Description Usage Arguments Details Value Examples
View source: R/sim_score_data.R
This function will simulate Person (raw)-scores for an arbitrary number of dimensions (latent variables), assessed with any type of questionnaire given the maximum and minimum raw score for each dimension.
1 2 3 4 5 6 7 8 | sim_score_data(
n = 1000,
cormat,
min.score = 0,
max.score = 40,
data.frame = FALSE,
...
)
|
n |
integer giving the number of cases (observations) in the data to simulate. |
cormat |
a correlation matrix describing the associations between the dimensions – for Hollnd's theory, typical a 6 x 6 matrix with named columns and rows with |
min.score |
numeric (possibly vector with max length == ncol(cormat) – will be recycled) with numeric value(s) defining the minimum raw scores per dimension |
max.score |
numeric (possibly vector with max length == ncol(cormat) – will be recycled) with numeric value(s) defining the maximum raw scores per dimension. |
data.frame |
logical whether to return a |
... |
additional parameters passed through to |
For Hollnd's theory, six dimensions (c("R","I","A","S","E","C")
) are assumed being assessed with an questionnaire with 10 questions per dimension with each question having five response categories which are scored from '0' to '4' – thus min. raw score is 0 and max. rax score is 40 for each of the six dimension respectively.
a data.frame
with simulated raw scores.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 | # get an RIASEC correlation matrix
data(AIST_2005_F_1270)
# simulate raw scores with minimum = 0 and maximum = 40
a<-sim_score_data(n=1000,cormat=AIST_2005_F_1270)
apply(a, 2, range)
apply(a, 2, mean)
apply(a, 2, sd)
# simulate raw scores with minimum = 10 and maximum = 50
b<-sim_score_data(n=1000,cormat=AIST_2005_F_1270,min.score=10,max.score=50)
apply(b, 2, range)
apply(b, 2, mean)
apply(b, 2, sd)
# simulate norm scores (range between 70 and 130)
c<-sim_score_data(n=1000,cormat=AIST_2005_M_1226,min.score=70,max.score=130)
apply(c, 2, range)
apply(c, 2, mean)
apply(c, 2, sd)
|
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.