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 |
| 0.310 | 0.584 | 1.0 |
Model:
AIM ~ expression + C(dose) + expression:C(dose)
OLS Regression Results
| Dep. Variable: | AIM | R-squared: | 0.658 |
| Model: | OLS | Adj. R-squared: | 0.604 |
| Method: | Least Squares | F-statistic: | 12.17 |
| Date: | Thu, 21 Nov 2024 | Prob (F-statistic): | 0.000113 |
| Time: | 04:49:26 | Log-Likelihood: | -100.77 |
| No. Observations: | 23 | AIC: | 209.5 |
| Df Residuals: | 19 | BIC: | 214.1 |
| Df Model: | 3 | | |
| coef | std err | t | P>|t| | [95.0% Conf. Int.] |
| Intercept | 71.9358 | 166.011 | 0.433 | 0.670 | -275.530 419.401 |
| C(dose)[T.1] | -26.0399 | 188.770 | -0.138 | 0.892 | -421.140 369.061 |
| expression | -2.3186 | 21.698 | -0.107 | 0.916 | -47.734 43.096 |
| expression:C(dose)[T.1] | 10.7938 | 24.953 | 0.433 | 0.670 | -41.433 63.020 |
| Omnibus: | 0.082 | Durbin-Watson: | 1.923 |
| Prob(Omnibus): | 0.960 | Jarque-Bera (JB): | 0.142 |
| Skew: | -0.108 | Prob(JB): | 0.931 |
| Kurtosis: | 2.681 | Cond. No. | 469. |
Model:
AIM ~ expression + C(dose)
OLS Regression Results
| Dep. Variable: | AIM | R-squared: | 0.654 |
| Model: | OLS | Adj. R-squared: | 0.620 |
| Method: | Least Squares | F-statistic: | 18.94 |
| Date: | Thu, 21 Nov 2024 | Prob (F-statistic): | 2.43e-05 |
| Time: | 04:49:26 | Log-Likelihood: | -100.89 |
| No. Observations: | 23 | AIC: | 207.8 |
| Df Residuals: | 20 | BIC: | 211.2 |
| Df Model: | 2 | | |
| coef | std err | t | P>|t| | [95.0% Conf. Int.] |
| Intercept | 9.5327 | 80.463 | 0.118 | 0.907 | -158.309 177.375 |
| C(dose)[T.1] | 55.5079 | 9.536 | 5.821 | 0.000 | 35.616 75.400 |
| expression | 5.8433 | 10.494 | 0.557 | 0.584 | -16.048 27.734 |
| Omnibus: | 0.051 | Durbin-Watson: | 1.898 |
| Prob(Omnibus): | 0.975 | Jarque-Bera (JB): | 0.190 |
| Skew: | -0.095 | Prob(JB): | 0.909 |
| Kurtosis: | 2.597 | Cond. No. | 141. |
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: | 04:49:26 | 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: | 0.069 |
| Model: | OLS | Adj. R-squared: | 0.025 |
| Method: | Least Squares | F-statistic: | 1.555 |
| Date: | Thu, 21 Nov 2024 | Prob (F-statistic): | 0.226 |
| Time: | 04:49:26 | Log-Likelihood: | -112.28 |
| No. Observations: | 23 | AIC: | 228.6 |
| Df Residuals: | 21 | BIC: | 230.8 |
| Df Model: | 1 | | |
| coef | std err | t | P>|t| | [95.0% Conf. Int.] |
| Intercept | 222.5876 | 114.780 | 1.939 | 0.066 | -16.110 461.285 |
| expression | -19.1310 | 15.341 | -1.247 | 0.226 | -51.035 12.773 |
| Omnibus: | 3.146 | Durbin-Watson: | 2.400 |
| Prob(Omnibus): | 0.207 | Jarque-Bera (JB): | 1.898 |
| Skew: | 0.468 | Prob(JB): | 0.387 |
| Kurtosis: | 1.950 | Cond. No. | 126. |
CP101
