Description Usage Arguments Details Value References Examples
Point-Biserial correlation coefficient is a correlation coefficient used when one variable is continuous and the other variable is dichotomous.
1 | biserial.cor(x, y, use = c("all.obs", "complete.obs"), level = 1)
|
x |
a numeric vector representing the continuous variable. |
y |
a numeric vector representing the dichotomous variable. |
use |
Is a option for the use of missing values. |
level |
which level of y to use. |
It is calculated by applying the Pearson correlation coefficient to the case where one of the variables has dichotomous nature. It is calculated as
r_{xy} = (\bar{x}_p - \bar{x}_q / S_x)*√{pq}
where p is the proportion of subjects with one of the two possible values of the variable Y, q is the proportion of subjects with the other possible value,
\bar{x}_p
and
\bar{x}_q
is the average X subjects whose proportion is p and q respectively, and $S_x$ is the standard deviation of all subjects X. This function was adapted from ltm_1.0 package.
The value of the point-biserial correlation.
U.Olsson, F.Drasgow, and N.Dorans (1982). The polyserial correlation coefficient. Psychometrika, 47:337-347.
Cox. N.R. (1974). Estimation of the Correlation between a Continuous and a Discrete Variable. Biometrics, 30:171-178.
1 2 | data <- simulateTest(model="2PL",items=10,individuals=1000)
biserial.cor(rowSums(data$test), data$test[,1])
|
[1] -0.399795
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