Locally dependent latent trait model for polytomous responses with application to inventory of hostility

Psychological tests often involve item clusters that are designed to solicit responses to behavioral stimuli. The dependency between individual responses within clusters beyond that which can be explained by the underlying trait sometimes reveals structures that are of substantive interest. The paper describes two general classes of models for this type of locally dependent responses. Specifically, the models include a generalized log-linear representation and a hybrid parameterization model for polytomous data. A compact matrix notation designed to succinctly represent the system of complex multivariate polytomous responses is presented. The matrix representation creates the necessary formulation for the locally dependent kernel for polytomous item responses. Using polytomous data from an inventory of hostility, we provide illustrations as to how the locally dependent models can be used in psychological measurement.

[1]  M. R. Novick,et al.  Statistical Theories of Mental Test Scores. , 1971 .

[2]  William Stout,et al.  The theoretical detect index of dimensionality and its application to approximate simple structure , 1999 .

[3]  Eric T. Bradlow,et al.  A Bayesian random effects model for testlets , 1999 .

[4]  W. Deming,et al.  On a Least Squares Adjustment of a Sampled Frequency Table When the Expected Marginal Totals are Known , 1940 .

[5]  D. Bates,et al.  Approximations to the Log-Likelihood Function in the Nonlinear Mixed-Effects Model , 1995 .

[6]  Kristof Vansteelandt,et al.  A formal model for the competency–demand hypothesis , 1999 .

[7]  Ole E. Barndorff-Nielsen,et al.  Cuts in Natural Exponential Families , 1996 .

[8]  Edward H. Ip,et al.  Adjusting for information inflation due to local dependency in moderately large item clusters , 2000 .

[9]  G. Masters A rasch model for partial credit scoring , 1982 .

[10]  Wendy M. Yen,et al.  Scaling Performance Assessments: Strategies for Managing Local Item Dependence , 1993 .

[11]  P. Holland,et al.  Discrete Multivariate Analysis. , 1976 .

[12]  J. Chambers,et al.  The New S Language , 1989 .

[13]  Howard Wainer,et al.  Item Clusters and Computerized Adaptive Testing: A Case for Testlets , 1987 .

[14]  Edward H. Ip,et al.  Testing for local dependency in dichotomous and polytomous item response models , 2001 .

[15]  Paul W. Holland,et al.  The Dutch Identity: A New Tool for the Study of Item Response Models. , 1990 .

[16]  Richard A. Becker,et al.  The New S Language , 1989 .

[17]  Isaac I. Bejar Achievement Testing: Recent Advances , 1983 .

[18]  Paul De Boeck,et al.  Multidimensional Componential Item Response Theory Models for Polytomous Items , 2001 .

[19]  S. Embretson A general latent trait model for response processes , 1984 .

[20]  H. Akaike,et al.  Information Theory and an Extension of the Maximum Likelihood Principle , 1973 .

[21]  Donald Hedeker,et al.  Full-information item bi-factor analysis , 1992 .

[22]  Yu. S. Khokhlov,et al.  The Domains of Attraction of Semistable Laws , 1996 .

[23]  Rosemary Baker,et al.  Item response theory , 1985 .

[24]  N. Endler,et al.  S-R inventories of hostility and comparisons of the proportions of variance from persons, responses, and situations for hostility and anxiousness. , 1968, Journal of personality and social psychology.

[25]  William Stout,et al.  A nonparametric approach for assessing latent trait unidimensionality , 1987 .

[26]  Paul De Boeck,et al.  A parametric model for local dependence among test items. , 1997 .

[27]  Robert J. Jannarone,et al.  Conjunctive item response theory kernels , 1986 .

[28]  D. Rubin,et al.  Maximum likelihood from incomplete data via the EM - algorithm plus discussions on the paper , 1977 .

[29]  Gerhard H. Fischer,et al.  The Linear Logistic Test Model , 1995 .

[30]  L. Zhao,et al.  Correlated binary regression using a quadratic exponential model , 1990 .

[31]  Andrea Rotnitzky,et al.  Regression Models for Discrete Longitudinal Responses , 1993 .

[32]  D. Cox The Analysis of Multivariate Binary Data , 1972 .

[33]  N. Laird,et al.  A likelihood-based method for analysing longitudinal binary responses , 1993 .

[34]  Edward H. Ip,et al.  Locally dependent latent trait model and the dutch identity revisited , 2002 .

[35]  G. H. Fischer,et al.  The linear logistic test model as an instrument in educational research , 1973 .

[36]  Stephen E. Fienberg,et al.  Discrete Multivariate Analysis: Theory and Practice , 1976 .

[37]  William Stout,et al.  Using New Proximity Measures With Hierarchical Cluster Analysis to Detect Multidimensionality , 1998 .

[38]  C. Fox,et al.  Applying the Rasch Model: Fundamental Measurement in the Human Sciences , 2001 .

[39]  G. Schwarz Estimating the Dimension of a Model , 1978 .

[40]  F. Samejima Estimation of latent ability using a response pattern of graded scores , 1968 .

[41]  Brian W. Junker,et al.  Essential independence and likelihood-based ability estimation for polytomous items , 1991 .

[42]  Paul De Boeck,et al.  Componential IRT Models for Polytomous Items , 1995 .

[43]  Yuchung J. Wang Order-dependent parameterization of multinomial distributions , 1986 .

[44]  J. F. C. Kingman,et al.  Information and Exponential Families in Statistical Theory , 1980 .

[45]  Edward H. Ip,et al.  Empirical Bayes and Item-Clustering Effects in a Latent Variable Hierarchical Model , 2002 .