Description Usage Format Source References Examples

The data (Keselman et al., 2003) represent the reaction times in milliseconds of children with attention-deficit hyperactivity (ADHD) and normal children when they are presented four kinds of inputs: a target alone or an arrow stimuli incongruent, congruent and neutral to the target. According to the authors, the dataset was artificially generated from the summary measures given in the original study by Jonkman et al. (1999), in groups of 20 and 10 children to create an unbalanced design.

1 |

A data frame with 30 rows and 5 variables:

- Group
whether the child has ADHD or is healty (normal)

.

- TargetAlone
Reaction time (milliseconds) to a target alone.

- Congruent
Reaction time (milliseconds) to a congruent stimulus.

- Neutral
Reaction time (milliseconds) to a neutral stimulus.

- Incongruent
Reaction time (milliseconds) to an incongruent stimulus.

H. J. Keselman, R. R. Wilcox, and L. M. Lix. A generally robust approach to hypothesis testing in independent and correlated groups designs. Psychophyisiology, 40:586-596, 2003. (Data displayed in page 593).

L. Jonkman, C. Kemner, M. Verbaten, H. van Engeland, J. Kenemans, G. Camfferman, J. Buitelaar, and H. Koelega. Perceptual and response interference in children with attention-deficit hyperactivity disorder, and the effects of methylphenidate. 36(4):419-429, 1999.

1 2 3 4 5 6 7 8 9 10 11 | ```
# Assuming a multivariate response
omnibus_LSM_multi <- welchADF.test(adhdData, response = c("TargetAlone", "Congruent",
"Neutral", "Incongruent"), between.s = "Group", within.s = "multivariate", contrast = "omnibus")
# The same using the S3 method for class formula
omnibus_LSM_multi_form <- welchADF.test(cbind(TargetAlone, Congruent, Neutral, Incongruent)
~ Group, data = adhdData)
# Pairwise comparisons of the implicit within-subjects effect present in the multivariate response
pairwise_LSM_multi <- update(omnibus_LSM_multi, contrast = "all.pairwise", effect = "multivariate")
summary(omnibus_LSM_multi)
summary(pairwise_LSM_multi)
``` |

```
Call:
welchADF.test(formula = adhdData, response = c("TargetAlone",
"Congruent", "Neutral", "Incongruent"), between.s = "Group",
within.s = "multivariate", contrast = "omnibus")
WJ statistic Numerator DF Denominator DF Pr(>WJ)
Group 0.2249 1 24.84 0.639482
multivariate 5.6591 3 21.02 0.005282 **
Group : multivariate 0.5750 3 21.02 0.637759
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Call:
welchADF.test(formula = adhdData, response = c("TargetAlone",
"Congruent", "Neutral", "Incongruent"), between.s = "Group",
within.s = "multivariate", contrast = "all.pairwise", effect = "multivariate")
WJ statistic Numerator DF Denominator DF adj.pval
Congruent:TargetAlone 3.8254 1 20.52 0.256928
Incongruent:TargetAlone 14.2331 1 27.90 0.003868 **
Neutral:TargetAlone 0.6215 1 25.19 0.459884
Congruent:Neutral 1.6498 1 16.87 0.459884
Incongruent:Neutral 15.6572 1 27.99 0.002830 **
Congruent:Incongruent 0.5703 1 18.07 0.459884
---
Signif. codes (Hochberg p-values): 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
```

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