Function estimating reliability with intra-class correlation for the complete or for the range-restricted sample.
ICCrestricted(
Data,
case,
var,
rank = NULL,
dir = "top",
sel = 1,
nsim = 100,
ci = 0.95,
seed = NULL
)
A data.frame
with the following columns:
number of ratees selected/subsetted.
proportion of ratees selected.
direction of range-restriction. NA
if range is
effectively not restricted (100% used).
variance due to ratee, "true variance", between-group variance.
residual variance.
total variance.
single-rater inter-rater reliability.
lower bound of the confidence
interval for ICC1
.
upper bound of the confidence
interval for ICC1
.
multiple-rater inter-rater reliability.
lower bound of the confidence interval for
ICC3
.
upper bound of the confidence interval for
ICC3
.
matrix
or data.frame
which includes variables
describing ID of ratees (specified in case
), ratings (specified in
var
), and (optionally) rank of ratees (specified in rank
).
character: name of the variable in Data
with ID of the
ratee (subject or object being evaluated, such as a respondent, proposal,
patient, applicant etc.)
character: name of the variable in Data
with the
ratings/scores.
numeric: vector of ranks of ratees. If not provided, rank of
ratee is calculated based on average rating based on var
variable.
character: direction of range-restriction, available options are
"top"
(default) or "bottom"
. Can be an unambiguous
abbreviation (i.e., "t"
or "b"
).
numeric: selected number (given > 1) or percentage (given <= 1) of ratees. Default value is 1 (complete dataset).
numeric: number of simulations for bootstrap confidence interval. Default value is 100.
numeric: confidence interval. Default value is 0.95.
seed for simulations. Default value is NULL
, random seed.
See lme4::bootMer()
for more detail.
Patricia Martinkova
Institute of Computer Science of the Czech Academy of Sciences
martinkova@cs.cas.cz
Jan Netik
Institute of Computer Science of the Czech Academy of Sciences
netik@cs.cas.cz
Erosheva, E., Martinkova, P., & Lee, C. (2021a). When zero may not be zero: A cautionary note on the use of inter-rater reliability in evaluating grant peer review. Journal of the Royal Statistical Society - Series A. Accepted.
Erosheva, E., Martinkova, P., & Lee, C. (2021b). Supplementary material for When zero may not be zero: A cautionary note on the use of inter-rater reliability in evaluating grant peer review.
# ICC for the whole sample
ICCrestricted(Data = AIBS, case = "ID", var = "Score", rank = "ScoreRankAdj")
# ICC for the range-restricted sample considering 80% of top ratees
ICCrestricted(
Data = AIBS, case = "ID", var = "Score", rank = "ScoreRankAdj",
sel = 0.8
)
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