AIM Score vs. Gene Expression
Full X range:
Auto X range:
Group Comparisons: Boxplots
CP73
Model Comparison: AIM ~ expression + C(dose) vs AIM ~ C(dose)
| F-statistic | p-value | df difference |
| 0.418 | 0.525 | 1.0 |
Model:
AIM ~ expression + C(dose) + expression:C(dose)
OLS Regression Results
| Dep. Variable: | AIM | R-squared: | 0.658 |
| Model: | OLS | Adj. R-squared: | 0.603 |
| Method: | Least Squares | F-statistic: | 12.16 |
| Date: | Mon, 27 Jan 2025 | Prob (F-statistic): | 0.000114 |
| Time: | 22:44:45 | Log-Likelihood: | -100.78 |
| No. Observations: | 23 | AIC: | 209.6 |
| Df Residuals: | 19 | BIC: | 214.1 |
| Df Model: | 3 | | |
| coef | std err | t | P>|t| | [95.0% Conf. Int.] |
| Intercept | -57.4617 | 164.707 | -0.349 | 0.731 | -402.198 287.275 |
| C(dose)[T.1] | 137.0766 | 326.084 | 0.420 | 0.679 | -545.424 819.577 |
| expression | 13.7785 | 20.308 | 0.678 | 0.506 | -28.727 56.284 |
| expression:C(dose)[T.1] | -10.4534 | 39.170 | -0.267 | 0.792 | -92.438 71.531 |
| Omnibus: | 0.728 | Durbin-Watson: | 2.072 |
| Prob(Omnibus): | 0.695 | Jarque-Bera (JB): | 0.689 |
| Skew: | -0.094 | Prob(JB): | 0.709 |
| Kurtosis: | 2.173 | Cond. No. | 729. |
Model:
AIM ~ expression + C(dose)
OLS Regression Results
| Dep. Variable: | AIM | R-squared: | 0.656 |
| Model: | OLS | Adj. R-squared: | 0.622 |
| Method: | Least Squares | F-statistic: | 19.09 |
| Date: | Mon, 27 Jan 2025 | Prob (F-statistic): | 2.30e-05 |
| Time: | 22:44:45 | Log-Likelihood: | -100.82 |
| No. Observations: | 23 | AIC: | 207.6 |
| Df Residuals: | 20 | BIC: | 211.1 |
| Df Model: | 2 | | |
| coef | std err | t | P>|t| | [95.0% Conf. Int.] |
| Intercept | -34.6881 | 137.567 | -0.252 | 0.803 | -321.648 252.272 |
| C(dose)[T.1] | 50.0973 | 10.021 | 4.999 | 0.000 | 29.194 71.001 |
| expression | 10.9686 | 16.958 | 0.647 | 0.525 | -24.405 46.342 |
| Omnibus: | 0.497 | Durbin-Watson: | 2.057 |
| Prob(Omnibus): | 0.780 | Jarque-Bera (JB): | 0.576 |
| Skew: | -0.035 | Prob(JB): | 0.750 |
| Kurtosis: | 2.228 | Cond. No. | 266. |
Model:
AIM ~ C(dose)
OLS Regression Results
| Dep. Variable: | AIM | R-squared: | 0.649 |
| Model: | OLS | Adj. R-squared: | 0.632 |
| Method: | Least Squares | F-statistic: | 38.84 |
| Date: | Mon, 27 Jan 2025 | Prob (F-statistic): | 3.51e-06 |
| Time: | 22:44:45 | Log-Likelihood: | -101.06 |
| No. Observations: | 23 | AIC: | 206.1 |
| Df Residuals: | 21 | BIC: | 208.4 |
| Df Model: | 1 | | |
| coef | std err | t | P>|t| | [95.0% Conf. Int.] |
| Intercept | 54.2083 | 5.919 | 9.159 | 0.000 | 41.900 66.517 |
| C(dose)[T.1] | 53.3371 | 8.558 | 6.232 | 0.000 | 35.539 71.135 |
| Omnibus: | 0.322 | Durbin-Watson: | 1.888 |
| Prob(Omnibus): | 0.851 | Jarque-Bera (JB): | 0.485 |
| Skew: | 0.060 | Prob(JB): | 0.785 |
| Kurtosis: | 2.299 | Cond. No. | 2.57 |
Model:
AIM ~ expression
OLS Regression Results
| Dep. Variable: | AIM | R-squared: | 0.227 |
| Model: | OLS | Adj. R-squared: | 0.190 |
| Method: | Least Squares | F-statistic: | 6.156 |
| Date: | Mon, 27 Jan 2025 | Prob (F-statistic): | 0.0216 |
| Time: | 22:44:45 | Log-Likelihood: | -110.15 |
| No. Observations: | 23 | AIC: | 224.3 |
| Df Residuals: | 21 | BIC: | 226.6 |
| Df Model: | 1 | | |
| coef | std err | t | P>|t| | [95.0% Conf. Int.] |
| Intercept | -360.1303 | 177.387 | -2.030 | 0.055 | -729.026 8.765 |
| expression | 53.3412 | 21.498 | 2.481 | 0.022 | 8.633 98.049 |
| Omnibus: | 0.414 | Durbin-Watson: | 2.869 |
| Prob(Omnibus): | 0.813 | Jarque-Bera (JB): | 0.543 |
| Skew: | 0.239 | Prob(JB): | 0.762 |
