Adjustment with Many Regressors Under Covariate-Adaptive Randomizations

Our paper discovers a new trade-off of using regression adjustments (RAs) in causal inference under covariate-adaptive randomizations (CARs). On one hand, RAs can improve the efficiency of causal estimators by incorporating information from covariates that are not used in the randomization. On the other hand, RAs can degrade estimation efficiency due to their estimation errors, which are not asymptotically negligible when the number of regressors is of the same order as the sample size. Ignoring the estimation errors of RAs may result in serious over-rejection of causal inference under the null hypothesis. To address the issue, we develop a unified inference theory for the regression-adjusted average treatment effect (ATE) estimator under CARs. Our theory has two key features: (1) it ensures the exact asymptotic size under the null hypothesis, regardless of whether the number of covariates is fixed or diverges no faster than the sample size; and (2) it guarantees weak efficiency improvement over the ATE estimator without adjustments.Comment: 71 pages, including appendi

Prevalence of COPD and its association with socioeconomic status in China: Findings from China Chronic Disease Risk Factor Surveillance 2007

<p>Abstract</p> <p>Background</p> <p>Socioeconomic status is likely an independent risk factor for Chronic Obstructive Pulmonary Disease (COPD), but little research has been done in China to study this association in a nationwide sample.</p> <p>Methods</p> <p>We used data from the 2007 China Chronic Disease Risk Factor Surveillance of 49,363 Chinese men and women aged 15-69 years to examine the association between the prevalence of self-reported physician diagnosed COPD and socioeconomic status defined by both educational level and annual household income. Multivariable logistic regression modelling was performed with adjustement for potential confounders.</p> <p>Results</p> <p>Both low educational attainment and low household income were independently associated with higher risk of physician-diagnosed COPD. Compared to subjects with high educational level, subjects with low educational level had a significantly increased risk of COPD (OR 1.67, 95%CI 1.32-2.13, p for trend< 0.001 for urban, OR 1.76, 95%CI 1.34-2.30, p for trend < 0.001 for rural) after adjusting for age, sex, smoking status, passive smoking and geographic regions. Similarly increased risk was observed for household income and COPD in urban (OR 1.64, 95%CI 1.28-2.09, P for trend< 0.001) but not rural areas. Among never smokers, low educational level and household income were still associated with a significant higher prevalence of COPD (OR 1.77, 95%CI 1.40-2.25, OR 1.31, 95%CI 1.05-1.62). Removal of those with asthma diagnosis did not alter the observed associations.</p> <p>Conclusions</p> <p>Socioeconomic status is a risk factor for self-reported physician-diagnosed COPD independently of current or passive smoking. Prospective studies are needed in China to better understand the association between socioeconomic status and COPD.</p

Clustering of cardiovascular behavioral risk factors and blood pressure among people diagnosed with hypertension: A nationally representative survey in China

This study aimed to examine association between the number of behavioral risk factors and blood pressure (BP) level among a nationally representative sample of Chinese people diagnosed with hypertension. A total of 31,694 respondents aged 18+ years with diagnosed hypertension were extracted from the 2013-2014 China Chronic Disease and Risk Factor Surveillance. BP of each respondent was classified into six levels according to criteria in 2007 Guidelines for the Management of Arterial Hypertension. Information for smoking, alcohol drinking, fruit and vegetables consumption, physical inactivity, and overweight and obesity were obtained. The average number of risk factors was determined by BP level to explore potential risk factor clustering. Ten generalized proportional odds models were used to examine association between clustering of behavioral risk factors and BP level. A clear gradient between the number of behavioral risk factors and BP level was observed for men and women (P \u3c 0.05 for both genders). BP level for men and women was much likely to upgrade as number of risk factors accumulated (P \u3c 0.01 for 10 models). Behavioral modifications may decrease BP, and combinations of two or more behavioral interventions could potentially result in even better BP management among people diagnosed with hypertension

Analyzing and Mitigating Interference in Neural Architecture Search

Weight sharing is a popular approach to reduce the cost of neural architecture search (NAS) by reusing the weights of shared operators from previously trained child models. However, the rank correlation between the estimated accuracy and ground truth accuracy of those child models is low due to the interference among different child models caused by weight sharing. In this paper, we investigate the interference issue by sampling different child models and calculating the gradient similarity of shared operators, and observe: 1) the interference on a shared operator between two child models is positively correlated with the number of different operators; 2) the interference is smaller when the inputs and outputs of the shared operator are more similar. Inspired by these two observations, we propose two approaches to mitigate the interference: 1) MAGIC-T: rather than randomly sampling child models for optimization, we propose a gradual modification scheme by modifying one operator between adjacent optimization steps to minimize the interference on the shared operators; 2) MAGIC-A: forcing the inputs and outputs of the operator across all child models to be similar to reduce the interference. Experiments on a BERT search space verify that mitigating interference via each of our proposed methods improves the rank correlation of super-pet and combining both methods can achieve better results. Our discovered architecture outperforms RoBERTa$_{\rm base}$ by 1.1 and 0.6 points and ELECTRA$_{\rm base}$ by 1.6 and 1.1 points on the dev and test set of GLUE benchmark. Extensive results on the BERT compression, reading comprehension and ImageNet task demonstrate the effectiveness and generality of our proposed methods.Comment: ICML 2022, Spotligh