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 |
| 3.322 | 0.083 | 1.0 |
Model:
AIM ~ expression + C(dose) + expression:C(dose)
OLS Regression Results
| Dep. Variable: | AIM | R-squared: | 0.699 |
| Model: | OLS | Adj. R-squared: | 0.652 |
| Method: | Least Squares | F-statistic: | 14.74 |
| Date: | Mon, 27 Jan 2025 | Prob (F-statistic): | 3.39e-05 |
| Time: | 21:34:55 | Log-Likelihood: | -99.282 |
| No. Observations: | 23 | AIC: | 206.6 |
| Df Residuals: | 19 | BIC: | 211.1 |
| Df Model: | 3 | | |
| coef | std err | t | P>|t| | [95.0% Conf. Int.] |
| Intercept | -55.3984 | 130.734 | -0.424 | 0.677 | -329.028 218.231 |
| C(dose)[T.1] | 65.9987 | 144.641 | 0.456 | 0.653 | -236.739 368.736 |
| expression | 19.2528 | 22.942 | 0.839 | 0.412 | -28.764 67.270 |
| expression:C(dose)[T.1] | -3.7460 | 24.967 | -0.150 | 0.882 | -56.003 48.511 |
| Omnibus: | 0.398 | Durbin-Watson: | 1.704 |
| Prob(Omnibus): | 0.820 | Jarque-Bera (JB): | 0.525 |
| Skew: | -0.001 | Prob(JB): | 0.769 |
| Kurtosis: | 2.260 | Cond. No. | 326. |
Model:
AIM ~ expression + C(dose)
OLS Regression Results
| Dep. Variable: | AIM | R-squared: | 0.699 |
| Model: | OLS | Adj. R-squared: | 0.669 |
| Method: | Least Squares | F-statistic: | 23.23 |
| Date: | Mon, 27 Jan 2025 | Prob (F-statistic): | 6.10e-06 |
| Time: | 21:34:55 | Log-Likelihood: | -99.296 |
| No. Observations: | 23 | AIC: | 204.6 |
| Df Residuals: | 20 | BIC: | 208.0 |
| Df Model: | 2 | | |
| coef | std err | t | P>|t| | [95.0% Conf. Int.] |
| Intercept | -37.3927 | 50.574 | -0.739 | 0.468 | -142.887 68.102 |
| C(dose)[T.1] | 44.3466 | 9.502 | 4.667 | 0.000 | 24.525 64.168 |
| expression | 16.0900 | 8.828 | 1.823 | 0.083 | -2.326 34.506 |
| Omnibus: | 0.297 | Durbin-Watson: | 1.684 |
| Prob(Omnibus): | 0.862 | Jarque-Bera (JB): | 0.469 |
| Skew: | 0.029 | Prob(JB): | 0.791 |
| Kurtosis: | 2.303 | Cond. No. | 77.3 |
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: | Mon, 27 Jan 2025 | Prob (F-statistic): | 3.51e-06 |
| Time: | 21:34:55 | 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: | 0.371 |
| Model: | OLS | Adj. R-squared: | 0.341 |
| Method: | Least Squares | F-statistic: | 12.40 |
| Date: | Mon, 27 Jan 2025 | Prob (F-statistic): | 0.00203 |
| Time: | 21:34:55 | Log-Likelihood: | -107.77 |
| No. Observations: | 23 | AIC: | 219.5 |
| Df Residuals: | 21 | BIC: | 221.8 |
| Df Model: | 1 | | |
| coef | std err | t | P>|t| | [95.0% Conf. Int.] |
| Intercept | -143.6748 | 63.693 | -2.256 | 0.035 | -276.133 -11.217 |
| expression | 37.4802 | 10.643 | 3.522 | 0.002 | 15.347 59.614 |
| Omnibus: | 3.720 | Durbin-Watson: | 1.799 |
| Prob(Omnibus): | 0.156 | Jarque-Bera (JB): | 2.130 |
| Skew: | 0.707 | Prob(JB): | 0.345 |
| Kurtosis: | 3.472 | Cond. No. | 68.5 |
