pool_cor | R Documentation |
pool_cor
Calculates the pooled correlation coefficient and
Confidence intervals.
pool_cor( data, conf.level = 0.95, dfcom = NULL, statistic = TRUE, df_small = TRUE, approxim = "tdistr" )
data |
An object of class 'mistats' ('Multiply Imputed Statistical Analysis'.) or a m x 2 matrix with C-index values and standard errors in the first and second column. For the latter option dfcom has to be provided. |
conf.level |
conf.level Confidence level of the confidence intervals. |
dfcom |
Number of completed-data analysis degrees of freedom.
Default number is taken from function |
statistic |
if TRUE (default) the test statistic and p-value are provided, if FALSE these are not shown. See details. |
df_small |
if TRUE (default) the (Barnard & Rubin) small sample correction for the degrees of freedom is applied, if FALSE the old number of degrees of freedom is calculated. |
approxim |
if "tdistr" a t-distribution is used (default), if "zdistr" a z-distribution is used to derive a p-value for the test statistic. |
Rubin's Rules are used for pooling. The correlation coefficient is
first transformed using Fisher z transformation (function cor2fz
) before
pooling and finally back transformed (function fz2cor
). The test
statistic and p-values are obtained using the Fisher z transformation.
An object of class mipool
from which the following objects
can be extracted:
cor
correlation coefficient
SE
standard error
t
t-value (for confidence interval)
low_r
lower limit of confidence interval
high_r
upper limit of confidence interval
statistic
test statistic
pval
p-value
Martijn Heymans, 2022
with.milist
, cor_est
imp_dat <- df2milist(lbpmilr, impvar="Impnr") res_stats <- with(data=imp_dat, expr = cor_est(y=BMI, x=Age)) res <- pool_cor(res_stats) res
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