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 |
| 0.450 | 0.510 | 1.0 |
Model:
AIM ~ expression + C(dose) + expression:C(dose)
OLS Regression Results
| Dep. Variable: | AIM | R-squared: | 0.734 |
| Model: | OLS | Adj. R-squared: | 0.692 |
| Method: | Least Squares | F-statistic: | 17.49 |
| Date: | Tue, 03 Dec 2024 | Prob (F-statistic): | 1.08e-05 |
| Time: | 11:49:20 | Log-Likelihood: | -97.868 |
| No. Observations: | 23 | AIC: | 203.7 |
| Df Residuals: | 19 | BIC: | 208.3 |
| Df Model: | 3 | | |
| coef | std err | t | P>|t| | [95.0% Conf. Int.] |
| Intercept | -31.7357 | 57.635 | -0.551 | 0.588 | -152.368 88.896 |
| C(dose)[T.1] | 223.5674 | 72.136 | 3.099 | 0.006 | 72.585 374.550 |
| expression | 22.5871 | 15.080 | 1.498 | 0.151 | -8.976 54.150 |
| expression:C(dose)[T.1] | -43.3432 | 18.428 | -2.352 | 0.030 | -81.913 -4.773 |
| Omnibus: | 1.389 | Durbin-Watson: | 1.758 |
| Prob(Omnibus): | 0.499 | Jarque-Bera (JB): | 0.346 |
| Skew: | -0.179 | Prob(JB): | 0.841 |
| Kurtosis: | 3.482 | Cond. No. | 109. |
Model:
AIM ~ expression + C(dose)
OLS Regression Results
| Dep. Variable: | AIM | R-squared: | 0.657 |
| Model: | OLS | Adj. R-squared: | 0.622 |
| Method: | Least Squares | F-statistic: | 19.14 |
| Date: | Tue, 03 Dec 2024 | Prob (F-statistic): | 2.27e-05 |
| Time: | 11:49:20 | Log-Likelihood: | -100.81 |
| 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 | 78.7074 | 37.014 | 2.126 | 0.046 | 1.497 155.917 |
| C(dose)[T.1] | 54.9839 | 9.014 | 6.100 | 0.000 | 36.182 73.786 |
| expression | -6.4386 | 9.599 | -0.671 | 0.510 | -26.462 13.585 |
| Omnibus: | 0.427 | Durbin-Watson: | 1.732 |
| Prob(Omnibus): | 0.808 | Jarque-Bera (JB): | 0.540 |
| Skew: | -0.021 | Prob(JB): | 0.763 |
| Kurtosis: | 2.250 | Cond. No. | 36.3 |
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: | 11:49:20 | 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: | 0.018 |
| Model: | OLS | Adj. R-squared: | -0.029 |
| Method: | Least Squares | F-statistic: | 0.3892 |
| Date: | Tue, 03 Dec 2024 | Prob (F-statistic): | 0.539 |
| Time: | 11:49:20 | Log-Likelihood: | -112.89 |
| No. Observations: | 23 | AIC: | 229.8 |
| Df Residuals: | 21 | BIC: | 232.1 |
| Df Model: | 1 | | |
| coef | std err | t | P>|t| | [95.0% Conf. Int.] |
| Intercept | 42.3648 | 60.297 | 0.703 | 0.490 | -83.030 167.759 |
| expression | 9.5109 | 15.245 | 0.624 | 0.539 | -22.192 41.214 |
| Omnibus: | 2.756 | Durbin-Watson: | 2.512 |
| Prob(Omnibus): | 0.252 | Jarque-Bera (JB): | 1.844 |
| Skew: | 0.489 | Prob(JB): | 0.398 |
| Kurtosis: | 2.016 | Cond. No. | 35.5 |
CP101
Model Comparison: AIM ~ expression + C(dose) vs AIM ~ C(dose)
