diff --git a/vignettes/htrfit.Rmd b/vignettes/tutorials/htrfit.Rmd
similarity index 93%
rename from vignettes/htrfit.Rmd
rename to vignettes/tutorials/htrfit.Rmd
index 1b63f22eb7ed6c06904e531ec6561e4f226a100d..cc567c0a50df3b2e6d0ac7875517aa5ab6472568 100644
--- a/vignettes/htrfit.Rmd
+++ b/vignettes/tutorials/htrfit.Rmd
@@ -588,7 +588,51 @@ resSimu$performances
 For certain experimental scenarios, such as those involving a high number of levels or longitudinal data, the utilization of mixed effects within your design formula can be beneficial. The **HTRfit** simulation framework also offers the capability to assess this type of design formula.
 
 
-Removed for test
+```{r example-evalMixed, warning = FALSE, message = FALSE}
+## -- init a design with a high number of levels
+input_var_list <- init_variable( name = "varA", mu = 0.2, sd = 0.74, level = 60) %>%
+                  init_variable( name = "varB", mu = 0.27, sd = 0.6, level = 2) %>%
+                    add_interaction( between_var = c("varA", "varB"), mu = 0.44, sd = 0.89)
+## -- simulate RNAseq data 
+mock_data <- mock_rnaseq(input_var_list, 
+                         n_genes = 30, ## small number to prevent excessively lengthy vignette construction
+                         min_replicates  = 10,
+                         max_replicates = 10, 
+                         basal_expression = 5 )
+## -- prepare data & fit a model with mixed effect
+data2fit = prepareData2fit(countMatrix = mock_data$counts, 
+                           metadata =  mock_data$metadata, 
+                           normalization = F,
+                           response_name = "kij")
+l_tmb <- fitModelParallel(formula = kij ~ varB + (varB | varA),
+                          data = data2fit, 
+                          group_by = "geneID",
+                          family = glmmTMB::nbinom2(link = "log"), 
+                          n.cores = 1)
+## -- evaluation
+resSimu <- evaluation_report(list_tmb = l_tmb,
+                             dds = NULL,
+                             mock_obj = mock_data,
+                             coeff_threshold = 0.27, 
+                             alt_hypothesis = "greater")
+```
+
+```{r example-outputResSimuMixed_id, warning = FALSE, message = FALSE, fig.align = 'center', fig.height = 4, fig.width = 5}
+## -- identity plot 
+###### 1) Model params
+resSimu$identity$params
+###### Dispersion params
+resSimu$identity$dispersion
+```
+
+```{r example-outputResSimuMixed_metric, warning = FALSE, message = FALSE, fig.align = 'center', fig.height = 4, fig.width = 7}
+## -- precision-recall curve
+resSimu$precision_recall$params
+## -- ROC curve
+resSimu$roc$params
+## -- Performances metrics
+resSimu$performances
+```
 
 ## Structure of evaluation report object
 
diff --git a/vignettes/test_vignette.Rmd b/vignettes/tutorials/test_vignette.Rmd
similarity index 100%
rename from vignettes/test_vignette.Rmd
rename to vignettes/tutorials/test_vignette.Rmd