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 |
| 0.246 | 0.625 | 1.0 |
Model:
AIM ~ expression + C(dose) + expression:C(dose)
OLS Regression Results
| Dep. Variable: | AIM | R-squared: | 0.679 |
| Model: | OLS | Adj. R-squared: | 0.629 |
| Method: | Least Squares | F-statistic: | 13.43 |
| Date: | Wed, 29 Jan 2025 | Prob (F-statistic): | 6.16e-05 |
| Time: | 01:07:17 | Log-Likelihood: | -100.02 |
| No. Observations: | 23 | AIC: | 208.0 |
| Df Residuals: | 19 | BIC: | 212.6 |
| Df Model: | 3 | | |
| coef | std err | t | P>|t| | [95.0% Conf. Int.] |
| Intercept | 91.4385 | 49.073 | 1.863 | 0.078 | -11.273 194.150 |
| C(dose)[T.1] | -12.5137 | 55.850 | -0.224 | 0.825 | -129.409 104.382 |
| expression | -8.1004 | 10.598 | -0.764 | 0.454 | -30.283 14.082 |
| expression:C(dose)[T.1] | 15.7796 | 12.678 | 1.245 | 0.228 | -10.756 42.316 |
| Omnibus: | 1.034 | Durbin-Watson: | 2.068 |
| Prob(Omnibus): | 0.596 | Jarque-Bera (JB): | 0.931 |
| Skew: | 0.289 | Prob(JB): | 0.628 |
| Kurtosis: | 2.203 | Cond. No. | 82.0 |
Model:
AIM ~ expression + C(dose)
OLS Regression Results
| Dep. Variable: | AIM | R-squared: | 0.653 |
| Model: | OLS | Adj. R-squared: | 0.619 |
| Method: | Least Squares | F-statistic: | 18.85 |
| Date: | Wed, 29 Jan 2025 | Prob (F-statistic): | 2.51e-05 |
| Time: | 01:07:17 | Log-Likelihood: | -100.92 |
| No. Observations: | 23 | AIC: | 207.8 |
| Df Residuals: | 20 | BIC: | 211.3 |
| Df Model: | 2 | | |
| coef | std err | t | P>|t| | [95.0% Conf. Int.] |
| Intercept | 40.7576 | 27.760 | 1.468 | 0.158 | -17.149 98.664 |
| C(dose)[T.1] | 55.8806 | 10.111 | 5.527 | 0.000 | 34.790 76.971 |
| expression | 2.9266 | 5.896 | 0.496 | 0.625 | -9.372 15.225 |
| Omnibus: | 0.539 | Durbin-Watson: | 1.944 |
| Prob(Omnibus): | 0.764 | Jarque-Bera (JB): | 0.627 |
| Skew: | 0.175 | Prob(JB): | 0.731 |
| Kurtosis: | 2.271 | Cond. No. | 29.4 |
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: | Wed, 29 Jan 2025 | Prob (F-statistic): | 3.51e-06 |
| Time: | 01:07:17 | 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: | 0.124 |
| Model: | OLS | Adj. R-squared: | 0.082 |
| Method: | Least Squares | F-statistic: | 2.969 |
| Date: | Wed, 29 Jan 2025 | Prob (F-statistic): | 0.0996 |
| Time: | 01:07:17 | Log-Likelihood: | -111.58 |
| No. Observations: | 23 | AIC: | 227.2 |
| Df Residuals: | 21 | BIC: | 229.4 |
| Df Model: | 1 | | |
| coef | std err | t | P>|t| | [95.0% Conf. Int.] |
| Intercept | 136.5166 | 33.649 | 4.057 | 0.001 | 66.539 206.494 |
| expression | -13.5869 | 7.885 | -1.723 | 0.100 | -29.985 2.812 |
| Omnibus: | 1.602 | Durbin-Watson: | 2.299 |
| Prob(Omnibus): | 0.449 | Jarque-Bera (JB): | 1.417 |
| Skew: | 0.534 | Prob(JB): | 0.492 |
| Kurtosis: | 2.417 | Cond. No. | 22.4 |
CP101
