Summarize Mediation Analysis Results — summary.mm • multimediate

summary.mm is used to display the results of the mediation analyzes done with multimediate.

Usage

## S3 method for class 'mm'
summary(object, opt = "navg", logit = "all", ...)

Arguments

object: element of the class mm.
opt: a character string indicating the details of the analysis "navg" for the average causal effects for t=0,1 and "avg" for the average causal effects.
logit: a character string indicating, when the outcome is binary, the scale of the average causal effects. "effects" for average causal effects, " OR" average causal effects on OR scale, "logOR" average causal effects on logOR scale and "all" for all scale.
...: additional arguments affecting the summary produced

Value

table summarizing the causal analysis

Examples

# Load example data
data(data2)
data2$Treatment <- as.factor(data2$Treatment)
data2$C1 <- as.factor(data2$C1)
data2$C2 <- as.factor(data2$C2)
data2$C3 <- as.factor(data2$C3)
data2$M1 <- as.numeric(data2$M1)
data2$M2 <- as.numeric(data2$M2)
data2$M3 <- as.numeric(data2$M3)
data2$Outcome <- as.factor(data2$Outcome)

# Fit mediator models
M1reg <- lm(M1 ~ Treatment + C1, data = data2)
M2reg <- lm(M2 ~ Treatment + C2, data = data2)
M3reg <- lm(M3 ~ Treatment + C3, data = data2)

# Fit outcome model (binary outcome)
Yreg <- glm(Outcome ~ Treatment + M1 + M2 + M3 + C1 + C2 + C3, 
               data = data2, family = binomial("logit"))

# Perform multiple mediation analysis
med.analysis <- multimediate(
  lmodel.m = list(M1reg, M2reg, M3reg),
  correlated = TRUE,
  model.y = Yreg,
  treat = "Treatment",
  treat.value = 1,
  control.value = 0,
  J = 100,
  conf.level = 0.95
)

# Different summary options
summary(med.analysis, opt = "avg", logit = "effects")
summary(med.analysis, opt = "avg", logit = "OR")
summary(med.analysis, opt = "avg", logit = "all")