Dear all,
I have a challenge that I cannot understand or deal with. When I run my regression I get a note saying 'omitted because of collinearity' even though when I run 'collin' or 'vif' commands there is no serious correlation detected.


. reg suic_new fear_z sadness_z shame_z despair_z anxiety_z
note: fear_zscore omitted because of collinearity
note: sadness_zscore omitted because of collinearity
note: shame_zscore omitted because of collinearity
note: despair_zscore omitted because of collinearity
note: anxiety_zscore omitted because of collinearity

Source | SS df MS Number of obs = 94
-------------+---------------------------------- F(0, 93) = 0.00
Model | 0 0 . Prob > F = .
Residual | 340.066465 93 3.65662865 R-squared = 0.0000
-------------+---------------------------------- Adj R-squared = 0.0000
Total | 340.066465 93 3.65662865 Root MSE = 1.9122

--------------------------------------------------------------------------------
suic_new | Coef. Std. Err. t P>|t| [95% Conf. Interval]
---------------+----------------------------------------------------------------
fear_zscore | 0 (omitted)
sadness_zscore | 0 (omitted)
shame_zscore | 0 (omitted)
despair_zscore | 0 (omitted)
anxiety_zscore | 0 (omitted)
_cons | 11.36497 .1972316 57.62 0.000 10.97331 11.75664
--------------------------------------------------------------------------------

.

Collinearity Diagnostics

SQRT R-
Variable VIF VIF Tolerance Squared
----------------------------------------------------
suic_new 1.06 1.03 0.9470 0.0530
fear_zscore 1.03 1.02 0.9698 0.0302
sadness_zscore 1.07 1.03 0.9353 0.0647
shame_zscore 1.06 1.03 0.9418 0.0582
despair_zscore 1.05 1.02 0.9559 0.0441
anxiety_zscore 1.02 1.01 0.9837 0.0163
----------------------------------------------------
Mean VIF 1.05

Cond
Eigenval Index
---------------------------------
1 2.1146 1.0000
2 1.2727 1.2890
3 1.0469 1.4212
4 0.9718 1.4751
5 0.8227 1.6033
6 0.7583 1.6699
7 0.0130 12.7747
---------------------------------
Condition Number 12.7747
Eigenvalues & Cond Index computed from scaled raw sscp (w/ intercept)
Det(correlation matrix) 0.8707


Moreover, even when I leave only one variable in my regression I get the same message. I cannot see how it is possible that one explanatory variable is collinear.

reg suic_new fear_z
note: fear_zscore omitted because of collinearity

Source | SS df MS Number of obs = 94
-------------+---------------------------------- F(0, 93) = 0.00
Model | 0 0 . Prob > F = .
Residual | 340.066465 93 3.65662865 R-squared = 0.0000
-------------+---------------------------------- Adj R-squared = 0.0000
Total | 340.066465 93 3.65662865 Root MSE = 1.9122

------------------------------------------------------------------------------
suic_new | Coef. Std. Err. t P>|t| [95% Conf. Interval]
-------------+----------------------------------------------------------------
fear_zscore | 0 (omitted)
_cons | 11.36497 .1972316 57.62 0.000 10.97331 11.75664
------------------------------------------------------------------------------

Now, this happens only when I standardize my explanatory variables, that is, when I transform them to their z-scores (I do all this in Excel). Otherwise, everything runs smoothly. But I need to transform them to z-scores since I want to give them all an equal weight. By the way, I am dealing here with Google Ngrams emotional/affective word frequencies in a time -series perspective, thus rows in the following table indicate years.

