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 |
| 0.623 | 0.439 | 1.0 |
Model:
AIM ~ expression + C(dose) + expression:C(dose)
OLS Regression Results
| Dep. Variable: | AIM | R-squared: | 0.663 |
| Model: | OLS | Adj. R-squared: | 0.610 |
| Method: | Least Squares | F-statistic: | 12.48 |
| Date: | Tue, 03 Dec 2024 | Prob (F-statistic): | 9.70e-05 |
| Time: | 11:42:49 | Log-Likelihood: | -100.58 |
| No. Observations: | 23 | AIC: | 209.2 |
| Df Residuals: | 19 | BIC: | 213.7 |
| Df Model: | 3 | | |
| coef | std err | t | P>|t| | [95.0% Conf. Int.] |
| Intercept | 28.4489 | 47.903 | 0.594 | 0.560 | -71.814 128.712 |
| C(dose)[T.1] | -12.3080 | 136.245 | -0.090 | 0.929 | -297.473 272.857 |
| expression | 4.8805 | 9.002 | 0.542 | 0.594 | -13.961 23.722 |
| expression:C(dose)[T.1] | 10.9007 | 23.765 | 0.459 | 0.652 | -38.840 60.641 |
| Omnibus: | 0.364 | Durbin-Watson: | 1.754 |
| Prob(Omnibus): | 0.834 | Jarque-Bera (JB): | 0.507 |
| Skew: | -0.038 | Prob(JB): | 0.776 |
| Kurtosis: | 2.276 | Cond. No. | 206. |
Model:
AIM ~ expression + C(dose)
OLS Regression Results
| Dep. Variable: | AIM | R-squared: | 0.660 |
| Model: | OLS | Adj. R-squared: | 0.626 |
| Method: | Least Squares | F-statistic: | 19.38 |
| Date: | Tue, 03 Dec 2024 | Prob (F-statistic): | 2.09e-05 |
| Time: | 11:42:49 | Log-Likelihood: | -100.71 |
| No. Observations: | 23 | AIC: | 207.4 |
| Df Residuals: | 20 | BIC: | 210.8 |
| Df Model: | 2 | | |
| coef | std err | t | P>|t| | [95.0% Conf. Int.] |
| Intercept | 20.1931 | 43.508 | 0.464 | 0.648 | -70.564 110.950 |
| C(dose)[T.1] | 50.0248 | 9.602 | 5.210 | 0.000 | 29.995 70.054 |
| expression | 6.4447 | 8.165 | 0.789 | 0.439 | -10.588 23.477 |
| Omnibus: | 0.409 | Durbin-Watson: | 1.686 |
| Prob(Omnibus): | 0.815 | Jarque-Bera (JB): | 0.531 |
| Skew: | -0.027 | Prob(JB): | 0.767 |
| Kurtosis: | 2.257 | Cond. No. | 58.3 |
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, 03 Dec 2024 | Prob (F-statistic): | 3.51e-06 |
| Time: | 11:42:49 | 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: | 0.198 |
| Model: | OLS | Adj. R-squared: | 0.160 |
| Method: | Least Squares | F-statistic: | 5.177 |
| Date: | Tue, 03 Dec 2024 | Prob (F-statistic): | 0.0335 |
| Time: | 11:42:49 | Log-Likelihood: | -110.57 |
| No. Observations: | 23 | AIC: | 225.1 |
| Df Residuals: | 21 | BIC: | 227.4 |
| Df Model: | 1 | | |
| coef | std err | t | P>|t| | [95.0% Conf. Int.] |
| Intercept | -58.5823 | 61.125 | -0.958 | 0.349 | -185.698 68.534 |
| expression | 25.0369 | 11.004 | 2.275 | 0.033 | 2.154 47.920 |
| Omnibus: | 2.306 | Durbin-Watson: | 2.107 |
| Prob(Omnibus): | 0.316 | Jarque-Bera (JB): | 1.138 |
| Skew: | 0.033 | Prob(JB): | 0.566 |
| Kurtosis: | 1.912 | Cond. No. | 54.2 |
CP101
