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 |
| 0.761 | 0.393 | 1.0 |
Model:
AIM ~ expression + C(dose) + expression:C(dose)
OLS Regression Results
| Dep. Variable: | AIM | R-squared: | 0.664 |
| Model: | OLS | Adj. R-squared: | 0.611 |
| Method: | Least Squares | F-statistic: | 12.54 |
| Date: | Thu, 21 Nov 2024 | Prob (F-statistic): | 9.42e-05 |
| Time: | 04:17:25 | Log-Likelihood: | -100.55 |
| No. Observations: | 23 | AIC: | 209.1 |
| Df Residuals: | 19 | BIC: | 213.6 |
| Df Model: | 3 | | |
| coef | std err | t | P>|t| | [95.0% Conf. Int.] |
| Intercept | -94.4372 | 166.426 | -0.567 | 0.577 | -442.770 253.895 |
| C(dose)[T.1] | 147.9023 | 260.839 | 0.567 | 0.577 | -398.040 693.844 |
| expression | 18.8316 | 21.070 | 0.894 | 0.383 | -25.269 62.932 |
| expression:C(dose)[T.1] | -12.2303 | 32.317 | -0.378 | 0.709 | -79.871 55.411 |
| Omnibus: | 0.802 | Durbin-Watson: | 2.026 |
| Prob(Omnibus): | 0.670 | Jarque-Bera (JB): | 0.718 |
| Skew: | -0.091 | Prob(JB): | 0.698 |
| Kurtosis: | 2.154 | Cond. No. | 608. |
Model:
AIM ~ expression + C(dose)
OLS Regression Results
| Dep. Variable: | AIM | R-squared: | 0.662 |
| Model: | OLS | Adj. R-squared: | 0.628 |
| Method: | Least Squares | F-statistic: | 19.58 |
| Date: | Thu, 21 Nov 2024 | Prob (F-statistic): | 1.95e-05 |
| Time: | 04:17:25 | Log-Likelihood: | -100.63 |
| No. Observations: | 23 | AIC: | 207.3 |
| Df Residuals: | 20 | BIC: | 210.7 |
| Df Model: | 2 | | |
| coef | std err | t | P>|t| | [95.0% Conf. Int.] |
| Intercept | -53.4016 | 123.519 | -0.432 | 0.670 | -311.058 204.255 |
| C(dose)[T.1] | 49.2622 | 9.794 | 5.030 | 0.000 | 28.833 69.692 |
| expression | 13.6329 | 15.630 | 0.872 | 0.393 | -18.971 46.237 |
| Omnibus: | 0.367 | Durbin-Watson: | 2.018 |
| Prob(Omnibus): | 0.833 | Jarque-Bera (JB): | 0.511 |
| Skew: | -0.068 | Prob(JB): | 0.774 |
| Kurtosis: | 2.282 | Cond. No. | 235. |
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: | 04:17:26 | 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: | 0.234 |
| Model: | OLS | Adj. R-squared: | 0.198 |
| Method: | Least Squares | F-statistic: | 6.424 |
| Date: | Thu, 21 Nov 2024 | Prob (F-statistic): | 0.0193 |
| Time: | 04:17:26 | Log-Likelihood: | -110.04 |
| No. Observations: | 23 | AIC: | 224.1 |
| Df Residuals: | 21 | BIC: | 226.3 |
| Df Model: | 1 | | |
| coef | std err | t | P>|t| | [95.0% Conf. Int.] |
| Intercept | -331.2313 | 162.266 | -2.041 | 0.054 | -668.682 6.220 |
| expression | 51.1363 | 20.176 | 2.534 | 0.019 | 9.177 93.095 |
| Omnibus: | 0.475 | Durbin-Watson: | 2.571 |
| Prob(Omnibus): | 0.789 | Jarque-Bera (JB): | 0.558 |
| Skew: | 0.282 | Prob(JB): | 0.756 |
| Kurtosis: | 2.487 | Cond. No. | 210. |
CP101
