| Title: | Sample Size Planning Based on Intrinsic Kappa Value |
| Version: | 0.1 |
| Maintainer: | David Schindler <dv.schindler@gmail.com> |
| Description: | Kappa statistics is one of the most used methods to evaluate the effectiveness of inpsections based on attribute assessments in industry. However, its estimation by available methods does not provide its "real" or "intrinstic" value. This package provides functions for the computation of the intrinsic kappa value as it is described in: Rafael Sanchez-Marquez, Frank Gerhorst and David Schindler (2023) "Effectiveness of quality inspections of attributive characteristics – A novel and practical method for estimating the “intrinsic” value of kappa based on alpha and beta statistics." <doi:10.1016/j.cie.2023.109006>. |
| License: | GPL (≥ 3) |
| Encoding: | UTF-8 |
| Depends: | R (≥ 4.2.0) |
| Imports: | stats |
| Suggests: | knitr, rmarkdown, utils |
| VignetteBuilder: | knitr |
| RoxygenNote: | 7.2.3 |
| NeedsCompilation: | no |
| Packaged: | 2023-06-01 11:13:06 UTC; DSCHIND2 |
| Author: | David Schindler [aut, cre], Rafael Sanchez-Marquez [aut], Frank Gerhorst [aut] |
| Repository: | CRAN |
| Date/Publication: | 2023-06-01 12:50:07 UTC |
Sample Size Planning Based on Intrinsic Kappa Value
Description
Providing functions for the computation of the intrinsic kappa value.
Author(s)
David Schindler dv.schindler@gmail.com, Rafael Sanchez-Marquez, Frank Gerhorst
References
R. Sanchez-Marquez, F. Gerhorst and D. Schindler (2023) "Effectiveness of quality inspections of attributive characteristics – A novel and practical method for estimating the “intrinsic” value of kappa based on alpha and beta statistics." Computers & Industrial Engineering, 109006.
See Also
For the computation of the intrinsic kappa value, see intrinsicKappa.
Compute Statistics
Description
Compute Statistics
Usage
computeStat(n1, n2, alpha)
Arguments
n1 |
integer |
n2 |
integer |
alpha |
one-sided significance level |
Intrinsic Kappa
Description
Intrinsic Kappa
Usage
intrinsicKappa(M, alpha = 0.05, alpha_adjusted = TRUE)
Arguments
M |
matrix to be assessed |
alpha |
one-sided significance level |
alpha_adjusted |
logical, whether the significance level shall be adjusted |
Details
Computation of intrinsic kappa with a dichotomous response and known relation of the input frequencies.
Value
Intrinsic kappa value
References
R. Sanchez-Marquez, F. Gerhorst and D. Schindler (2023) "Effectiveness of quality inspections of attributive characteristics – A novel and practical method for estimating the “intrinsic” value of kappa based on alpha and beta statistics." Computers & Industrial Engineering, 109006.
Examples
M <- matrix(c(2375, 25, 10, 2390), ncol = 2)
rownames(M) <- c('ok-rating', 'nok-rating')
colnames(M) <- c('ok-standard', 'nok-standard')
alpha <- 0.05
alpha_adjusted <- FALSE
intrinsicKappa(M, alpha, alpha_adjusted)