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 |
| 0.110 | 0.744 | 1.0 |
Model:
AIM ~ expression + C(dose) + expression:C(dose)
OLS Regression Results
| Dep. Variable: | AIM | R-squared: | 0.656 |
| Model: | OLS | Adj. R-squared: | 0.602 |
| Method: | Least Squares | F-statistic: | 12.08 |
| Date: | Thu, 21 Nov 2024 | Prob (F-statistic): | 0.000118 |
| Time: | 04:49:12 | Log-Likelihood: | -100.83 |
| No. Observations: | 23 | AIC: | 209.7 |
| Df Residuals: | 19 | BIC: | 214.2 |
| Df Model: | 3 | | |
| coef | std err | t | P>|t| | [95.0% Conf. Int.] |
| Intercept | -59.5589 | 187.871 | -0.317 | 0.755 | -452.777 333.659 |
| C(dose)[T.1] | 195.4039 | 271.180 | 0.721 | 0.480 | -372.181 762.989 |
| expression | 14.3829 | 23.739 | 0.606 | 0.552 | -35.302 64.068 |
| expression:C(dose)[T.1] | -17.8145 | 33.545 | -0.531 | 0.602 | -88.024 52.395 |
| Omnibus: | 0.311 | Durbin-Watson: | 1.856 |
| Prob(Omnibus): | 0.856 | Jarque-Bera (JB): | 0.482 |
| Skew: | 0.109 | Prob(JB): | 0.786 |
| Kurtosis: | 2.325 | Cond. No. | 648. |
Model:
AIM ~ expression + C(dose)
OLS Regression Results
| Dep. Variable: | AIM | R-squared: | 0.651 |
| Model: | OLS | Adj. R-squared: | 0.616 |
| Method: | Least Squares | F-statistic: | 18.65 |
| Date: | Thu, 21 Nov 2024 | Prob (F-statistic): | 2.68e-05 |
| Time: | 04:49:12 | Log-Likelihood: | -101.00 |
| No. Observations: | 23 | AIC: | 208.0 |
| Df Residuals: | 20 | BIC: | 211.4 |
| Df Model: | 2 | | |
| coef | std err | t | P>|t| | [95.0% Conf. Int.] |
| Intercept | 11.0093 | 130.404 | 0.084 | 0.934 | -261.009 283.028 |
| C(dose)[T.1] | 51.4977 | 10.356 | 4.973 | 0.000 | 29.894 73.101 |
| expression | 5.4614 | 16.468 | 0.332 | 0.744 | -28.891 39.814 |
| Omnibus: | 0.117 | Durbin-Watson: | 1.913 |
| Prob(Omnibus): | 0.943 | Jarque-Bera (JB): | 0.337 |
| Skew: | 0.054 | Prob(JB): | 0.845 |
| Kurtosis: | 2.417 | Cond. No. | 245. |
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: | 04:49:12 | 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: | 0.219 |
| Model: | OLS | Adj. R-squared: | 0.182 |
| Method: | Least Squares | F-statistic: | 5.905 |
| Date: | Thu, 21 Nov 2024 | Prob (F-statistic): | 0.0241 |
| Time: | 04:49:12 | Log-Likelihood: | -110.26 |
| No. Observations: | 23 | AIC: | 224.5 |
| Df Residuals: | 21 | BIC: | 226.8 |
| Df Model: | 1 | | |
| coef | std err | t | P>|t| | [95.0% Conf. Int.] |
| Intercept | -318.3466 | 163.934 | -1.942 | 0.066 | -659.265 22.572 |
| expression | 49.3204 | 20.296 | 2.430 | 0.024 | 7.112 91.528 |
| Omnibus: | 2.182 | Durbin-Watson: | 2.332 |
| Prob(Omnibus): | 0.336 | Jarque-Bera (JB): | 1.585 |
| Skew: | 0.450 | Prob(JB): | 0.453 |
| Kurtosis: | 2.081 | Cond. No. | 211. |
CP101
