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 |
| 1.199 | 0.287 | 1.0 |
Model:
AIM ~ expression + C(dose) + expression:C(dose)
OLS Regression Results
| Dep. Variable: | AIM | R-squared: | 0.670 |
| Model: | OLS | Adj. R-squared: | 0.618 |
| Method: | Least Squares | F-statistic: | 12.87 |
| Date: | Thu, 21 Nov 2024 | Prob (F-statistic): | 8.02e-05 |
| Time: | 04:33:01 | Log-Likelihood: | -100.35 |
| No. Observations: | 23 | AIC: | 208.7 |
| Df Residuals: | 19 | BIC: | 213.2 |
| Df Model: | 3 | | |
| coef | std err | t | P>|t| | [95.0% Conf. Int.] |
| Intercept | -30.5262 | 140.059 | -0.218 | 0.830 | -323.674 262.621 |
| C(dose)[T.1] | 4.9887 | 201.182 | 0.025 | 0.980 | -416.090 426.067 |
| expression | 9.0258 | 14.905 | 0.606 | 0.552 | -22.171 40.222 |
| expression:C(dose)[T.1] | 6.0201 | 22.096 | 0.272 | 0.788 | -40.228 52.268 |
| Omnibus: | 1.442 | Durbin-Watson: | 2.055 |
| Prob(Omnibus): | 0.486 | Jarque-Bera (JB): | 0.965 |
| Skew: | 0.150 | Prob(JB): | 0.617 |
| Kurtosis: | 2.042 | Cond. No. | 543. |
Model:
AIM ~ expression + C(dose)
OLS Regression Results
| Dep. Variable: | AIM | R-squared: | 0.669 |
| Model: | OLS | Adj. R-squared: | 0.636 |
| Method: | Least Squares | F-statistic: | 20.20 |
| Date: | Thu, 21 Nov 2024 | Prob (F-statistic): | 1.58e-05 |
| Time: | 04:33:01 | Log-Likelihood: | -100.39 |
| No. Observations: | 23 | AIC: | 206.8 |
| Df Residuals: | 20 | BIC: | 210.2 |
| Df Model: | 2 | | |
| coef | std err | t | P>|t| | [95.0% Conf. Int.] |
| Intercept | -56.2423 | 101.053 | -0.557 | 0.584 | -267.035 154.551 |
| C(dose)[T.1] | 59.7248 | 10.325 | 5.785 | 0.000 | 38.188 81.262 |
| expression | 11.7650 | 10.746 | 1.095 | 0.287 | -10.650 34.180 |
| Omnibus: | 1.770 | Durbin-Watson: | 2.025 |
| Prob(Omnibus): | 0.413 | Jarque-Bera (JB): | 1.045 |
| Skew: | 0.129 | Prob(JB): | 0.593 |
| Kurtosis: | 1.988 | Cond. No. | 220. |
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: | 04:33:01 | 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: | 0.115 |
| Model: | OLS | Adj. R-squared: | 0.073 |
| Method: | Least Squares | F-statistic: | 2.727 |
| Date: | Thu, 21 Nov 2024 | Prob (F-statistic): | 0.114 |
| Time: | 04:33:01 | Log-Likelihood: | -111.70 |
| No. Observations: | 23 | AIC: | 227.4 |
| Df Residuals: | 21 | BIC: | 229.7 |
| Df Model: | 1 | | |
| coef | std err | t | P>|t| | [95.0% Conf. Int.] |
| Intercept | 292.9569 | 129.306 | 2.266 | 0.034 | 24.051 561.862 |
| expression | -23.3600 | 14.146 | -1.651 | 0.114 | -52.777 6.057 |
| Omnibus: | 2.572 | Durbin-Watson: | 2.023 |
| Prob(Omnibus): | 0.276 | Jarque-Bera (JB): | 1.338 |
| Skew: | 0.235 | Prob(JB): | 0.512 |
| Kurtosis: | 1.916 | Cond. No. | 176. |
CP101
