View source: R/mcnemartestClust.R
mcnemartestClust | R Documentation |
Performs a test of marginal homogeneity of paired clustered data with potentially informative cluster size.
mcnemartestClust(x, y, id, variance = c("MoM", "emp"))
x, y |
vector or factor objects of equal length. |
id |
a vector or factor object which identifies the clusters. The length of |
variance |
character string specifying the method of variance estimation. Must be one of " |
The null is that the marginal probabilities of being classified into cells [i,j]
and
[j,i]
are equal.
Arguments x
, y
, and id
must be vectors or factors of the same length.
Incomplete cases are removed.
When variance
is MoM
, a method of moments variance estimate evaluated under the null is used.
This is equivalent to the test by Durkalski et al. (2003). When variance
is emp
,
an empirical variance estimate is used. See Gregg (2020) for details.
A list with class "htest
" containing the following components:
statistic |
the value of the test statistic. |
parameter |
the degrees of freedom of the approximate chi-squared distribution of the test statistic. |
p.value |
the p-value of the test. |
method |
a character string indicating the test performed and which variance estimation method was used. |
data.name |
a character string giving the name(s) of the data and the total number of clusters. |
M |
the number of clusters. |
Durkalski, V., Palesch, Y., Lipsitz, S., Rust, P. (2003). Analysis of clustered matched pair data. Statistics in Medicine, 22, 2417–2428.
Gregg, M., Marginal methods and software for clustered data with cluster- and group-size informativeness. PhD dissertation, University of Louisville, 2020.
data(screen8) ## Is marginal proportion of students in lowest fitness category ## at the end of year equal to the beginning of year? screen8$low.start <- 1*(screen8$qfit.s=='Q1') screen8$low.end <- 1*(screen8$qfit=='Q1') mcnemartestClust(screen8$low.start, screen8$low.end, screen8$sch.id)
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