title: Problems due to having too many single PSUs at stage one
body: <p>I am calculating the anthropometric failure prevalence for 25 countries with r-studio and the package survey.
  For 24 countries it worked fine. But for India I get illogical values.
  I get an underweight prevalence for India 2016 of 20.8%(18.4%-23.1%) according to statcompiler it should be 35.7%. 
  When I calculate it manually then I get a value of 34.8%, however I need the standard error for my analysis so I have to consider the complex study design with the package survey in R. I get the error message: Error in onestrat(x[index, , drop = FALSE], clusters[index], nPSU[index][1],  : 
    Stratum (5610) has only one PSU at stage 1 , </p>
  
  <p>I tried various things first I excluded manually the observations for which only one PSU at stage 1 was available and then I tried the command options(survey.lonely.psu="remove"), (I also tried "adjust" and "average"). The first approach gives me even worse results than the lonely.psu approach.</p>
  
  <pre><code>IN16_final&lt;- IN16_final[ which(IN16_final$waz&lt;+5 &amp; IN16_final$waz &gt;= -6),]
  
  # categorize underweight in children 
  IN16_final$Category[IN16_final$waz &lt;=-3                                      ] = "2"#severly underweight"
  IN16_final$Category[IN16_final$waz &lt;= -2 &amp; IN16_final$waz &gt;= -3] = "1"#moderately underweight"
  IN16_final$Category[IN16_final$waz &gt;-2                                       ] = "0"#not underweight"
  
  #dummy for underweight or not underweight
  IN16_final$wazcat&lt;-ifelse(IN16_final$waz&gt;=-2,0,1)# 0 not underweight, 1 underweight
  
  
  #manual exclusion of values that have only one obs for PSU stage 1
  IN16_final&lt;- IN16_final[IN16_final$v023 != "912",]
  
  #alternative
  options(survey.lonely.psu="remove")
  
  #result for India 2016
                        mean     SE
  #underweight_prevalence 0.20776 0.0119 
  
  </code></pre>