Hi,

I did a diary study and people had to answer to 2 times a day for 5 days. They had to answer in the morning and in the afternoon, and the variables used in both assessments were different (for instance: in the morning I asked about sleeping problems from the night before, in the afternoon I did not ask about sleeping problems).

I joined both databases for morning and afternoon. I was trying to calculate the reliability for each variable (calculating RkF), but I always get the same error.

I was trying to calculate Sleeping Problems:

I put:

```
base_w_final = dataset
code= the code they had to create before fulfilling each assessment
register= the day (day 1, day 2, day 3, day 4 and day 5).
items= columns 20 to 24 correspond to the columns for sleeping problems.
library(psych)
mlr(base_w_final, grp = "code", Time = "register", items = c(20:24))
```

console output:

```
At least one item had no variance when finding alpha for subject = 1. Proceed with caution At least one item had no variance when finding alpha for subject = 2. Proceed with caution At least one item had no variance when finding alpha for subject = 3. Proceed with caution At least one item had no variance when finding alpha for subject = 5. Proceed with caution At least one item had no variance when finding alpha for subject = 6. Proceed with caution At least one item had no variance when finding alpha for subject = 7. Proceed with caution At least one item had no variance when finding alpha for subject = 8. Proceed with caution At least one item had no variance when finding alpha for subject = 9. Proceed with caution At least one item had no variance when finding alpha for subject = 10. Proceed with caution At least one item had no variance when finding alpha for subject = 11. Proceed with caution At least one item had no variance when finding alpha for subject = 13. Proceed with caution At least one item had no variance when finding alpha for subject = 15. Proceed with caution At least one item had no variance when finding alpha for subject = 16. Proceed with caution At least one item had no variance when finding alpha for subject = 17. Proceed with caution At least one item had no variance when finding alpha for subject = 18. Proceed with caution At least one item had no variance when finding alpha for subject = 19. Proceed with caution At least one item had no variance when finding alpha for subject = 20. Proceed with caution At least one item had no variance when finding alpha for subject = 21. Proceed with caution At least one item had no variance when finding alpha for subject = 23. Proceed with caution At least one item had no variance when finding alpha for subject = 24. Proceed with caution At least one item had no variance when finding alpha for subject = 25. Proceed with caution At least one item had no variance when finding alpha for subject = 27. Proceed with caution At least one item had no variance when finding alpha for subject = 29. Proceed with caution At least one item had no variance when finding alpha for subject = 30. Proceed with caution At least one item had no variance when finding alpha for subject = 33. Proceed with caution At least one item had no variance when finding alpha for subject = 34. Proceed with caution At least one item had no variance when finding alpha for subject = 37. Proceed with caution At least one item had no variance when finding alpha for subject = 38. Proceed with caution At least one item had no variance when finding alpha for subject = 40. Proceed with caution At least one item had no variance when finding alpha for subject = 41. Proceed with caution At least one item had no variance when finding alpha for subject = 42. Proceed with caution At least one item had no variance when finding alpha for subject = 43. Proceed with caution At least one item had no variance when finding alpha for subject = 44. Proceed with caution At least one item had no variance when finding alpha for subject = 45. Proceed with caution At least one item had no variance when finding alpha for subject = 47. Proceed with caution At least one item had no variance when finding alpha for subject = 49. Proceed with caution At least one item had no variance when finding alpha for subject = 51. Proceed with caution At least one item had no variance when finding alpha for subject = 52. Proceed with caution At least one item had no variance when finding alpha for subject = 53. Proceed with caution At least one item had no variance when finding alpha for subject = 55. Proceed with caution At least one item had no variance when finding alpha for subject = 56. Proceed with caution At least one item had no variance when finding alpha for subject = 57. Proceed with caution At least one item had no variance when finding alpha for subject = 58. Proceed with caution At least one item had no variance when finding alpha for subject = 59. Proceed with caution At least one item had no variance when finding alpha for