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 |
| 5.345 | 0.032 | 1.0 |
Model:
AIM ~ expression + C(dose) + expression:C(dose)
OLS Regression Results
| Dep. Variable: | AIM | R-squared: | 0.729 |
| Model: | OLS | Adj. R-squared: | 0.686 |
| Method: | Least Squares | F-statistic: | 17.03 |
| Date: | Thu, 21 Nov 2024 | Prob (F-statistic): | 1.29e-05 |
| Time: | 04:26:02 | Log-Likelihood: | -98.096 |
| No. Observations: | 23 | AIC: | 204.2 |
| Df Residuals: | 19 | BIC: | 208.7 |
| Df Model: | 3 | | |
| coef | std err | t | P>|t| | [95.0% Conf. Int.] |
| Intercept | -16.6208 | 44.138 | -0.377 | 0.711 | -109.002 75.760 |
| C(dose)[T.1] | 86.2606 | 49.632 | 1.738 | 0.098 | -17.621 190.142 |
| expression | 17.7230 | 10.959 | 1.617 | 0.122 | -5.215 40.661 |
| expression:C(dose)[T.1] | -7.8763 | 12.356 | -0.637 | 0.531 | -33.737 17.985 |
| Omnibus: | 3.204 | Durbin-Watson: | 2.156 |
| Prob(Omnibus): | 0.202 | Jarque-Bera (JB): | 1.994 |
| Skew: | 0.716 | Prob(JB): | 0.369 |
| Kurtosis: | 3.179 | Cond. No. | 78.4 |
Model:
AIM ~ expression + C(dose)
OLS Regression Results
| Dep. Variable: | AIM | R-squared: | 0.723 |
| Model: | OLS | Adj. R-squared: | 0.695 |
| Method: | Least Squares | F-statistic: | 26.11 |
| Date: | Thu, 21 Nov 2024 | Prob (F-statistic): | 2.65e-06 |
| Time: | 04:26:02 | Log-Likelihood: | -98.339 |
| No. Observations: | 23 | AIC: | 202.7 |
| Df Residuals: | 20 | BIC: | 206.1 |
| Df Model: | 2 | | |
| coef | std err | t | P>|t| | [95.0% Conf. Int.] |
| Intercept | 8.1420 | 20.641 | 0.394 | 0.697 | -34.915 51.199 |
| C(dose)[T.1] | 55.0302 | 7.825 | 7.033 | 0.000 | 38.708 71.352 |
| expression | 11.5268 | 4.986 | 2.312 | 0.032 | 1.127 21.927 |
| Omnibus: | 2.353 | Durbin-Watson: | 2.251 |
| Prob(Omnibus): | 0.308 | Jarque-Bera (JB): | 1.690 |
| Skew: | 0.659 | Prob(JB): | 0.430 |
| Kurtosis: | 2.837 | Cond. No. | 22.7 |
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: | 04:26:02 | 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: | 0.038 |
| Model: | OLS | Adj. R-squared: | -0.008 |
| Method: | Least Squares | F-statistic: | 0.8341 |
| Date: | Thu, 21 Nov 2024 | Prob (F-statistic): | 0.371 |
| Time: | 04:26:02 | Log-Likelihood: | -112.66 |
| No. Observations: | 23 | AIC: | 229.3 |
| Df Residuals: | 21 | BIC: | 231.6 |
| Df Model: | 1 | | |
| coef | std err | t | P>|t| | [95.0% Conf. Int.] |
| Intercept | 47.3451 | 36.145 | 1.310 | 0.204 | -27.823 122.513 |
| expression | 8.2452 | 9.028 | 0.913 | 0.371 | -10.529 27.020 |
| Omnibus: | 3.482 | Durbin-Watson: | 2.685 |
| Prob(Omnibus): | 0.175 | Jarque-Bera (JB): | 1.685 |
| Skew: | 0.335 | Prob(JB): | 0.431 |
| Kurtosis: | 1.856 | Cond. No. | 21.7 |
CP101
