title: R: ICC (psych) function with multilevel organization
body: <p>I am trying to apply the ICC(2,k)function to assess the reliability of a new machine. Any help is appreciated!</p>
  <ul>
  <li>There was only 1 rater throughout the experiment</li>
  <li>14 people were scanned monocularly</li>
  <li>They were scanned 3 times per session (3 traces/eye)</li>
  <li>They came back 3 times in the same day (9 traces/eye in a day)</li>
  <li>They came back 3 days in the same week (27 traces/eye in a week)</li>
  </ul>
  <p><a href="https://i.stack.imgur.com/ceWbH.png" rel="nofollow noreferrer"><img src="https://i.stack.imgur.com/ceWbH.png" alt="enter image description here" /></a></p>
  <p>The ICC function internally uses <code>lmer</code> to fit a random effects model. Specifically, it fits the model lmer(y~1 + (1|samples) + (1|repeats)). When I run the ICC code for the log values of my outcome variable, I get the following output:</p>
  <p><a href="https://i.stack.imgur.com/dDdzq.png" rel="nofollow noreferrer"><img src="https://i.stack.imgur.com/dDdzq.png" alt="enter image description here" /></a></p>
  <p>I interpret the number of judges as the number of repeats (3 traces per session). However, it is treating each row as an independent sample/subject (226 total), when many of them belong to the same person, as indicated by the variable <code>ID</code>.</p>
  <p>I am unsure how to to make the ICC function realize there are 14 people rather than 226 and calculate the ICC accordingly. Should I reformat my data? I am not sure how to do it while conserving the hierarchy.</p>
  <p>I will be posting to cross-validated as well. I have been using this <a href="https://stats.stackexchange.com/questions/439502/icc-value-of-0-boundary-singular-fit-interpretation">post</a> to guide my thought process.</p>
  <p>This is my data:</p>
  <pre><code>structure(list(ID = structure(c(1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
  1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 
  2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 3L, 3L, 3L, 3L, 3L, 
  3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 4L, 4L, 4L, 4L, 4L, 
  4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 5L, 5L, 5L, 5L, 
  5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 6L, 6L, 6L, 6L, 
  6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 7L, 7L, 
  7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 8L, 
  8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 
  9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 10L, 
  10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 
  10L, 10L, 10L, 10L, 11L, 11L, 11L, 11L, 11L, 11L, 11L, 12L, 12L, 
  12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 
  12L, 12L, 13L, 13L, 13L, 13L, 13L, 13L, 13L, 13L, 13L, 13L, 13L, 
  13L, 13L, 13L, 13L, 14L, 14L, 14L, 14L, 14L, 14L, 14L, 14L, 14L, 
  14L, 14L, 14L, 14L, 14L, 14L, 14L, 14L, 14L), .Label = c(&quot;S01&quot;, 
  &quot;S02&quot;, &quot;S03&quot;, &quot;S04&quot;, &quot;S05&quot;, &quot;S06&quot;, &quot;S07&quot;, &quot;S08&quot;, &quot;S09&quot;, &quot;S10&quot;, 
  &quot;S13&quot;, &quot;S15&quot;, &quot;S16&quot;, &quot;S17&quot;), class = &quot;factor&quot;), eye = c(&quot;L&quot;, 
  &quot;L&quot;, &quot;L&quot;, &quot;L&quot;, &quot;L&quot;, &quot;L&quot;, &quot;L&quot;, &quot;L&quot;, &quot;L&quot;, &quot;R&quot;, &quot;R&quot;, &quot;R&quot;, &quot;R&quot;, &quot;R&quot;, 
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  &quot;R&quot;, &quot;R&quot;, &quot;R&quot;, &quot;R&quot;, &quot;R&quot;, &quot;L&quot;, &quot;L&quot;, &quot;L&quot;, &quot;L&quot;, &quot;L&quot;, &quot;L&quot;, &quot;L&quot;, &quot;R&quot;, 
  &quot;R&quot;, &quot;R&quot;, &quot;R&quot;, &quot;R&quot;, &quot;R&quot;, &quot;R&quot;, &quot;R&quot;, &quot;L&quot;, &quot;L&quot;, &quot;L&quot;, &quot;L&quot;, &quot;L&quot;, &quot;L&quot;, 
