mma (version 1.0-0)

summary.mma: Summary of an mma project

Description

Compute the estimations, standard deviations and confidence intervals of the mediation effects.

Usage

## S3 method for class 'mma':
summary(object,..., alpha=0.05)

Arguments

object

a mma object created initially call to mma, boot.met.binx, or boot.met.contx.

...

other arguments passed to the print function.

alpha

the alpha level for confidence interval.

Value

• Return a list. In each of the following item, est is the estimation of the corresponding mediation effects based on the whole data, mean is the average estimated effects from the bootstrap samples, sd is the standard deviation of the estimates from the bootstrap sample. upbd and lwbd are the upper and lower bound of the confidence interval of the estimation using parametric method from the bootstrap sample, upbd_q and lwbd_q are the corresponding quantiles of the estimation from the bootstrap sample.
• ie
  a matrix of statistics inference on the indirect effects from the mma object.
• te
  statistics inference on the total effects from the mma object.
• de
  statistics inference on the direct effects from the mma object.

Details

summary.mma gives a list of the estimations and summary statistics based on the bootstrap results.

References

Yu, Q., Fan, Y., and Wu, X. (2014). "General Multiple Mediation Analysis With an Application to Explore Racial Disparity in Breast Cancer Survival," Journal of Biometrics & Biostatistics,5(2): 189.

See Also

"mma","boot.med.binx" , "boot.met.contx"

Examples

data("weight_behavior")
 x=weight_behavior[,2:14]
 y=weight_behavior[,15]
 temp.b.b.glm<-mma(x,y,pred=2,contmed=c(8:10,12:13),binmed=c(7,11),
   binref=c(1,1),catmed=6,catref=1,predref="M",alpha=0.4,alpha2=0.4, 
   jointm=NULL,margin=1, n=2,seed=sample(1:1000,1),mart=FALSE,nu=0.001,
   D=3,distn="bernoulli",family1=binomial(link = "logit"),n2=2)
 summary(temp.b.b.glm)