Input.Checking | R Documentation |
Based on the given model, checking whether user speciflied input variables are correct. If the input variables are acceptable, this function will format them and then return them as a list
. Otherwise, this function will return a error message to indicate which variables are unacceptable.
Input.Checking(Model, data,
PriorA=c(0,0.25), PriorB=c(0,4), PriorC=c(4,16), PriorS=c(4,16),
PriorAlpha=c(-1.9,1), PriorBeta=c(0,4), PriorGamma=c(-1.39,0.25),
InitialA=NA, InitialB=NA, InitialC=NA, InitialS=NA,
InitialAlpha=NA, InitialBeta=NA, InitialGamma=NA,
Tol=0.0001, max.ECycle=1000L, max.MCycle=100L, n.Quadpts=31L, n.decimal=3L,
Theta.lim=c(-6,6), Missing=-9, ParConstraint=FALSE, BiasSE=FALSE)
Model |
A
These parameter labels are capitalized in program for emphasis. |
data |
A |
PriorA |
The user specified logarithmic normal distribution prior for item discrimation (a) parameters in the 3PL and 4PL models. Can be:
|
PriorB |
The user specified normal distribution prior for item difficulty (b) parameters in the 3PL and 4PL models. Can be:
|
PriorC |
The user specified Beta(x,y) distribution prior for item guessing (c) parameters in the 3PL and 4PL models. Can be:
|
PriorS |
The user specified Beta(x,y) distribution prior for item slipping (s) parameters in the 4PL model. Can be:
|
PriorAlpha |
The user specified normal distribution prior for the logarithmic weight of the ability in the guessing component (ln(alpha)) parameter in the 1PLAG model. Can be:
|
PriorBeta |
The user specified normal distribution prior for item difficulty (beta) parameters in the 1PLAG and 1PLG model. Can be:
|
PriorGamma |
The user specified normal distribution prior for item guessing (gamma) parameters in the 1PLAG and 1PLG model. Can be:
|
InitialA |
The user specified starting values for item discrimation (a) parameters in the 3PL and 4PL models. Can be:
|
InitialB |
The user specified starting values for item difficulty (b) parameters in the 3PL and 4PL models. Can be:
|
InitialC |
The user specified starting values for item guessing (c) parameters in the 3PL and 4PL models. Can be:
|
InitialS |
The user specified starting values for item slipping (s) parameters in the 4PL model. Can be:
|
InitialAlpha |
The user specified starting value for the weight of the ability in the guessing component (alpha) parameters in the 1PLAG model. Can be:
|
InitialBeta |
The user specified starting values for item difficulty (beta) parameters in the 1PLAG and 1PLG models. Can be:
|
InitialGamma |
The user specified starting values for item guessing (gamma) parameters in the 1PLAG and 1PLG models. Can be:
|
Tol |
A single number ( |
max.ECycle |
A single |
max.MCycle |
A single |
n.Quadpts |
A single |
n.decimal |
A single |
Theta.lim |
A |
Missing |
A single number ( |
ParConstraint |
A logical value to indicate whether estimates parametes in a reasonable range; default is FALSE. If ParConstraint=TRUE: a in [0.001, 6], b in [-6, 6], c in [0.0001, 0.5], s in [0.0001, c], alpha in [0, 0.707], beta in [-6, 6], gamma in [-7, 0]. |
BiasSE |
A logical value to determine whether directly estimating SEs from inversed Hession matrix rather than USEM method, default is FALSE. |
Barton, M. A., & Lord, F. M. (1981). An upper asymptote for the three-parameter logistic item response model. ETS Research Report Series, 1981(1), 1-8. \Sexpr[results=rd]{tools:::Rd_expr_doi("10.1002/j.2333-8504.1981.tb01255.x")}
Birnbaum, A. (1968). Some latent trait models and their use in inferring an examinee's ability. In F. M. Lord & M. R. Novick (Eds.), Statistical theories of mental test scores (pp. 395-479). MA: Adison-Wesley.
San Martín, E., Del Pino, G., & De Boeck, P. (2006). IRT models for ability-based guessing. Applied Psychological Measurement, 30(3), 183-203. \Sexpr[results=rd]{tools:::Rd_expr_doi("10.1177/0146621605282773")}
#An example to show the error message when the variance of a normal prior is negative.
library(IRTBEMM)
#generate a response matrix with 1000 examinees and 10 items randomly
data=matrix(rbinom(10000,1,0.5), 1000, 10)
#test whether variable data is correct.
res=Input.Checking('3PL',data)
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