RCI {LogisticRCI} | R Documentation |
Calculate the Linear or Logistic Regression-Based Reliable Change Index (RCI)
Description
This function calculates the RCI for lm
and binomial glm
objects.
Usage
RCI(model)
Arguments
model |
An |
Details
This function takes a fitted model object as input and computes either the linear (for lm
objects) or logistic (for binomial glm
) regression-based reliable change index for each observation.
Value
The function returns a numeric vector.
Author(s)
Rafael A. Moral, Unai Diaz-Orueta and Javier Oltra-Cucarella.
References
Moral, R.A., Diaz-Orueta, U., Oltra-Cucarella, J. (preprint) Logistic versus linear regression-based Reliable Change Index: implications for clinical studies with diverse sample sizes. DOI: 10.31234/osf.io/gq7az
Examples
data(RCI_sample_data)
linear_fit <- lm(score ~ baseline + age + gender + education,
data = RCI_sample_data)
logistic_fit <- glm(cbind(score, 15 - score) ~ baseline + age + gender + education,
family = binomial,
data = RCI_sample_data)
linear_RCI <- RCI(linear_fit)
logistic_RCI <- RCI(logistic_fit)
plot(linear_RCI, logistic_RCI)
[Package LogisticRCI version 1.1 Index]