list suic_new fear_z sadness_z general_dislike_z shame_z despair_z anxiety_z

+-----------------------------------------------------------------------------------------+
| suic_new fear_zsc~e sadness_~e general_~e shame_zs~e despair_~e anxiety_~e |
|-----------------------------------------------------------------------------------------|
1. | 5.7776296 9.437e-16 -6.606e-15 3.109e-15 1.776e-15 0 -8.327e-16 |
2. | 7.3340097 -1.621e-14 -1.749e-15 -1.027e-14 -5.274e-16 1.887e-15 1.998e-15 |
3. | 7.8030722 7.994e-15 -2.220e-15 -4.774e-15 -2.609e-15 0 -5.551e-16 |
4. | 7.8814376 2.498e-15 -5.440e-15 -5.995e-15 1.027e-15 -1.998e-15 1.277e-15 |
5. | 9.1750743 3.109e-15 9.437e-16 -1.565e-14 0 0 -2.442e-15 |
|-----------------------------------------------------------------------------------------|
6. | 8.9673257 -1.127e-14 3.331e-16 -5.773e-15 5.523e-15 -1.665e-15 0 |
7. | 9.1869375 3.109e-15 -5.135e-15 2.665e-15 1.554e-15 1.443e-15 2.165e-15 |
8. | 9.8899214 -2.998e-15 -2.304e-15 1.887e-15 4.441e-15 3.664e-15 1.388e-15 |
9. | 9.9566368 0 1.971e-15 -1.410e-14 -2.998e-15 -2.442e-15 3.331e-15 |
10. | 9.0044233 1.016e-14 -1.416e-15 -2.476e-14 -6.772e-15 -2.220e-15 3.497e-15 |
|-----------------------------------------------------------------------------------------|
11. | 8.8672193 -1.732e-14 -3.580e-15 5.107e-15 -4.441e-16 1.998e-15 -1.388e-15 |
12. | 9.3839625 -6.439e-15 3.109e-15 1.588e-14 -5.718e-15 0 -5.052e-15 |
13. | 9.1308341 -2.665e-15 3.830e-15 1.998e-15 -3.164e-15 2.442e-15 0 |
14. | 8.2565447 5.662e-15 3.164e-15 -1.432e-14 -1.443e-15 0 4.441e-15 |
15. | 10.048094 1.038e-14 -1.166e-15 1.155e-14 2.054e-15 -2.220e-15 4.052e-15 |
|-----------------------------------------------------------------------------------------|
16. | 9.8828704 9.548e-15 0 -1.621e-14 3.109e-15 2.442e-15 0 |
17. | 9.9118333 -8.826e-15 -2.554e-15 0 2.498e-16 -1.776e-15 0 |
18. | 10.381302 1.954e-14 -7.133e-15 1.121e-14 1.554e-15 0 5.107e-15 |
19. | 10.540538 0 -2.220e-15 1.188e-14 1.943e-15 -3.553e-15 -1.443e-15 |
20. | 11.143385 -3.331e-15 -2.220e-15 -1.943e-14 -3.331e-15 0 -2.054e-15 |
|-----------------------------------------------------------------------------------------|
21. | 11.841895 9.714e-15 -1.499e-15 5.773e-15 -4.163e-16 2.109e-15 3.497e-15 |
22. | 12.770001 9.437e-16 2.054e-15 1.110e-14 0 -3.553e-15 5.385e-15 |
23. | 13.176805 7.216e-16 -6.023e-15 1.432e-14 6.661e-16 -4.108e-15 9.881e-15 |
24. | 14.88746 1.277e-15 -3.997e-15 -1.388e-14 0 -9.992e-16 -8.882e-16 |
25. | 15.968281 -8.993e-15 7.772e-16 6.883e-15 -4.441e-16 0 -2.720e-15 |
|-----------------------------------------------------------------------------------------|
26. | 16.537906 -1.632e-14 3.331e-15 -1.144e-14 -2.193e-15 2.554e-15 -7.216e-15 |
27. | 15.920686 7.327e-15 -3.053e-15 5.551e-15 0 -8.882e-16 -3.775e-15 |
28. | 14.898661 7.216e-16 -1.776e-15 0 -4.829e-15 5.440e-15 2.776e-15 |
29. | 14.31353 -1.094e-14 7.216e-15 -1.887e-15 1.860e-15 8.882e-16 7.050e-15 |
30. | 14.286252 -2.442e-15 2.803e-15 1.110e-15 -2.220e-16 0 -2.387e-15 |
|-----------------------------------------------------------------------------------------|
31. | 14.976927 -4.219e-15 6.189e-15 6.439e-15 0 -2.442e-15 -3.719e-15 |
