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 |
| 0.019 | 0.892 | 1.0 |
Model:
AIM ~ expression + C(dose) + expression:C(dose)
OLS Regression Results
| Dep. Variable: | AIM | R-squared: | 0.684 |
| Model: | OLS | Adj. R-squared: | 0.634 |
| Method: | Least Squares | F-statistic: | 13.71 |
| Date: | Tue, 28 Jan 2025 | Prob (F-statistic): | 5.38e-05 |
| Time: | 19:17:24 | Log-Likelihood: | -99.855 |
| No. Observations: | 23 | AIC: | 207.7 |
| Df Residuals: | 19 | BIC: | 212.3 |
| Df Model: | 3 | | |
| coef | std err | t | P>|t| | [95.0% Conf. Int.] |
| Intercept | 75.8256 | 22.415 | 3.383 | 0.003 | 28.910 122.741 |
| C(dose)[T.1] | 0.9330 | 37.393 | 0.025 | 0.980 | -77.331 79.197 |
| expression | -5.9528 | 5.955 | -1.000 | 0.330 | -18.416 6.510 |
| expression:C(dose)[T.1] | 13.9653 | 9.672 | 1.444 | 0.165 | -6.279 34.210 |
| Omnibus: | 2.769 | Durbin-Watson: | 2.086 |
| Prob(Omnibus): | 0.250 | Jarque-Bera (JB): | 1.236 |
| Skew: | 0.025 | Prob(JB): | 0.539 |
| Kurtosis: | 1.866 | Cond. No. | 44.2 |
Model:
AIM ~ expression + C(dose)
OLS Regression Results
| Dep. Variable: | AIM | R-squared: | 0.649 |
| Model: | OLS | Adj. R-squared: | 0.614 |
| Method: | Least Squares | F-statistic: | 18.52 |
| Date: | Tue, 28 Jan 2025 | Prob (F-statistic): | 2.81e-05 |
| Time: | 19:17:24 | Log-Likelihood: | -101.05 |
| No. Observations: | 23 | AIC: | 208.1 |
| Df Residuals: | 20 | BIC: | 211.5 |
| Df Model: | 2 | | |
| coef | std err | t | P>|t| | [95.0% Conf. Int.] |
| Intercept | 56.6052 | 18.517 | 3.057 | 0.006 | 17.980 95.231 |
| C(dose)[T.1] | 53.4763 | 8.824 | 6.060 | 0.000 | 35.069 71.884 |
| expression | -0.6600 | 4.818 | -0.137 | 0.892 | -10.710 9.390 |
| Omnibus: | 0.257 | Durbin-Watson: | 1.924 |
| Prob(Omnibus): | 0.879 | Jarque-Bera (JB): | 0.444 |
| Skew: | 0.038 | Prob(JB): | 0.801 |
| Kurtosis: | 2.323 | Cond. No. | 17.4 |
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: | 19:17:24 | 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: | 0.006 |
| Model: | OLS | Adj. R-squared: | -0.042 |
| Method: | Least Squares | F-statistic: | 0.1179 |
| Date: | Tue, 28 Jan 2025 | Prob (F-statistic): | 0.735 |
| Time: | 19:17:24 | Log-Likelihood: | -113.04 |
| No. Observations: | 23 | AIC: | 230.1 |
| Df Residuals: | 21 | BIC: | 232.4 |
| Df Model: | 1 | | |
| coef | std err | t | P>|t| | [95.0% Conf. Int.] |
| Intercept | 69.6354 | 30.227 | 2.304 | 0.032 | 6.775 132.495 |
| expression | 2.7013 | 7.866 | 0.343 | 0.735 | -13.656 19.059 |
| Omnibus: | 3.330 | Durbin-Watson: | 2.439 |
| Prob(Omnibus): | 0.189 | Jarque-Bera (JB): | 1.499 |
| Skew: | 0.237 | Prob(JB): | 0.473 |
| Kurtosis: | 1.843 | Cond. No. | 17.2 |
CP101
Model Comparison: AIM ~ expression + C(dose) vs AIM ~ C(dose)
