draw_sample_ir {drawsample} | R Documentation |
Sample data with individual responses
Description
A Function to sample data close to desired characteristics with individual responses.
Usage
draw_sample_ir(
dist,
n,
skew,
kurts,
replacement = FALSE,
col_id = 1,
col_total = numeric(),
save.output = FALSE,
output_name = c("sample", "1")
)
Arguments
dist |
data frame:consists of id and scores with no missing |
n |
numeric: desired sample size |
skew |
numeric: the skewness value |
kurts |
numeric: the kurtosis value |
replacement |
logical:Sample with or without replacement? (default is FALSE). |
col_id |
index of column ID's |
col_total |
index of column total score |
save.output |
logical: should the output be saved into a text file? (Default is FALSE). |
output_name |
character: a vector of two components. The first component is the name of the output file, user can change the second component. |
Details
The execution of the function may take some time since it tries to obtain the specified value for skewness and kurtosis.
Value
This function returns a list
including following:
a matrix: Descriptive statistics of the given data, the reference vector and the sample.
a data frame: The id's and individual response of the sample.
graph: Histograms for the “data” and the “sample”
References
Fleishman AI (1978). A Method for Simulating Non-normal Distributions. Psychometrika, 43, 521-532. doi:10.1007/BF02293811.
Fialkowski, A. C. (2018). SimMultiCorrData: Simulation of Correlated Data with Multiple #' Variable Types. R package version 0.2.2. Retrieved from https://cran.r-project.org/web/packages/SimMultiCorrData/index.html
Atalay Kabasakal, K. & Gunduz, T. (2020). Drawing a Sample with Desired Properties from Population in R Package “drawsample”.Journal of Measurement and Evaluation in Education and Psychology,11(4),405-429. doi:10.21031/epod.790449
Examples
## Not run:
# Example data provided with package
data(likert_example)
# First 6 rows of the example_data
head(likert_example)
# Draw a sample based on total(from flattened to normal)
output3 <- draw_sample_ir(dist=likert_example,n=200,skew = 1,kurts = 1.2,
col_id=1,col_total=7,save.output = FALSE) # Histogram of the reference data set
# descriptive statistics of the given data,reference data, and drawn sample
output3$desc
# First 6 rows of the drawn sample
head(output3$sample)
# Histogram of the given data set and drawn sample
output3$graph
# Draw a sample based on total(from flattened to normal)
draw_sample_ir(dist=likert_example,n=200,skew = 0.5,kurts =0.5,
col_id=1,col_total=7,save.output = TRUE,
output_name = c("sample", "3"))
## End(Not run)