ind_excl_step {ionr} | R Documentation |
One step in indicator exclusion procedure
Description
See ind_excl
for details.
Usage
ind_excl_step(indicators, outcome, indicatornames = 1:ncol(indicators),
exclude = vector(), coruse = "everything", round = F)
Arguments
indicators |
Set of numeric indicators (items) in a matrix. |
outcome |
A numeric outcome vector. Indicators and outcome can be simulated with
|
indicatornames |
An array of strings for labelling the outcome. Default to numbers from 1 to n of indicators |
exclude |
Exclude an item excluded at previous step, e.g., as decided by |
coruse |
argument for function cor(). Defaults to 'everything', as simulations have no missing data. |
round |
Allows rounding of values in returned matrix. |
Value
Provides the results of a single step in indicator exclusion procedure. See example for details
Examples
## Create a scale-outcome set that violates ION. Only 2 indicators out of 8 relate to
## the outcome, the others just relate to the 2 indicators
set.seed(466)
a<-scale_sim(n=2500, to_n=2, tn_n=6)
res=ind_excl_step(a[[1]],a[[2]])
print(res)
# note that the p-values for upper items (7 & 8 ) are much smaller than for the rest
#row number indicator number
#r.test.t t value of the r.test.
#t.test.p p value of the r.test.
#cor_excl correlation between outcome and sum-score when an item is excluded.
#cor_all correlation between outcome and sum-score when all items are included
# (i.e., full scale).
#cor.excl_all correlation between two sum-scores.
[Package ionr version 0.3.0 Index]