Update troubleshooting.qmd

chapters/troubleshooting.qmd

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   eval: false
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+In this tutorial, we have demonstrated how to use linear mixed models for different experiment designs. However, it is likely that you will eventually have issues in conducting mixed models in R, such as lack of convergence 
 
 
+This section discusses common issues and errors that might come up when implementing mixed models.
 ## Common Errors we Encounter
 
+1. Singular fit error in linear mixed models
+
+error produced in output is:
+`boundary (singular) fit: see ?isSingular`.
+
+This error occurs because one of the variance component is approximately 0. 
+If a model is "singular", this means that some dimensions of the variance-covariance matrix have been estimated as exactly zero or really close to zero. This often occurs for mixed models with complex random effects structures.
+
+
+2. Model failed to converge 
+
 ### Convergence Issues