32. | 15.252848 6.717e-15 2.331e-15 -7.994e-15 2.276e-15 0 -1.776e-15 |
33. | 14.143521 9.381e-15 3.830e-15 1.998e-14 -1.915e-15 1.776e-15 7.216e-16 |
34. | 14.31021 6.939e-15 -3.886e-16 -1.465e-14 -6.106e-16 -2.109e-15 2.165e-15 |
35. | 12.819852 4.330e-15 -2.609e-15 9.992e-15 -2.748e-15 -1.332e-15 9.770e-15 |
|-----------------------------------------------------------------------------------------|
36. | 11.950952 9.881e-15 -3.331e-16 0 -8.604e-16 -3.109e-15 2.887e-15 |
37. | 10.037345 -4.607e-15 1.110e-15 -3.331e-15 -4.607e-15 2.554e-15 0 |
38. | 9.5601545 7.494e-15 9.631e-15 0 0 0 -1.388e-15 |
39. | 10.563992 -8.604e-15 2.692e-15 1.243e-14 -5.274e-16 -2.776e-15 -5.218e-15 |
40. | 11.423837 -1.271e-14 8.049e-16 -6.439e-15 0 0 -1.610e-15 |
|-----------------------------------------------------------------------------------------|
41. | 11.474676 8.715e-15 -3.192e-15 1.066e-14 -2.276e-15 -9.992e-16 -5.329e-15 |
42. | 11.153144 -1.832e-14 6.939e-16 6.439e-15 -2.831e-15 0 5.274e-15 |
43. | 11.390316 5.107e-15 -4.913e-15 3.331e-15 7.494e-16 -2.554e-15 -6.606e-15 |
44. | 11.2595 -3.275e-15 4.607e-15 1.910e-14 1.943e-15 -2.665e-15 0 |
45. | 10.271963 0 8.327e-16 5.107e-15 -2.831e-15 2.220e-15 -1.332e-15 |
|-----------------------------------------------------------------------------------------|
46. | 9.880501 8.882e-16 -3.192e-15 1.732e-14 3.053e-15 -3.331e-15 1.332e-15 |
47. | 9.9554143 7.772e-15 5.024e-15 -9.104e-15 3.914e-15 -2.665e-15 -2.220e-15 |
48. | 10.032764 -6.051e-15 -2.803e-15 2.043e-14 0 4.663e-15 2.498e-15 |
49. | 10.100572 -3.109e-15 -5.496e-15 -1.199e-14 -1.665e-15 0 2.442e-15 |
50. | 9.9033155 2.276e-15 -3.331e-15 -4.663e-15 3.331e-16 1.221e-15 -2.276e-15 |
|-----------------------------------------------------------------------------------------|
51. | 9.6706597 1.832e-15 -6.689e-15 0 0 0 -4.829e-15 |
52. | 10.589432 -3.497e-15 -5.385e-15 -1.066e-14 1.110e-15 0 7.605e-15 |
53. | 10.478007 -5.274e-15 1.360e-15 3.997e-15 1.138e-15 2.887e-15 -3.331e-15 |
54. | 10.539037 -1.338e-14 3.109e-15 8.660e-15 -3.192e-15 4.441e-15 1.554e-15 |
55. | 10.342886 4.441e-15 -3.109e-15 2.243e-14 3.442e-15 -3.553e-15 0 |
|-----------------------------------------------------------------------------------------|
56. | 10.832661 6.661e-16 -4.163e-16 2.376e-14 4.996e-16 2.109e-15 -1.887e-15 |
57. | 11.00444 -2.071e-14 1.582e-15 -3.775e-15 6.661e-16 8.882e-16 6.883e-15 |
58. | 10.729131 1.610e-15 2.748e-15 -5.329e-15 2.609e-15 4.330e-15 -3.886e-15 |
59. | 11.068797 1.332e-15 -3.303e-15 0 7.772e-16 -1.665e-15 1.005e-14 |
60. | 10.826701 6.883e-15 2.609e-15 -4.885e-15 -3.691e-15 8.882e-16 0 |
|-----------------------------------------------------------------------------------------|
61. | 10.731609 -1.227e-14 -1.610e-15 -6.661e-15 -1.332e-15 -8.882e-16 5.995e-15 |
62. | 10.648408 -5.884e-15 -2.720e-15 0 -2.359e-15 -1.776e-15 3.719e-15 |
63. | 11.034309 1.371e-14 3.719e-15 1.799e-14 -8.882e-16 0 3.220e-15 |
64. | 11.450744 5.995e-15 -4.358e-15 0 -1.943e-15 1.665e-15 -3.442e-15 |
65. | 11.601619 -1.149e-14 -3.358e-15 0 -3.386e-15 0 7.438e-15 |
|-----------------------------------------------------------------------------------------|
