In general, (i) pre-treatment variables should be controlled for; (ii) with x controlled for, the conditional effect E(y1 - y0|x) is identified where yj is the potential response when d = j; (iii) 'regression discontinuity design' may be useful if the values of x do not overlap. ...
It is shown that in such research there is a potential for the estimates of change to be erroneous due to the effect of regression to the mean. The source of the regression effect is shown to arise from measurement error and a sampling bias of this measurement error in the process of ...
Species-specific relationships between bird abundance and water depth necessarily are non-linear; thus, we developed a methodology to correct waterbird abundance for variation in water depth, based on the non-parametric regression of these two variables. Accordingly, we used the difference between ...
which can then be used as controls for the true variables; the method achieves exact FDR control in finite sample settings no matter the design or covariates, the number of variables in the model, and the amplitudes of the unknown regression coefficients, and does not require any knowledge of...
Saddlepoint approximations for distributions of quadratic forms in normal variables. Biometrika 86, 4 (1999). Dey, R., Schmidt, E. M., Abecasis, G. R. & Lee, S. A fast and accurate algorithm to test for binary phenotypes and its application to PheWAS. Am. J. Hum. Genet. 101, 37–...
Since we had a large and diverse sample, we further tested whether and how other covariates might be predictive of visual crowding: We ran a linear mixed-effects regression model with visual crowding as the dependent variable and participant as a random variable. We included age and age_square...
fit(Y, T, X=X, Z=Z) # Z -> instrumental variables treatment_effects = est.effect(X_test) See the References section for more details. Interpretability Tree Interpreter of the CATE model (click to expand) from econml.cate_interpreter import SingleTreeCateInterpreter intrp = SingleTreeCate...
Distribution of Variables by Method of Outlier Detection The presence of outliers can very problematic in data analysis, leading statisticians to develop a wide variety of methods for identifying them in both the... FW Holmes - 《Frontiers in Psychology》 被引量: 14发表: 2012年 加载更多来源...
sample undergoing screening for several transdiagnostic psychiatric research studies. A total of 1,724 participants were analyzed for association of CRP with variables using multivariate linear regression. An unadjusted model with no covariates showed that PHQ-9 was significantly associated with CRP in ...
fit(Y, T, X=X, Z=Z) # Z -> instrumental variables treatment_effects = est.effect(X_test) See the References section for more details. Interpretability Tree Interpreter of the CATE model (click to expand) from econml.cate_interpreter import SingleTreeCateInterpreter intrp = SingleTreeCate...