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 |
| 0.159 | 0.694 | 1.0 |
Model:
AIM ~ expression + C(dose) + expression:C(dose)
OLS Regression Results
| Dep. Variable: | AIM | R-squared: | 0.655 |
| Model: | OLS | Adj. R-squared: | 0.600 |
| Method: | Least Squares | F-statistic: | 12.00 |
| Date: | Mon, 27 Jan 2025 | Prob (F-statistic): | 0.000123 |
| Time: | 21:13:55 | Log-Likelihood: | -100.88 |
| No. Observations: | 23 | AIC: | 209.8 |
| Df Residuals: | 19 | BIC: | 214.3 |
| Df Model: | 3 | | |
| coef | std err | t | P>|t| | [95.0% Conf. Int.] |
| Intercept | 74.3506 | 117.776 | 0.631 | 0.535 | -172.157 320.859 |
| C(dose)[T.1] | 165.7786 | 279.061 | 0.594 | 0.559 | -418.304 749.861 |
| expression | -2.4997 | 14.596 | -0.171 | 0.866 | -33.050 28.050 |
| expression:C(dose)[T.1] | -12.5014 | 32.123 | -0.389 | 0.701 | -79.735 54.732 |
| Omnibus: | 1.307 | Durbin-Watson: | 1.846 |
| Prob(Omnibus): | 0.520 | Jarque-Bera (JB): | 0.886 |
| Skew: | 0.068 | Prob(JB): | 0.642 |
| Kurtosis: | 2.048 | Cond. No. | 631. |
Model:
AIM ~ expression + C(dose)
OLS Regression Results
| Dep. Variable: | AIM | R-squared: | 0.652 |
| Model: | OLS | Adj. R-squared: | 0.617 |
| Method: | Least Squares | F-statistic: | 18.72 |
| Date: | Mon, 27 Jan 2025 | Prob (F-statistic): | 2.62e-05 |
| Time: | 21:13:55 | Log-Likelihood: | -100.97 |
| No. Observations: | 23 | AIC: | 207.9 |
| Df Residuals: | 20 | BIC: | 211.3 |
| Df Model: | 2 | | |
| coef | std err | t | P>|t| | [95.0% Conf. Int.] |
| Intercept | 95.1491 | 102.702 | 0.926 | 0.365 | -119.084 309.382 |
| C(dose)[T.1] | 57.3023 | 13.225 | 4.333 | 0.000 | 29.716 84.889 |
| expression | -5.0808 | 12.724 | -0.399 | 0.694 | -31.622 21.460 |
| Omnibus: | 0.953 | Durbin-Watson: | 1.879 |
| Prob(Omnibus): | 0.621 | Jarque-Bera (JB): | 0.761 |
| Skew: | 0.024 | Prob(JB): | 0.684 |
| Kurtosis: | 2.110 | Cond. No. | 203. |
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: | Mon, 27 Jan 2025 | Prob (F-statistic): | 3.51e-06 |
| Time: | 21:13:55 | 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: | 0.325 |
| Model: | OLS | Adj. R-squared: | 0.293 |
| Method: | Least Squares | F-statistic: | 10.11 |
| Date: | Mon, 27 Jan 2025 | Prob (F-statistic): | 0.00451 |
| Time: | 21:13:55 | Log-Likelihood: | -108.58 |
| No. Observations: | 23 | AIC: | 221.2 |
| Df Residuals: | 21 | BIC: | 223.4 |
| Df Model: | 1 | | |
| coef | std err | t | P>|t| | [95.0% Conf. Int.] |
| Intercept | -226.4322 | 96.461 | -2.347 | 0.029 | -427.033 -25.831 |
| expression | 36.3120 | 11.419 | 3.180 | 0.005 | 12.564 60.060 |
| Omnibus: | 1.295 | Durbin-Watson: | 2.292 |
| Prob(Omnibus): | 0.523 | Jarque-Bera (JB): | 1.079 |
| Skew: | 0.328 | Prob(JB): | 0.583 |
| Kurtosis: | 2.166 | Cond. No. | 139. |
CP101
