I have a dataset which has independent variable, dependent variable and Mediator. I am trying to measure the direct effect and indirect effect. I am using mediation package in R for doing this.

I followed these steps:

model.M <- lm(M~X,data)
model.Y <- lm(Y~X+M,data)
results <- mediate(model.M,model.Y,sims=500,boot=T,mediator="M",treat="X")
plot(results)
summary(results)
Causal Mediation Analysis 

Nonparametric Bootstrap Confidence Intervals with the Percentile Method

               Estimate 95% CI Lower 95% CI Upper
ACME             -0.184       -0.418        -0.02
ADE               0.808        0.347         1.18
Total Effect      0.624        0.122         1.08
Prop. Mediated   -0.295       -1.850        -0.01
               p-value    
ACME             0.016 *  
ADE             <2e-16 ***
Total Effect     0.024 *  
Prop. Mediated   0.040 *  
---
Signif. codes:  
0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1

Sample Size Used: 205 


Simulations: 500

After running mediation, I know that if there is mediation the direct effect is reduced or becomes 0 in comparison to total effect But in my case the direct effect is increased: does it mean after controlling for M, M is not a mediator? I am not able to interpret the increased value Can anyone who has done mediation analysis provide any comments/feedback Thank you.