cor_est: Calculates the correlation coefficient

In miceafter: Data and Statistical Analyses after Multiple Imputation

Calculates the correlation coefficient

Description

cor_est Calculates the correlation coefficient and standard error to be used in function with.miceafter.

Usage

cor_est(y, x, data, method = "pearson", se_method = "normal")

Arguments

y	name of numeric vector variable.
x	name of numeric vector variable.
data	An objects of class milist, created by df2milist, list2milist or mids2milist.
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.

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})

Value

The correlation coefficient, standard error and complete data degrees of freedom (dfcom).

Author(s)

Martijn Heymans, 2022

See Also

with.milist, pool_cor

Examples

imp_dat <- df2milist(lbpmilr, impvar="Impnr")
ra <- with(imp_dat, expr=cor_est(y=BMI, x=Age))

miceafter documentation built on Oct. 2, 2022, 5:08 p.m.