Describe numeric variables

Source: R/describe.R

Describe numeric variables by several measures of central tendency and variability. If no variables are specified, all numeric (integer or double) variables are described.

describe(data, ..., na.rm = TRUE)

Arguments

data

a tibble or a tdcmm model

...

Variables to describe (column names). Leave empty to describe all numeric variables in data.

na.rm

a logical value indicating whether NA values should be stripped before the computation proceeds. Defaults to TRUE.

Value

a tdcmm model

Details

  • N: number of valid cases (i.e., all but missing)

  • Missing: number of NA cases

  • M: mean average

  • SD: standard deviation, sd

  • Min: minimum value, min

  • Q25: 25% quantile, quantile

  • Mdn: median average, same as 50% quantile

  • Q75: 75% quantile, quantile

  • Max: maximum value, max

  • Range: difference between Min and Max

  • CI_95_LL: \(M - Q(0.975) \times \frac{SD}{\sqrt{N}}\) where \(Q(0.975)\) denotes Student t's stats::quantile function with a probability of \(0.975\) and \(N-1\) degrees of freedom

  • CI_95_UL: \(M + Q(0.975) \times \frac{SD}{\sqrt{N}}\) where \(Q(0.975)\) denotes Student t's stats::quantile function with a probability of \(0.975\) and \(N-1\) degrees of freedom

  • Skewness: traditional Fisher-Pearson coefficient of skewness of valid cases as per \(\frac{\frac{1}{N} \sum\limits_{i=1}^N (x_{i}-\overline{x})^3}{[\frac{1}{N}\sum\limits_{i=1}^N (x_{i}-\overline{x})^2]^{3/2}}\) where \(\overline{x}\) denotes \(M\), following Doane & Seward, 2011, p. 6, 1a

  • Kurtosis: empirical sample kurtosis (i.e., standardized fourth population moment about the mean) as per \(\frac{\sum (x-\overline{x})^4 / N}{(\sum (x-\overline{x})^2 / N)^2}\), following DeCarlo, 1997, p. 292, b2

See also

Other descriptives: describe_cat(), tab_percentiles()

Examples

WoJ %>% describe(autonomy_selection, autonomy_emphasis, work_experience)
#> # A tibble: 3 × 15
#>   Variable            N Missing     M     SD   Min   Q25   Mdn   Q75   Max Range
#> * <chr>           <int>   <int> <dbl>  <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 autonomy_selec…  1197       3  3.88  0.803     1     4     4     4     5     4
#> 2 autonomy_empha…  1195       5  4.08  0.793     1     4     4     5     5     4
#> 3 work_experience  1187      13 17.8  10.9       1     8    17    25    53    52
#> # ℹ 4 more variables: CI_95_LL <dbl>, CI_95_UL <dbl>, Skewness <dbl>,
#> #   Kurtosis <dbl>
fbposts %>% describe(n_pictures)
#> # A tibble: 1 × 15
#>   Variable       N Missing     M    SD   Min   Q25   Mdn   Q75   Max Range
#> * <chr>      <int>   <int> <dbl> <dbl> <int> <dbl> <dbl> <dbl> <int> <int>
#> 1 n_pictures   270       0 0.952  1.47     0     0     1     1    12    12
#> # ℹ 4 more variables: CI_95_LL <dbl>, CI_95_UL <dbl>, Skewness <dbl>,
#> #   Kurtosis <dbl>