stats.default {table1}

Compute some basic descriptive statistics.

Description

Values of type factor, character and logical are treated as categorical. For logicals, the two categories are given the labels 'Yes' for TRUE, and 'No' for FALSE. Factor levels with zero counts are retained.

Usage

stats.default(x, quantile.type = 7, ...)

Arguments

x

A vector or numeric, factor, character or logical values.

quantile.type

An integer from 1 to 9, passed as the type argument to function quantile.

...

Further arguments (ignored).

Value

A list. For numeric x, the list contains the numeric elements:

• N: the number of non-missing values

• NMISS: the number of missing values

• SUM: the sum of the non-missing values

• MEAN: the mean of the non-missing values

• SD: the standard deviation of the non-missing values

• MIN: the minimum of the non-missing values

• MEDIAN: the median of the non-missing values

• CV: the percent coefficient of variation of the non-missing values

• GMEAN: the geometric mean of the non-missing values if non-negative, or NA

• GSD: the geometric standard deviation of the non-missing values if non-negative, or NA

• GCV: the percent geometric coefficient of variation of the non-missing values if non-negative, or NA

• qXX: various quantiles (percentiles) of the non-missing values (q01: 1%, q02.5: 2.5%, q05: 5%, q10: 10%, q25: 25% (first quartile), q33.3: 33.33333% (first tertile), q50: 50% (median, or second quartile), q66.7: 66.66667% (second tertile), q75: 75% (third quartile), q90: 90%, q95: 95%, q97.5: 97.5%, q99: 99%)

• Q1: the first quartile of the non-missing values (alias q25)

• Q2: the second quartile of the non-missing values (alias q50 or Median)

• Q3: the third quartile of the non-missing values (alias q75)

• IQR: the inter-quartile range of the non-missing values (i.e., Q3 - Q1)

• T1: the first tertile of the non-missing values (alias q33.3)

• T2: the second tertile of the non-missing values (alias q66.7)

If x is categorical (i.e. factor, character or logical), the list contains a sublist for each category, where each sublist contains the numeric elements:

• FREQ: the frequency count

• PCT: the percent relative frequency, including NA in the denominator

• PCTnoNA: the percent relative frequency, excluding NA from the denominator

• NMISS: the number of missing values

Examples

x <- exp(rnorm(100, 1, 1))
stats.default(x)

y <- factor(sample(0:1, 99, replace=TRUE), labels=c("Female", "Male"))
y[1:10] <- NA
stats.default(y)
stats.default(is.na(y))