CQmodel: ConQuest Output Processing

In WrightMap: IRT Item-Person Map with 'ConQuest' Integration

ConQuest Output Processing

Description

The CQmodel function reads ConQuest item parameter and person parameter output files and converts them into a list of data frames for more convenient data processing.

Usage

CQmodel(p.est = NULL, show = NULL, p.type = NULL, equation = NULL)
## S3 method for class 'CQmodel'
print(x,...)
## S3 method for class 'SOE'
print(x,...)

Arguments

p.est	Conquest person parameters file (EAPs, MLEs, etc.).
show	ConQuest show file.
p.type	Type of person parameter estimate (EAP, MLE or WLE). If not specified, will try to determine from the extension of the p.est file.
equation	String giving the model equation, if the Summary of Estimation table was not included in the show file.
x	Object that determines which function to call.
...	Additional arguments.

Value

CQmodel returns an object of type CQmodel. Usually contains: Tables:

RMP	A list of data frames containing the response model parameter estimates. One data frame is created for each table in the output. Each data frame contains parameter estimates, errors, and fit information.
GIN	A matrix containing the item thresholds (if included in the ConQuest output). The rows are items and the columns are steps.
p.est	A data frame containing the person parameter estimates

Summary of estimation:

SOE	A list of various parameters related to the estimation

Items that may be in the SOE list include:

method	Estimation method
distribution	Assumed population distribution
constraint	Constraint
format	Specified format of the datafile
equation	A character string containing the item model (e.g. "item+item*step")
participants	Sample size
deviance	Final deviance of the model
parameters	Total number of estimated parameters
iterations	Number of iterations
seed	Random number generation seed
PV.nodes	Number of nodes used when drawing PVs
fit.nodes	Number of nodes used when computing fit
n.plausible.values	Number of plausible values drawn
max.iterations.no.improvement	Maximum number of iterations without a deviance improvement
max.steps	Maximum number of Newton steps in M-step
zero.perfect.value	Value for obtaining finite MLEs for zero/perfects
termination.reason	Reason for iteration termination
max.iterations
parameter.change
deviance.change

Run details:

run.details

A list of details of the run

Items that may be included in the run.details list include:

date	The date of the ConQuest run
data.file	The name of the datafile used
format	The specified format of the datafile
names	Names of items and/or dimensions

Additional items:

deviance	The deviance of the model
equation	A character string containing the model specification (e.g. "item+item*step")
participants	The number of participants
parameters	The number of parameters
title	The run title
reg.coef	Regression coefficients
rel.coef	Reliability coefficients
variances
nDim	Number of dimensions
dimensions	Dimension names
p.est.type

Author(s)

Rebecca Freund and David Torres Irribarra

Examples

	
fpath <- system.file("extdata", package="WrightMap")

# Partial credit model
model1 <- CQmodel(p.est = file.path(fpath,"ex2.eap"), 
show = file.path(fpath,"ex2.shw")) 
model1 #Shows what tables are available

model1$SOE #Summary of estimation
model1$equation # Model specification
model1$reg.coef # Regression coefficients
model1$rel.coef # Reliability coefficients
model1$variances # Variances

names(model1$RMP) # Names of parameter tables
head(model1$RMP$item) #Item parameters
head(model1$RMP$"item*step") #Item by step parameters

# Complex model
model2 <- CQmodel(file.path(fpath,"ex4a.mle"), 
file.path(fpath,"ex4a.shw")) 
model2$equation # Model specification
names(model2$RMP) # Names of parameter tables
head(model2$RMP$"rater*topic*criteria*step") #An interaction table

model1$GIN #Item thresholds
model2$GIN #Item thresholds

head(model1$p.est)  ##EAPs
head(model2$p.est)  ##MLEs

WrightMap documentation built on June 19, 2022, 1:05 a.m.