Gore Test
Performs Gore's test. The null hypothesis H_0: θ_i = θ_j~~(i \ne j) is tested against the alternative H_{\mathrm{A}}: θ_i \ne θ_j, with at least one inequality beeing strict.
goreTest(y, groups, blocks)
y |
a numeric vector of data values. |
groups |
a vector or factor object giving the group for the
corresponding elements of |
blocks |
a vector or factor object giving the group for the
corresponding elements of |
The function has implemented Gore's test for testing main effects in unbalanced CRB designs, i.e. there are one ore more observations per cell. The statistic is assymptotically chi-squared distributed.
A list with class "htest"
containing the following components:
a character string indicating what type of test was performed.
a character string giving the name(s) of the data.
the estimated quantile of the test statistic.
the p-value for the test.
the parameters of the test statistic, if any.
a character string describing the alternative hypothesis.
the estimates, if any.
the estimate under the null hypothesis, if any.
Gore, A. P. (1975) Some nonparametric tests and selection procedures for main effects in two-way layouts. Ann. Inst. Stat. Math. 27, 487–500.
## Crop Yield of 3 varieties on two ## soil classes X <-c("130,A,Light 115,A,Light 123,A,Light 142,A,Light 117,A,Heavy 125,A,Heavy 139,A,Heavy 108,B,Light 114,B,Light 124,B,Light 106,B,Light 91,B,Heavy 111,B,Heavy 110,B,Heavy 155,C,Light 146,C,Light 151,C,Light 165,C,Light 97,C,Heavy 108,C,Heavy") con <- textConnection(X) x <- read.table(con, header=FALSE, sep=",") close(con) colnames(x) <- c("Yield", "Variety", "SoilType") goreTest(y = x$Yield, groups = x$Variety, blocks = x$SoilType)
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