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 |
| 0.170 | 0.684 | 1.0 |
Model:
AIM ~ expression + C(dose) + expression:C(dose)
OLS Regression Results
| Dep. Variable: | AIM | R-squared: | 0.654 |
| Model: | OLS | Adj. R-squared: | 0.600 |
| Method: | Least Squares | F-statistic: | 11.99 |
| Date: | Thu, 21 Nov 2024 | Prob (F-statistic): | 0.000124 |
| Time: | 04:50:19 | Log-Likelihood: | -100.89 |
| 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 | 2.2085 | 98.059 | 0.023 | 0.982 | -203.031 207.448 |
| C(dose)[T.1] | 99.0931 | 124.275 | 0.797 | 0.435 | -161.016 359.203 |
| expression | 9.0382 | 17.010 | 0.531 | 0.601 | -26.564 44.640 |
| expression:C(dose)[T.1] | -7.8715 | 22.168 | -0.355 | 0.726 | -54.269 38.526 |
| Omnibus: | 0.700 | Durbin-Watson: | 1.963 |
| Prob(Omnibus): | 0.705 | Jarque-Bera (JB): | 0.670 |
| Skew: | -0.065 | Prob(JB): | 0.715 |
| Kurtosis: | 2.174 | Cond. No. | 216. |
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: | 18.74 |
| Date: | Thu, 21 Nov 2024 | Prob (F-statistic): | 2.60e-05 |
| Time: | 04:50:19 | 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 | 28.8731 | 61.666 | 0.468 | 0.645 | -99.760 157.506 |
| C(dose)[T.1] | 55.1068 | 9.728 | 5.665 | 0.000 | 34.814 75.399 |
| expression | 4.4036 | 10.667 | 0.413 | 0.684 | -17.847 26.654 |
| Omnibus: | 0.237 | Durbin-Watson: | 1.922 |
| Prob(Omnibus): | 0.888 | Jarque-Bera (JB): | 0.431 |
| Skew: | -0.002 | Prob(JB): | 0.806 |
| Kurtosis: | 2.329 | Cond. No. | 81.8 |
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: | Thu, 21 Nov 2024 | Prob (F-statistic): | 3.51e-06 |
| Time: | 04:50:19 | 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: | 0.094 |
| Model: | OLS | Adj. R-squared: | 0.051 |
| Method: | Least Squares | F-statistic: | 2.171 |
| Date: | Thu, 21 Nov 2024 | Prob (F-statistic): | 0.155 |
| Time: | 04:50:19 | Log-Likelihood: | -111.97 |
| No. Observations: | 23 | AIC: | 227.9 |
| Df Residuals: | 21 | BIC: | 230.2 |
| Df Model: | 1 | | |
| coef | std err | t | P>|t| | [95.0% Conf. Int.] |
| Intercept | 203.2976 | 84.146 | 2.416 | 0.025 | 28.306 378.289 |
| expression | -22.2221 | 15.081 | -1.474 | 0.155 | -53.584 9.140 |
| Omnibus: | 2.498 | Durbin-Watson: | 2.280 |
| Prob(Omnibus): | 0.287 | Jarque-Bera (JB): | 1.518 |
| Skew: | 0.366 | Prob(JB): | 0.468 |
| Kurtosis: | 1.975 | Cond. No. | 70.5 |
CP101
Model Comparison: AIM ~ expression + C(dose) vs AIM ~ C(dose)
| F-statistic | p-value | df difference |
| 2.279 | 0.157 | 1.0 |
Model:
AIM ~ expression + C(dose) + expression:C(dose)
OLS Regression Results
| Dep. Variable: | AIM | R-squared: | 0.539 |
| Model: | OLS | Adj. R-squared: | 0.413 |
| Method: | Least Squares | F-statistic: | 4.280 |
| Date: | Thu, 21 Nov 2024 | Prob (F-statistic): | 0.0313 |
| Time: | 04:50:19 | Log-Likelihood: | -69.499 |
| No. Observations: | 15 | AIC: | 147.0 |
| Df Residuals: | 11 | BIC: | 149.8 |
| Df Model: | 3 | | |
| coef | std err | t | P>|t| | [95.0% Conf. Int.] |
| Intercept | 233.0272 | 115.338 | 2.020 | 0.068 | -20.830 486.885 |
| C(dose)[T.1] | -32.7963 | 358.546 | -0.091 | 0.929 | -821.951 756.359 |
| expression | -27.3728 | 18.978 | -1.442 | 0.177 | -69.144 14.398 |
| expression:C(dose)[T.1] | 12.8901 | 61.769 | 0.209 | 0.839 | -123.063 148.843 |
| Omnibus: | 3.547 | Durbin-Watson: | 1.503 |
| Prob(Omnibus): | 0.170 | Jarque-Bera (JB): | 1.701 |
| Skew: | -0.807 | Prob(JB): | 0.427 |
| Kurtosis: | 3.339 | Cond. No. | 336. |
Model:
AIM ~ expression + C(dose)
OLS Regression Results
| Dep. Variable: | AIM | R-squared: | 0.537 |
| Model: | OLS | Adj. R-squared: | 0.460 |
| Method: | Least Squares | F-statistic: | 6.952 |
| Date: | Thu, 21 Nov 2024 | Prob (F-statistic): | 0.00988 |
| Time: | 04:50:19 | Log-Likelihood: | -69.529 |
| No. Observations: | 15 | AIC: | 145.1 |
| Df Residuals: | 12 | BIC: | 147.2 |
| Df Model: | 2 | | |
| coef | std err | t | P>|t| | [95.0% Conf. Int.] |
| Intercept | 225.6657 | 105.344 | 2.142 | 0.053 | -3.859 455.191 |
| C(dose)[T.1] | 41.9527 | 15.206 | 2.759 | 0.017 | 8.822 75.083 |
| expression | -26.1560 | 17.326 | -1.510 | 0.157 | -63.905 11.593 |
| Omnibus: | 4.284 | Durbin-Watson: | 1.465 |
| Prob(Omnibus): | 0.117 | Jarque-Bera (JB): | 1.954 |
| Skew: | -0.822 | Prob(JB): | 0.376 |
| Kurtosis: | 3.652 | Cond. No. | 89.5 |
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: | Thu, 21 Nov 2024 | Prob (F-statistic): | 0.00629 |
| Time: | 04:50:19 | 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: | 0.243 |
| Model: | OLS | Adj. R-squared: | 0.185 |
| Method: | Least Squares | F-statistic: | 4.171 |
| Date: | Thu, 21 Nov 2024 | Prob (F-statistic): | 0.0620 |
| Time: | 04:50:19 | Log-Likelihood: | -73.213 |
| No. Observations: | 15 | AIC: | 150.4 |
| Df Residuals: | 13 | BIC: | 151.8 |
| Df Model: | 1 | | |
| coef | std err | t | P>|t| | [95.0% Conf. Int.] |
| Intercept | 337.0651 | 119.508 | 2.820 | 0.014 | 78.884 595.246 |
| expression | -41.2397 | 20.193 | -2.042 | 0.062 | -84.864 2.385 |
| Omnibus: | 0.775 | Durbin-Watson: | 1.868 |
| Prob(Omnibus): | 0.679 | Jarque-Bera (JB): | 0.701 |
| Skew: | 0.246 | Prob(JB): | 0.704 |
| Kurtosis: | 2.061 | Cond. No. | 82.3 |