Model Comparison: AIM ~ expression + C(dose) vs AIM ~ C(dose)
| F-statistic | p-value | df difference |
| 0.008 | 0.930 | 1.0 |
Model:
AIM ~ expression + C(dose) + expression:C(dose)
OLS Regression Results
| Dep. Variable: | AIM | R-squared: | 0.493 |
| Model: | OLS | Adj. R-squared: | 0.355 |
| Method: | Least Squares | F-statistic: | 3.564 |
| Date: | Thu, 21 Nov 2024 | Prob (F-statistic): | 0.0508 |
| Time: | 04:26:02 | Log-Likelihood: | -70.207 |
| No. Observations: | 15 | AIC: | 148.4 |
| Df Residuals: | 11 | BIC: | 151.2 |
| Df Model: | 3 | | |
| coef | std err | t | P>|t| | [95.0% Conf. Int.] |
| Intercept | 108.1132 | 69.444 | 1.557 | 0.148 | -44.731 260.958 |
| C(dose)[T.1] | -67.8432 | 120.773 | -0.562 | 0.586 | -333.663 197.977 |
| expression | -8.6934 | 14.633 | -0.594 | 0.564 | -40.901 23.514 |
| expression:C(dose)[T.1] | 26.7746 | 27.480 | 0.974 | 0.351 | -33.708 87.257 |
| Omnibus: | 5.929 | Durbin-Watson: | 0.833 |
| Prob(Omnibus): | 0.052 | Jarque-Bera (JB): | 3.296 |
| Skew: | -1.112 | Prob(JB): | 0.192 |
| Kurtosis: | 3.571 | Cond. No. | 87.3 |
Model:
AIM ~ expression + C(dose)
OLS Regression Results
| Dep. Variable: | AIM | R-squared: | 0.449 |
| Model: | OLS | Adj. R-squared: | 0.357 |
| Method: | Least Squares | F-statistic: | 4.892 |
| Date: | Thu, 21 Nov 2024 | Prob (F-statistic): | 0.0279 |
| Time: | 04:26:02 | Log-Likelihood: | -70.828 |
| No. Observations: | 15 | AIC: | 147.7 |
| Df Residuals: | 12 | BIC: | 149.8 |
| Df Model: | 2 | | |
| coef | std err | t | P>|t| | [95.0% Conf. Int.] |
| Intercept | 72.5818 | 58.973 | 1.231 | 0.242 | -55.910 201.073 |
| C(dose)[T.1] | 48.6931 | 16.718 | 2.913 | 0.013 | 12.268 85.118 |
| expression | -1.1011 | 12.360 | -0.089 | 0.930 | -28.031 25.828 |
| Omnibus: | 2.551 | Durbin-Watson: | 0.826 |
| Prob(Omnibus): | 0.279 | Jarque-Bera (JB): | 1.784 |
| Skew: | -0.818 | Prob(JB): | 0.410 |
| Kurtosis: | 2.581 | Cond. No. | 35.8 |
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: | 04:26:02 | 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: | 0.060 |
| Model: | OLS | Adj. R-squared: | -0.013 |
| Method: | Least Squares | F-statistic: | 0.8254 |
| Date: | Thu, 21 Nov 2024 | Prob (F-statistic): | 0.380 |
| Time: | 04:26:02 | Log-Likelihood: | -74.838 |
| No. Observations: | 15 | AIC: | 153.7 |
| Df Residuals: | 13 | BIC: | 155.1 |
| Df Model: | 1 | | |
| coef | std err | t | P>|t| | [95.0% Conf. Int.] |
| Intercept | 152.5173 | 65.522 | 2.328 | 0.037 | 10.967 294.068 |
| expression | -13.2660 | 14.602 | -0.909 | 0.380 | -44.811 18.279 |
| Omnibus: | 1.196 | Durbin-Watson: | 1.647 |
| Prob(Omnibus): | 0.550 | Jarque-Bera (JB): | 0.873 |
| Skew: | 0.289 | Prob(JB): | 0.646 |
| Kurtosis: | 1.969 | Cond. No. | 31.3 |