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isBalanced: Check a Design for Balance

Description

Check the design of the experiment or study for balance.

Usage

isBalanced(object, countOnly, level)

Value

TRUE or FALSE according to whether the data are balanced or not

Arguments

object

A groupedData object containing a data frame and a formula that describes the roles of variables in the data frame. The object will have one or more nested grouping factors and a primary covariate.

countOnly

A logical value indicating if the check for balance should only consider the number of observations at each level of the grouping factor(s). Defaults to FALSE.

level

an optional integer vector specifying the desired prediction levels. Levels increase from outermost to innermost grouping, with level 0 representing the population (fixed effects) predictions. Defaults to the innermost level.

Author

José Pinheiro and Douglas Bates bates@stat.wisc.edu

Details

A design is balanced with respect to the grouping factor(s) if there are the same number of observations at each distinct value of the grouping factor or each combination of distinct levels of the nested grouping factors. If countOnly is FALSE the design is also checked for balance with respect to the primary covariate, which is often the time of the observation. A design is balanced with respect to the grouping factor and the covariate if the number of observations at each distinct level (or combination of levels for nested factors) is constant and the times at which the observations are taken (in general, the values of the primary covariates) also are constant.

See Also

table, groupedData

Examples

Run this code
isBalanced(Orthodont)                    # should return TRUE
isBalanced(Orthodont, countOnly = TRUE)  # should return TRUE
isBalanced(Pixel)                        # should return FALSE
isBalanced(Pixel, level = 1)             # should return FALSE

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