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 |
| 0.536 | 0.473 | 1.0 |
Model:
AIM ~ expression + C(dose) + expression:C(dose)
OLS Regression Results
| Dep. Variable: | AIM | R-squared: | 0.675 |
| Model: | OLS | Adj. R-squared: | 0.624 |
| Method: | Least Squares | F-statistic: | 13.14 |
| Date: | Wed, 29 Jan 2025 | Prob (F-statistic): | 7.03e-05 |
| Time: | 01:05:07 | Log-Likelihood: | -100.18 |
| No. Observations: | 23 | AIC: | 208.4 |
| Df Residuals: | 19 | BIC: | 212.9 |
| Df Model: | 3 | | |
| coef | std err | t | P>|t| | [95.0% Conf. Int.] |
| Intercept | -333.9222 | 320.554 | -1.042 | 0.311 | -1004.848 337.004 |
| C(dose)[T.1] | 510.0715 | 467.815 | 1.090 | 0.289 | -469.076 1489.219 |
| expression | 36.3137 | 29.986 | 1.211 | 0.241 | -26.448 99.075 |
| expression:C(dose)[T.1] | -42.5728 | 43.188 | -0.986 | 0.337 | -132.966 47.820 |
| Omnibus: | 0.421 | Durbin-Watson: | 2.014 |
| Prob(Omnibus): | 0.810 | Jarque-Bera (JB): | 0.554 |
| Skew: | -0.151 | Prob(JB): | 0.758 |
| Kurtosis: | 2.302 | Cond. No. | 1.52e+03 |
Model:
AIM ~ expression + C(dose)
OLS Regression Results
| Dep. Variable: | AIM | R-squared: | 0.658 |
| Model: | OLS | Adj. R-squared: | 0.624 |
| Method: | Least Squares | F-statistic: | 19.26 |
| Date: | Wed, 29 Jan 2025 | Prob (F-statistic): | 2.18e-05 |
| Time: | 01:05:07 | Log-Likelihood: | -100.76 |
| No. Observations: | 23 | AIC: | 207.5 |
| Df Residuals: | 20 | BIC: | 210.9 |
| Df Model: | 2 | | |
| coef | std err | t | P>|t| | [95.0% Conf. Int.] |
| Intercept | -114.5648 | 230.567 | -0.497 | 0.625 | -595.520 366.390 |
| C(dose)[T.1] | 49.0344 | 10.461 | 4.687 | 0.000 | 27.213 70.856 |
| expression | 15.7905 | 21.565 | 0.732 | 0.473 | -29.193 60.774 |
| Omnibus: | 0.079 | Durbin-Watson: | 1.973 |
| Prob(Omnibus): | 0.961 | Jarque-Bera (JB): | 0.213 |
| Skew: | -0.119 | Prob(JB): | 0.899 |
| Kurtosis: | 2.593 | Cond. No. | 583. |
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: | 01:05:07 | 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: | 0.283 |
| Model: | OLS | Adj. R-squared: | 0.249 |
| Method: | Least Squares | F-statistic: | 8.278 |
| Date: | Wed, 29 Jan 2025 | Prob (F-statistic): | 0.00902 |
| Time: | 01:05:07 | Log-Likelihood: | -109.28 |
| No. Observations: | 23 | AIC: | 222.6 |
| Df Residuals: | 21 | BIC: | 224.8 |
| Df Model: | 1 | | |
| coef | std err | t | P>|t| | [95.0% Conf. Int.] |
| Intercept | -705.3925 | 272.942 | -2.584 | 0.017 | -1273.006 -137.779 |
| expression | 72.5705 | 25.223 | 2.877 | 0.009 | 20.117 125.024 |
| Omnibus: | 1.584 | Durbin-Watson: | 2.234 |
| Prob(Omnibus): | 0.453 | Jarque-Bera (JB): | 0.770 |
| Skew: | 0.443 | Prob(JB): | 0.681 |
| Kurtosis: | 3.129 | Cond. No. | 487. |
CP101
