r.pbis: Personal biserial statistic

Description Usage Arguments Details Value Author(s) References Examples

View source: R/rpbis.R

Description

Donlon and Fischer's personal biserial statistic.

Usage

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r.pbis(matrix,
       NA.method = "Pairwise", Save.MatImp = FALSE,
       IP = NULL, IRT.PModel = "2PL", Ability = NULL, Ability.PModel = "ML",
       mu = 0, sigma = 1)

Arguments

matrix

Data matrix of dichotomous item scores: Persons as rows, items as columns, item scores are either 0 or 1, missing values allowed.

NA.method

Method to deal with missing values. The default is pairwise elimination ("Pairwise"). Alternatively, simple imputation methods are also available. The options available are "Hotdeck", "NPModel" (default), and "PModel".

Save.MatImp

Logical. Save (imputted) data matrix to file? Default is FALSE.

IP

Matrix with previously estimated item parameters: One row per item, and three columns ([,1] item discrimination; [,2] item difficulty; [,3] lower-asymptote, also referred to as pseudo-guessing parameter).

In case no item parameters are available then IP=NULL.

IRT.PModel

Specify the IRT model to use in order to estimate the item parameters (only if IP=NULL). The options available are "1PL", "2PL" (default), and "3PL".

Ability

Vector with previoulsy estimated latent ability parameters, one per respondent, following the order of the row index of matrix.

In case no ability parameters are available then Ability=NULL.

Ability.PModel

Specify the method to use in order to estimate the latent ability parameters (only if Ability=NULL). The options available are "ML" (default), "BM", and "WL".

mu

Mean of the apriori distribution. Only used when method="BM". Default is 0.

sigma

Standard deviation of the apriori distribution. Only used when method="BM". Default is 1.

Details

Donlon and Fischer (1968) suggested to use the correlation between a respondent's score vector and the item proportion-correct scores in the sample as a measure of person fit. Low values should be indicative of misfit of the response vector with respect to the group of respondents.

Missing values in matrix are dealt with by means of pairwise elimination by default. Alternatively, single imputation is also available. Three single imputation methods exist: Hotdeck imputation (NA.method = "Hotdeck"), nonparametric model imputation (NA.method = "NPModel"), and parametric model imputation (NA.method = "PModel"); see Zhang and Walker (2008).

Value

An object of class "PerFit", which is a list with 12 elements:

PFscores

A list of length N (number of respondents) with the values of the person-fit statistic.

PFstatistic

The person-fit statistic used.

PerfVects

A message indicating whether perfect response vectors (all-0s or all-1s) were removed from the analysis.

ID.all0s

Row indices of all-0s response vectors removed from the analysis (if applicable).

ID.all1s

Row indices of all-1s response vectors removed from the analysis (if applicable).

matrix

The data matrix after imputation of missing values was performed (if applicable).

Ncat

The number of response categories (2 in this case).

IRT.PModel

The parametric IRT model used in case NA.method="PModel", otherwise NULL.

IP

The Ix3 matrix of estimated item parameters in case NA.method="PModel", otherwise NULL.

Ability.PModel

The method used to estimate abilities in case NA.method="PModel", otherwise NULL.

Ability

The vector of N estimated ability parameters in case NA.method="PModel", otherwise NULL.

NAs.method

The imputation method used (if applicable).

Author(s)

Jorge N. Tendeiro [email protected]

References

Donlon, T. F., and Fischer, F. E. (1968) An index of an individual's agreement with group-defined item difficulties. Educational and Psychological Measurement, 28(1), 105–113.

Karabatsos, G. (2003) Comparing the Aberrant Response Detection Performance of Thirty-Six Person-Fit Statistics. Applied Measurement In Education, 16(4), 277–298.

Meijer, R. R., and Sijtsma, K. (2001) Methodology review: Evaluating person fit. Applied Psychological Measurement, 25(2), 107–135.

Zhang, B., and Walker, C. M. (2008) Impact of missing data on person-model fit and person trait estimation. Applied Psychological Measurement, 32(6), 466–479.

Examples

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# Load the inadequacy scale data (dichotomous item scores):
data(InadequacyData)

# Compute the r.pbis scores:
rpbis.out <- r.pbis(InadequacyData)

PerFit documentation built on May 31, 2017, 5 a.m.