NewBorn: Respiratory Physiotherapy on Premature Newborns
In mcglm: Multivariate Covariance Generalized Linear Models

NewBorn

R Documentation

Respiratory Physiotherapy on Premature Newborns

Description

The NewBorn dataset is from a prospective study assessing the effect of respiratory physiotherapy on cardiopulmonary function in ventilated preterm newborn infants with birth weight less than 1500 g. The dataset was collected by the nursing team of Waldemar Monastier Hospital, Campo Largo, PR, Brazil, and analyzed in Bonat and Jorgensen (2016) as an example of mixed outcomes regression models.

Usage

data(NewBorn)

Format

A data.frame with 270 observations and 21 variables:

Sex: Factor with levels Female and Male.
GA: Gestational age in weeks.
BW: Birth weight in grams.
APGAR1M: APGAR index at the first minute of life.
APGAR5M: APGAR index at the fifth minute of life.
PRE: Factor indicating prematurity (YES/NO).
HD: Factor indicating Hansen's disease (YES/NO).
SUR: Factor indicating surfactant administration (YES/NO).
JAU: Factor indicating jaundice (YES/NO).
PNE: Factor indicating pneumonia (YES/NO).
PDA: Factor indicating persistence of ductus arteriosus (YES/NO).
PPI: Factor indicating primary pulmonary infection (YES/NO).
OTHERS: Factor indicating other diseases (YES/NO).
DAYS: Age in days.
AUX: Factor indicating type of respiratory auxiliary (HOOD/OTHERS).
RR: Respiratory rate (continuous).
HR: Heart rate (continuous).
SPO2: Oxygen saturation (bounded).
TREAT: Factor with three levels: Respiratory physiotherapy, Evaluation 1, Evaluation 2, Evaluation 3.
NBI: Newborn index.
TIME: Days of treatment.

Source

Bonat, W. H. and Jorgensen, B. (2016). "Multivariate covariance generalized linear models." Journal of Royal Statistical Society, Series C, 65:649–675.

Examples

library(mcglm)
library(Matrix)
data(NewBorn, package = "mcglm")

# Linear predictor example
formu <- SPO2 ~ Sex + APGAR1M + APGAR5M + PRE + HD + SUR
Z0 <- mc_id(NewBorn)
fit <- mcglm(
  linear_pred = c(formu),
  matrix_pred = list(Z0),
  link = "logit",
  variance = "binomialP",
  power_fixed = TRUE,
  data = NewBorn,
  control_algorithm = list(verbose = FALSE, tuning = 0.5)
)
summary(fit)

mcglm documentation built on Jan. 9, 2026, 1:07 a.m.