For a given table one can specify which of the classifying factors to expand by one or more levels to hold margins to be calculated. One may for example form sums and means over the first dimension and medians over the second. The resulting table will then have two extra levels for the first dimension and one extra level for the second. The default is to sum over all margins in the table. Other possibilities may give results that depend on the order in which the margins are computed. This is flagged in the printed output from the function.
table or array. The function uses the presence of the
vector of dimensions over which to form margins. Margins
are formed in the order in which dimensions are specified in
logical which suppresses the message telling the order in which the margins were computed.
If the functions used to form margins are not commutative the result
depends on the order in which margins are computed. Annotation
of margins is done via naming the
array with the same number of
with extra levels of the dimensions mentioned in
number of levels added to each dimension is the length of the entries
FUN. A message with the order of computation of margins is
Bendix Carstensen, Steno Diabetes Center & Department of Biostatistics, University of Copenhagen, https://BendixCarstensen.com, autumn 2003. Margin naming enhanced by Duncan Murdoch.
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Aye <- sample(c("Yes", "Si", "Oui"), 177, replace = TRUE) Bee <- sample(c("Hum", "Buzz"), 177, replace = TRUE) Sea <- sample(c("White", "Black", "Red", "Dead"), 177, replace = TRUE) (A <- table(Aye, Bee, Sea)) (aA <- addmargins(A)) ftable(A) ftable(aA) # Non-commutative functions - note differences between resulting tables: ftable( addmargins(A, c(3, 1), FUN = list(list(Min = min, Max = max), Sum = sum))) ftable( addmargins(A, c(1, 3), FUN = list(Sum = sum, list(Min = min, Max = max)))) # Weird function needed to return the N when computing percentages sqsm <- function(x) sum(x)^2/100 B <- table(Sea, Bee) round(sweep(addmargins(B, 1, list(list(All = sum, N = sqsm))), 2, apply(B, 2, sum)/100, "/"), 1) round(sweep(addmargins(B, 2, list(list(All = sum, N = sqsm))), 1, apply(B, 1, sum)/100, "/"), 1) # A total over Bee requires formation of the Bee-margin first: mB <- addmargins(B, 2, FUN = list(list(Total = sum))) round(ftable(sweep(addmargins(mB, 1, list(list(All = sum, N = sqsm))), 2, apply(mB, 2, sum)/100, "/")), 1) ## Zero.Printing table+margins: set.seed(1) x <- sample( 1:7, 20, replace = TRUE) y <- sample( 1:7, 20, replace = TRUE) tx <- addmargins( table(x, y) ) print(tx, zero.print = ".")
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