View source: R/fmd_scaled_owANOVA.R
fmd_scaled_owANOVA | R Documentation |
This function calculates allometrically-scaled flow-mediated dilation responses for one-way ANOVA study designs and returns the corresponding comparisons between groups. The function will also return back-transformed means, standard errors, and 95% confidence intervals. Users must label the data set columns as "dpeak", "dbase", and "group" respectively. This Rtery
function also requires that users arrange data in long format.
fmd_scaled_owANOVA(dat)
dat |
data frame object; does not have to be named 'dat', but the columns that correspond to peak artery diameter, baseline artery diameter, and group (or condition) must be labeled "dpeak", "dbase", and "group", respectively. |
This function returns the following:
model.coef |
A dataframe continaing coefficients from the linear model |
main.effects |
A dataframe containing main effects and statistical contrasts |
transformed.emmeans |
Backtransformed estimated marginal means and model standard error |
plot |
Graphical representation using |
Simulated data with peak and baseline artery diameters from 12 participants:
EXAMPLE 1: Allometric scaling not required
dat <- data.frame(participant = c("P1", "P2", "P3", "P4", "P5", "P6", "P7", "P8", "P9", "P10", "P11", "P12"), dpeak = c(4.1, 3.2, 6.5, 5.9, 4.3, 2.1, 4.0, 6.3, 3.3, 4.9, 5.2, 7.1), dbase = c(4.0, 2.9, 6.0, 5.7, 4.1, 2.0, 3.7, 6.2, 3.2, 4.3, 5.1, 6.9), group = as.factor(c("NS", "NS", "NS", "NS", "SD", "SD", "SD", "SD", "SR", "SR", "SR", "SR")))
fmd_scaled_owANOVA(dat)
EXAMPLE 2: Allometric scaling required and calculated:
dat <- data.frame(dpeak = rnorm(30, 4.27, 1.12), dbase = rnorm(30, 4.16, 1.21)*0.8, group = as.factor(c(rep("NS", 10), rep("SD", 10), rep("SR", 10))))
fmd_scaled_owANOVA(dat)
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