Groupwise means and confidence intervals

Calculates means and confidence intervals for groups.

Usage

groupwiseMean(
  formula = NULL,
  data = NULL,
  var = NULL,
  group = NULL,
  trim = 0,
  na.rm = FALSE,
  conf = 0.95,
  R = 5000,
  boot = FALSE,
  traditional = TRUE,
  normal = FALSE,
  basic = FALSE,
  percentile = FALSE,
  bca = FALSE,
  digits = 3,
  ...
)

Arguments

formula: A formula indicating the measurement variable and the grouping variables. e.g. y ~ x1 + x2.
data: The data frame to use.
var: The measurement variable to use. The name is in double quotes.
group: The grouping variable to use. The name is in double quotes. Multiple names are listed as a vector. (See example.)
trim: The proportion of observations trimmed from each end of the values before the mean is calculated. (As in mean())
na.rm: If TRUE, NA values are removed during calculations. (As in mean())
conf: The confidence interval to use.
R: The number of bootstrap replicates to use for bootstrapped statistics.
boot: If TRUE, includes the mean of the bootstrapped means. This can be used as an estimate of the mean for the group.
traditional: If TRUE, includes the traditional confidence intervals for the group means, using the t-distribution. If trim is not 0, the traditional confidence interval will produce NA. Likewise, if there are NA values that are not removed, the traditional confidence interval will produce NA.
normal: If TRUE, includes the normal confidence intervals for the group means by bootstrap. See boot.ci.
basic: If TRUE, includes the basic confidence intervals for the group means by bootstrap. See boot.ci.
percentile: If TRUE, includes the percentile confidence intervals for the group means by bootstrap. See boot.ci.
bca: If TRUE, includes the BCa confidence intervals for the group means by bootstrap. See boot.ci.
digits: The number of significant figures to use in output.
...: Other arguments passed to the boot function.

Value

A data frame of requested statistics by group.

Details

The input should include either formula and data; or data, var, and group. (See examples).

Results for ungrouped (one-sample) data can be obtained by either setting the right side of the formula to 1, e.g. y ~ 1, or by setting group=NULL when using var.

Note

The parsing of the formula is simplistic. The first variable on the left side is used as the measurement variable. The variables on the right side are used for the grouping variables.

In general, it is advisable to handle NA values before using this function. With some options, the function may not handle missing values well, or in the manner desired by the user. In particular, if bca=TRUE and there are NA values, the function may fail.

For a traditional method to calculate confidence intervals on trimmed means, see Rand Wilcox, Introduction to Robust Estimation and Hypothesis Testing.

References

https://rcompanion.org/handbook/C_03.html

Author

Salvatore Mangiafico, mangiafico@njaes.rutgers.edu

Examples

### Example with formula notation
data(Catbus)
groupwiseMean(Steps ~ Teacher + Gender,
              data        = Catbus,
              traditional = FALSE,
              percentile  = TRUE)
#>   Teacher Gender n Mean Conf.level Percentile.lower Percentile.upper
#> 1  Catbus female 6 8000       0.95             7000             9000
#> 2  Catbus   male 4 7000       0.95             5500             8500
#> 3 Satsuki female 4 8500       0.95             8000             9000
#> 4 Satsuki   male 3 7000       0.95             6000             8000
#> 5  Totoro female 5 8200       0.95             7000             9400
#> 6  Totoro   male 4 7000       0.95             6250             7750

### Example with variable notation
data(Catbus)
groupwiseMean(data        = Catbus,
              var         = "Steps",
              group       = c("Teacher", "Gender"),
              traditional = FALSE,
              percentile  = TRUE)
#>   Teacher Gender n Mean Conf.level Percentile.lower Percentile.upper
#> 1  Catbus female 6 8000       0.95             7000             9000
#> 2  Catbus   male 4 7000       0.95             5500             8500
#> 3 Satsuki female 4 8500       0.95             8000             9000
#> 4 Satsuki   male 3 7000       0.95             6000             8000
#> 5  Totoro female 5 8200       0.95             7000             9400
#> 6  Totoro   male 4 7000       0.95             6250             7750