simul.rasch: Simulate data according to the Rasch model
In pwrRasch: Statistical Power Simulation for Testing the Rasch Model
Description
Usage
Arguments
Details
Value
Author(s)
References
See Also
Examples
Description
This function simulates data according to the Rasch model
based on user-specified item and person parameters.
Usage
1
simul.rasch(persons, items, sum0 = TRUE)
Arguments
persons
Either a vector of specified person parameters or an integer indicating the number of persons.
items
Either a vector of specified item parameters or an integer indicating the number of items.
sum0
If TRUE, specified item parameters need to be normalized to sum-0.
Details
If persons is an integer value, the corresponding parameter vector
is drawn from N(0, 1.5). If items is an integer value, the corresponding parameter vector
is equally spaced between [-3, 3]. Note that item parameters need to be normalized to sum-0.
This precondition can be overruled using argument sum0 = FALSE.
Value
Returns a 0-1 matrix according to the Rasch model.
Author(s)
Takuya Yanagida takuya.yanagida@univie.ac.at,
Jan Steinfeld jan.steinfeld@univie.ac.at
References
Kubinger, K. D., Rasch, D., & Yanagida, T. (2009). On designing data-sampling for Rasch model
calibrating an achievement test. Psychology Science Quarterly, 51, 370-384.
Kubinger, K. D., Rasch, D., & Yanagida, T. (2011). A new approach for testing the Rasch model.
Educational Research and Evaluation, 17, 321-333.
See Also
Examples
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
## Not run:
# simulate Rasch model based data
# 100 persons, 20 items,
# person parameter drawn from a normal distribution: N(0,1.5)
# item parameters equally spaced between [-3, 3]
simul.rasch(100, items = 20)
# simulate Rasch model based data
# 100 persons, 17 items
# person parameter drawn from a uniform distribution: U[-4, 4]
# item parameters: [-4.0, -3.5, -3.0, ... , 3.0, 3.5, 4.0]
simul.rasch(runif(100, -4, 4), items = seq(-4, 4, by = 0.5))
## End(Not run)
Example output
|----------------------------------------------------------|
| pwrRasch 0.1-2 (2015-09-28) |
| Statistical Power Simulation for Testing the Rasch Model |
|----------------------------------------------------------|
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pwrRasch documentation built on May 1, 2019, 10:37 p.m.
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Description Usage Arguments Details Value Author(s) References See Also Examples
Description
This function simulates data according to the Rasch model based on user-specified item and person parameters.
Usage
1 | simul.rasch(persons, items, sum0 = TRUE)
|
Arguments
persons |
Either a vector of specified person parameters or an integer indicating the number of persons. |
items |
Either a vector of specified item parameters or an integer indicating the number of items. |
sum0 |
If |
Details
If persons is an integer value, the corresponding parameter vector
is drawn from N(0, 1.5). If items is an integer value, the corresponding parameter vector
is equally spaced between [-3, 3]. Note that item parameters need to be normalized to sum-0.
This precondition can be overruled using argument sum0 = FALSE.
Value
Returns a 0-1 matrix according to the Rasch model.
Author(s)
Takuya Yanagida takuya.yanagida@univie.ac.at, Jan Steinfeld jan.steinfeld@univie.ac.at
References
Kubinger, K. D., Rasch, D., & Yanagida, T. (2009). On designing data-sampling for Rasch model calibrating an achievement test. Psychology Science Quarterly, 51, 370-384.
Kubinger, K. D., Rasch, D., & Yanagida, T. (2011). A new approach for testing the Rasch model. Educational Research and Evaluation, 17, 321-333.