Model Comparison: AIM ~ expression + C(dose) vs AIM ~ C(dose)
| F-statistic | p-value | df difference |
| 2.406 | 0.147 | 1.0 |
Model:
AIM ~ expression + C(dose) + expression:C(dose)
OLS Regression Results
| Dep. Variable: | AIM | R-squared: | 0.541 |
| Model: | OLS | Adj. R-squared: | 0.416 |
| Method: | Least Squares | F-statistic: | 4.320 |
| Date: | Tue, 03 Dec 2024 | Prob (F-statistic): | 0.0305 |
| Time: | 11:42:49 | Log-Likelihood: | -69.462 |
| No. Observations: | 15 | AIC: | 146.9 |
| Df Residuals: | 11 | BIC: | 149.8 |
| Df Model: | 3 | | |
| coef | std err | t | P>|t| | [95.0% Conf. Int.] |
| Intercept | 189.9839 | 128.645 | 1.477 | 0.168 | -93.161 473.129 |
| C(dose)[T.1] | 38.2253 | 162.127 | 0.236 | 0.818 | -318.613 395.064 |
| expression | -20.8199 | 21.775 | -0.956 | 0.360 | -68.746 27.107 |
| expression:C(dose)[T.1] | 0.8596 | 27.970 | 0.031 | 0.976 | -60.702 62.421 |
| Omnibus: | 1.007 | Durbin-Watson: | 0.987 |
| Prob(Omnibus): | 0.604 | Jarque-Bera (JB): | 0.859 |
| Skew: | -0.498 | Prob(JB): | 0.651 |
| Kurtosis: | 2.381 | Cond. No. | 179. |
Model:
AIM ~ expression + C(dose)
OLS Regression Results
| Dep. Variable: | AIM | R-squared: | 0.541 |
| Model: | OLS | Adj. R-squared: | 0.464 |
| Method: | Least Squares | F-statistic: | 7.068 |
| Date: | Tue, 03 Dec 2024 | Prob (F-statistic): | 0.00937 |
| Time: | 11:42:49 | Log-Likelihood: | -69.462 |
| No. Observations: | 15 | AIC: | 144.9 |
| Df Residuals: | 12 | BIC: | 147.0 |
| Df Model: | 2 | | |
| coef | std err | t | P>|t| | [95.0% Conf. Int.] |
| Intercept | 186.9172 | 77.737 | 2.404 | 0.033 | 17.543 356.291 |
| C(dose)[T.1] | 43.1850 | 14.879 | 2.902 | 0.013 | 10.767 75.603 |
| expression | -20.2989 | 13.085 | -1.551 | 0.147 | -48.809 8.211 |
| Omnibus: | 1.001 | Durbin-Watson: | 0.986 |
| Prob(Omnibus): | 0.606 | Jarque-Bera (JB): | 0.855 |
| Skew: | -0.496 | Prob(JB): | 0.652 |
| Kurtosis: | 2.380 | Cond. No. | 64.6 |
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, 03 Dec 2024 | Prob (F-statistic): | 0.00629 |
| Time: | 11:42:49 | 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: | 0.219 |
| Model: | OLS | Adj. R-squared: | 0.158 |
| Method: | Least Squares | F-statistic: | 3.635 |
| Date: | Tue, 03 Dec 2024 | Prob (F-statistic): | 0.0789 |
| Time: | 11:42:49 | Log-Likelihood: | -73.451 |
| No. Observations: | 15 | AIC: | 150.9 |
| Df Residuals: | 13 | BIC: | 152.3 |
| Df Model: | 1 | | |
| coef | std err | t | P>|t| | [95.0% Conf. Int.] |
| Intercept | 266.6155 | 91.158 | 2.925 | 0.012 | 69.681 463.550 |
| expression | -30.1909 | 15.836 | -1.907 | 0.079 | -64.402 4.020 |
| Omnibus: | 1.420 | Durbin-Watson: | 2.010 |
| Prob(Omnibus): | 0.492 | Jarque-Bera (JB): | 1.086 |
| Skew: | 0.449 | Prob(JB): | 0.581 |
| Kurtosis: | 2.035 | Cond. No. | 60.2 |