Model Comparison: AIM ~ expression + C(dose) vs AIM ~ C(dose)
| F-statistic | p-value | df difference |
| 0.051 | 0.824 | 1.0 |
Model:
AIM ~ expression + C(dose) + expression:C(dose)
OLS Regression Results
| Dep. Variable: | AIM | R-squared: | 0.460 |
| Model: | OLS | Adj. R-squared: | 0.313 |
| Method: | Least Squares | F-statistic: | 3.123 |
| Date: | Thu, 21 Nov 2024 | Prob (F-statistic): | 0.0700 |
| Time: | 04:33:01 | Log-Likelihood: | -70.679 |
| No. Observations: | 15 | AIC: | 149.4 |
| Df Residuals: | 11 | BIC: | 152.2 |
| Df Model: | 3 | | |
| coef | std err | t | P>|t| | [95.0% Conf. Int.] |
| Intercept | 134.5461 | 176.244 | 0.763 | 0.461 | -253.364 522.456 |
| C(dose)[T.1] | -123.9458 | 408.191 | -0.304 | 0.767 | -1022.368 774.476 |
| expression | -6.9581 | 18.230 | -0.382 | 0.710 | -47.082 33.165 |
| expression:C(dose)[T.1] | 17.8625 | 42.011 | 0.425 | 0.679 | -74.602 110.327 |
| Omnibus: | 3.845 | Durbin-Watson: | 0.859 |
| Prob(Omnibus): | 0.146 | Jarque-Bera (JB): | 2.229 |
| Skew: | -0.944 | Prob(JB): | 0.328 |
| Kurtosis: | 3.061 | Cond. No. | 585. |
Model:
AIM ~ expression + C(dose)
OLS Regression Results
| Dep. Variable: | AIM | R-squared: | 0.451 |
| Model: | OLS | Adj. R-squared: | 0.360 |
| Method: | Least Squares | F-statistic: | 4.931 |
| Date: | Thu, 21 Nov 2024 | Prob (F-statistic): | 0.0273 |
| Time: | 04:33:01 | Log-Likelihood: | -70.801 |
| No. Observations: | 15 | AIC: | 147.6 |
| Df Residuals: | 12 | BIC: | 149.7 |
| Df Model: | 2 | | |
| coef | std err | t | P>|t| | [95.0% Conf. Int.] |
| Intercept | 102.1025 | 153.351 | 0.666 | 0.518 | -232.021 436.226 |
| C(dose)[T.1] | 49.4741 | 15.754 | 3.140 | 0.009 | 15.150 83.798 |
| expression | -3.5947 | 15.854 | -0.227 | 0.824 | -38.137 30.947 |
| Omnibus: | 2.256 | Durbin-Watson: | 0.816 |
| Prob(Omnibus): | 0.324 | Jarque-Bera (JB): | 1.662 |
| Skew: | -0.770 | Prob(JB): | 0.436 |
| Kurtosis: | 2.464 | Cond. No. | 192. |
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: | 04:33:01 | 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: | 0.000 |
| Model: | OLS | Adj. R-squared: | -0.077 |
| Method: | Least Squares | F-statistic: | 0.0001806 |
| Date: | Thu, 21 Nov 2024 | Prob (F-statistic): | 0.989 |
| Time: | 04:33:01 | Log-Likelihood: | -75.300 |
| No. Observations: | 15 | AIC: | 154.6 |
| Df Residuals: | 13 | BIC: | 156.0 |
| Df Model: | 1 | | |
| coef | std err | t | P>|t| | [95.0% Conf. Int.] |
| Intercept | 90.9985 | 198.816 | 0.458 | 0.655 | -338.516 520.513 |
| expression | 0.2754 | 20.497 | 0.013 | 0.989 | -44.005 44.556 |
| Omnibus: | 0.568 | Durbin-Watson: | 1.620 |
| Prob(Omnibus): | 0.753 | Jarque-Bera (JB): | 0.567 |
| Skew: | 0.041 | Prob(JB): | 0.753 |
| Kurtosis: | 2.051 | Cond. No. | 192. |