Importance Socioeconomically disadvantaged individuals (ie, those with low socioeconomic status [SES]) have difficulty quitting smoking and may benefit from incentive-based cessation interventions. Objectives To evaluate the impact of incentivizing abstinence on among adults SES. Design, Setting, Participants This study used a 2-group randomized clinical trial design. Data collection occurred between January 30, 2017, February 7, 2022. included SES who were willing to undergo treatment....

Item nonresponse in surveys is often treated through some form of imputation. We introduce multiply robust imputation finite population sampling. This closely related to multiple robustness, which extends double robustness. In practice, models and may be fitted, each involving different subsets covariates possibly link functions. An procedure said if the resulting estimator consistent when all but one are misspecified. A jackknife variance proposed shown consistent. Random fractional...

Sample estimates derived from data with missing values may be unreliable and negatively impact the inferences that researchers make about underlying population due to nonresponse bias. As a result, imputation is often preferred listwise deletion in handling multivariate data. In this study, we compared three popular methods: sequential multiple imputation, fractional hot-deck generalized efficient regression-based latent processes for missingness under different patterns by conducting...

Data integration combining a probability sample with another nonprobability is an emerging area of research in survey sampling. We consider the case when study variable interest measured only sample, but comparable auxiliary information available for both data sources. mass imputation using as training set imputation. The parametric sensitive to model assumptions. To develop improved and robust methods, we nonparametric integration. In particular, kernel smoothing low-dimensional covariate...

Anti-poverty has always been an important issue to be settled. What policies should selected help individuals escaping from the poverty trap: by directly offering transfer payments or indirectly providing public services? This paper is among first explore effects of anti-poverty programs system in China.We Using unbalanced panel data China Health and Nutrition Survey (CHNS) 1989 2009, we demonstrate how individual status determined through a four-staged simultaneous model. We choose 3SLS...

In this study, we examined potential influences of cultural and linguistic background on PPVT-4 performance in a community sample preschool-age children from low-SES households. We did by evaluating item-level across African American Hispanic low-income families. compared for 332 (Mage = 48 months) using Wald chi-square tests independence. There were clinically significant differences accuracy 14 test items with most favouring the group. then looked at relationship between English use scores...

Abstract Missing data reduce the representativeness of sample and can lead to inference problems. In this article, we apply Bayesian jackknife empirical likelihood (BJEL) method for on that are missing at random, as well causal inference. The semiparametric fractional imputation estimator, propensity score‐weighted doubly robust estimator used constructing pseudo values, which needed conducting BJEL‐based with data. Existing methods, such normal approximation JEL, compared BJEL approach in a...

Abstract Background Oklahoma’s cumulative COVID-19 incidence is higher in rural than urban counties and the overall US incidence. Furthermore, fewer Oklahomans have received at least one vaccine compared to average. Our goal conduct a randomized controlled trial using multiphase optimization strategy (MOST) test multiple educational interventions improve uptake of vaccination among underserved populations Oklahoma. Methods study uses preparation phases MOST framework. We focus groups...

Previous studies have shown disparities in health conditions and behaviors among different ethnic groups. Sampling designs that do not consider oversampling certain minority populations, such as American Indians or African Americans, may produce sufficient sample sizes for estimating parameters populations. Oversampling is one of the most common approaches researchers use to achieve required precision levels small domain estimation. However, it has been rigorously investigated dual-frame...

To ascertain the variables predicting gap between ideal and actual practice in embedding school-based physical therapy services.School-based therapists completed an online survey estimating of services. Predictive modeling was used to determine whether disability, interventions, goals, families, teachers, workload, billing, and/or contracts predicted estimated practice.Data from 410 participants revealed that severity students' written contracts, families' preferences Actual varied based on...

Multi-stage sampling designs are often used in household surveys because a frame of elements may not be available or for cost considerations when data collection involves face-to-face interviews. In this context, variance estimation is complex task as it relies on the availability second-order inclusion probabilities at each stage. To cope with issue, several bootstrap algorithms have been proposed literature context two-stage design. paper, we describe some these and compare them...

Journal Article Geographic Oversampling for Race/Ethnicity Using Data from the 2010 U.S. Population Census Get access Sixia Chen, Chen Search other works by this author on: Oxford Academic Google Scholar Graham Kalton * *Address correspondence to Kalton, Westat, 1600 Research Blvd, MD 20850; E-mail: grahamkalton@westat.com. of Survey Statistics and Methodology, Volume 3, Issue 4, December 2015, Pages 543–565, https://doi.org/10.1093/jssam/smv023 Published: 09 November 2015

The empirical likelihood method is a powerful tool for incorporating moment conditions in statistical inference. We propose novel application of the handling item non-response survey sampling. proposed takes form fractional imputation but it does not require parametric model assumptions. Instead, only first condition based on regression assumed and applied to observed residuals get weights. resulting semiparametric provides -consistent estimates various parameters. Variance estimation...

OBJECTIVE Quality improvement (QI) tools are increasingly being used to calibrate healthcare quality. Achieving quality is essential, as there a movement toward value-based delivery. Visual management, such living Pareto chart, strategy for within the QI framework. The authors herein hypothesized that transparency of data through chart powerful way improve patient outcomes and gain clinical efficiency. METHODS retrospectively reviewed complications; cerebrospinal fluid (CSF) leaks; shunt,...

Abstract Background Previous literature showed significant health disparities between Native American population and other populations such as Non-Hispanic White. Most existing studies for Health were based on non-probability samples which suffer with selection bias. In this paper, we are the first to evaluate effectiveness of data integration methods, including calibration sequential mass imputation, improve representativeness Tribal Behavioral Risk Factor Surveillance System (TBRFSS) in...

Nonprobability samples have been used frequently in practice including public health study, economics, education, and political polls. Naïve estimates based on nonprobability without any further adjustments may suffer from serious selection bias. Mass imputation has shown to be effective improve the representativeness of samples. It builds an model generates imputed values for all units probability In this paper, we compare two mass approaches latent joint multivariate normal (e.g.,...

Self-selected samples are frequently obtained due to different levels of survey participation propensity the individuals. When is related topic interest, score weighting adjustment using auxiliary information may lead biased estimation. In this paper, we consider a parametric model for response probability that includes study variable itself in covariates and proposes novel application two-phase sampling estimate parameters model. The proposed method an experiment which data collected again...

Abstract Item nonresponse in surveys is usually dealt with through single imputation. It well known that treating the imputed values as if they were observed may lead to serious underestimation of variance point estimators. In this article, we propose three pseudo-population bootstrap schemes for estimating estimators obtained after applying a multiply robust imputation procedure. The proposed procedures can handle large sampling fractions and enjoy multiple robustness property. Results from...

Sequencing-based genetic association analysis is typically performed by first generating genotype calls from sequence data and then performing tests on the called genotypes. Standard approaches require accurate calling (GC), which can be achieved either with high sequencing depth (typically available in a small number of individuals) or via computationally intensive multi-sample linkage disequilibrium (LD)-aware methods. We propose efficient two-stage combination approach for analysis,...

To study the relationship between genetic variants and phenotypes, association testing is adopted; however, most studies are conducted by genotype-based testing. Testing methods based on next-generation sequencing (NGS) data without genotype calling demonstrate an advantage over genotypes in scenarios when estimation not accurate. Our objective was to develop NGS data-based for fill gap literature. Single-variant have been proposed, including our previously proposed single-variant method,...