Model Comparison: AIM ~ expression + C(dose) vs AIM ~ C(dose)
| F-statistic | p-value | df difference |
| 7.745 | 0.017 | 1.0 |
Model:
AIM ~ expression + C(dose) + expression:C(dose)
OLS Regression Results
| Dep. Variable: | AIM | R-squared: | 0.765 |
| Model: | OLS | Adj. R-squared: | 0.701 |
| Method: | Least Squares | F-statistic: | 11.93 |
| Date: | Thu, 21 Nov 2024 | Prob (F-statistic): | 0.000881 |
| Time: | 04:49:26 | Log-Likelihood: | -64.444 |
| No. Observations: | 15 | AIC: | 136.9 |
| Df Residuals: | 11 | BIC: | 139.7 |
| Df Model: | 3 | | |
| coef | std err | t | P>|t| | [95.0% Conf. Int.] |
| Intercept | 288.2330 | 120.584 | 2.390 | 0.036 | 22.831 553.636 |
| C(dose)[T.1] | 598.4693 | 257.943 | 2.320 | 0.041 | 30.741 1166.197 |
| expression | -25.5541 | 13.926 | -1.835 | 0.094 | -56.205 5.096 |
| expression:C(dose)[T.1] | -65.6225 | 30.365 | -2.161 | 0.054 | -132.456 1.211 |
| Omnibus: | 5.538 | Durbin-Watson: | 0.741 |
| Prob(Omnibus): | 0.063 | Jarque-Bera (JB): | 2.802 |
| Skew: | 0.985 | Prob(JB): | 0.246 |
| Kurtosis: | 3.774 | Cond. No. | 496. |
Model:
AIM ~ expression + C(dose)
OLS Regression Results
| Dep. Variable: | AIM | R-squared: | 0.665 |
| Model: | OLS | Adj. R-squared: | 0.609 |
| Method: | Least Squares | F-statistic: | 11.91 |
| Date: | Thu, 21 Nov 2024 | Prob (F-statistic): | 0.00141 |
| Time: | 04:49:26 | Log-Likelihood: | -67.098 |
| No. Observations: | 15 | AIC: | 140.2 |
| Df Residuals: | 12 | BIC: | 142.3 |
| Df Model: | 2 | | |
| coef | std err | t | P>|t| | [95.0% Conf. Int.] |
| Intercept | 407.4911 | 122.520 | 3.326 | 0.006 | 140.543 674.439 |
| C(dose)[T.1] | 41.5347 | 12.575 | 3.303 | 0.006 | 14.135 68.934 |
| expression | -39.3560 | 14.141 | -2.783 | 0.017 | -70.168 -8.544 |
| Omnibus: | 0.064 | Durbin-Watson: | 1.298 |
| Prob(Omnibus): | 0.969 | Jarque-Bera (JB): | 0.219 |
| Skew: | -0.124 | Prob(JB): | 0.896 |
| Kurtosis: | 2.463 | Cond. No. | 174. |
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: | 04:49:26 | 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: | 0.360 |
| Model: | OLS | Adj. R-squared: | 0.311 |
| Method: | Least Squares | F-statistic: | 7.327 |
| Date: | Thu, 21 Nov 2024 | Prob (F-statistic): | 0.0180 |
| Time: | 04:49:26 | Log-Likelihood: | -71.948 |
| No. Observations: | 15 | AIC: | 147.9 |
| Df Residuals: | 13 | BIC: | 149.3 |
| Df Model: | 1 | | |
| coef | std err | t | P>|t| | [95.0% Conf. Int.] |
| Intercept | 516.9345 | 156.583 | 3.301 | 0.006 | 178.658 855.211 |
| expression | -49.5813 | 18.317 | -2.707 | 0.018 | -89.153 -10.009 |
| Omnibus: | 4.171 | Durbin-Watson: | 2.483 |
| Prob(Omnibus): | 0.124 | Jarque-Bera (JB): | 1.402 |
| Skew: | 0.240 | Prob(JB): | 0.496 |
| Kurtosis: | 1.581 | Cond. No. | 167. |