66. | 11.912565 -1.033e-14 4.413e-15 0 1.388e-15 -3.664e-15 -4.774e-15 |
67. | 11.853213 1.127e-14 -5.551e-16 8.882e-15 -1.915e-15 0 0 |
68. | 12.009599 0 8.021e-15 1.688e-14 -2.859e-15 -9.992e-16 5.829e-15 |
69. | 12.530721 -3.386e-15 4.885e-15 -7.550e-15 1.471e-15 0 2.609e-15 |
70. | 12.306272 -3.386e-15 5.940e-15 -7.105e-15 5.551e-16 -1.887e-15 4.385e-15 |
|-----------------------------------------------------------------------------------------|
71. | 13.022646 6.661e-16 1.138e-15 7.550e-15 -1.221e-15 1.665e-15 4.441e-15 |
72. | 12.262307 8.826e-15 -4.663e-15 -3.997e-15 1.998e-15 0 -1.260e-14 |
73. | 12.088574 7.605e-15 4.385e-15 -7.105e-15 0 2.109e-15 -1.832e-15 |
74. | 11.82486 -8.993e-15 -3.358e-15 0 -1.943e-15 1.443e-15 2.665e-15 |
75. | 12.026198 -4.940e-15 -8.188e-15 -1.288e-14 -3.053e-16 3.664e-15 -3.442e-15 |
|-----------------------------------------------------------------------------------------|
76. | 12.190908 -6.661e-16 -4.829e-15 0 -2.387e-15 -1.776e-15 -2.331e-15 |
77. | 12.102639 2.942e-15 -8.188e-15 0 -6.384e-16 -1.665e-15 -3.664e-15 |
78. | 12.418536 -2.276e-15 -1.499e-15 0 2.581e-15 1.110e-15 1.721e-15 |
79. | 12.379174 -1.021e-14 5.607e-15 1.688e-14 0 -1.554e-15 0 |
80. | 12.869541 1.832e-15 -8.882e-16 9.326e-15 -2.776e-15 2.665e-15 1.277e-15 |
|-----------------------------------------------------------------------------------------|
81. | 12.710445 3.664e-15 0 0 -1.527e-15 5.329e-15 1.110e-14 |
82. | 12.436453 -1.021e-14 3.164e-15 3.997e-15 -6.106e-16 0 -7.716e-15 |
83. | 12.24864 1.277e-15 2.776e-15 -3.997e-15 -3.803e-15 0 4.052e-15 |
84. | 12.388942 1.776e-15 0 4.885e-15 1.305e-15 -2.442e-15 2.554e-15 |
85. | 12.218767 -4.330e-15 -4.746e-15 8.882e-15 -3.386e-15 -4.219e-15 -2.554e-15 |
|-----------------------------------------------------------------------------------------|
86. | 11.953118 -1.499e-15 -1.860e-15 -7.994e-15 2.026e-15 -1.221e-15 -5.218e-15 |
87. | 12.065205 -9.159e-15 3.303e-15 2.309e-14 -3.525e-15 2.220e-15 3.830e-15 |
88. | 11.962646 -8.771e-15 -1.249e-15 -1.110e-14 0 -4.219e-15 0 |
89. | 11.903961 -6.661e-15 1.166e-15 0 0 -2.554e-15 -4.829e-15 |
90. | 11.65146 -1.221e-15 0 0 -2.054e-15 0 -6.051e-15 |
|-----------------------------------------------------------------------------------------|
91. | 11.402864 1.282e-14 1.638e-15 8.882e-15 6.661e-16 1.332e-15 7.105e-15 |
92. | 11.313682 -3.941e-15 -2.692e-15 5.773e-15 4.163e-16 1.110e-15 -7.105e-15 |
93. | 10.700764 5.884e-15 -3.608e-16 9.326e-15 7.494e-16 -1.221e-15 1.388e-15 |
94. | 10.418166 -2.276e-15 -1.332e-15 -1.310e-14 -2.387e-15 1.998e-15 -4.441e-16 |
+-----------------------------------------------------------------------------------------+

I understand that there is potentially some redundancy among my explanatory variables (all measured words refer - to some extent - to emotional/affective lexicon) but that is sort of a given in my case and my goal is to minimize it as much as possible, though would I not see it in 'collin' 'vif' results if they very redundant?

Do you have some advice for me? Is there a way to deal with this issue? I have a hunch that I overlooked something, but I cannot figure it out yet.
Thank you for your help!