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)a tdcmm model
a tibble or a tdcmm model
Variables to describe (column names). Leave empty to describe all numeric variables in data.
a logical value indicating whether NA values should be stripped
before the computation proceeds. Defaults to TRUE.
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). See DOI tools:::Rd_expr_doi("10.1080/10691898.2011.11889611").
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 DOI tools:::Rd_expr_doi("10.1037/1082-989X.2.3.292").
Other descriptives:
describe_cat(),
tab_percentiles()
WoJ %>% describe(autonomy_selection, autonomy_emphasis, work_experience)
fbposts %>% describe(n_pictures)
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