title: FMI function for MI datasets is acting up?
body: <p>I used the fmi function from SemTools package just a few weeks ago, and it worked great! Here is the code that I saved and that worked fine:</p>
  
  <pre><code>dat.imp2 &lt;- mice(data = dat1, m = 37, method = "pmm", seed = 444)
  out &lt;- fmi(dat.imp2$imputations)
  out
  </code></pre>
  
  <p>I have used it to compare the loss of efficiency in using 4 source variables vs 1 composite, so I re-ran it twice - first with the 4 source variables and then with 1 composite, and it was much better for composite. Also, the output showed fmi for means and variances separately.</p>
  
  <p>Come back to this code a few weeks later, and it doens't work! The error message reads: </p>
  
  <pre><code>Error in dim(robj) &lt;- c(dX, dY) : 
    dims [product 0] do not match the length of object [1]
  </code></pre>
  
  <p>So, I modified the code as follows:</p>
  
  <pre><code>imp2 &lt;- mice(dat1, m = 37, method = "pmm", seed = 444)
  out &lt;- fmi(imp2$data)
  out 
  </code></pre>
  
  <p>This works but only with the composite variable in the dataset, and only gives me fmi for means but not variances. If I substitute this composite variable with the four source variables it gives me the following error:
  Warning message:</p>
  
  <pre><code>In lavaan(slotOptions = object@Options, slotParTable = object@ParTable,  :
    lavaan WARNING: model has NOT converged!
  </code></pre>
  
  <p>I don't understand how the code that worked a couple weeks ago does not work now? Did anyone come across this problem? I wasn't able to find much online.
  Thank you!</p>
  
