It is quite easy to generate tables of outputs for the various concurve functions and in different formats. Here we show how to do this with a simple example. First, we’ll simulate some fake data as usual, compare the means, and then produce a confidence function of the outputs.

library(concurve)
#> Please see the documentation on https://data.lesslikely.com/concurve/ or by typing `help(concurve)`
GroupA <- rnorm(500)
GroupB <- rnorm(500)
RandomData <- data.frame(GroupA, GroupB)

intervalsdf <- curve_mean(GroupA, GroupB,
  data = RandomData, method = "default"
)

The results are now stored in intervalsdf. Using the curve_table() function, we can now produce a high quality table with several values of interest.

(x <- curve_table(data = intervalsdf[[1]], format = "image"))

Lower Limit

Upper Limit

Interval Width

Interval Level (%)

CDF

P-value

S-value (bits)

0.070

0.111

0.041

25.0

0.625

0.750

0.415

0.047

0.134

0.087

50.0

0.750

0.500

1.000

0.016

0.164

0.148

75.0

0.875

0.250

2.000

0.008

0.173

0.165

80.0

0.900

0.200

2.322

-0.002

0.183

0.186

85.0

0.925

0.150

2.737

-0.016

0.196

0.212

90.0

0.950

0.100

3.322

-0.036

0.217

0.253

95.0

0.975

0.050

4.322

-0.054

0.235

0.289

97.5

0.988

0.025

5.322

-0.076

0.257

0.332

99.0

0.995

0.010

6.644

Here we specified the format as “image”, which will give us just that. We can also specify other options such as

(z <- curve_table(intervalsdf[[1]], format = "latex"))
Lower Limit Upper Limit Interval Width Interval Level (%) CDF P-value S-value (bits)
2501 0.070 0.111 0.041 25.0 0.625 0.750 0.415
5001 0.047 0.134 0.087 50.0 0.750 0.500 1.000
7501 0.016 0.164 0.148 75.0 0.875 0.250 2.000
8001 0.008 0.173 0.165 80.0 0.900 0.200 2.322
8501 -0.002 0.183 0.186 85.0 0.925 0.150 2.737
9001 -0.016 0.196 0.212 90.0 0.950 0.100 3.322
9501 -0.036 0.217 0.253 95.0 0.975 0.050 4.322
9751 -0.054 0.235 0.289 97.5 0.988 0.025 5.322
9901 -0.076 0.257 0.332 99.0 0.995 0.010 6.644

which is useful for inserting the output into a TeX document, and we can also specify options such as

(df <- curve_table(intervalsdf[[1]], format = "data.frame"))
#>      Lower Limit Upper Limit Interval Width Interval Level (%)   CDF P-value
#> 2501       0.070       0.111          0.041               25.0 0.625   0.750
#> 5001       0.047       0.134          0.087               50.0 0.750   0.500
#> 7501       0.016       0.164          0.148               75.0 0.875   0.250
#> 8001       0.008       0.173          0.165               80.0 0.900   0.200
#> 8501      -0.002       0.183          0.186               85.0 0.925   0.150
#> 9001      -0.016       0.196          0.212               90.0 0.950   0.100
#> 9501      -0.036       0.217          0.253               95.0 0.975   0.050
#> 9751      -0.054       0.235          0.289               97.5 0.988   0.025
#> 9901      -0.076       0.257          0.332               99.0 0.995   0.010
#>      S-value (bits)
#> 2501          0.415
#> 5001          1.000
#> 7501          2.000
#> 8001          2.322
#> 8501          2.737
#> 9001          3.322
#> 9501          4.322
#> 9751          5.322
#> 9901          6.644

The options “pptx” and “docx” can also be specified as format options, but specifying these will open those programs if they are installed, which may not be ideal for all because no everyone has access.

Cite R Packages

Please remember to cite the packages that you use.

citation("concurve")
#> 
#> Rafi Z, Vigotsky A (2020). _concurve: Computes and Plots Compatibility
#> (Confidence) Intervals, P-Values, S-Values, & Likelihood Intervals to
#> Form Consonance, Surprisal, & Likelihood Functions_. R package version
#> 2.7.7, <URL: https://CRAN.R-project.org/package=concurve>.
#> 
#> Rafi Z, Greenland S (2020). "Semantic and Cognitive Tools to Aid
#> Statistical Science: Replace Confidence and Significance by
#> Compatibility and Surprise." _BMC Medical Research Methodology_, *20*,
#> 244. ISSN 1471-2288, doi: 10.1186/s12874-020-01105-9 (URL:
#> https://doi.org/10.1186/s12874-020-01105-9), <URL:
#> https://doi.org/10.1186/s12874-020-01105-9>.
#> 
#> To see these entries in BibTeX format, use 'print(<citation>,
#> bibtex=TRUE)', 'toBibtex(.)', or set
#> 'options(citation.bibtex.max=999)'.
citation("flextable")
#> 
#> To cite package 'flextable' in publications use:
#> 
#>   David Gohel (2020). flextable: Functions for Tabular Reporting. R
#>   package version 0.5.11. https://CRAN.R-project.org/package=flextable
#> 
#> A BibTeX entry for LaTeX users is
#> 
#>   @Manual{,
#>     title = {flextable: Functions for Tabular Reporting},
#>     author = {David Gohel},
#>     year = {2020},
#>     note = {R package version 0.5.11},
#>     url = {https://CRAN.R-project.org/package=flextable},
#>   }
citation("officer")
#> 
#> To cite package 'officer' in publications use:
#> 
#>   David Gohel (2020). officer: Manipulation of Microsoft Word and
#>   PowerPoint Documents. R package version 0.3.14.
#>   https://CRAN.R-project.org/package=officer
#> 
#> A BibTeX entry for LaTeX users is
#> 
#>   @Manual{,
#>     title = {officer: Manipulation of Microsoft Word and PowerPoint Documents},
#>     author = {David Gohel},
#>     year = {2020},
#>     note = {R package version 0.3.14},
#>     url = {https://CRAN.R-project.org/package=officer},
#>   }

References