| F-statistic | p-value | df difference |
| 6.357 | 0.027 | 1.0 |
Model:
AIM ~ expression + C(dose) + expression:C(dose)
OLS Regression Results
| Dep. Variable: | AIM | R-squared: | 0.640 |
| Model: | OLS | Adj. R-squared: | 0.541 |
| Method: | Least Squares | F-statistic: | 6.510 |
| Date: | Tue, 28 Jan 2025 | Prob (F-statistic): | 0.00857 |
| Time: | 19:17:24 | Log-Likelihood: | -67.644 |
| No. Observations: | 15 | AIC: | 143.3 |
| Df Residuals: | 11 | BIC: | 146.1 |
| Df Model: | 3 | | |
| coef | std err | t | P>|t| | [95.0% Conf. Int.] |
| Intercept | 201.1318 | 111.319 | 1.807 | 0.098 | -43.881 446.144 |
| C(dose)[T.1] | 56.1135 | 130.361 | 0.430 | 0.675 | -230.810 343.037 |
| expression | -26.3451 | 21.851 | -1.206 | 0.253 | -74.439 21.749 |
| expression:C(dose)[T.1] | -0.7988 | 25.414 | -0.031 | 0.975 | -56.735 55.137 |
| Omnibus: | 0.214 | Durbin-Watson: | 0.758 |
| Prob(Omnibus): | 0.899 | Jarque-Bera (JB): | 0.159 |
| Skew: | -0.185 | Prob(JB): | 0.924 |
| Kurtosis: | 2.658 | Cond. No. | 156. |
Model:
AIM ~ expression + C(dose)
OLS Regression Results
| Dep. Variable: | AIM | R-squared: | 0.640 |
| Model: | OLS | Adj. R-squared: | 0.580 |
| Method: | Least Squares | F-statistic: | 10.65 |
| Date: | Tue, 28 Jan 2025 | Prob (F-statistic): | 0.00219 |
| Time: | 19:17:24 | Log-Likelihood: | -67.645 |
| No. Observations: | 15 | AIC: | 141.3 |
| Df Residuals: | 12 | BIC: | 143.4 |
| Df Model: | 2 | | |
| coef | std err | t | P>|t| | [95.0% Conf. Int.] |
| Intercept | 204.1286 | 55.008 | 3.711 | 0.003 | 84.275 323.982 |
| C(dose)[T.1] | 52.0378 | 12.776 | 4.073 | 0.002 | 24.202 79.873 |
| expression | -26.9356 | 10.683 | -2.521 | 0.027 | -50.212 -3.659 |
| Omnibus: | 0.220 | Durbin-Watson: | 0.753 |
| Prob(Omnibus): | 0.896 | Jarque-Bera (JB): | 0.165 |
| Skew: | -0.190 | Prob(JB): | 0.921 |
| Kurtosis: | 2.656 | Cond. No. | 46.7 |
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: | 19:17:24 | 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: | 0.141 |
| Model: | OLS | Adj. R-squared: | 0.075 |
| Method: | Least Squares | F-statistic: | 2.142 |
| Date: | Tue, 28 Jan 2025 | Prob (F-statistic): | 0.167 |
| Time: | 19:17:24 | Log-Likelihood: | -74.156 |
| No. Observations: | 15 | AIC: | 152.3 |
| Df Residuals: | 13 | BIC: | 153.7 |
| Df Model: | 1 | | |
| coef | std err | t | P>|t| | [95.0% Conf. Int.] |
| Intercept | 212.1856 | 81.525 | 2.603 | 0.022 | 36.061 388.311 |
| expression | -23.0971 | 15.781 | -1.464 | 0.167 | -57.191 10.997 |
| Omnibus: | 1.631 | Durbin-Watson: | 1.923 |
| Prob(Omnibus): | 0.442 | Jarque-Bera (JB): | 0.920 |
| Skew: | 0.187 | Prob(JB): | 0.631 |
| Kurtosis: | 1.845 | Cond. No. | 46.4 |