  <hr>
  
  <p>Here is the dataset with one composite variable instead (mommh)</p>
  
  <pre><code>&gt; dput(dat2)
  structure(list(mompa = structure(c(0, 0, 0, 0, 0, 0, 0, 0, 1, 
  1, 1, 1, 0, 1, 0, 1, 0, 1, 0, 0, 0, 0, 0, 1, 1, 1, 1, 1, 1, 1, 
  1, 0, 0, 0, 1, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 0, 1, 0, 
  1, 1, 0, 1, 0, 1, 0, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 
  0, 0, 1, 0, 0, 1, 1, 0, 0, 0, 0, 1, 0, 0, 1, 0, 1, 0, 1, 0, 0, 
  0, 0, 0, 1, 1, 0, 1, 1, 1, 0, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 
  0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 0, 0, 0, 
  0, 1, 1, 1, 1, 0, 1, 0, 0, 0, 0, 1, 1, 1, 0, 0, 1, 0, 1, 1, 1, 
  0, 0, 0, 0, 0, 1, 0, 1, 0, 0, 0, 1, 1, 0, 0, 1, 0, 0, 0, 0, 1, 
  0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 
  0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 
  0, 0, 1, 1, 1, 0, 1, 0, 1, 0, 0, 0, 0, 0, 1, 0, 1, 1, 1, 0, 0, 
  0, 1, 0, 0), format.spss = "F8.2", display_width = 10L), momabhx = structure(c(1, 
  0, 0, 1, 1, 1, 1, 0, 1, 1, 0, 1, 1, 0, 0, 0, 1, 0, 0, 0, 0, 1, 
  1, 1, 0, 0, 1, 0, 1, 1, 0, 0, 1, 0, 0, 0, 1, 1, 0, 0, 1, 1, 0, 
  0, 0, 1, 1, 1, 0, 1, 0, 1, 1, 1, 1, 1, 1, 0, 1, 1, 0, 1, 0, 0, 
  0, 0, 0, 0, 0, 1, 0, 0, 0, 1, 0, 1, 0, 0, 1, 0, 0, 0, 0, 0, 1, 
  0, 0, 0, 1, 0, 1, 1, 1, 0, 0, 0, 0, 1, 0, 1, 0, 1, 1, 1, 0, 0, 
  0, 0, 0, 0, 0, 1, 0, 0, 1, 0, 1, 0, 0, 1, 0, 0, 0, 1, 0, 0, 0, 
  0, 1, 0, 1, 1, 1, 1, 1, 1, 0, 0, 0, 1, 0, 0, 0, 0, 0, 1, 1, 1, 
  0, 1, 0, 1, 1, 1, 1, 1, 0, 1, 1, 1, 0, 0, 1, 1, 1, 0, 1, 1, 0, 
  0, 0, 1, 0, 1, 0, 1, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 1, 
  0, 0, 0, 0, 1, 1, 0, 1, 1, 1, 0, 0, 1, 1, 1, 0, 0, 1, 0, 0, 0, 
  0, 0, 1, 0, 1, 1, 0, 0, 0, 0, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 1, 
  0, 1, 1, 0, 1, 1, 1, 1, 0, 1, 1, 1), format.spss = "F8.2", display_width = 10L), 
      mommh = c(63, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 
      NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 
      NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 
      NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 35.75, NA, NA, 
      NA, NA, NA, NA, NA, NA, NA, NA, 43.25, NA, NA, 63, 41.5, 
      34.25, 38.5, 39, 38.5, NA, 49.75, 57.5, 59.25, 50, 42.75, 
      45, 49, 32.75, NA, 35.75, 64.75, 50.5, 46.5, 39.75, 51.75, 
      34.75, 61.25, 46, 43, 56.25, 47, 42.25, 36.5, 34.5, 47, 50, 
      35, 48.25, 46.5, 58.5, 35.5, 55.25, 43.5, 42.75, 35.75, 38, 
      35.5, 50, 38.25, 57, 45.75, 38.5, 44.25, 51.75, NA, 38.25, 
      39.75, 34, 57.25, 39.25, 42.25, 37.25, NA, 32.75, 52.75, 
      NA, NA, 55.75, 62.25, 59.75, 43.75, 59.75, 35.75, NA, 34.25, 
      59.25, 39, 34.75, 32.75, NA, 53.5, NA, 40.5, 50, 33.5, 45.25, 
      41, 50, NA, 38.5, 61.5, 36.25, 46.25, 46, 44.75, 44.75, 62.5, 
      38.25, 49.5, 33.75, NA, 50.25, 43, 43.75, 42.25, 60.5, NA, 
      50.25, 54.75, 42.75, 45.75, 61, 58.25, 44.5, 46.5, 34.25, 
      56.75, 40.5, 47, 42.25, 48, 44, 36.75, 39.75, 48.75, 38.25, 
      49.25, 49.25, NA, NA, 34.25, 44.5, NA, 51, 44, 50.75, 56.25, 
      35, 55, 58.75, 56.5, 68.75, 54, 53, 41.5, 50.75, NA, 32.75, 
      46.75, 32.75, 43, 57, 55.25, NA, NA, 43.75, 55.5, NA, NA, 