Model Comparison: AIM ~ expression + C(dose) vs AIM ~ C(dose)
| F-statistic | p-value | df difference |
| 0.912 | 0.358 | 1.0 |
Model:
AIM ~ expression + C(dose) + expression:C(dose)
OLS Regression Results
| Dep. Variable: | AIM | R-squared: | 0.490 |
| Model: | OLS | Adj. R-squared: | 0.350 |
| Method: | Least Squares | F-statistic: | 3.518 |
| Date: | Wed, 29 Jan 2025 | Prob (F-statistic): | 0.0525 |
| Time: | 01:07:17 | Log-Likelihood: | -70.255 |
| No. Observations: | 15 | AIC: | 148.5 |
| Df Residuals: | 11 | BIC: | 151.3 |
| Df Model: | 3 | | |
| coef | std err | t | P>|t| | [95.0% Conf. Int.] |
| Intercept | 101.2805 | 59.275 | 1.709 | 0.116 | -29.183 231.744 |
| C(dose)[T.1] | 70.0589 | 95.664 | 0.732 | 0.479 | -140.496 280.614 |
| expression | -7.0723 | 12.146 | -0.582 | 0.572 | -33.806 19.661 |
| expression:C(dose)[T.1] | -3.9452 | 19.272 | -0.205 | 0.842 | -46.362 38.472 |
| Omnibus: | 0.735 | Durbin-Watson: | 0.956 |
| Prob(Omnibus): | 0.693 | Jarque-Bera (JB): | 0.451 |
| Skew: | -0.396 | Prob(JB): | 0.798 |
| Kurtosis: | 2.693 | Cond. No. | 79.4 |
Model:
AIM ~ expression + C(dose)
OLS Regression Results
| Dep. Variable: | AIM | R-squared: | 0.488 |
| Model: | OLS | Adj. R-squared: | 0.402 |
| Method: | Least Squares | F-statistic: | 5.712 |
| Date: | Wed, 29 Jan 2025 | Prob (F-statistic): | 0.0181 |
| Time: | 01:07:17 | Log-Likelihood: | -70.284 |
| No. Observations: | 15 | AIC: | 146.6 |
| Df Residuals: | 12 | BIC: | 148.7 |
| Df Model: | 2 | | |
| coef | std err | t | P>|t| | [95.0% Conf. Int.] |
| Intercept | 108.7816 | 44.694 | 2.434 | 0.032 | 11.402 206.162 |
| C(dose)[T.1] | 50.7481 | 15.260 | 3.326 | 0.006 | 17.499 83.997 |
| expression | -8.6394 | 9.046 | -0.955 | 0.358 | -28.349 11.070 |
| Omnibus: | 0.770 | Durbin-Watson: | 0.907 |
| Prob(Omnibus): | 0.681 | Jarque-Bera (JB): | 0.536 |
| Skew: | -0.423 | Prob(JB): | 0.765 |
| Kurtosis: | 2.624 | Cond. No. | 30.6 |
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: | Wed, 29 Jan 2025 | Prob (F-statistic): | 0.00629 |
| Time: | 01:07:17 | 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: | 0.016 |
| Model: | OLS | Adj. R-squared: | -0.060 |
| Method: | Least Squares | F-statistic: | 0.2060 |
| Date: | Wed, 29 Jan 2025 | Prob (F-statistic): | 0.657 |
| Time: | 01:07:17 | Log-Likelihood: | -75.182 |
| No. Observations: | 15 | AIC: | 154.4 |
| Df Residuals: | 13 | BIC: | 155.8 |
| Df Model: | 1 | | |
| coef | std err | t | P>|t| | [95.0% Conf. Int.] |
| Intercept | 120.2109 | 59.349 | 2.026 | 0.064 | -8.004 248.426 |
| expression | -5.4368 | 11.979 | -0.454 | 0.657 | -31.316 20.443 |
| Omnibus: | 1.384 | Durbin-Watson: | 1.534 |
| Prob(Omnibus): | 0.501 | Jarque-Bera (JB): | 0.852 |
| Skew: | 0.172 | Prob(JB): | 0.653 |
| Kurtosis: | 1.884 | Cond. No. | 30.3 |