Model Comparison: AIM ~ expression + C(dose) vs AIM ~ C(dose)
| F-statistic | p-value | df difference |
| 0.013 | 0.911 | 1.0 |
Model:
AIM ~ expression + C(dose) + expression:C(dose)
OLS Regression Results
| Dep. Variable: | AIM | R-squared: | 0.545 |
| Model: | OLS | Adj. R-squared: | 0.421 |
| Method: | Least Squares | F-statistic: | 4.395 |
| Date: | Thu, 21 Nov 2024 | Prob (F-statistic): | 0.0290 |
| Time: | 04:17:26 | Log-Likelihood: | -69.391 |
| No. Observations: | 15 | AIC: | 146.8 |
| Df Residuals: | 11 | BIC: | 149.6 |
| Df Model: | 3 | | |
| coef | std err | t | P>|t| | [95.0% Conf. Int.] |
| Intercept | -30.7201 | 131.287 | -0.234 | 0.819 | -319.680 258.240 |
| C(dose)[T.1] | 402.9769 | 232.962 | 1.730 | 0.112 | -109.769 915.722 |
| expression | 12.5907 | 16.784 | 0.750 | 0.469 | -24.350 49.531 |
| expression:C(dose)[T.1] | -45.7588 | 30.057 | -1.522 | 0.156 | -111.914 20.396 |
| Omnibus: | 1.095 | Durbin-Watson: | 1.069 |
| Prob(Omnibus): | 0.578 | Jarque-Bera (JB): | 0.718 |
| Skew: | -0.507 | Prob(JB): | 0.699 |
| Kurtosis: | 2.655 | Cond. No. | 303. |
Model:
AIM ~ expression + C(dose)
OLS Regression Results
| Dep. Variable: | AIM | R-squared: | 0.449 |
| Model: | OLS | Adj. R-squared: | 0.358 |
| Method: | Least Squares | F-statistic: | 4.897 |
| Date: | Thu, 21 Nov 2024 | Prob (F-statistic): | 0.0279 |
| Time: | 04:17:26 | Log-Likelihood: | -70.825 |
| No. Observations: | 15 | AIC: | 147.6 |
| Df Residuals: | 12 | BIC: | 149.8 |
| Df Model: | 2 | | |
| coef | std err | t | P>|t| | [95.0% Conf. Int.] |
| Intercept | 80.5013 | 114.916 | 0.701 | 0.497 | -169.879 330.881 |
| C(dose)[T.1] | 49.0486 | 15.784 | 3.107 | 0.009 | 14.658 83.439 |
| expression | -1.6770 | 14.668 | -0.114 | 0.911 | -33.635 30.281 |
| Omnibus: | 2.607 | Durbin-Watson: | 0.782 |
| Prob(Omnibus): | 0.272 | Jarque-Bera (JB): | 1.796 |
| Skew: | -0.825 | Prob(JB): | 0.407 |
| Kurtosis: | 2.614 | Cond. No. | 116. |
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: | 04:17:26 | 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: | 0.006 |
| Model: | OLS | Adj. R-squared: | -0.070 |
| Method: | Least Squares | F-statistic: | 0.08223 |
| Date: | Thu, 21 Nov 2024 | Prob (F-statistic): | 0.779 |
| Time: | 04:17:26 | Log-Likelihood: | -75.253 |
| No. Observations: | 15 | AIC: | 154.5 |
| Df Residuals: | 13 | BIC: | 155.9 |
| Df Model: | 1 | | |
| coef | std err | t | P>|t| | [95.0% Conf. Int.] |
| Intercept | 135.5888 | 146.545 | 0.925 | 0.372 | -181.002 452.180 |
| expression | -5.4105 | 18.868 | -0.287 | 0.779 | -46.172 35.351 |
| Omnibus: | 0.368 | Durbin-Watson: | 1.548 |
| Prob(Omnibus): | 0.832 | Jarque-Bera (JB): | 0.484 |
| Skew: | -0.022 | Prob(JB): | 0.785 |
| Kurtosis: | 2.121 | Cond. No. | 114. |