View source: R/generate_responses.R
generate_item_responses_sml | R Documentation |
Function generates responses in the GPCM way with a whole scoring matrix used at once. Only (G)PCM/NRM approach is suitable in such a case, because with complicated scoring matrices there is no guarantee that probabilities of responses are increasing along with order of responses (rows) in a scoring matrix. Consequently, no normal ogive models can be used.
generate_item_responses_sml(theta, scoringMatrix, slopes, intercepts)
theta |
a matrix of latent traits' values |
scoringMatrix |
a matrix describing scoring patterns on each latent trait |
slopes |
a vector of slope parameters of each trait |
intercepts |
a vector of intercept parameters |
a vector of responses on item
link{generate_test_responses}
,
generate_item_responses_sqn
,
generate_item_responeses_gpcm
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