title: how can I extract the standard error from the random effects of JointModel?
body: <ol>
  <li>Model joint Risque compétitifs
  1.1. linear mixed model</li>
  </ol>
  <pre><code>mod_mml=lme(MDRD~DELAI_MONTH, data=Mixed, random=~1+DELAI_MONTH|N_ID,na.action=na.exclude)
  </code></pre>
  <p>1.2. Competing Risks joint model with two competing risks being death and transplantation</p>
  <pre><code>SurvieCR=crLong(Survie,&quot;Statut1_60m&quot;,&quot;Vivant 60m&quot;)
  </code></pre>
  <p>1.3. however, for the survival model we need to use the data in the long format, and include the competing risks indicator as a stratification factor.</p>
  <pre><code>Surv_comp=coxph(Surv(DELAI_M,status2) ~ 1*strata + strata(strata),
                  data=SurvieCR, x=TRUE,method=&quot;efron&quot;,na.action=na.exclude)
  </code></pre>
  <p>1.4. the corresponding joint model is fitted simply by including the above two submodels as main arguments, setting argument CompRisk to TRUE</p>
  <pre><code>JM_comp=jointModel(mod_mml, Surv_comp, timeVar=&quot;DELAI_MONTH&quot;,
                     method=&quot;spline-PH-aGH&quot;,
                     interFact=list(value= ~ strata, data=SurvieCR),
                     CompRisk=TRUE)
  </code></pre>
  <ol start="2">
  <li>results random effects, I tested</li>
  </ol>
  <pre><code>summary(JM_comp)
  random.effects(JM_comp)
  coef(JM_comp) 
  coef(JM_comp, process = &quot;Longitudinal&quot;) ....etc
  </code></pre>
  <ol start="3">
  <li>example of the output</li>
  </ol>
  <pre><code>  random.effects(JM_comp)
       (Intercept)   DELAI_MONTH
  1    3.727740214 -0.2020818077
  2    1.070965087  0.0370529800
  3    3.440276448  0.1582811172
  4   -4.551210225 -0.1568204062
  5   -2.943917109 -0.0389127841
  </code></pre>
  <ol start="4">
  <li>but I need the standard deviation of each intercept and of each slope. if someone can help me?thank you very much</li>
  </ol>