16 0.16845789 FALSE 16
#> 17 0.31507254 FALSE 17
#> 18 0.02835668 FALSE 18
#> 19 0.17087133 FALSE 19
#>
#> $by_cluster
#> study n max_abs_studentized max_leverage cook_sum cook_max n_flagged
#> 1 1 1 0.30137140 0.07748085 0.0076282176 0.0076282176 0
#> 2 2 1 0.18682016 0.06597902 0.0024654527 0.0024654527 0
#> 3 3 1 1.06582956 0.05708170 0.0687698934 0.0687698934 0
#> 4 4 1 2.78234449 0.01688697 0.1329750145 0.1329750145 1
#> 5 5 1 0.45167461 0.01720288 0.0035709903 0.0035709903 0
#> 6 6 1 0.87858944 0.09064966 0.0769496905 0.0769496905 0
#> 7 7 1 0.63402950 0.09064966 0.0400731836 0.0400731836 0
#> 8 8 1 1.58893713 0.03967313 0.1043015704 0.1043015704 0
#> 9 9 1 0.89787390 0.05833025 0.0499373993 0.0499373993 0
#> 10 10 1 2.54603515 0.03259370 0.2184004330 0.2184004330 1
#> 11 11 1 1.39265980 0.02423925 0.0481799030 0.0481799030 0
#> 12 12 1 0.37526445 0.03892041 0.0057028630 0.0057028630 0
#> 13 13 1 0.32850505 0.02606338 0.0028879136 0.0028879136 0
#> 14 14 1 0.46205632 0.02591144 0.0056791442 0.0056791442 0
#> 15 15 1 1.29521460 0.06044566 0.1079261528 0.1079261528 0
#> 16 16 1 0.68466785 0.05708170 0.0283780594 0.0283780594 0
#> 17 17 1 1.14877819 0.06996008 0.0992707047 0.0992707047 0
#> 18 18 1 0.08673857 0.09655766 0.0008041015 0.0008041015 0
#> 19 19 1 0.71314407 0.05429260 0.0291970100 0.0291970100 0
#>
#> $by_outcome
#> NULL
#>
#> $thresholds
#> n p cooks_distance leverage abs_studentized
#> 1 19 1 0.2105263 0.1052632 2
#>
#> $top
#> index fitted raw studentized leverage cooks_distance
#> 10 10 0.08370128 0.7162987 2.546035 0.03259370 0.2184004
#> 4 4 0.08370128 1.0962987 2.782344 0.01688697 0.1329750
#> 15 15 0.08370128 -0.2637013 -1.295215 0.06044566 0.1079262
#> 8 8 0.08370128 -0.4037013 -1.588937 0.03967313 0.1043016
#> 17 17 0.08370128 0.2162987 1.148778 0.06996008 0.0992707
#> influence_score flagged cluster
#> 10 0.4673333 TRUE 10
#> 4 0.3646574 TRUE 4
#> 15 0.3285212 FALSE 15
#> 8 0.3229575 FALSE 8
#> 17 0.3150725 FALSE 17
#>
#> attr(,"class")
#> [1] "mars_influence_diagnostics"
# }