Description Usage Arguments Author(s) Examples
Calculating Pearson product-moment correlation coefficient.
1 2 | corr_p_cell(x, y, z, w, cell_ids, row_ids, col_ids, vnames, vars, n_min,
digits = 3)
|
x |
The x variable |
y |
The y variable |
z |
NOT USED |
w |
Weights for x and y variable. |
cell_ids |
Index vector for selecting values in cell. |
row_ids |
NOT USED |
col_ids |
NOT USED |
vnames |
NOT USED |
vars |
NOT USED |
n_min |
Minimum n in the cell for useful calculation. Cells with n<n_min deliver no output. |
digits |
Integer indicating the number of decimal places. |
Andreas Schulz <ades-s@web.de>
1 2 3 4 5 6 7 8 9 | sex <- factor(rbinom(1000, 1, 0.4), labels=c('Men', 'Women'))
height <- rnorm(1000, mean=1.70, sd=0.1)
weight <- rnorm(1000, mean=70, sd=5)
bmi <- weight/height^2
d<-data.frame(sex, bmi, height, weight)
tabular.ade(x_vars=c('bmi','height','weight'), xname=c('BMI','Height','Weight'),
y_vars=c('bmi','height','weight'), yname=c('BMI','Height','Weight'),
rows=c('sex','ALL'), rnames=c('Gender'), data=d, FUN=corr_p_cell)
|
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