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 |
| 0.491 | 0.491 | 1.0 |
Model:
AIM ~ expression + C(dose) + expression:C(dose)
OLS Regression Results
| Dep. Variable: | AIM | R-squared: | 0.681 |
| Model: | OLS | Adj. R-squared: | 0.630 |
| Method: | Least Squares | F-statistic: | 13.49 |
| Date: | Thu, 03 Apr 2025 | Prob (F-statistic): | 5.96e-05 |
| Time: | 22:49:22 | Log-Likelihood: | -99.980 |
| No. Observations: | 23 | AIC: | 208.0 |
| Df Residuals: | 19 | BIC: | 212.5 |
| Df Model: | 3 | | |
| coef | std err | t | P>|t| | [95.0% Conf. Int.] |
| Intercept | 179.4182 | 98.114 | 1.829 | 0.083 | -25.936 384.772 |
| C(dose)[T.1] | -135.8769 | 163.432 | -0.831 | 0.416 | -477.944 206.190 |
| expression | -18.6624 | 14.597 | -1.279 | 0.216 | -49.214 11.889 |
| expression:C(dose)[T.1] | 27.8498 | 23.755 | 1.172 | 0.256 | -21.870 77.569 |
| Omnibus: | 0.413 | Durbin-Watson: | 1.992 |
| Prob(Omnibus): | 0.813 | Jarque-Bera (JB): | 0.533 |
| Skew: | -0.020 | Prob(JB): | 0.766 |
| Kurtosis: | 2.255 | Cond. No. | 328. |
Model:
AIM ~ expression + C(dose)
OLS Regression Results
| Dep. Variable: | AIM | R-squared: | 0.657 |
| Model: | OLS | Adj. R-squared: | 0.623 |
| Method: | Least Squares | F-statistic: | 19.19 |
| Date: | Thu, 03 Apr 2025 | Prob (F-statistic): | 2.22e-05 |
| Time: | 22:49:22 | Log-Likelihood: | -100.78 |
| 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 | 108.8656 | 78.213 | 1.392 | 0.179 | -54.284 272.015 |
| C(dose)[T.1] | 55.4327 | 9.165 | 6.048 | 0.000 | 36.314 74.552 |
| expression | -8.1466 | 11.623 | -0.701 | 0.491 | -32.392 16.099 |
| Omnibus: | 0.461 | Durbin-Watson: | 1.906 |
| Prob(Omnibus): | 0.794 | Jarque-Bera (JB): | 0.562 |
| Skew: | 0.070 | Prob(JB): | 0.755 |
| Kurtosis: | 2.247 | Cond. No. | 127. |
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: | Thu, 03 Apr 2025 | Prob (F-statistic): | 3.51e-06 |
| Time: | 22:49:22 | 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: | 0.031 |
| Model: | OLS | Adj. R-squared: | -0.015 |
| Method: | Least Squares | F-statistic: | 0.6721 |
| Date: | Thu, 03 Apr 2025 | Prob (F-statistic): | 0.422 |
| Time: | 22:49:22 | Log-Likelihood: | -112.74 |
| No. Observations: | 23 | AIC: | 229.5 |
| Df Residuals: | 21 | BIC: | 231.8 |
| Df Model: | 1 | | |
| coef | std err | t | P>|t| | [95.0% Conf. Int.] |
| Intercept | -21.3022 | 123.422 | -0.173 | 0.865 | -277.973 235.369 |
| expression | 14.7857 | 18.035 | 0.820 | 0.422 | -22.720 52.291 |
| Omnibus: | 1.994 | Durbin-Watson: | 2.494 |
| Prob(Omnibus): | 0.369 | Jarque-Bera (JB): | 1.115 |
| Skew: | 0.147 | Prob(JB): | 0.573 |
| Kurtosis: | 1.962 | Cond. No. | 121. |
CP101
Model Comparison: AIM ~ expression + C(dose) vs AIM ~ C(dose)