Model Comparison: AIM ~ expression + C(dose) vs AIM ~ C(dose)
| F-statistic | p-value | df difference |
| 4.810 | 0.049 | 1.0 |
Model:
AIM ~ expression + C(dose) + expression:C(dose)
OLS Regression Results
| Dep. Variable: | AIM | R-squared: | 0.608 |
| Model: | OLS | Adj. R-squared: | 0.501 |
| Method: | Least Squares | F-statistic: | 5.689 |
| Date: | Wed, 29 Jan 2025 | Prob (F-statistic): | 0.0133 |
| Time: | 01:05:07 | Log-Likelihood: | -68.275 |
| No. Observations: | 15 | AIC: | 144.5 |
| Df Residuals: | 11 | BIC: | 147.4 |
| Df Model: | 3 | | |
| coef | std err | t | P>|t| | [95.0% Conf. Int.] |
| Intercept | -689.6866 | 422.633 | -1.632 | 0.131 | -1619.895 240.522 |
| C(dose)[T.1] | 164.1424 | 711.178 | 0.231 | 0.822 | -1401.150 1729.435 |
| expression | 71.4829 | 39.891 | 1.792 | 0.101 | -16.317 159.283 |
| expression:C(dose)[T.1] | -13.7755 | 65.058 | -0.212 | 0.836 | -156.967 129.415 |
| Omnibus: | 1.922 | Durbin-Watson: | 1.207 |
| Prob(Omnibus): | 0.382 | Jarque-Bera (JB): | 1.469 |
| Skew: | -0.622 | Prob(JB): | 0.480 |
| Kurtosis: | 2.103 | Cond. No. | 1.42e+03 |
Model:
AIM ~ expression + C(dose)
OLS Regression Results
| Dep. Variable: | AIM | R-squared: | 0.606 |
| Model: | OLS | Adj. R-squared: | 0.541 |
| Method: | Least Squares | F-statistic: | 9.248 |
| Date: | Wed, 29 Jan 2025 | Prob (F-statistic): | 0.00371 |
| Time: | 01:05:07 | Log-Likelihood: | -68.305 |
| No. Observations: | 15 | AIC: | 142.6 |
| Df Residuals: | 12 | BIC: | 144.7 |
| Df Model: | 2 | | |
| coef | std err | t | P>|t| | [95.0% Conf. Int.] |
| Intercept | -634.8301 | 320.352 | -1.982 | 0.071 | -1332.818 63.158 |
| C(dose)[T.1] | 13.6264 | 20.974 | 0.650 | 0.528 | -32.071 59.324 |
| expression | 66.3036 | 30.232 | 2.193 | 0.049 | 0.434 132.174 |
| Omnibus: | 1.798 | Durbin-Watson: | 1.174 |
| Prob(Omnibus): | 0.407 | Jarque-Bera (JB): | 1.386 |
| Skew: | -0.595 | Prob(JB): | 0.500 |
| Kurtosis: | 2.105 | Cond. No. | 531. |
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: | 01:05:07 | 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: | 0.593 |
| Model: | OLS | Adj. R-squared: | 0.561 |
| Method: | Least Squares | F-statistic: | 18.91 |
| Date: | Wed, 29 Jan 2025 | Prob (F-statistic): | 0.000788 |
| Time: | 01:05:07 | Log-Likelihood: | -68.564 |
| No. Observations: | 15 | AIC: | 141.1 |
| Df Residuals: | 13 | BIC: | 142.5 |
| Df Model: | 1 | | |
| coef | std err | t | P>|t| | [95.0% Conf. Int.] |
| Intercept | -792.7780 | 203.928 | -3.888 | 0.002 | -1233.338 -352.217 |
| expression | 81.4921 | 18.738 | 4.349 | 0.001 | 41.011 121.973 |
| Omnibus: | 1.075 | Durbin-Watson: | 1.427 |
| Prob(Omnibus): | 0.584 | Jarque-Bera (JB): | 0.857 |
| Skew: | -0.324 | Prob(JB): | 0.651 |
| Kurtosis: | 2.024 | Cond. No. | 345. |