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 |
| 0.195 | 0.663 | 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: | 0.599 |
| Method: | Least Squares | F-statistic: | 11.96 |
| Date: | Thu, 21 Nov 2024 | Prob (F-statistic): | 0.000126 |
| Time: | 05:17:12 | Log-Likelihood: | -100.91 |
| No. Observations: | 23 | AIC: | 209.8 |
| Df Residuals: | 19 | BIC: | 214.4 |
| Df Model: | 3 | | |
| coef | std err | t | P>|t| | [95.0% Conf. Int.] |
| Intercept | 61.6667 | 107.212 | 0.575 | 0.572 | -162.730 286.064 |
| C(dose)[T.1] | 85.8841 | 133.834 | 0.642 | 0.529 | -194.233 366.001 |
| expression | -1.1738 | 16.845 | -0.070 | 0.945 | -36.430 34.083 |
| expression:C(dose)[T.1] | -5.7470 | 21.784 | -0.264 | 0.795 | -51.341 39.848 |
| Omnibus: | 0.114 | Durbin-Watson: | 1.910 |
| Prob(Omnibus): | 0.945 | Jarque-Bera (JB): | 0.338 |
| Skew: | 0.003 | Prob(JB): | 0.844 |
| Kurtosis: | 2.406 | Cond. No. | 254. |
Model:
AIM ~ expression + C(dose)
OLS Regression Results
| Dep. Variable: | AIM | R-squared: | 0.652 |
| Model: | OLS | Adj. R-squared: | 0.618 |
| Method: | Least Squares | F-statistic: | 18.77 |
| Date: | Thu, 21 Nov 2024 | Prob (F-statistic): | 2.57e-05 |
| Time: | 05:17:12 | Log-Likelihood: | -100.95 |
| 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 | 83.5015 | 66.546 | 1.255 | 0.224 | -55.310 222.313 |
| C(dose)[T.1] | 50.6925 | 10.581 | 4.791 | 0.000 | 28.620 72.765 |
| expression | -4.6101 | 10.430 | -0.442 | 0.663 | -26.366 17.146 |
| Omnibus: | 0.254 | Durbin-Watson: | 1.880 |
| Prob(Omnibus): | 0.881 | Jarque-Bera (JB): | 0.442 |
| Skew: | 0.017 | Prob(JB): | 0.802 |
| Kurtosis: | 2.322 | Cond. No. | 96.2 |
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: | 05:17:12 | 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: | 0.254 |
| Model: | OLS | Adj. R-squared: | 0.218 |
| Method: | Least Squares | F-statistic: | 7.136 |
| Date: | Thu, 21 Nov 2024 | Prob (F-statistic): | 0.0143 |
| Time: | 05:17:12 | Log-Likelihood: | -109.74 |
| No. Observations: | 23 | AIC: | 223.5 |
| Df Residuals: | 21 | BIC: | 225.8 |
| Df Model: | 1 | | |
| coef | std err | t | P>|t| | [95.0% Conf. Int.] |
| Intercept | 279.5164 | 75.056 | 3.724 | 0.001 | 123.429 435.603 |
| expression | -32.8629 | 12.302 | -2.671 | 0.014 | -58.447 -7.278 |
| Omnibus: | 2.373 | Durbin-Watson: | 2.303 |
| Prob(Omnibus): | 0.305 | Jarque-Bera (JB): | 1.253 |
| Skew: | 0.200 | Prob(JB): | 0.534 |
| Kurtosis: | 1.929 | Cond. No. | 75.4 |
CP101
Model Comparison: AIM ~ expression + C(dose) vs AIM ~ C(dose)
| F-statistic | p-value | df difference |
| 0.568 | 0.465 | 1.0 |
Model:
AIM ~ expression + C(dose) + expression:C(dose)
OLS Regression Results
| Dep. Variable: | AIM | R-squared: | 0.502 |
| Model: | OLS | Adj. R-squared: | 0.366 |
| Method: | Least Squares | F-statistic: | 3.699 |
| Date: | Thu, 21 Nov 2024 | Prob (F-statistic): | 0.0462 |
| Time: | 05:17:12 | Log-Likelihood: | -70.068 |
| No. Observations: | 15 | AIC: | 148.1 |
| Df Residuals: | 11 | BIC: | 151.0 |
| Df Model: | 3 | | |
| coef | std err | t | P>|t| | [95.0% Conf. Int.] |
| Intercept | 92.4576 | 144.906 | 0.638 | 0.536 | -226.478 411.393 |
| C(dose)[T.1] | 238.3761 | 246.931 | 0.965 | 0.355 | -305.115 781.868 |
| expression | -3.9634 | 22.875 | -0.173 | 0.866 | -54.311 46.384 |
| expression:C(dose)[T.1] | -32.5555 | 41.010 | -0.794 | 0.444 | -122.819 57.708 |
| Omnibus: | 7.316 | Durbin-Watson: | 0.745 |
| Prob(Omnibus): | 0.026 | Jarque-Bera (JB): | 4.237 |
| Skew: | -1.238 | Prob(JB): | 0.120 |
| Kurtosis: | 3.802 | Cond. No. | 243. |
Model:
AIM ~ expression + C(dose)
OLS Regression Results
| Dep. Variable: | AIM | R-squared: | 0.474 |
| Model: | OLS | Adj. R-squared: | 0.386 |
| Method: | Least Squares | F-statistic: | 5.400 |
| Date: | Thu, 21 Nov 2024 | Prob (F-statistic): | 0.0213 |
| Time: | 05:17:12 | Log-Likelihood: | -70.486 |
| No. Observations: | 15 | AIC: | 147.0 |
| Df Residuals: | 12 | BIC: | 149.1 |
| Df Model: | 2 | | |
| coef | std err | t | P>|t| | [95.0% Conf. Int.] |
| Intercept | 156.4204 | 118.568 | 1.319 | 0.212 | -101.917 414.758 |
| C(dose)[T.1] | 42.8639 | 17.524 | 2.446 | 0.031 | 4.683 81.045 |
| expression | -14.0920 | 18.691 | -0.754 | 0.465 | -54.816 26.632 |
| Omnibus: | 2.663 | Durbin-Watson: | 0.578 |
| Prob(Omnibus): | 0.264 | Jarque-Bera (JB): | 1.615 |
| Skew: | -0.799 | Prob(JB): | 0.446 |
| Kurtosis: | 2.831 | Cond. No. | 97.2 |
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: | 05:17:12 | 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: | 0.211 |
| Model: | OLS | Adj. R-squared: | 0.151 |
| Method: | Least Squares | F-statistic: | 3.483 |
| Date: | Thu, 21 Nov 2024 | Prob (F-statistic): | 0.0847 |
| Time: | 05:17:12 | Log-Likelihood: | -73.520 |
| No. Observations: | 15 | AIC: | 151.0 |
| Df Residuals: | 13 | BIC: | 152.5 |
| Df Model: | 1 | | |
| coef | std err | t | P>|t| | [95.0% Conf. Int.] |
| Intercept | 312.4144 | 117.564 | 2.657 | 0.020 | 58.433 566.396 |
| expression | -36.0055 | 19.294 | -1.866 | 0.085 | -77.687 5.676 |
| Omnibus: | 2.786 | Durbin-Watson: | 0.831 |
| Prob(Omnibus): | 0.248 | Jarque-Bera (JB): | 1.323 |
| Skew: | -0.363 | Prob(JB): | 0.516 |
| Kurtosis: | 1.740 | Cond. No. | 81.5 |