draw_sample_n_ir: Sample data close to desired characteristics with individual...

In drawsample: Draw Samples with the Desired Properties from a Data Set

Sample data close to desired characteristics with individual responses - nearest

Description

A function to sample data with desired properties.

Usage

draw_sample_n_ir(
  dist,
  n,
  skew,
  kurts,
  location = 0,
  delta_var = 0,
  col_id = 1,
  col_total = numeric(),
  save.output = FALSE,
  output_name = c("sample", "default")
)

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
location	numeric: the value for adjusting mean (default is 0).
delta_var	numeric: the value for adjusting variance (default is 0).
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 desired skewness and kurtosis values cannot be met while the function execution is faster. The attributes of kurtosis are in doubt. This is because the range of kurtosis is greater than the skewness.

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 scores 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

# Example data provided with package
data(likert_example)
# First 6 rows of the example_data
head(likert_example)
# Draw a sample based on Score_1(from negatively skewed to normal)
output4 <- draw_sample_n_ir(dist=likert_example,n=200,skew = 0,kurts = 0,
location= 0,delta_var = 0,
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
output4$desc
# First 6 rows of the drawn sample
head(output4$sample)
# Histogram of the given data set and drawn sample
output4$graph
## Not run: 
output4 <- draw_sample_n_ir(dist=likert_example,n=200,skew = 0.5,kurts = 0.5,
location= 0,delta_var = 0,
col_id=1,col_total=7,save.output=TRUE,
output_name = c("sample", "1")) 

## End(Not run)

drawsample documentation built on Sept. 6, 2022, 1:06 a.m.