cor_est | R Documentation |
cor_est
Calculates the correlation coefficient and
standard error to be used in function with.miceafter
.
cor_est(y, x, data, method = "pearson", se_method = "normal")
y |
name of numeric vector variable. |
x |
name of numeric vector variable. |
data |
An objects of class |
method |
a character string indicating which correlation coefficient is used for the test. One of "pearson" (default), "kendall", or "spearman". |
se_method |
Method to calculate standard error. See details. |
The basic method to calculate the standard error is by:
se = √(\frac{1}{n-3})
For the Spearman correlation coefficients se_method "fieller" is calculated as:
se = √(\frac{1.06}{n-3})
For the Kendall correlation coefficients se_method "fieller" is calculated as:
se = √(\frac{0.437}{n-4})
The correlation coefficient, standard error and complete data degrees of freedom (dfcom).
Martijn Heymans, 2022
with.milist
, pool_cor
imp_dat <- df2milist(lbpmilr, impvar="Impnr") ra <- with(imp_dat, expr=cor_est(y=BMI, x=Age))
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