Description Usage Arguments Details Value Examples
View source: R/elicit_functions.R
This builds the structure that will store elicited data. The linear predictor
has a normal prior g(θ) ~ N(m, V), θ is the elicitation
target. Link functions g(.): logit
, log
, cloglog
,
identity
.
1 2 3 4 5 6 7 8 9 10 11  designLink(
design,
link = "identity",
target = "Target",
CI.prob = 1/2,
expertID = "Expert",
facilitator = "Facilitator",
rapporteur = "none",
intro.comments = "This is a record of the elicitation session.",
fit.method = "KL"
)

design 
a dataframe with covariate values that will be displayed to the expert(s) during the elicitation session. 
link 
character 
target 
character, name of target parameter of elicitation exercise 
CI.prob 
numeric, a fraction between 0 and 1 that defines probability attributed to central credible interval. For example, 1/2 for a central credible interval of probability 0.5, or 1/3 for a central credible interval of probablity 0.333... The default is probability 1/2. 
expertID 
character, identifier for expert or group of experts 
facilitator 
character, facilitator identifier 
rapporteur 
character, rapporteur identifier. Default "none". 
intro.comments 
character, text with any prefacing comments. This may
include, for example, the definition of the target parameter for the
elictation session. Beware of nonASCII text and special characters, which
may affect the ability to save the elicitation record with function 
fit.method 
character, method used to fit conditional means prior:

Assumption: at least two fractiles selected from the median, upper and lower
bounds of hte central credible interval of probability CI.prob
will be
elicited at each design point. The probabilities assigned to the central
credible intervals can vary across design points. The argument
CI.prob
can later be adjusted by design point during the elicitation
exercise, see function elicitPt
. In the first instance, it is
set to a global value specified by CI.prob
in function
designLink
with default value 0.5.
list of design
with entries: theta
, a n x 4
matrix with columns that give lower, median and upper quantiles followed by
CI.prob
and n equal to the number of design points
(scenarios); link
, the link function used; target
;
expert
facilitator
; rapporteur
; date
;
intro.comments
; fit.method
.
1 2 3  X < matrix(c(1, 1, 0, 1), nrow = 2) # design
Z < designLink(design = X, link = "logit", target = "target",
CI.prob = 1/2, expertID = "Expert", facilitator = "facilitator")

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