rtmpt (version 2.0-3)

to_ertmpt_model: Create a model list to fit an RT-MPT

Description

Create a model list of the class ertmpt_model by providing either eqn_file or mdl_file. If both are provided mdl_file will be used.

Usage

to_ertmpt_model(eqn_file = NULL, mdl_file = NULL)
to_rtmpt_model(eqn_file = NULL, mdl_file = NULL)

Value

A list of the class ertmpt_model.

Arguments

eqn_file

Character string as shown in example 2 or path to the text file that specifies the (RT-)MPT model with standard .eqn syntax (Heck et al., 2018; Hu, 1999). E.g. studied ; hit ; (1-do)*g for a correct guess in the detect-guess 2HT model.

mdl_file

Character string as shown in example 1 or path to the text file that specifies the (RT-)MPT model and gives on each line the equation of one category using + to separate branches and * to separate processes (Singmann and Kellen, 2013). E.g. do+(1-do)*g for the category "hit" in the detect-guess 2HT model.

Author

Raphael Hartmann

References

Heck, D. W., Arnold, N. R., & Arnold, D. (2018). TreeBUGS: An R package for hierarchical multinomial-processing-tree modeling. Behavior Research Methods, 50(1), 264-284.

Hu, X. (1999). Multinomial processing tree models: An implementation. Behavior Research Methods, Instruments, & Computers, 31(4), 689-695.

Singmann, H., & Kellen, D. (2013). MPTinR: Analysis of multinomial processing tree models in R. Behavior Research Methods, 45(2), 560-575.

See Also

delta2delta, theta2const, tau2zero, theta2theta, and tau2tau for functions to change the model

Examples

########################################################################################
# Detect-Guess variant of the Two-High Threshold model
#   with constant guessing and
#   suppressed process completion times for both failed detections.
# The encoding and motor execution times are assumed to be different for each response.
########################################################################################

## 1. using the mdl syntax
mdl_2HTM <- "
# targets
do+(1-do)*g     ; 0
(1-do)*(1-g)    ; 1

# lures
(1-dn)*g        ; 0
dn+(1-dn)*(1-g) ; 1

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

# OPTIONAL MPT CONSTRAINTS
# for constant thetas and suppressed taus
# please use theta2cons() and tau2
"

model <- to_ertmpt_model(mdl_file = mdl_2HTM)
model

## 2. using the eqn syntax
eqn_2HTM <- "
# CORE MPT EQN
# tree ; cat ; mpt
     0 ;   0 ; do
     0 ;   0 ; (1-do)*g
     0 ;   1 ; (1-do)*(1-g)
       
     1 ;   2 ; (1-dn)*g
     1 ;   3 ; dn
     1 ;   3 ; (1-dn)*(1-g)

# OPTIONAL MPT CONSTRAINTS
# for constant thetas and suppressed taus
# please use theta2cons() and tau2

#     tree ; cat ;  MAP
resp:    0 ;   0 ;    0
resp:    0 ;   1 ;    1
resp:    1 ;   2 ;    0
resp:    1 ;   3 ;    1
# different motor execution times for old and new responses.
"

model <- to_ertmpt_model(eqn_file = eqn_2HTM)
model


mdl_2HTM <- "
# targets
do+(1-do)*g     ; 0
(1-do)*(1-g)    ; 1

# lures
(1-dn)*g        ; 0
dn+(1-dn)*(1-g) ; 1

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

model <- to_rtmpt_model(mdl_file = mdl_2HTM)
model