See Also
Examples
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 | ## Not run:
# simulate Rasch model based data
# 100 persons, 20 items,
# person parameter drawn from a normal distribution: N(0,1.5)
# item parameters equally spaced between [-3, 3]
simul.rasch(100, items = 20)
# simulate Rasch model based data
# 100 persons, 17 items
# person parameter drawn from a uniform distribution: U[-4, 4]
# item parameters: [-4.0, -3.5, -3.0, ... , 3.0, 3.5, 4.0]
simul.rasch(runif(100, -4, 4), items = seq(-4, 4, by = 0.5))
## End(Not run)
|
Example output
|----------------------------------------------------------|
| pwrRasch 0.1-2 (2015-09-28) |
| Statistical Power Simulation for Testing the Rasch Model |
|----------------------------------------------------------|
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10] [,11] [,12] [,13]
[1,] 1 1 1 1 1 1 1 1 0 0 0 0 0
[2,] 1 1 1 1 1 1 1 1 1 1 0 1 1
[3,] 1 1 1 1 0 0 1 0 0 0 0 0 0
[4,] 1 1 1 1 1 1 0 1 1 0 0 0 0
[5,] 1 1 1 1 1 0 1 1 0 1 1 0 0
[6,] 1 1 1 1 1 1 0 1 0 0 1 0 0
[7,] 1 1 1 1 1 1 1 1 1 1 1 0 1
[8,] 1 1 1 0 1 1 1 0 0 0 0 0 0
[9,] 1 1 0 1 1 1 1 0 0 0 0 0 0
[10,] 1 1 1 1 1 1 1 1 1 1 0 1 1
[11,] 1 1 1 1 1 1 1 1 1 1 1 1 0
[12,] 1 1 1 1 0 0 0 0 0 0 0 0 0
[13,] 1 1 1 1 1 1 1 0 0 0 0 0 1
[14,] 1 1 1 1 1 1 1 1 1 1 1 0 0
[15,] 1 1 1 1 0 1 1 1 1 0 0 1 0
[16,] 1 1 1 0 1 1 1 1 0 0 0 1 1
[17,] 1 1 1 1 0 0 1 1 1 0 0 0 0
[18,] 1 1 1 1 1 1 1 1 1 1 1 1 1
[19,] 1 1 1 1 1 1 1 1 1 1 1 1 1
[20,] 1 1 1 1 0 1 1 1 0 1 0 1 0
[21,] 0 1 1 1 1 1 1 0 0 1 0 0 0
[22,] 1 0 1 0 0 0 1 0 0 0 0 0 0
[23,] 1 1 1 1 1 1 1 1 1 0 1 0 0
[24,] 1 1 1 1 1 1 1 1 1 1 1 0 0
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[56,] 1 1 1 1 1 1 1 1 1 1 1 1 1
[57,] 1 1 1 1 1 1 1 1 1 1 1 1 0
[58,] 1 1 1 0 1 1 1 1 1 1 1 1 1
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[,14] [,15] [,16] [,17] [,18] [,19] [,20]
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[12,] 1 1 0 0 0 0 0
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[16,] 0 0 0 0 0 0 0
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[18,] 1 1 0 0 1 1 1
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[22,] 0 0 0 0 0 0 0
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[25,] 0 0 0 0 0 0 0
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[27,] 0 0 0 0 0 0 0
[28,] 1 0 0 0 1 1 1
[29,] 0 0 0 0 0 0 0
[30,] 0 0 1 0 0 1 0
[31,] 0 0 0 0 0 0 0
[32,] 0 1 0 0 0 0 0
[33,] 1 1 1 1 1 0 1
[34,] 0 1 1 0 1 0 0
[35,] 0 0 0 0 0 0 0
[36,] 1 1 1 0 1 0 0
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[40,] 0 0 0 0 0 0 0
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[42,] 1 1 1 0 1 1 0
[43,] 1 1 1 0 0 1 1
[44,] 0 0 1 0 0 0 0
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[47,] 0 0 0 0 0 0 0
[48,] 0 0 1 0 0 0 0
[49,] 0 0 0 0 0 0 0
[50,] 1 1 1 0 1 1 1
[51,] 0 0 0 0 0 0 0
[52,] 0 0 0 0 0 0 0
[53,] 0 1 1 0 0 0 0
[54,] 1 1 1 1 1 1 1
[55,] 1 1 1 0 0 0 0
[56,] 1 1 0 0 0 0 0
[57,] 1 1 1 0 1 1 0
[58,] 1 0 0 0 1 1 0
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[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10] [,11] [,12] [,13]
