CQmodel: ConQuest Output Processing

Description Usage Arguments Value Author(s) Examples

View source: R/CQmodel.R

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

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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

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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 May 1, 2019, 8:18 p.m.