Table 4.
Summary of Estimates From Multivariable Linear Regression Model
| Predictor Variable (Photogrammetry)a |
Outcome Variable (Cephalometric)b |
Constant |
Parameter Estimate |
95% Confidence Interval |
R2 |
P Value |
|
| Lower Bound |
Upper Bound |
||||||
| StAM-MC (°) | SNA (°) | 81.561 | –0.092 | –0.635 | 0.451 | 0.126 | .723 |
| StBM-MC (°) | SNB (°) | 79.576 | –0.81 | –0.575 | 0.413 | 0.278 | .73 |
| StAM-StBM (°) | ANB (°) | –11.49 | 1.074 | 0.792 | 1.357 | 0.865 | <.0001** |
| (SA-MCP) - (SB-MCP) | Witts (mm) | –4.794 | 0.689 | 0.239 | 1.138 | 0.56 | .005 |
| 3DLAFH (mm) | DLAFH (mm) | –30.765 | 1.398 | 0.881 | 1.915 | 0.844 | <.0001** |
| 3DTAFH (mm) | TAFH (mm) | –6.278 | 0.982 | 0.393 | 1.57 | 0.705 | .003** |
| StMP-MA (°) | MPSN (°) | 12.789 | 0.58 | 0.211 | 0.95 | 0.698 | .005 |
| StMP-MA (°) | MPFH (°) | 2.055 | 0.625 | 0.22 | 1.031 | 0.522 | .005 |
| U1-MC (°) | U1-NA (°) | 11.517 | 0.651 | 0.33 | 0.972 | 0.626 | .001** |
| U1-MC (°) | U1-SN (°) | 93.166 | 0.513 | 0.258 | 0.767 | 0.672 | .001** |
| U1-MC (mm) | U1-NA (mm) | 3.419 | 0.18 | –0.256 | 0.616 | 0.436 | .39 |
| L1-MC (°) | L1-NB (°) | 5.738 | 0.678 | 0.456 | 0.9 | 0.872 | <.0001** |
| L1-MC (°) | L1-MP (°) | 79.5 | 0.761 | 0.328 | 1.194 | 0.548 | .002** |
| L1-MC (mm) | L1-NB (mm) | 1.596 | 0.297 | –0.044 | 0.637 | 0.649 | .083 |
a
Regression model is adjusted for the effects of age (adult vs adolescent), sex, and race.
b
Outcome = Constant + Parameter estimate of predictor variable.
**
Statistically significance for regression set at P < .004.