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 |
| 0.431 | 0.519 | 1.0 |
Model:
AIM ~ expression + C(dose) + expression:C(dose)
OLS Regression Results
| Dep. Variable: | AIM | R-squared: | 0.657 |
| Model: | OLS | Adj. R-squared: | 0.603 |
| Method: | Least Squares | F-statistic: | 12.15 |
| Date: | Tue, 28 Jan 2025 | Prob (F-statistic): | 0.000114 |
| Time: | 19:50:25 | Log-Likelihood: | -100.79 |
| 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 | 69.4483 | 59.964 | 1.158 | 0.261 | -56.058 194.955 |
| C(dose)[T.1] | 70.3749 | 79.306 | 0.887 | 0.386 | -95.615 236.365 |
| expression | -2.1819 | 8.540 | -0.255 | 0.801 | -20.056 15.692 |
| expression:C(dose)[T.1] | -2.4667 | 11.311 | -0.218 | 0.830 | -26.141 21.208 |
| Omnibus: | 0.078 | Durbin-Watson: | 2.043 |
| Prob(Omnibus): | 0.962 | Jarque-Bera (JB): | 0.062 |
| Skew: | -0.049 | Prob(JB): | 0.969 |
| Kurtosis: | 2.764 | Cond. No. | 171. |
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: | 19.11 |
| Date: | Tue, 28 Jan 2025 | Prob (F-statistic): | 2.29e-05 |
| Time: | 19:50:25 | Log-Likelihood: | -100.82 |
| No. Observations: | 23 | AIC: | 207.6 |
| Df Residuals: | 20 | BIC: | 211.0 |
| Df Model: | 2 | | |
| coef | std err | t | P>|t| | [95.0% Conf. Int.] |
| Intercept | 79.2688 | 38.640 | 2.051 | 0.054 | -1.334 159.871 |
| C(dose)[T.1] | 53.1893 | 8.680 | 6.128 | 0.000 | 35.084 71.295 |
| expression | -3.5879 | 5.465 | -0.657 | 0.519 | -14.988 7.812 |
| Omnibus: | 0.043 | Durbin-Watson: | 2.064 |
| Prob(Omnibus): | 0.979 | Jarque-Bera (JB): | 0.071 |
| Skew: | 0.017 | Prob(JB): | 0.965 |
| Kurtosis: | 2.730 | Cond. No. | 63.9 |
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: | Tue, 28 Jan 2025 | Prob (F-statistic): | 3.51e-06 |
| Time: | 19:50:25 | 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: | 0.011 |
| Model: | OLS | Adj. R-squared: | -0.036 |
| Method: | Least Squares | F-statistic: | 0.2428 |
| Date: | Tue, 28 Jan 2025 | Prob (F-statistic): | 0.627 |
| Time: | 19:50:25 | Log-Likelihood: | -112.97 |
| No. Observations: | 23 | AIC: | 229.9 |
| Df Residuals: | 21 | BIC: | 232.2 |
| Df Model: | 1 | | |
| coef | std err | t | P>|t| | [95.0% Conf. Int.] |
| Intercept | 110.7574 | 63.400 | 1.747 | 0.095 | -21.089 242.604 |
| expression | -4.4565 | 9.044 | -0.493 | 0.627 | -23.265 14.352 |
| Omnibus: | 4.670 | Durbin-Watson: | 2.563 |
| Prob(Omnibus): | 0.097 | Jarque-Bera (JB): | 1.768 |
| Skew: | 0.264 | Prob(JB): | 0.413 |
| Kurtosis: | 1.748 | Cond. No. | 63.2 |
CP101
Model Comparison: AIM ~ expression + C(dose) vs AIM ~ C(dose)
| F-statistic | p-value | df difference |
| 1.024 | 0.331 | 1.0 |
Model:
