epm | R Documentation |
A simulated dataset, based on the the simRasch function. The data were generated on the basis of a 1PL IRT model with 50 items with a normal distribution and a mean difficulty of m = 0 and sd = 1 and 1400 cases. The age trajectory features a curve linear increase wit a slight scissor effect. The sample consists of seven age groups with 200 cases each and it includes information on the latent ability, the age specific latent ability and norm scores based on conventional norming with differing granularity of the age brackets.
epm
A data frame with 1400 rows and 10 variables:
the raw score
the age specific latent ability, z standardized
the overall latent trait with respect to the population model
the chronological age
grouping variable based on six month age brackets
Resulting norm score of cNORM, based on the automatic model selection
conventional T scores on the basis of one month age brackets
conventional T scores on the basis of three month age brackets
conventional T scores on the basis of six month age brackets
conventional T scores on the basis of one year age brackets
A data frame with 1400 rows and 10 columns
Lenhard, W. & Lenhard, A. (2020). Improvement of Norm Score Quality via Regression-Based Continuous Norming. Educational and Psychological Measurement. https://doi.org/10.1177/0013164420928457
## Not run:
# Example with continuous age variable
data.epm <- prepareData(epm, raw=epm$raw, group=epm$halfYearGroup, age=epm$age)
model.epm <- bestModel(data.epm)
## End(Not run)
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