e_item | R Documentation |
e_*()
and array_e_*()
are C++ functions for calculating expected scores.
e_1pl(x, b)
e_2pl(x, a, b)
e_m_2pl(x, a, d)
e_3pl(x, a, b, c)
e_m_3pl(x, a, d, c)
e_pc(x, b)
e_gpc(x, a, b)
e_m_gpc(x, a, d)
e_gr(x, a, b)
e_m_gr(x, a, d)
array_e_1pl(x, b)
array_e_2pl(x, a, b)
array_e_3pl(x, a, b, c)
array_e_pc(x, b)
array_e_gpc(x, a, b)
array_e_gr(x, a, b)
x |
the theta value. The number of columns should correspond to the number of dimensions.
For |
b , d |
the difficulty parameter. |
a |
the a-parameter. |
c |
the c-parameter. |
e_*()
functions accept a single theta value, and array_p_*()
functions accept multiple theta values.
Supports unidimensional and multidimensional models.
e_1pl()
, array_e_1pl()
: 1PL models
e_2pl()
, array_e_2pl()
: 2PL models
e_3pl()
, array_e_3pl()
: 3PL models
e_pc()
, array_e_pc()
: PC (partial credit) models
e_gpc()
, array_e_gpc()
: GPC (generalized partial credit) models
e_gr()
, array_e_gr()
: GR (graded response) models
e_m_2pl()
, array_e_m_2pl()
: multidimensional 2PL models
e_m_3pl()
, array_e_m_3pl()
: multidimensional 3PL models
e_m_gpc()
, array_e_m_gpc()
: multidimensional GPC models
e_m_gr()
, array_e_m_gr()
: multidimensional GR models
Rasch, G. (1960). Probabilistic models for some intelligence and attainment tests. Copenhagen: Danish Institute for Educational Research.
Lord, F. M. (1952). A theory of test scores (Psychometric Monograph No. 7). Richmond, VA: Psychometric Corporation.
Birnbaum, A. (1957). Efficient design and use of tests of mental ability for various decision-making problems (Series Report No. 58-16. Project No. 7755-23). Randolph Air Force Base, TX: USAF School of Aviation Medicine.
Birnbaum, A. (1958). On the estimation of mental ability (Series Report No. 15. Project No. 7755-23). Randolph Air Force Base, TX: USAF School of Aviation Medicine.
Birnbaum, A. (1958). Further considerations of efficiency in tests of a mental ability (Series Report No. 17. Project No. 7755-23). Randolph Air Force Base, TX: USAF School of Aviation Medicine.
Birnbaum, A. (1968). Some latent trait models and their use in inferring an examinee's ability. In Lord, F. M., Novick, M. R. (eds.), Statistical Theories of Mental Test Scores, 397-479. Reading, MA: Addison-Wesley.
Masters, G. N. (1982). A Rasch model for partial credit scoring. Psychometrika, 47(2), 149-174.
Andrich, D. (1978). A rating formulation for ordered response categories. Psychometrika, 43(4), 561-573.
Muraki, E. (1992). A generalized partial credit model: Application of an EM algorithm. Applied Psychological Measurement, 16(2), 159-176.
Samejima, F. (1969). Estimation of latent ability using a response pattern of graded scores. Psychometrika Monograph, 17.
x <- 0.5
e_1pl(x, 1)
e_2pl(x, 1, 2)
e_3pl(x, 1, 2, 0.25)
e_pc(x, c(0, 1))
e_gpc(x, 2, c(0, 1))
e_gr(x, 2, c(0, 2))
x <- matrix(seq(-3, 3, 1)) # three theta values, unidimensional
array_e_1pl(x, 1)
array_e_2pl(x, 1, 2)
array_e_3pl(x, 1, 2, 0.25)
array_e_pc(x, c(0, 1))
array_e_gpc(x, 2, c(0, 1))
array_e_gr(x, 2, c(0, 2))
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