diff --git a/_posts/2018-02-22-heteroskedasticity.md b/_posts/2018-02-22-heteroskedasticity.md
new file mode 100644
index 00000000..a62039f0
--- /dev/null
+++ b/_posts/2018-02-22-heteroskedasticity.md
@@ -0,0 +1,54 @@
+---
+layout: post
+title: "Heteroskedasticity in bird point counts"
+description: ""
+category: [Consulting]
+tags: [Poisson regression,Poisson]
+---
+{% include JB/setup %}
+
+
+## Problem description
+
+### Data
+
+Bird (Dabbling Ducks) count data on 30 wetlands for 2 years for about 10 weeks.
+
+### Modeling
+
+Starting with a mixed effect Poisson regression model.
+Then moved to 
+a mixed effect linear model using square root of the count as the response
+and week as a weight (due to heteroskedasticity by week).
+
+#### Fixed effects
+
+- Week (numeric or categorical)
+- Emergent
+- Year
+- Area
+- Age of wetland
+- WC ?
+
+#### Random effects
+
+- site
+- site x year
+
+
+### Results
+
+Heteroskedasticity appears to exist with more variability in early weeks 
+compared to later. 
+
+
+
+## Advice
+
+Think about
+
+- At least for model building, use linear model with square root of count
+- Treat week as categorical
+- Consider repeated measures structure on random effects
+- Try the analysis in SAS so that you have easier control of random effects
+and error variances