      32.75, NA, NA, NA, NA, 60.5, 32.75, NA, 68.25, 50.5, 32.75, 
      66.5, 33, 38.5, 43, 43.75, 62.75, 47, 36.5, 39.5, 39.5), 
      risk6 = structure(c(0, 0, 0, 0, 3, 1, 1, 1, 1, 0, 1, 1, 0, 
      0, 0, 2, 1, 1, 0, 1, 0, 1, 0, 1, 2, 1, 1, 0, 0, 2, 1, 1, 
      2, 0, 1, 0, 1, 0, 1, 1, 0, 0, 0, 2, 1, 3, 2, 2, 0, 0, 0, 
      2, 0, 2, 2, 1, 2, 2, 1, 3, 2, 3, 1, 1, 0, 1, 3, 1, 2, 2, 
      0, 1, 0, 0, 1, 3, 1, 0, 1, 0, 0, 1, 3, 0, 1, 1, 0, 0, 2, 
      3, 3, 1, 2, 3, 2, 0, 0, 4, 1, 2, 1, 3, 2, 1, 2, 0, 1, 1, 
      2, 1, 1, 0, 0, 0, 0, 0, 1, 1, 2, 2, 1, 2, 1, 1, 2, 1, 1, 
      NA, 1, 1, 1, 2, 0, NA, 3, 0, 2, 2, 3, 4, 4, 0, 1, 0, 2, 3, 
      2, 2, 2, 2, 1, 3, 2, 2, 3, 1, 1, 1, 0, 0, 1, 1, 0, 2, 0, 
      1, 2, 3, 1, 1, 1, 2, 1, 2, 0, 0, 2, 2, 0, 1, 2, 0, 0, 2, 
      1, 1, 1, 1, 1, 3, 1, 0, 3, 0, 1, 0, 1, 1, 1, 2, 2, 0, 2, 
      3, 3, 0, 0, 0, 1, 2, 1, 1, 1, 0, 1, 1, 3, 1, 1, 0, 0, 3, 
      2, 0, 0, 3, 2, 1, 3, 1, 0, 3, 0, 1, 1, 2, 3, 3, 1, 4, 2, 
      3, 2, 2), format.spss = "F8.2", display_width = 10L), eadiff = structure(c(-1.26734803867686, 
      -0.355541076313792, 0.518653050779668, 1.50568568368194, 
      0.0940935989894723, 2.07356799670629, 1.01843817310907, -1.26734803867686, 
      -0.317928241044189, 0.531190662536203, 0.0940935989894723, 
      -1.47335895869369, -0.586627219843691, -1.26734803867686, 
      0.325179742519372, 0.556265886049271, 1.4179224013862, 1.2244490931259, 
      -0.586627219843691, 0.081555987232938, -0.149530156296961, 
      -0.380616299826861, -0.805175751617057, -0.368078688070326, 
      0.0940935989894723, -0.124454932783893, 0.955750114326398, 
      -0.805175751617057, 0.531190662536203, -0.830250975130125, 
      0.968287726082933, 0.749739194309568, -0.368078688070326, 
      -1.03626189514696, 3.19138587908619, -0.574089608087157, 
      1.67408376842917, -0.586627219843691, -0.343003464557258, 
      -0.162067768053496, 0.325179742519372, -1.24227281516379, 
      -1.03626189514696, 0.749739194309568, 0.325179742519372, 
      0.556265886049271, 0.762276806066102, -0.817713363373591, 
      -0.805175751617057, 0.119168822502541, -0.805175751617057, 
      -0.149530156296961, 0.0940935989894723, -1.48589657045022, 
      1.01843817310907, 0.312642130762837, 1.21191148136937, -0.355541076313792, 
      -1.04879950690349, -0.368078688070326, -0.124454932783893, 
      0.312642130762837, -1.25481042692032, -0.136992544540427, 
      1.01843817310907, -0.124454932783893, -0.368078688070326, 
      -0.805175751617057, 0.081555987232938, -0.805175751617057, 
      0.325179742519372, 2.97283734731282, 0.337717354275906, 0.0690183754764037, 
      -0.136992544540427, -0.830250975130125, 3.03552540609549, 
      0.0940935989894723, 0.0690183754764037, -0.124454932783893, 
      -0.817713363373591, -0.355541076313792, 0.312642130762837, 
      0.980825337839467, -0.343003464557258, 0.993362949596001, 
      -0.586627219843691, -0.574089608087157, -1.02372428339042, 
      -0.561551996330623, -0.111917321027358, -0.136992544540427, 
      -0.149530156296961, -0.830250975130125, 0.568803497805805, 
      0.0690183754764037, -0.805175751617057, -0.830250975130125, 
      0.556265886049271, 0.968287726082933, 0.531190662536203, 