| F-statistic | p-value | df difference |
| 0.059 | 0.811 | 1.0 |
Model:
AIM ~ expression + C(dose) + expression:C(dose)
OLS Regression Results
| Dep. Variable: | AIM | R-squared: | 0.454 |
| Model: | OLS | Adj. R-squared: | 0.305 |
| Method: | Least Squares | F-statistic: | 3.052 |
| Date: | Thu, 03 Apr 2025 | Prob (F-statistic): | 0.0739 |
| Time: | 22:49:23 | Log-Likelihood: | -70.758 |
| No. Observations: | 15 | AIC: | 149.5 |
| Df Residuals: | 11 | BIC: | 152.3 |
| Df Model: | 3 | | |
| coef | std err | t | P>|t| | [95.0% Conf. Int.] |
| Intercept | 6.0241 | 196.863 | 0.031 | 0.976 | -427.267 439.316 |
| C(dose)[T.1] | 99.3219 | 221.701 | 0.448 | 0.663 | -388.639 587.283 |
| expression | 17.9508 | 57.444 | 0.312 | 0.761 | -108.483 144.384 |
| expression:C(dose)[T.1] | -14.9322 | 63.526 | -0.235 | 0.818 | -154.752 124.887 |
| Omnibus: | 2.598 | Durbin-Watson: | 0.912 |
| Prob(Omnibus): | 0.273 | Jarque-Bera (JB): | 1.815 |
| Skew: | -0.826 | Prob(JB): | 0.404 |
| Kurtosis: | 2.585 | Cond. No. | 163. |
Model:
AIM ~ expression + C(dose)
OLS Regression Results
| Dep. Variable: | AIM | R-squared: | 0.451 |
| Model: | OLS | Adj. R-squared: | 0.360 |
| Method: | Least Squares | F-statistic: | 4.939 |
| Date: | Thu, 03 Apr 2025 | Prob (F-statistic): | 0.0272 |
| Time: | 22:49:23 | Log-Likelihood: | -70.796 |
| No. Observations: | 15 | AIC: | 147.6 |
| Df Residuals: | 12 | BIC: | 149.7 |
| Df Model: | 2 | | |
| coef | std err | t | P>|t| | [95.0% Conf. Int.] |
| Intercept | 47.7906 | 81.343 | 0.588 | 0.568 | -129.440 225.021 |
| C(dose)[T.1] | 47.3835 | 17.372 | 2.728 | 0.018 | 9.533 85.234 |
| expression | 5.7409 | 23.542 | 0.244 | 0.811 | -45.553 57.034 |
| Omnibus: | 2.164 | Durbin-Watson: | 0.872 |
| Prob(Omnibus): | 0.339 | Jarque-Bera (JB): | 1.567 |
| Skew: | -0.752 | Prob(JB): | 0.457 |
| Kurtosis: | 2.507 | Cond. No. | 41.0 |
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: | Thu, 03 Apr 2025 | Prob (F-statistic): | 0.00629 |
| Time: | 22:49:23 | 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: | 0.111 |
| Model: | OLS | Adj. R-squared: | 0.043 |
| Method: | Least Squares | F-statistic: | 1.630 |
| Date: | Thu, 03 Apr 2025 | Prob (F-statistic): | 0.224 |
| Time: | 22:49:23 | Log-Likelihood: | -74.414 |
| No. Observations: | 15 | AIC: | 152.8 |
| Df Residuals: | 13 | BIC: | 154.2 |
| Df Model: | 1 | | |
| coef | std err | t | P>|t| | [95.0% Conf. Int.] |
| Intercept | -25.5673 | 93.876 | -0.272 | 0.790 | -228.373 177.238 |
| expression | 33.2208 | 26.019 | 1.277 | 0.224 | -22.990 89.431 |
| Omnibus: | 0.956 | Durbin-Watson: | 1.472 |
| Prob(Omnibus): | 0.620 | Jarque-Bera (JB): | 0.433 |
| Skew: | 0.410 | Prob(JB): | 0.805 |
| Kurtosis: | 2.858 | Cond. No. | 38.1 |