Model Comparison: AIM ~ expression + C(dose) vs AIM ~ C(dose)
| F-statistic | p-value | df difference |
| 4.096 | 0.066 | 1.0 |
Model:
AIM ~ expression + C(dose) + expression:C(dose)
OLS Regression Results
| Dep. Variable: | AIM | R-squared: | 0.591 |
| Model: | OLS | Adj. R-squared: | 0.479 |
| Method: | Least Squares | F-statistic: | 5.292 |
| Date: | Thu, 21 Nov 2024 | Prob (F-statistic): | 0.0168 |
| Time: | 04:49:12 | Log-Likelihood: | -68.600 |
| No. Observations: | 15 | AIC: | 145.2 |
| Df Residuals: | 11 | BIC: | 148.0 |
| Df Model: | 3 | | |
| coef | std err | t | P>|t| | [95.0% Conf. Int.] |
| Intercept | 283.9736 | 150.396 | 1.888 | 0.086 | -47.047 614.994 |
| C(dose)[T.1] | 94.2280 | 249.449 | 0.378 | 0.713 | -454.805 643.261 |
| expression | -25.3074 | 17.535 | -1.443 | 0.177 | -63.902 13.287 |
| expression:C(dose)[T.1] | -6.3100 | 29.745 | -0.212 | 0.836 | -71.778 59.158 |
| Omnibus: | 2.104 | Durbin-Watson: | 0.935 |
| Prob(Omnibus): | 0.349 | Jarque-Bera (JB): | 1.181 |
| Skew: | -0.684 | Prob(JB): | 0.554 |
| Kurtosis: | 2.869 | Cond. No. | 375. |
Model:
AIM ~ expression + C(dose)
OLS Regression Results
| Dep. Variable: | AIM | R-squared: | 0.589 |
| Model: | OLS | Adj. R-squared: | 0.521 |
| Method: | Least Squares | F-statistic: | 8.600 |
| Date: | Thu, 21 Nov 2024 | Prob (F-statistic): | 0.00482 |
| Time: | 04:49:12 | Log-Likelihood: | -68.631 |
| No. Observations: | 15 | AIC: | 143.3 |
| Df Residuals: | 12 | BIC: | 145.4 |
| Df Model: | 2 | | |
| coef | std err | t | P>|t| | [95.0% Conf. Int.] |
| Intercept | 302.7374 | 116.696 | 2.594 | 0.023 | 48.478 556.997 |
| C(dose)[T.1] | 41.4026 | 14.126 | 2.931 | 0.013 | 10.626 72.179 |
| expression | -27.5003 | 13.589 | -2.024 | 0.066 | -57.108 2.107 |
| Omnibus: | 2.230 | Durbin-Watson: | 0.940 |
| Prob(Omnibus): | 0.328 | Jarque-Bera (JB): | 1.220 |
| Skew: | -0.697 | Prob(JB): | 0.543 |
| Kurtosis: | 2.915 | Cond. No. | 147. |
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: | 04:49:12 | 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: | 0.295 |
| Model: | OLS | Adj. R-squared: | 0.241 |
| Method: | Least Squares | F-statistic: | 5.435 |
| Date: | Thu, 21 Nov 2024 | Prob (F-statistic): | 0.0365 |
| Time: | 04:49:12 | Log-Likelihood: | -72.680 |
| No. Observations: | 15 | AIC: | 149.4 |
| Df Residuals: | 13 | BIC: | 150.8 |
| Df Model: | 1 | | |
| coef | std err | t | P>|t| | [95.0% Conf. Int.] |
| Intercept | 416.0939 | 138.567 | 3.003 | 0.010 | 116.738 715.450 |
| expression | -38.3594 | 16.454 | -2.331 | 0.036 | -73.906 -2.812 |
| Omnibus: | 1.935 | Durbin-Watson: | 1.822 |
| Prob(Omnibus): | 0.380 | Jarque-Bera (JB): | 1.060 |
| Skew: | 0.282 | Prob(JB): | 0.589 |
| Kurtosis: | 1.826 | Cond. No. | 139. |