select significant residuals only

[Tina Zorgt]

Hello,

The residuals function returns a very large matrix even when I use supress (giving na values for anything not suppressed)

 residuals(model, type = "Q3",suppress = .20)

How can I get on output with only those residuals  that meet my criteria? The current matrix is too large to oversee it all.

cheers, T

[Tina Zorgt]

I have a work around but I'd hoped on a more friendly solution

residuals_Yen <- residuals(model, type = "Q3")

findCorrelation(residuals_Yen, cutoff = 0.20, names=TRUE, verbose = TRUE) # flagged colnames included, package Caret

rownames(residuals_Yen) # check rownames

Then I can look the correlations up by han by combinding all info

Op vrijdag 19 juni 2020 12:01:31 UTC+2 schreef Tina Zorgt:

[Tina Zorgt]

A bit quicker:

LI <- mirt(data, model = 1, itemtype = "graded")

residuals_Yen <- residuals(LI, type = "Q3")

# library(caret)

# flag significant correlations by a cutoff

findCorrelation(residuals_Yen, cutoff = 0.20, names=TRUE, verbose = TRUE) # flagged colnames included; names = FALSE shows positions only

# e.g.output = Compare row 2 and column  3 with corr  0.214 Means:  0.067 vs 0.068 so flagging column 3 

# than the 2nd and 3th variable have a flagged correlation of 0.214

# look up the 2nd and 3th variable with rownames to identify the corresponding variable names

rownames(residuals_Yen)[c(2,3)] # example with correlated variables 2 and 3

Op maandag 22 juni 2020 10:57:14 UTC+2 schreef Tina Zorgt:

[Phil Chalmers]

Do you still need help with this task, or have you worked out a reasonable coding solution?

Phil

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[Guido]

Phil,

I think I have a reasonable coding solution now.

Thx!

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