| F-statistic | p-value | df difference |
| 0.026 | 0.874 | 1.0 |
Model:
AIM ~ expression + C(dose) + expression:C(dose)
OLS Regression Results
| Dep. Variable: | AIM | R-squared: | 0.505 |
| Model: | OLS | Adj. R-squared: | 0.370 |
| Method: | Least Squares | F-statistic: | 3.739 |
| Date: | Tue, 03 Dec 2024 | Prob (F-statistic): | 0.0450 |
| Time: | 11:49:20 | Log-Likelihood: | -70.028 |
| No. Observations: | 15 | AIC: | 148.1 |
| Df Residuals: | 11 | BIC: | 150.9 |
| Df Model: | 3 | | |
| coef | std err | t | P>|t| | [95.0% Conf. Int.] |
| Intercept | 58.0528 | 74.331 | 0.781 | 0.451 | -105.549 221.655 |
| C(dose)[T.1] | 335.3364 | 260.551 | 1.287 | 0.225 | -238.133 908.806 |
| expression | 2.6132 | 20.473 | 0.128 | 0.901 | -42.448 47.674 |
| expression:C(dose)[T.1] | -87.4640 | 79.184 | -1.105 | 0.293 | -261.746 86.818 |
| Omnibus: | 1.113 | Durbin-Watson: | 1.034 |
| Prob(Omnibus): | 0.573 | Jarque-Bera (JB): | 0.968 |
| Skew: | -0.487 | Prob(JB): | 0.616 |
| Kurtosis: | 2.224 | Cond. No. | 143. |
Model:
AIM ~ expression + C(dose)
OLS Regression Results
| Dep. Variable: | AIM | R-squared: | 0.450 |
| Model: | OLS | Adj. R-squared: | 0.358 |
| Method: | Least Squares | F-statistic: | 4.909 |
| Date: | Tue, 03 Dec 2024 | Prob (F-statistic): | 0.0277 |
| Time: | 11:49:20 | Log-Likelihood: | -70.817 |
| No. Observations: | 15 | AIC: | 147.6 |
| Df Residuals: | 12 | BIC: | 149.8 |
| Df Model: | 2 | | |
| coef | std err | t | P>|t| | [95.0% Conf. Int.] |
| Intercept | 79.0307 | 72.520 | 1.090 | 0.297 | -78.977 237.039 |
| C(dose)[T.1] | 48.1418 | 17.017 | 2.829 | 0.015 | 11.066 85.218 |
| expression | -3.2337 | 19.957 | -0.162 | 0.874 | -46.717 40.250 |
| Omnibus: | 2.657 | Durbin-Watson: | 0.802 |
| Prob(Omnibus): | 0.265 | Jarque-Bera (JB): | 1.873 |
| Skew: | -0.838 | Prob(JB): | 0.392 |
| Kurtosis: | 2.567 | Cond. No. | 34.9 |
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: | 11:49:20 | 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: | 0.083 |
| Model: | OLS | Adj. R-squared: | 0.013 |
| Method: | Least Squares | F-statistic: | 1.178 |
| Date: | Tue, 03 Dec 2024 | Prob (F-statistic): | 0.297 |
| Time: | 11:49:20 | Log-Likelihood: | -74.649 |
| No. Observations: | 15 | AIC: | 153.3 |
| Df Residuals: | 13 | BIC: | 154.7 |
| Df Model: | 1 | | |
| coef | std err | t | P>|t| | [95.0% Conf. Int.] |
| Intercept | 178.4388 | 78.694 | 2.267 | 0.041 | 8.430 348.447 |
| expression | -24.8309 | 22.874 | -1.086 | 0.297 | -74.247 24.585 |
| Omnibus: | 1.127 | Durbin-Watson: | 1.545 |
| Prob(Omnibus): | 0.569 | Jarque-Bera (JB): | 0.756 |
| Skew: | -0.098 | Prob(JB): | 0.685 |
| Kurtosis: | 1.918 | Cond. No. | 30.1 |