tau2tau: Set process completion times equal

Description

Setting multiple process completion times (taus) equal. This means all process times of negative outcomes will be set equal and all process times of positive outcomes will be set equal. Only two process times (one for the negative and one for the positive outcome) of the named processes will be estimated. The equality can be removed by just naming only one process name.

Usage

tau2tau(model, names, outcome, keep_zeros = FALSE)
set_taus_equal(model, names, outcome, keep_zeros = FALSE)
set_lambdas_equal(model, names, outcome, keep_zeros = FALSE)
lambda2lambda(model, names, outcome, keep_zeros = FALSE)

Value

A list of the class ertmpt_model.

Arguments

model

A list of the class ertmpt_model.

names

Character vector giving the names of the processes for which the process completion times should be equal. If length(names) = 1 then the corresponding process completion times (for negative and positive outcomes) will be estimates (i.e., they will be set to NA)

outcome

Character (no vector) indicating for which process outcome the process completion times should be set equal. Allowed characters are:

"minus": the negative outcome of the processes.
"plus": the positive outcome of the processes.
"both": the negative and positive outcome of the processes. This will set all process completion times for the "minus" outcome equal and all process completion times for the "plus" outcome equal.

keep_zeros

Can be one of the following

logical value: FALSE (default) means none of the zeros for names in the model will be kept; The times of the reference process (i.e., first of names in alphabetical order) will be set to NA (i.e., will be estimated) and the others will be set to the name of the reference process (i.e., will be set to equal the reference process times). TRUE means the zero(s) of the reference process times (if specified) is used for the same outcome of all other processes.
numeric value: index for names. If 1, the zero(s) of the first process in names (in original order defined by the user) is used for the same outcome of all other processes in names. If 2, the zero(s) of the second process is used. And so on.

Author

Raphael Hartmann

Examples

Run this code

####################################################################################
# Detect-Guess variant of the Two-High Threshold model.
# The encoding and motor execution times are assumed to be equal for each category.
# The process completion times for both detection processes ("do" and "dn") will be
# set equal.
####################################################################################

mdl_2HTM <- "
# targets
do+(1-do)*g
(1-do)*(1-g)

# lures
(1-dn)*g
dn+(1-dn)*(1-g)

# do: detect old; dn: detect new; g: guess
"

model <- to_ertmpt_model(mdl_file = mdl_2HTM)

## make do = dn
new_model <- tau2tau(model = model, names = c("do", "dn"), outcome = "both")
new_model


## make do = dn
new_model <- set_taus_equal(model = model, names = c("do", "dn"), outcome = "both")
new_model

## make do = dn
new_model <- set_lambdas_equal(model = model, names = c("do", "dn"), outcome = "both")
new_model

## make do = dn
new_model <- lambda2lambda(model = model, names = c("do", "dn"), outcome = "both")
new_model