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 |
0.160 | 0.693 | 1.0 |
Model:
AIM ~ expression + C(dose) + expression:C(dose)
OLS Regression Results
Dep. Variable: | AIM | R-squared: | 0.655 |
Model: | OLS | Adj. R-squared: | 0.601 |
Method: | Least Squares | F-statistic: | 12.03 |
Date: | Thu, 21 Nov 2024 | Prob (F-statistic): | 0.000121 |
Time: | 03:34:36 | Log-Likelihood: | -100.86 |
No. Observations: | 23 | AIC: | 209.7 |
Df Residuals: | 19 | BIC: | 214.3 |
Df Model: | 3 | | |
| coef | std err | t | P>|t| | [95.0% Conf. Int.] |
Intercept | 53.0012 | 99.918 | 0.530 | 0.602 | -156.129 262.131 |
C(dose)[T.1] | 110.1199 | 138.820 | 0.793 | 0.437 | -180.434 400.674 |
expression | 0.1727 | 14.265 | 0.012 | 0.990 | -29.684 30.030 |
expression:C(dose)[T.1] | -8.7439 | 20.577 | -0.425 | 0.676 | -51.812 34.324 |
Omnibus: | 0.221 | Durbin-Watson: | 1.980 |
Prob(Omnibus): | 0.896 | Jarque-Bera (JB): | 0.313 |
Skew: | 0.199 | Prob(JB): | 0.855 |
Kurtosis: | 2.590 | Cond. No. | 277. |
Model:
AIM ~ expression + C(dose)
OLS Regression Results
Dep. Variable: | AIM | R-squared: | 0.652 |
Model: | OLS | Adj. R-squared: | 0.617 |
Method: | Least Squares | F-statistic: | 18.72 |
Date: | Thu, 21 Nov 2024 | Prob (F-statistic): | 2.62e-05 |
Time: | 03:34:36 | Log-Likelihood: | -100.97 |
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 | 82.3794 | 70.644 | 1.166 | 0.257 | -64.982 229.741 |
C(dose)[T.1] | 51.2938 | 10.117 | 5.070 | 0.000 | 30.189 72.398 |
expression | -4.0296 | 10.068 | -0.400 | 0.693 | -25.031 16.972 |
Omnibus: | 0.139 | Durbin-Watson: | 1.877 |
Prob(Omnibus): | 0.933 | Jarque-Bera (JB): | 0.306 |
Skew: | 0.147 | Prob(JB): | 0.858 |
Kurtosis: | 2.517 | Cond. No. | 112. |
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: | 03:34:36 | 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: | 0.204 |
Model: | OLS | Adj. R-squared: | 0.167 |
Method: | Least Squares | F-statistic: | 5.396 |
Date: | Thu, 21 Nov 2024 | Prob (F-statistic): | 0.0303 |
Time: | 03:34:36 | Log-Likelihood: | -110.47 |
No. Observations: | 23 | AIC: | 224.9 |
Df Residuals: | 21 | BIC: | 227.2 |
Df Model: | 1 | | |
| coef | std err | t | P>|t| | [95.0% Conf. Int.] |
Intercept | 280.7277 | 86.776 | 3.235 | 0.004 | 100.267 461.188 |
expression | -29.7857 | 12.823 | -2.323 | 0.030 | -56.453 -3.119 |
Omnibus: | 1.355 | Durbin-Watson: | 2.247 |
Prob(Omnibus): | 0.508 | Jarque-Bera (JB): | 0.731 |
Skew: | 0.437 | Prob(JB): | 0.694 |
Kurtosis: | 3.002 | Cond. No. | 93.2 |
CP101
Model Comparison: AIM ~ expression + C(dose) vs AIM ~ C(dose)
F-statistic | p-value | df difference |
1.029 | 0.330 | 1.0 |
Model:
AIM ~ expression + C(dose) + expression:C(dose)
OLS Regression Results
Dep. Variable: | AIM | R-squared: | 0.498 |
Model: | OLS | Adj. R-squared: | 0.362 |
Method: | Least Squares | F-statistic: | 3.644 |
Date: | Thu, 21 Nov 2024 | Prob (F-statistic): | 0.0480 |
Time: | 03:34:36 | Log-Likelihood: | -70.125 |
No. Observations: | 15 | AIC: | 148.2 |
Df Residuals: | 11 | BIC: | 151.1 |
Df Model: | 3 | | |
| coef | std err | t | P>|t| | [95.0% Conf. Int.] |
Intercept | -152.2352 | 264.969 | -0.575 | 0.577 | -735.429 430.959 |
C(dose)[T.1] | 163.2167 | 313.275 | 0.521 | 0.613 | -526.298 852.731 |
expression | 29.8191 | 35.936 | 0.830 | 0.424 | -49.275 108.913 |
expression:C(dose)[T.1] | -15.5758 | 42.391 | -0.367 | 0.720 | -108.879 77.727 |
Omnibus: | 3.186 | Durbin-Watson: | 0.455 |
Prob(Omnibus): | 0.203 | Jarque-Bera (JB): | 2.211 |
Skew: | -0.922 | Prob(JB): | 0.331 |
Kurtosis: | 2.628 | Cond. No. | 443. |
Model:
AIM ~ expression + C(dose)
OLS Regression Results
Dep. Variable: | AIM | R-squared: | 0.492 |
Model: | OLS | Adj. R-squared: | 0.408 |
Method: | Least Squares | F-statistic: | 5.818 |
Date: | Thu, 21 Nov 2024 | Prob (F-statistic): | 0.0171 |
Time: | 03:34:36 | Log-Likelihood: | -70.216 |
No. Observations: | 15 | AIC: | 146.4 |
Df Residuals: | 12 | BIC: | 148.6 |
Df Model: | 2 | | |
| coef | std err | t | P>|t| | [95.0% Conf. Int.] |
Intercept | -69.7818 | 135.717 | -0.514 | 0.616 | -365.485 225.921 |
C(dose)[T.1] | 48.2557 | 15.134 | 3.189 | 0.008 | 15.282 81.229 |
expression | 18.6261 | 18.363 | 1.014 | 0.330 | -21.382 58.635 |
Omnibus: | 3.475 | Durbin-Watson: | 0.536 |
Prob(Omnibus): | 0.176 | Jarque-Bera (JB): | 2.369 |
Skew: | -0.961 | Prob(JB): | 0.306 |
Kurtosis: | 2.691 | Cond. No. | 136. |
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: | 03:34:36 | 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: | 0.062 |
Model: | OLS | Adj. R-squared: | -0.010 |
Method: | Least Squares | F-statistic: | 0.8615 |
Date: | Thu, 21 Nov 2024 | Prob (F-statistic): | 0.370 |
Time: | 03:34:36 | Log-Likelihood: | -74.819 |
No. Observations: | 15 | AIC: | 153.6 |
Df Residuals: | 13 | BIC: | 155.1 |
Df Model: | 1 | | |
| coef | std err | t | P>|t| | [95.0% Conf. Int.] |
Intercept | -70.5723 | 177.222 | -0.398 | 0.697 | -453.438 312.294 |
expression | 22.2140 | 23.933 | 0.928 | 0.370 | -29.490 73.918 |
Omnibus: | 1.805 | Durbin-Watson: | 1.532 |
Prob(Omnibus): | 0.406 | Jarque-Bera (JB): | 0.915 |
Skew: | 0.083 | Prob(JB): | 0.633 |
Kurtosis: | 1.801 | Cond. No. | 136. |