| Kurtosis: | 2.419 | Cond. No. | 234. |
CP101
Model Comparison: AIM ~ expression + C(dose) vs AIM ~ C(dose)
| F-statistic | p-value | df difference |
| 1.417 | 0.257 | 1.0 |
Model:
AIM ~ expression + C(dose) + expression:C(dose)
OLS Regression Results
| Dep. Variable: | AIM | R-squared: | 0.510 |
| Model: | OLS | Adj. R-squared: | 0.376 |
| Method: | Least Squares | F-statistic: | 3.817 |
| Date: | Mon, 27 Jan 2025 | Prob (F-statistic): | 0.0426 |
| Time: | 22:44:45 | Log-Likelihood: | -69.949 |
| No. Observations: | 15 | AIC: | 147.9 |
| Df Residuals: | 11 | BIC: | 150.7 |
| Df Model: | 3 | | |
| coef | std err | t | P>|t| | [95.0% Conf. Int.] |
| Intercept | -175.0566 | 238.863 | -0.733 | 0.479 | -700.791 350.678 |
| C(dose)[T.1] | 134.3304 | 359.802 | 0.373 | 0.716 | -657.588 926.248 |
| expression | 30.6036 | 30.113 | 1.016 | 0.331 | -35.674 96.881 |
| expression:C(dose)[T.1] | -11.5644 | 44.330 | -0.261 | 0.799 | -109.133 86.004 |
| Omnibus: | 1.138 | Durbin-Watson: | 0.990 |
| Prob(Omnibus): | 0.566 | Jarque-Bera (JB): | 0.983 |
| Skew: | -0.483 | Prob(JB): | 0.612 |
| Kurtosis: | 2.199 | Cond. No. | 501. |
Model:
AIM ~ expression + C(dose)
OLS Regression Results
| Dep. Variable: | AIM | R-squared: | 0.507 |
| Model: | OLS | Adj. R-squared: | 0.425 |
| Method: | Least Squares | F-statistic: | 6.170 |
| Date: | Mon, 27 Jan 2025 | Prob (F-statistic): | 0.0144 |
| Time: | 22:44:45 | Log-Likelihood: | -69.996 |
| No. Observations: | 15 | AIC: | 146.0 |
| Df Residuals: | 12 | BIC: | 148.1 |
| Df Model: | 2 | | |
| coef | std err | t | P>|t| | [95.0% Conf. Int.] |
| Intercept | -132.7757 | 168.513 | -0.788 | 0.446 | -499.933 234.382 |
| C(dose)[T.1] | 40.5755 | 16.553 | 2.451 | 0.031 | 4.510 76.641 |
| expression | 25.2674 | 21.223 | 1.191 | 0.257 | -20.974 71.509 |
| Omnibus: | 1.174 | Durbin-Watson: | 0.963 |
| Prob(Omnibus): | 0.556 | Jarque-Bera (JB): | 1.003 |
| Skew: | -0.482 | Prob(JB): | 0.605 |
| Kurtosis: | 2.177 | Cond. No. | 188. |
Model:
AIM ~ C(dose)
OLS Regression Results
| Dep. Variable: | AIM | R-squared: | 0.449 |
| Model: | OLS | Adj. R-squared: | 0.406 |
| Method: | Least Squares | F-statistic: | 10.58 |
| Date: | Mon, 27 Jan 2025 | Prob (F-statistic): | 0.00629 |
| Time: | 22:44:45 | Log-Likelihood: | -70.833 |
| No. Observations: | 15 | AIC: | 145.7 |
| Df Residuals: | 13 | BIC: | 147.1 |
| Df Model: | 1 | | |
| coef | std err | t | P>|t| | [95.0% Conf. Int.] |
| Intercept | 67.4286 | 11.044 | 6.106 | 0.000 | 43.570 91.287 |
| C(dose)[T.1] | 49.1964 | 15.122 | 3.253 | 0.006 | 16.527 81.866 |
| Omnibus: | 2.713 | Durbin-Watson: | 0.810 |
| Prob(Omnibus): | 0.258 | Jarque-Bera (JB): | 1.868 |
| Skew: | -0.843 | Prob(JB): | 0.393 |
| Kurtosis: | 2.619 | Cond. No. | 2.70 |
Model:
AIM ~ expression
OLS Regression Results
| Dep. Variable: | AIM | R-squared: | 0.260 |
| Model: | OLS | Adj. R-squared: | 0.203 |
| Method: | Least Squares | F-statistic: | 4.571 |
| Date: | Mon, 27 Jan 2025 | Prob (F-statistic): | 0.0521 |
| Time: | 22:44:45 | Log-Likelihood: | -73.040 |
| No. Observations: | 15 | AIC: | 150.1 |
| Df Residuals: | 13 | BIC: | 151.5 |
| Df Model: | 1 | | |
| coef | std err | t | P>|t| | [95.0% Conf. Int.] |
| Intercept | -295.5981 | 182.277 | -1.622 | 0.129 | -689.384 98.188 |
| expression | 48.0254 | 22.463 | 2.138 | 0.052 | -0.502 96.553 |
| Omnibus: | 1.556 | Durbin-Watson: | 1.314 |
| Prob(Omnibus): | 0.459 | Jarque-Bera (JB): | 1.049 |
| Skew: | 0.370 | Prob(JB): | 0.592 |
| Kurtosis: | 1.936 | Cond. No. | 172. |