      0.312642130762837, 0.337717354275906, 0.774814417822636, 
      0.337717354275906, 0.337717354275906, -0.586627219843691, 
      0.106631210746007, -1.02372428339042, -0.574089608087157, 
      -0.355541076313792, 0.737201582553033, 0.325179742519372, 
      0.312642130762837, 0.556265886049271, 0.0940935989894723, 
      0.300104519006303, -0.330465852800723, 0.0940935989894723, 
      -0.355541076313792, -0.599164831600226, 0.312642130762837, 
      0.531190662536203, -1.25481042692032, 0.531190662536203, 
      1.89263230020253, -0.817713363373591, -1.02372428339042, 
      0.980825337839467, -0.149530156296961, -0.586627219843691, 
      1.23698670488244, 0.556265886049271, 0.325179742519372, -0.817713363373591, 
      1.01843817310907, -1.02372428339042, -0.805175751617057, 
      -0.355541076313792, 1.67408376842917, 0.0690183754764037, 
      -0.368078688070326, -0.124454932783893, 0.980825337839467, 
      -1.03626189514696, 0.119168822502541, -1.03626189514696, 
      -1.03626189514696, 1.4555352366558, -0.136992544540427, -1.04879950690349, 
      0.749739194309568, -0.792638139860522, 0.312642130762837, 
      -0.0993797092708241, -0.17460537981003, -0.343003464557258, 
      -0.586627219843691, 0.300104519006303, -0.355541076313792, 
      -0.805175751617057, 0.518653050779668, -1.26734803867686, 
      -1.25481042692032, -0.368078688070326, -0.805175751617057, 
      -0.343003464557258, -0.343003464557258, -0.599164831600226, 
      -0.124454932783893, 1.66154615667263, -0.586627219843691, 
      -0.586627219843691, -0.124454932783893, 0.955750114326398, 
      -0.355541076313792, -0.343003464557258, 0.0940935989894723, 
      -0.792638139860522, -0.599164831600226, NA, -0.586627219843691, 
      -1.26734803867686, 0.762276806066102, 1.2244490931259, 0.081555987232938, 
      -0.574089608087157, -1.01118667163389, 0.312642130762837, 
      0.081555987232938, -0.368078688070326, -1.26734803867686, 
      1.63647093315956, -0.368078688070326, 0.531190662536203, 
      0.081555987232938, 0.543728274292737, 0.0564807637198694, 
      0.955750114326398, -1.25481042692032, 1.44299762489927, -1.04879950690349, 
      0.106631210746007, -0.586627219843691, 0.0940935989894723, 
      -0.162067768053496, 0.0940935989894723, -0.111917321027358, 
      0.968287726082933, 0.0940935989894723, 0.312642130762837, 
      -0.586627219843691, 0.543728274292737, -0.124454932783893, 
      0.543728274292737, -0.817713363373591, -0.586627219843691, 
      -0.368078688070326, 0.0940935989894723, -0.599164831600226, 
      -1.03626189514696, 0.774814417822636, 0.106631210746007, 
      -0.111917321027358, -0.817713363373591, -0.330465852800723, 
      0.993362949596001, -0.368078688070326, 1.19937386961283, 
      0.531190662536203, 0.749739194309568, 1.6490085449161, 0.0690183754764037, 
      -0.574089608087157, -0.368078688070326, 1.00590056135254, 
      1.4555352366558, -0.574089608087157, -0.586627219843691, 
      -0.817713363373591, -0.817713363373591, 0.0940935989894723, 
      -0.792638139860522, 0.0690183754764037), format.spss = "F8.2", display_width = 10L)), .Names = c("mompa", 
  "momabhx", "mommh", "risk6", "eadiff"), row.names = c(NA, -244L
  ), class = "data.frame")
  </code></pre>
  
