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This function returns a summary statistics tibble. It will use the y column from the tidy_ distribution function.

Usage

tidy_distribution_summary_tbl(.data, ...)

Arguments

.data

The data that is going to be passed from a a tidy_ distribution function.

...

This is the grouping variable that gets passed to dplyr::group_by() and dplyr::select().

Value

A summary stats tibble

Details

This function takes in a tidy_ distribution table and will return a tibble of the following information:

  • sim_number

  • mean_val

  • median_val

  • std_val

  • min_val

  • max_val

  • skewness

  • kurtosis

  • range

  • iqr

  • variance

  • ci_hi

  • ci_lo

The kurtosis and skewness come from the package healthyR.ai

Author

Steven P. Sanderson II, MPH

Examples

library(dplyr)
#> Warning: package 'dplyr' was built under R version 4.2.3
#> 
#> Attaching package: 'dplyr'
#> The following objects are masked from 'package:stats':
#> 
#>     filter, lag
#> The following objects are masked from 'package:base':
#> 
#>     intersect, setdiff, setequal, union

tn <- tidy_normal(.num_sims = 5)
tb <- tidy_beta(.num_sims = 5)

tidy_distribution_summary_tbl(tn)
#> # A tibble: 1 × 12
#>   mean_val median_val std_val min_val max_val skewness kurtosis range   iqr
#>      <dbl>      <dbl>   <dbl>   <dbl>   <dbl>    <dbl>    <dbl> <dbl> <dbl>
#> 1   0.0531      0.111    1.01   -2.66    3.25    0.128     3.05  5.90  1.35
#> # ℹ 3 more variables: variance <dbl>, ci_low <dbl>, ci_high <dbl>
tidy_distribution_summary_tbl(tn, sim_number)
#> # A tibble: 5 × 13
#>   sim_number mean_val median_val std_val min_val max_val skewness kurtosis range
#>   <fct>         <dbl>      <dbl>   <dbl>   <dbl>   <dbl>    <dbl>    <dbl> <dbl>
#> 1 1            0.235       0.235   1.03    -2.47    3.25    0.150     3.79  5.72
#> 2 2           -0.166      -0.209   0.842   -2.34    1.50   -0.254     2.93  3.85
#> 3 3            0.124       0.188   0.851   -1.55    2.04    0.233     2.65  3.60
#> 4 4           -0.0756     -0.117   1.17    -2.37    2.71    0.377     2.77  5.08
#> 5 5            0.148       0.284   1.11    -2.66    2.30   -0.123     2.41  4.96
#> # ℹ 4 more variables: iqr <dbl>, variance <dbl>, ci_low <dbl>, ci_high <dbl>

data_tbl <- tidy_combine_distributions(tn, tb)

tidy_distribution_summary_tbl(data_tbl)
#> # A tibble: 1 × 12
#>   mean_val median_val std_val min_val max_val skewness kurtosis range   iqr
#>      <dbl>      <dbl>   <dbl>   <dbl>   <dbl>    <dbl>    <dbl> <dbl> <dbl>
#> 1    0.275      0.336   0.778   -2.66    3.25   -0.516     4.65  5.90 0.724
#> # ℹ 3 more variables: variance <dbl>, ci_low <dbl>, ci_high <dbl>
tidy_distribution_summary_tbl(data_tbl, dist_type)
#> # A tibble: 2 × 13
#>   dist_type mean_val median_val std_val  min_val max_val skewness kurtosis range
#>   <fct>        <dbl>      <dbl>   <dbl>    <dbl>   <dbl>    <dbl>    <dbl> <dbl>
#> 1 Gaussian…   0.0531      0.111   1.01  -2.66      3.25    0.128      3.05 5.90 
#> 2 Beta c(1…   0.497       0.493   0.304  0.00583   0.999   0.0281     1.66 0.993
#> # ℹ 4 more variables: iqr <dbl>, variance <dbl>, ci_low <dbl>, ci_high <dbl>