  &quot;L&quot;, &quot;L&quot;, &quot;L&quot;, &quot;R&quot;, &quot;R&quot;, &quot;R&quot;, &quot;R&quot;, &quot;R&quot;, &quot;R&quot;, &quot;R&quot;, &quot;R&quot;, &quot;R&quot;, &quot;R&quot;, 
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  &quot;L&quot;, &quot;R&quot;, &quot;R&quot;, &quot;R&quot;, &quot;R&quot;, &quot;R&quot;, &quot;R&quot;, &quot;R&quot;, &quot;R&quot;, &quot;R&quot;, &quot;L&quot;, &quot;L&quot;, &quot;L&quot;, 
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  &quot;R&quot;, &quot;R&quot;, &quot;R&quot;, &quot;R&quot;), Day = c(1, 1, 1, 2, 2, 2, 3, 3, 3, 1, 1, 
  1, 2, 2, 2, 3, 3, 3, 1, 1, 1, 2, 2, 2, 3, 3, 3, 1, 1, 2, 2, 2, 
  3, 3, 3, 1, 1, 1, 2, 2, 2, 3, 3, 3, 1, 1, 2, 2, 3, 3, 3, 1, 1, 
  1, 2, 2, 2, 3, 3, 3, 1, 1, 1, 2, 2, 2, 3, 3, 1, 1, 1, 2, 2, 3, 
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  1, 2, 2, 2, 3, 3, 3, 1, 1, 1, 2, 2, 2, 3, 3, 3, 1, 1, 1, 2, 2, 
  2, 3, 3, 1, 1, 1, 2, 2, 3, 3, 3, 1, 1, 1, 2, 2, 2, 3, 3, 3, 1, 
  1, 1, 2, 2, 2, 3, 1, 1, 1, 2, 2, 3, 3, 3, 1, 1, 1, 2, 2, 2, 3, 
  3, 3, 1, 1, 1, 2, 2, 2, 3, 3, 3, 1, 2, 2, 2, 3, 3, 3, 1, 1, 1, 
  2, 2, 2, 3, 3, 1, 1, 1, 2, 2, 2, 3, 3, 3, 1, 1, 1, 2, 2, 3, 3, 
  3, 1, 1, 2, 2, 3, 3, 3, 1, 1, 1, 2, 2, 2, 3, 3, 3, 1, 1, 1, 2, 
  2, 2, 3, 3, 3), Time = c(1, 2, 3, 1, 2, 3, 1, 2, 3, 1, 2, 3, 
  1, 2, 3, 1, 2, 3, 1, 2, 3, 1, 2, 3, 1, 2, 3, 1, 2, 1, 2, 3, 1, 
  2, 3, 1, 2, 3, 1, 2, 3, 1, 2, 3, 1, 2, 2, 3, 1, 2, 3, 1, 2, 3, 
  1, 2, 3, 1, 2, 3, 1, 2, 3, 1, 2, 3, 1, 2, 1, 2, 3, 1, 3, 1, 2, 
  3, 1, 2, 1, 2, 3, 1, 2, 3, 1, 2, 3, 1, 2, 3, 1, 2, 3, 1, 2, 3, 
  1, 2, 3, 1, 2, 3, 1, 2, 3, 1, 2, 3, 1, 2, 3, 1, 2, 3, 1, 2, 3, 
  2, 3, 1, 2, 3, 1, 3, 1, 2, 3, 1, 2, 3, 1, 2, 3, 1, 2, 3, 1, 2, 
  3, 1, 2, 3, 2, 1, 2, 3, 1, 2, 1, 2, 3, 1, 2, 3, 1, 2, 3, 1, 2, 
  3, 1, 2, 3, 1, 2, 3, 1, 2, 3, 3, 1, 2, 3, 1, 2, 3, 1, 2, 3, 1, 
  2, 3, 1, 3, 1, 2, 3, 1, 2, 3, 1, 2, 3, 1, 2, 3, 2, 3, 1, 2, 3, 
  1, 3, 2, 3, 1, 2, 3, 1, 2, 3, 1, 2, 3, 1, 2, 3, 1, 2, 3, 1, 2, 
  3, 1, 2, 3), Video1 = c(0.087980907, 0.138229468, 0.087265621, 
  0.195986087, NA, 0.169965326, 0.087600668, NA, NA, 0.092477223, 
  0.091350528, 0.032918043, 0.152168109, 0.099289976, 0.073414486, 
  0.55374223, 0.145585337, 0.183976925, 0.036795848, 0.181787784, 
  0.056040284, 0.118583723, 0.077361293, 0.102967699, 0.160763961, 
  0.124360548, 0.149915938, 0.179175193, 0.071730328, 0.149968128, 
  0.153503167, 0.095037811, 0.075409002, 0.174832967, 0.141088859, 
  0.038881157, 0.061564117, 0.054163262, 0.046867349, 0.040123011, 
  0.054647735, 0.060849565, 0.074817049, 0.047454334, 0.087318019, 
  0.039463224, 0.079722026, 0.052817568, 0.021839778, 0.059919709, 
  0.090052431, 0.180300519, 0.160604452, 0.287542322, 0.200999919, 
  0.20508116, 0.083250047, 0.157708361, 0.284022821, 0.136359313, 
  0.086814307, 0.16719986, 0.137407529, 0.102210657, 0.168310974, 
  0.161919932, 0.130113124, 0.107775902, 0.054302189, 0.060560227, 
  0.053947741, 0.062641303, 0.052143943, 0.071859386, 0.068697917, 
  0.074580461, 0.062634558, 0.052877909, 0.045341566, 0.036891534, 
  0.0519817, 0.068383676, 0.072422589, 0.065883961, NA, NA, NA, 
  0.18704615, 0.064510084, NA, NA, NA, 0.281343398, NA, NA, NA, 
  NA, NA, NA, NA, NA, 0.132005827, 0.166076829, 0.156412738, 0.124993123, 
  0.153797119, 0.23523115, 0.204244576, 0.179591735, 0.241662374, 
  0.206093404, 0.194222736, NA, 0.160341745, 0.228276279, NA, 0.148244217, 
  0.267088919, 0.142376066, 0.120874336, 0.116038161, 0.07570081, 
  0.092018565, 0.18764035, 0.097570968, 0.275982193, 0.083032991, 
  0.076835039, 0.129962405, 0.039216406, 0.092339901, 0.09752681, 
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  0.04305756, 0.020832593, 0.050751347, 0.058208723, 0.114863961, 
  0.07299349, 0.065228472, 0.042690128), Video2 = c(0.114125673, 
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  0.061012224, 0.079270672, 0.037756581, 0.091278191, 0.07024436, 
  0.061057298, NA, NA, NA, NA, NA, 0.087830029, 0.255102736, NA, 
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  </code></pre>