drawsample (version 1.0.2)

draw_sample_ir: 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")
)

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”

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.

References

Fleishman AI (1978). A Method for Simulating Non-normal Distributions. Psychometrika, 43, 521-532. tools:::Rd_expr_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. tools:::Rd_expr_doi("10.21031/epod.790449")

Examples

if (FALSE) {
# 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"))
}