  <hr>
  
  <p>And here is the same dataset with 4 source variables (depr, anxt, host, bpsipdr1)</p>
  
  <pre><code>&gt; dput(dat3)
  structure(list(mompa = structure(c(0, 0, 0, 0, 0, 0, 0, 0, 1, 
  1, 1, 1, 0, 1, 0, 1, 0, 1, 0, 0, 0, 0, 0, 1, 1, 1, 1, 1, 1, 1, 
  1, 0, 0, 0, 1, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 0, 1, 0, 
  1, 1, 0, 1, 0, 1, 0, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 
  0, 0, 1, 0, 0, 1, 1, 0, 0, 0, 0, 1, 0, 0, 1, 0, 1, 0, 1, 0, 0, 
  0, 0, 0, 1, 1, 0, 1, 1, 1, 0, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 
  0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 0, 0, 0, 
  0, 1, 1, 1, 1, 0, 1, 0, 0, 0, 0, 1, 1, 1, 0, 0, 1, 0, 1, 1, 1, 
  0, 0, 0, 0, 0, 1, 0, 1, 0, 0, 0, 1, 1, 0, 0, 1, 0, 0, 0, 0, 1, 
  0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 
  0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 
  0, 0, 1, 1, 1, 0, 1, 0, 1, 0, 0, 0, 0, 0, 1, 0, 1, 1, 1, 0, 0, 
  0, 1, 0, 0), format.spss = "F8.2", display_width = 10L), momabhx = structure(c(1, 
  0, 0, 1, 1, 1, 1, 0, 1, 1, 0, 1, 1, 0, 0, 0, 1, 0, 0, 0, 0, 1, 
  1, 1, 0, 0, 1, 0, 1, 1, 0, 0, 1, 0, 0, 0, 1, 1, 0, 0, 1, 1, 0, 
  0, 0, 1, 1, 1, 0, 1, 0, 1, 1, 1, 1, 1, 1, 0, 1, 1, 0, 1, 0, 0, 
  0, 0, 0, 0, 0, 1, 0, 0, 0, 1, 0, 1, 0, 0, 1, 0, 0, 0, 0, 0, 1, 
  0, 0, 0, 1, 0, 1, 1, 1, 0, 0, 0, 0, 1, 0, 1, 0, 1, 1, 1, 0, 0, 
  0, 0, 0, 0, 0, 1, 0, 0, 1, 0, 1, 0, 0, 1, 0, 0, 0, 1, 0, 0, 0, 
  0, 1, 0, 1, 1, 1, 1, 1, 1, 0, 0, 0, 1, 0, 0, 0, 0, 0, 1, 1, 1, 
  0, 1, 0, 1, 1, 1, 1, 1, 0, 1, 1, 1, 0, 0, 1, 1, 1, 0, 1, 1, 0, 
  0, 0, 1, 0, 1, 0, 1, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 1, 
  0, 0, 0, 0, 1, 1, 0, 1, 1, 1, 0, 0, 1, 1, 1, 0, 0, 1, 0, 0, 0, 
  0, 0, 1, 0, 1, 1, 0, 0, 0, 0, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 1, 
  0, 1, 1, 0, 1, 1, 1, 1, 0, 1, 1, 1), format.spss = "F8.2", display_width = 10L), 
      risk6 = structure(c(0, 0, 0, 0, 3, 1, 1, 1, 1, 0, 1, 1, 0, 
      0, 0, 2, 1, 1, 0, 1, 0, 1, 0, 1, 2, 1, 1, 0, 0, 2, 1, 1, 
      2, 0, 1, 0, 1, 0, 1, 1, 0, 0, 0, 2, 1, 3, 2, 2, 0, 0, 0, 
      2, 0, 2, 2, 1, 2, 2, 1, 3, 2, 3, 1, 1, 0, 1, 3, 1, 2, 2, 
      0, 1, 0, 0, 1, 3, 1, 0, 1, 0, 0, 1, 3, 0, 1, 1, 0, 0, 2, 
      3, 3, 1, 2, 3, 2, 0, 0, 4, 1, 2, 1, 3, 2, 1, 2, 0, 1, 1, 
      2, 1, 1, 0, 0, 0, 0, 0, 1, 1, 2, 2, 1, 2, 1, 1, 2, 1, 1, 
      NA, 1, 1, 1, 2, 0, NA, 3, 0, 2, 2, 3, 4, 4, 0, 1, 0, 2, 3, 
      2, 2, 2, 2, 1, 3, 2, 2, 3, 1, 1, 1, 0, 0, 1, 1, 0, 2, 0, 
      1, 2, 3, 1, 1, 1, 2, 1, 2, 0, 0, 2, 2, 0, 1, 2, 0, 0, 2, 
      1, 1, 1, 1, 1, 3, 1, 0, 3, 0, 1, 0, 1, 1, 1, 2, 2, 0, 2, 
      3, 3, 0, 0, 0, 1, 2, 1, 1, 1, 0, 1, 1, 3, 1, 1, 0, 0, 3, 
      2, 0, 0, 3, 2, 1, 3, 1, 0, 3, 0, 1, 1, 2, 3, 3, 1, 4, 2, 
      3, 2, 2), format.spss = "F8.2", display_width = 10L), eadiff = structure(c(-1.26734803867686, 
      -0.355541076313792, 0.518653050779668, 1.50568568368194, 
      0.0940935989894723, 2.07356799670629, 1.01843817310907, -1.26734803867686, 
      -0.317928241044189, 0.531190662536203, 0.0940935989894723, 
      -1.47335895869369, -0.586627219843691, -1.26734803867686, 
      0.325179742519372, 0.556265886049271, 1.4179224013862, 1.2244490931259, 
      -0.586627219843691, 0.081555987232938, -0.149530156296961, 
      -0.380616299826861, -0.805175751617057, -0.368078688070326, 
      0.0940935989894723, -0.124454932783893, 0.955750114326398, 
      -0.805175751617057, 0.531190662536203, -0.830250975130125, 
      0.968287726082933, 0.749739194309568, -0.368078688070326, 
      -1.03626189514696, 3.19138587908619, -0.574089608087157, 
      1.67408376842917, -0.586627219843691, -0.343003464557258, 
      -0.162067768053496, 0.325179742519372, -1.24227281516379, 
      -1.03626189514696, 0.749739194309568, 0.325179742519372, 
      0.556265886049271, 0.762276806066102, -0.817713363373591, 
      -0.805175751617057, 0.119168822502541, -0.805175751617057, 
      -0.149530156296961, 0.0940935989894723, -1.48589657045022, 
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      -1.04879950690349, -0.368078688070326, -0.124454932783893, 
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  </code></pre>