subject = 60. Proceed with caution At least one item had no variance when finding alpha for subject = 63. Proceed with caution At least one item had no variance when finding alpha for subject = 64. Proceed with caution At least one item had no variance when finding alpha for subject = 65. Proceed with caution At least one item had no variance when finding alpha for subject = 66. Proceed with caution At least one item had no variance when finding alpha for subject = 67. Proceed with caution At least one item had no variance when finding alpha for subject = 69. Proceed with caution At least one item had no variance when finding alpha for subject = 70. Proceed with caution At least one item had no variance when finding alpha for subject = 71. Proceed with caution At least one item had no variance when finding alpha for subject = 72. Proceed with caution At least one item had no variance when finding alpha for subject = 73. Proceed with caution At least one item had no variance when finding alpha for subject = 77. Proceed with caution At least one item had no variance when finding alpha for subject = 78. Proceed with caution At least one item had no variance when finding alpha for subject = 80. Proceed with caution At least one item had no variance when finding alpha for subject = 81. Proceed with caution At least one item had no variance when finding alpha for subject = 82. Proceed with caution At least one item had no variance when finding alpha for subject = 84. Proceed with caution At least one item had no variance when finding alpha for subject = 85. Proceed with caution At least one item had no variance when finding alpha for subject = 86. Proceed with caution At least one item had no variance when finding alpha for subject = 87. Proceed with caution At least one item had no variance when finding alpha for subject = 89. Proceed with caution At least one item had no variance when finding alpha for subject = 91. Proceed with caution At least one item had no variance when finding alpha for subject = 93. Proceed with caution At least one item had no variance when finding alpha for subject = 96. Proceed with caution At least one item had no variance when finding alpha for subject = 98. Proceed with caution At least one item had no variance when finding alpha for subject = 99. Proceed with caution At least one item had no variance when finding alpha for subject = 103. Proceed with caution At least one item had no variance when finding alpha for subject = 105. Proceed with caution At least one item had no variance when finding alpha for subject = 106. Proceed with caution At least one item had no variance when finding alpha for subject = 107. Proceed with caution At least one item had no variance when finding alpha for subject = 110. Proceed with caution At least one item had no variance when finding alpha for subject = 112. Proceed with caution At least one item had no variance when finding alpha for subject = 113. Proceed with caution At least one item had no variance when finding alpha for subject = 114. Proceed with caution At least one item had no variance when finding alpha for subject = 115. Proceed with caution At least one item had no variance when finding alpha for subject = 116. Proceed with caution At least one item had no variance when finding alpha for subject = 118. Proceed with caution At least one item had no variance when finding alpha for subject = 120. Proceed with caution At least one item had no variance when finding alpha for subject = 121. Proceed with caution At least one item had no variance when finding alpha for subject = 123. Proceed with caution At least one item had no variance when finding alpha for subject = 125. Proceed with caution At least one item had no variance when finding alpha for subject = 127. Proceed with caution At least one item had no variance when finding alpha for subject = 128. Proceed with caution At least one item had no variance when finding alpha for subject = 130. Proceed with caution At least one item had no variance when finding alpha for subject = 131. Proceed with caution At least one item had no variance when finding alpha for subject = 132. Proceed with caution At least one item had no variance when finding alpha for subject = 134. Proceed with caution At least one item had no variance when finding alpha for subject = 135. Proceed with caution **Error in dimnames(x) <- dn : length of 'dimnames' [1] not equal to array extent In addition: There were 50 or more warnings (use warnings() to see the first 50)**
```

I think this is due to the fact that I have NA values when it´s the afternoon assessments. But I tried to sperate the datasets (have 1 for the morning assessments and have 1 for the afternoon assessments) and calculate then, but I still get errors.

If I keep the same database, is there any possibility to tell RStudio to dismiss missing values or do you think the error has nothing to do with that?

Thank you so much for all the help!