CP101
Model Comparison: AIM ~ expression + C(dose) vs AIM ~ C(dose)
| F-statistic | p-value | df difference |
| 2.817 | 0.119 | 1.0 |
Model:
AIM ~ expression + C(dose) + expression:C(dose)
OLS Regression Results
| Dep. Variable: | AIM | R-squared: | 0.554 |
| Model: | OLS | Adj. R-squared: | 0.432 |
| Method: | Least Squares | F-statistic: | 4.547 |
| Date: | Mon, 27 Jan 2025 | Prob (F-statistic): | 0.0263 |
| Time: | 21:34:55 | Log-Likelihood: | -69.251 |
| No. Observations: | 15 | AIC: | 146.5 |
| Df Residuals: | 11 | BIC: | 149.3 |
| Df Model: | 3 | | |
| coef | std err | t | P>|t| | [95.0% Conf. Int.] |
| Intercept | -126.5321 | 150.850 | -0.839 | 0.419 | -458.551 205.487 |
| C(dose)[T.1] | 35.0099 | 264.413 | 0.132 | 0.897 | -546.959 616.979 |
| expression | 33.4202 | 25.925 | 1.289 | 0.224 | -23.641 90.482 |
| expression:C(dose)[T.1] | -0.6331 | 42.892 | -0.015 | 0.988 | -95.037 93.771 |
| Omnibus: | 2.018 | Durbin-Watson: | 1.331 |
| Prob(Omnibus): | 0.364 | Jarque-Bera (JB): | 1.485 |
| Skew: | -0.725 | Prob(JB): | 0.476 |
| Kurtosis: | 2.477 | Cond. No. | 283. |
Model:
AIM ~ expression + C(dose)
OLS Regression Results
| Dep. Variable: | AIM | R-squared: | 0.554 |
| Model: | OLS | Adj. R-squared: | 0.479 |
| Method: | Least Squares | F-statistic: | 7.440 |
| Date: | Mon, 27 Jan 2025 | Prob (F-statistic): | 0.00792 |
| Time: | 21:34:55 | Log-Likelihood: | -69.252 |
| No. Observations: | 15 | AIC: | 144.5 |
| Df Residuals: | 12 | BIC: | 146.6 |
| Df Model: | 2 | | |
| coef | std err | t | P>|t| | [95.0% Conf. Int.] |
| Intercept | -125.1896 | 115.230 | -1.086 | 0.299 | -376.254 125.875 |
| C(dose)[T.1] | 31.1164 | 17.796 | 1.749 | 0.106 | -7.657 69.890 |
| expression | 33.1889 | 19.774 | 1.678 | 0.119 | -9.896 76.274 |
| Omnibus: | 2.003 | Durbin-Watson: | 1.325 |
| Prob(Omnibus): | 0.367 | Jarque-Bera (JB): | 1.475 |
| Skew: | -0.722 | Prob(JB): | 0.478 |
| Kurtosis: | 2.477 | Cond. No. | 103. |
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: | 21:34:55 | 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: | 0.440 |
| Model: | OLS | Adj. R-squared: | 0.397 |
| Method: | Least Squares | F-statistic: | 10.21 |
| Date: | Mon, 27 Jan 2025 | Prob (F-statistic): | 0.00704 |
| Time: | 21:34:55 | Log-Likelihood: | -70.954 |
| No. Observations: | 15 | AIC: | 145.9 |
| Df Residuals: | 13 | BIC: | 147.3 |
| Df Model: | 1 | | |
| coef | std err | t | P>|t| | [95.0% Conf. Int.] |
| Intercept | -236.1498 | 103.513 | -2.281 | 0.040 | -459.777 -12.523 |
| expression | 54.1195 | 16.940 | 3.195 | 0.007 | 17.524 90.715 |
| Omnibus: | 0.833 | Durbin-Watson: | 1.938 |
| Prob(Omnibus): | 0.659 | Jarque-Bera (JB): | 0.746 |
| Skew: | 0.290 | Prob(JB): | 0.689 |
| Kurtosis: | 2.075 | Cond. No. | 85.4 |