[1,] 1 1 1 1 1 1 1 0 1 1 1 0 1
[2,] 1 1 1 1 1 1 1 1 1 1 1 1 1
[3,] 1 1 0 1 1 1 0 0 0 0 0 0 0
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[5,] 1 0 1 1 1 1 0 1 0 0 0 0 0
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[38,] 1 1 1 1 1 0 1 1 1 1 0 1 1
[39,] 1 1 1 1 1 1 1 1 1 1 1 1 0
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[45,] 1 1 1 1 1 1 1 1 1 1 1 1 0
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[47,] 1 1 1 1 1 1 1 1 1 1 0 0 0
[48,] 1 1 1 1 1 1 1 1 1 1 1 1 1
[49,] 1 1 1 1 1 1 1 1 1 1 1 1 1
[50,] 1 1 1 1 1 1 0 0 1 0 0 0 0
[51,] 1 1 1 1 1 1 1 1 1 1 1 1 1
[52,] 1 1 1 1 1 1 1 0 0 0 1 0 1
[53,] 1 1 1 1 1 1 0 0 0 0 1 0 1
[54,] 1 1 1 1 1 1 1 0 1 1 1 1 1
[55,] 1 0 0 0 0 0 0 1 0 0 0 0 0
[56,] 1 1 1 1 1 1 1 1 0 0 1 1 1
[57,] 1 1 1 0 0 0 0 0 0 0 0 0 0
[58,] 1 0 0 1 1 0 1 0 0 0 0 0 1
[59,] 1 1 1 1 1 1 1 1 1 1 0 0 0
[60,] 1 1 1 1 1 1 1 1 1 1 1 1 1
[61,] 1 1 0 0 0 0 0 0 0 0 0 0 0
[62,] 1 1 1 1 1 1 1 1 1 1 1 0 1
[63,] 1 0 0 0 0 0 0 0 0 0 0 0 0
[64,] 1 0 0 0 0 0 0 0 0 0 0 0 0
[65,] 1 1 1 1 1 0 0 1 1 1 1 0 1
[66,] 1 1 1 1 1 1 1 1 1 1 1 1 0
[67,] 1 1 1 1 1 1 1 1 1 0 0 0 0
[68,] 1 1 1 1 1 1 1 1 1 0 1 1 1
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[75,] 1 1 1 1 1 1 1 1 1 1 1 1 1
[76,] 1 1 1 1 1 0 0 0 0 1 0 0 0
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[78,] 1 1 1 1 1 1 1 1 1 1 1 1 1
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[89,] 1 1 1 1 1 0 0 0 0 0 0 0 0
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[,14] [,15] [,16] [,17]
[1,] 0 0 0 0
[2,] 1 0 0 0
[3,] 0 0 0 0
[4,] 0 0 0 0
[5,] 0 0 0 0
[6,] 0 0 0 0
[7,] 0 0 0 0
[8,] 0 1 0 0
[9,] 0 0 0 0
[10,] 1 0 1 0
[11,] 0 0 0 0
[12,] 0 0 0 0
[13,] 0 0 0 0
[14,] 0 0 0 0
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[16,] 0 0 0 0
[17,] 0 0 0 0
[18,] 0 0 0 0
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[21,] 0 0 0 0
[22,] 0 0 0 0
[23,] 1 1 1 0
[24,] 0 1 1 0
[25,] 0 0 0 0
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[29,] 0 0 0 0
[30,] 0 1 0 0
[31,] 1 0 0 0
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[33,] 0 0 0 0
[34,] 1 0 1 0
[35,] 0 0 0 0
[36,] 0 0 0 0
[37,] 0 0 0 0
[38,] 0 1 0 1
[39,] 0 1 0 0
[40,] 1 0 0 1
[41,] 1 0 0 0
[42,] 0 0 0 0
[43,] 0 0 0 0
[44,] 0 0 0 0
[45,] 0 1 0 0
[46,] 0 0 0 0
[47,] 0 1 0 0
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[51,] 0 1 1 0
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[54,] 0 0 1 0
[55,] 0 0 0 0
[56,] 0 1 1 0
[57,] 0 0 0 0
[58,] 0 0 0 0
[59,] 0 0 1 0
[60,] 1 1 1 0
[61,] 0 0 0 0
[62,] 0 0 0 0
[63,] 0 0 0 0
[64,] 0 0 0 0
[65,] 0 0 0 0
[66,] 0 1 1 0
[67,] 0 0 0 0
[68,] 1 1 0 0
[69,] 0 0 0 1
[70,] 0 0 0 0
[71,] 0 0 0 0
[72,] 0 0 0 0
[73,] 0 0 0 0
[74,] 1 1 1 0
[75,] 0 0 1 0
[76,] 0 0 1 0
[77,] 0 0 0 0
[78,] 0 1 0 0
[79,] 0 0 0 0
[80,] 0 0 0 0
[81,] 0 0 0 0
[82,] 0 1 0 0
[83,] 1 1 0 1
[84,] 0 0 0 0
[85,] 0 1 0 0
[86,] 0 0 0 0
[87,] 0 0 0 0
[88,] 1 0 0 0
[89,] 0 0 0 0
[90,] 1 0 0 0
[91,] 0 0 0 0
[92,] 0 0 0 0
[93,] 0 0 0 0
[94,] 0 0 0 0
[95,] 0 0 0 0
[96,] 0 0 0 0
[97,] 1 1 1 1
[98,] 0 0 0 0
[99,] 0 0 0 0
[100,] 0 0 0 0
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