Model Comparison: AIM ~ expression + C(dose) vs AIM ~ C(dose)
| F-statistic | p-value | df difference |
| 1.285 | 0.279 | 1.0 |
Model:
AIM ~ expression + C(dose) + expression:C(dose)
OLS Regression Results
| Dep. Variable: | AIM | R-squared: | 0.527 |
| Model: | OLS | Adj. R-squared: | 0.398 |
| Method: | Least Squares | F-statistic: | 4.082 |
| Date: | Mon, 27 Jan 2025 | Prob (F-statistic): | 0.0356 |
| Time: | 21:13:55 | Log-Likelihood: | -69.688 |
| No. Observations: | 15 | AIC: | 147.4 |
| Df Residuals: | 11 | BIC: | 150.2 |
| Df Model: | 3 | | |
| coef | std err | t | P>|t| | [95.0% Conf. Int.] |
| Intercept | 228.5457 | 120.571 | 1.896 | 0.085 | -36.830 493.922 |
| C(dose)[T.1] | -94.9758 | 193.046 | -0.492 | 0.632 | -519.868 329.916 |
| expression | -26.4928 | 19.741 | -1.342 | 0.207 | -69.943 16.957 |
| expression:C(dose)[T.1] | 23.7507 | 31.339 | 0.758 | 0.464 | -45.225 92.727 |
| Omnibus: | 2.346 | Durbin-Watson: | 1.087 |
| Prob(Omnibus): | 0.309 | Jarque-Bera (JB): | 1.358 |
| Skew: | -0.734 | Prob(JB): | 0.507 |
| Kurtosis: | 2.861 | Cond. No. | 204. |
Model:
AIM ~ expression + C(dose)
OLS Regression Results
| Dep. Variable: | AIM | R-squared: | 0.502 |
| Model: | OLS | Adj. R-squared: | 0.419 |
| Method: | Least Squares | F-statistic: | 6.050 |
| Date: | Mon, 27 Jan 2025 | Prob (F-statistic): | 0.0152 |
| Time: | 21:13:55 | Log-Likelihood: | -70.070 |
| No. Observations: | 15 | AIC: | 146.1 |
| Df Residuals: | 12 | BIC: | 148.3 |
| Df Model: | 2 | | |
| coef | std err | t | P>|t| | [95.0% Conf. Int.] |
| Intercept | 171.2293 | 92.223 | 1.857 | 0.088 | -29.708 372.166 |
| C(dose)[T.1] | 50.8683 | 15.032 | 3.384 | 0.005 | 18.117 83.620 |
| expression | -17.0682 | 15.058 | -1.134 | 0.279 | -49.876 15.740 |
| Omnibus: | 2.410 | Durbin-Watson: | 0.899 |
| Prob(Omnibus): | 0.300 | Jarque-Bera (JB): | 1.782 |
| Skew: | -0.798 | Prob(JB): | 0.410 |
| Kurtosis: | 2.448 | Cond. No. | 78.3 |
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: | Mon, 27 Jan 2025 | Prob (F-statistic): | 0.00629 |
| Time: | 21:13:55 | 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: | 0.027 |
| Model: | OLS | Adj. R-squared: | -0.048 |
| Method: | Least Squares | F-statistic: | 0.3595 |
| Date: | Mon, 27 Jan 2025 | Prob (F-statistic): | 0.559 |
| Time: | 21:13:55 | Log-Likelihood: | -75.095 |
| No. Observations: | 15 | AIC: | 154.2 |
| Df Residuals: | 13 | BIC: | 155.6 |
| Df Model: | 1 | | |
| coef | std err | t | P>|t| | [95.0% Conf. Int.] |
| Intercept | 167.6902 | 123.860 | 1.354 | 0.199 | -99.892 435.273 |
| expression | -12.0682 | 20.127 | -0.600 | 0.559 | -55.549 31.413 |
| Omnibus: | 2.477 | Durbin-Watson: | 1.751 |
| Prob(Omnibus): | 0.290 | Jarque-Bera (JB): | 1.135 |
| Skew: | 0.240 | Prob(JB): | 0.567 |
| Kurtosis: | 1.741 | Cond. No. | 78.0 |