Hello all:
I am completing an aligned rank transformation as follows, using the 'ARTool' package:
model = art(Proportioncorrect~Trialtype+Method+Trialtype:Method,data=Cummulativecounting)
I have two factors (independent variables), being Method and Trial type
My dependent variable is the proportion of correct trials (Proportioncorrect)
Anova(model)
Analysis of Variance of Aligned Rank Transformed Data
Table Type: Anova Table (Type III tests)
Model: No Repeated Measures (lm)
Response: art(Proportioncorrect)
Df Df.res F value Pr(>F)
1 Trialtype 1 26 41.1793 8.4687e-07 ***
2 Method 1 26 8.6554 0.0067722 **
3 Trialtype:Method 1 26 5.3010 0.0295733 *
---
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
I want to test for an interaction between these two factors
I have tried the following command, which I know is testing contrasts between contrasts:
testInteractions(artlm(model, "Trialtype:Method"), pairwise=c("Trialtype", "Method"),adjust="bonferroni")
F Test:
P-value adjustment method: bonferroni
Value Df Sum of Sq F Pr(>F)
Beaconed-Probe : Counting-Not-counting 17.667 1 374.53 5.301 0.02957 *
Residuals 26 1837.00
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ‘ ’ 1
However, I want to compare the results for Trial Type across Method.
However, when I try the formula below using the 'phia' package:
(testInteractions(model, pairwise="Method" ,across="Trialtype",adjust="bonferroni")
I get this error: Error in terms.default(model) : no terms component nor attribute
Would anybody be kind enough to give me a helping hand?
Here is my raw data:
structure(list(ID = c("P_200214123342", "P_200224092247", "P_200219163622",
"P_200220130332", "P_200219091823", "P_200225184226", "P_200219123120",
"P_200219175102", "P_200214103155", "P_200219111605", "P_200217101213",
"P_200219102411", "P_200221101028", "P_200220145557", "P_200225171612",
"P_200224092247", "P_200219163622", "P_200220130332", "P_200214123342",
"P_200219091823", "P_200225184226", "P_200219123120", "P_200219175102",
"P_200214103155", "P_200219111605", "P_200217101213", "P_200219102411",
"P_200221101028", "P_200220145557", "P_200225171612"), Trialtype = c("Beaconed",
"Beaconed", "Beaconed", "Beaconed", "Beaconed", "Beaconed", "Beaconed",
"Beaconed", "Beaconed", "Beaconed", "Beaconed", "Beaconed", "Beaconed",
"Beaconed", "Beaconed", "Probe", "Probe", "Probe", "Probe", "Probe",
"Probe", "Probe", "Probe", "Probe", "Probe", "Probe", "Probe",
"Probe", "Probe", "Probe"), Proportioncorrect = c(66.666667,
97.333333, 66.666667, 88, 54.666667, 92, 97.333333, 90.666667,
96, 90.666667, 96, 90.666667, 96, 96, 93.333333, 29.333333, 16,
14.666667, 6.666667, 8, 16, 13.333333, 21.333333, 16, 26.666667,
33.333333, 24, 21.333333, 62.666667, 93.333333), Method = c("Counting",
"Counting", "Counting", "Counting", "Counting", "Counting", "Counting",
"Not-counting", "Counting", "Counting", "Counting", "Counting",
"Counting", "Not-counting", "Not-counting", "Counting", "Counting",
"Counting", "Counting", "Counting", "Counting", "Counting", "Not-counting",
"Counting", "Counting", "Counting", "Counting", "Counting", "Not-counting",
"Not-counting")), row.names = c(NA, -30L), class = "data.frame")