AIM ~ expression + C(dose) + expression:C(dose)
OLS Regression Results
| Dep. Variable: | AIM | R-squared: | 0.571 |
| Model: | OLS | Adj. R-squared: | 0.454 |
| Method: | Least Squares | F-statistic: | 4.884 |
| Date: | Tue, 28 Jan 2025 | Prob (F-statistic): | 0.0214 |
| Time: | 19:50:25 | Log-Likelihood: | -68.949 |
| No. Observations: | 15 | AIC: | 145.9 |
| Df Residuals: | 11 | BIC: | 148.7 |
| Df Model: | 3 | | |
| coef | std err | t | P>|t| | [95.0% Conf. Int.] |
| Intercept | 42.6188 | 82.857 | 0.514 | 0.617 | -139.749 224.987 |
| C(dose)[T.1] | -202.8687 | 179.165 | -1.132 | 0.282 | -597.208 191.470 |
| expression | 3.1855 | 10.551 | 0.302 | 0.768 | -20.038 26.409 |
| expression:C(dose)[T.1] | 33.4359 | 23.475 | 1.424 | 0.182 | -18.233 85.104 |
| Omnibus: | 1.997 | Durbin-Watson: | 0.601 |
| Prob(Omnibus): | 0.368 | Jarque-Bera (JB): | 1.449 |
| Skew: | -0.583 | Prob(JB): | 0.485 |
| Kurtosis: | 2.021 | Cond. No. | 230. |
Model:
AIM ~ expression + C(dose)
OLS Regression Results
| Dep. Variable: | AIM | R-squared: | 0.492 |
| Model: | OLS | Adj. R-squared: | 0.407 |
| Method: | Least Squares | F-statistic: | 5.814 |
| Date: | Tue, 28 Jan 2025 | Prob (F-statistic): | 0.0172 |
| Time: | 19:50:25 | Log-Likelihood: | -70.219 |
| No. Observations: | 15 | AIC: | 146.4 |
| Df Residuals: | 12 | BIC: | 148.6 |
| Df Model: | 2 | | |
| coef | std err | t | P>|t| | [95.0% Conf. Int.] |
| Intercept | -9.9898 | 77.283 | -0.129 | 0.899 | -178.374 158.395 |
| C(dose)[T.1] | 51.4626 | 15.273 | 3.370 | 0.006 | 18.186 84.740 |
| expression | 9.9402 | 9.821 | 1.012 | 0.331 | -11.458 31.338 |
| Omnibus: | 2.562 | Durbin-Watson: | 0.656 |
| Prob(Omnibus): | 0.278 | Jarque-Bera (JB): | 1.824 |
| Skew: | -0.697 | Prob(JB): | 0.402 |
| Kurtosis: | 2.013 | Cond. No. | 80.6 |
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: | Tue, 28 Jan 2025 | Prob (F-statistic): | 0.00629 |
| Time: | 19:50:25 | 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: | 0.012 |
| Model: | OLS | Adj. R-squared: | -0.064 |
| Method: | Least Squares | F-statistic: | 0.1527 |
| Date: | Tue, 28 Jan 2025 | Prob (F-statistic): | 0.702 |
| Time: | 19:50:25 | Log-Likelihood: | -75.212 |
| No. Observations: | 15 | AIC: | 154.4 |
| Df Residuals: | 13 | BIC: | 155.8 |
| Df Model: | 1 | | |
| coef | std err | t | P>|t| | [95.0% Conf. Int.] |
| Intercept | 54.6511 | 100.341 | 0.545 | 0.595 | -162.122 271.424 |
| expression | 5.0889 | 13.021 | 0.391 | 0.702 | -23.042 33.219 |
| Omnibus: | 0.593 | Durbin-Watson: | 1.753 |
| Prob(Omnibus): | 0.743 | Jarque-Bera (JB): | 0.577 |
| Skew: | 0.047 | Prob(JB): | 0.749 |
| Kurtosis: | 2.043 | Cond. No. | 77.8 |