or_glm: Calculate Odds Ratios of Generalized Linear (Mixed) Models

In pat-s/oddsratio: Odds Ratio Calculation for GAM(M)s & GLM(M)s

Calculate Odds Ratios of Generalized Linear (Mixed) Models

Description

This function calculates odds ratio(s) for specific increment steps of GLMs.

Usage

or_glm(data, model, incr, ci = 0.95)

Arguments

data	The data used for model fitting.
model	A fitted GLM(M).
incr	Increment values of each predictor given in a named list.
ci	Which confidence interval to calculate. Must be between 0 and 1. Default to 0.95

Details

ci_low and ci_high are only calculated for GLM models because MASS::glmmPQL() does not return confident intervals due to its penalizing behavior.

Currently supported functions: stats::glm,MASS::glmmPQL

Value

A data frame with five columns:

predictor	Predictor name(s)
oddsratio	Calculated odds ratio(s)
ci_low	Lower confident interval of odds ratio
ci_high	Higher confident interval of odds ratio
increment	Increment of the predictor(s)

See Also

or_gam()

Examples

## Example with glm()
library(oddsratio)
# load data (source: http://www.ats.ucla.edu/stat/r/dae/logit.htm) and
# fit model
fit_glm <- glm(admit ~ gre + gpa + rank,
  data = data_glm,
  family = "binomial"
) # fit model

# Calculate OR for specific increment step of continuous variable
or_glm(data = data_glm, model = fit_glm, incr = list(gre = 380, gpa = 5))

# Calculate OR and change the confidence interval level
or_glm(
  data = data_glm, model = fit_glm,
  incr = list(gre = 380, gpa = 5), ci = .70
)

## Example with MASS:glmmPQL()
# load data
library(MASS)
data(bacteria)
fit_glmmPQL <- glmmPQL(y ~ trt + week,
  random = ~ 1 | ID,
  family = binomial, data = bacteria,
  verbose = FALSE
)

# Apply function
or_glm(data = bacteria, model = fit_glmmPQL, incr = list(week = 5))

pat-s/oddsratio documentation built on April 19, 2024, 8:46 p.m.