Table 2.
Average (mean) and median (med) computation times (in seconds) for the different models in the 16 conditions
| Condition | Rotate | Lasso (ortho) | Lasso (obli) | |||
|---|---|---|---|---|---|---|
| Mean | Med | Mean | Med | Mean | Med | |
, Simple,
,
|
46283.61 | 45216.68 | 57253.41 | 54403.83 | 68838.00 | 68667.01 |
, Simple,
,
|
58324.05 | 53068.87 | 58462.86 | 50916.01 | 72311.45 | 56909.65 |
, Complex,
,
|
47302.36 | 47547.84 | 92965.29 | 85280.05 | 102951.27 | 99220.47 |
, Complex,
,
|
48059.90 | 36611.60 | 51141.60 | 49861.19 | 86535.05 | 76092.09 |
, Simple,
,
|
52099.54 | 51481.72 | 68512.43 | 67672.44 | 87602.04 | 83895.90 |
, Simple,
,
|
61413.70 | 42997.00 | 55539.63 | 56794.52 | 92688.53 | 84882.30 |
, Complex,
,
|
59194.82 | 60043.06 | 91861.01 | 87082.48 | 150744.07 | 144386.86 |
, Complex,
,
|
42349.63 | 33879.25 | 53489.87 | 51615.20 | 127026.13 | 115657.41 |
, Simple,
,
|
108298.80 | 97179.92 | 106282.62 | 100873.23 | 135246.50 | 130528.46 |
, Simple,
,
|
128602.85 | 103645.72 | 95848.96 | 89897.84 | 130119.02 | 114287.96 |
, Complex,
,
|
125037.58 | 103165.51 | 124297.37 | 106175.32 | 158021.63 | 142434.77 |
, Complex,
,
|
100351.37 | 85896.33 | 88783.71 | 77286.90 | 170419.37 | 161424.27 |
, Simple,
,
|
121959.14 | 102129.61 | 130078.07 | 124749.49 | 189087.04 | 175435.80 |
, Simple,
,
|
93551.76 | 77246.24 | 101061.76 | 90799.99 | 174620.27 | 155440.97 |
, Complex,
,
|
136516.21 | 128835.08 | 165670.78 | 167072.77 | 231389.87 | 206651.94 |
, Complex,
,
|
100963.79 | 88346.76 | 120748.39 | 121954.97 | 218278.40 | 208264.54 |
Note: Note that the lasso models include hyperparameter tuning, and thus multiple model fits in one instance, but for the first hyperparameter grid value, the rotate fit parameter estimates were used as start values (yielding a 1-iteration run of the algorithm). obli = oblique (latent traits are a priori assumed to be correlated). ortho = orthogonal (latent traits are a priori assumed to be orthogonal). L = number of latent traits.
= true latent trait correlation. m = number of items per trait.