Estimating Ratio of Proportions Using Auxiliary Information

The problem of estimation of ratio of population proportions is considered and a difference-type estimator is proposed using auxiliary information. The bias and mean squared error of the proposed estimator is found and compared to the usual estimator and also to WYNN'S (1976) type estimator. An example is included for illustration.     

A New Exponential Ratio-Type Estimator with Linear Combination of Two Auxiliary Variables

In sample surveys, it is usual to make use of auxiliary information to increase the precision of estimators. We propose a new exponential ratio-type estimator of a finite population mean using linear combination of two auxiliary variables and obtain mean square error (MSE) equation for proposed estimator. We find theoretical conditions that make proposed estimator more efficient than traditional multivariate ratio estimator using information of two auxiliary variables, the estimator of Bahl and Tuteja and the estimator proposed by Abu-Dayeh et al. In addition, we support these theoretical results with the aid of two numerical examples.     

The Chain Ratio Estimator and Regression Estimator with Linear Combination of Two Auxiliary Variables

In sample surveys, it is usual to make use of auxiliary information to increase the precision of the estimators. We propose a new chain ratio estimator and regression estimator of a finite population mean using linear combination of two auxiliary variables and obtain the mean squared error (MSE) equations for the proposed estimators. We find theoretical conditions that make proposed estimators more efficient than the traditional multivariate ratio estimator and the regression estimator using information of two auxiliary variables.     

Overweight and obesity among foreign‐born and U.S.‐born Hispanics

Abstract

In this study, data from the New Immigrant Survey and the National Health and Nutrition Examination Survey are combined to examine patterns of overweight and obesity among U.S.‐born and foreign‐born Hispanics. Results indicate that, after using height and weight measures adjusted for self‐reporting bias, foreign‐born Hispanic men and women have substantially lower likelihoods of being overweight and obese than the U.S.‐born. However, both likelihoods increase as years in the U.S. accumulate for the foreign‐born. Controls for smoking behavior, physical activity, and the degree of dietary change do not reduce the strength of the positive relationship between years in the U.S. and overweight/obesity.     

Ratio estimation with measurement error in the auxiliary variate

Summary .  With auxiliary information that is well correlated with the primary variable of interest, ratio estimation of the finite population total may be much more efficient than alternative estimators that do not make use of the auxiliary variate. The well-known properties of ratio estimators are perturbed when the auxiliary variate is measured with error. In this contribution we examine the effect of measurement error in the auxiliary variate on the design-based statistical properties of three common ratio estimators. We examine the case of systematic measurement error as well as measurement error that varies according to a fixed distribution. Aside from presenting expressions for the bias and variance of these estimators when they are contaminated with measurement error we provide numerical results based on a specific population. Under systematic measurement error, the biasing effect is asymmetric around zero, and precision may be improved or degraded depending on the magnitude of the error. Under variable measurement error, bias of the conventional ratio-of-means estimator increased slightly with increasing error dispersion, but far less than the increased bias of the conventional mean-of-ratios estimator. In similar fashion, the variance of the mean-of-ratios estimator incurs a greater loss of precision with increasing error dispersion compared with the other estimators we examine. Overall, the ratio-of-means estimator appears to be remarkably resistant to the effects of measurement error in the auxiliary variate.     

Breastfeeding and child disability: A comparison of siblings from the United States

Little is known about whether breastfeeding may prevent disabilities throughout childhood. We evaluate the effects of breastfeeding on child disability using data from the National Survey of Family Growth merged to the National Health Interview Survey for a large nationally representative sample of children aged 1–18 years from the U.S. including over 3000 siblings who are discordant on breastfeeding status/duration. We focus on a mother fixed effect model that compares siblings in order to account for family-level unobservable confounders and employ multiple specifications including a dynamic model that accounts for disability status of the prior child. Breastfeeding the child for a longer duration is associated with a lower risk of child disability, by about 0.2 percentage-points per month of breastfeeding. This effect is only observed on the intensive margin among breastfed children, as any breastfeeding has no effect on the extensive margin. We conclude that very short breastfeeding durations are unlikely to have an effect on reducing disability risk.     

Is handedness exogenously determined? Counterevidence from South Korea

Establishing whether handedness is exogenously determined can help explain the relationship between handedness and various health and economic outcomes. It can also ensure the use of handedness as an instrument in empirical applications. Using data from the Korean National Health and Nutrition Examination Survey and the National Health and Nutrition Examination Survey in the United States, I investigate the exogeneity of children’s handedness by examining the determinants of mixed-handedness. In the analysis using Korean data, parents’ age, parents’ non-right-handedness, and family income influence the likelihood of children’s mixed-handedness. In the U.S. data analysis, however, none of the child and family characteristics, except being Asian, predict the likelihood of mixed-handedness. These results suggest that mixed-handedness, further handedness cannot be generalized as exogenous and is a race-specific characteristic.     

Causes of death and mortality crossovers by race

Abstract

The phenomenon of “mortality crossovers,” the intersection of age curves of mortality at older ages, has been observed in comparisons of various populations for some time. Some researchers have argued that crossovers are an artifact of deficient reporting of age that is greater for some populations than others. Other researchers attribute crossovers to selective processes by age that vary by group. We use mortality data from the National Center for Health Statistics for the U.S. at ages 55 and over, supplemented by comparable data from matched records of the National Health Interview Survey and National Death Index, to reexamine causes of death linked to mortality crossovers for Whites and Blacks in the U.S. Findings portray a more elaborate set of influences of causes of death than has been discovered heretofore; however, the major finding is that the mortality crossover for Whites and Blacks in the U. S. is real and, although observed for several causes of death, operates principally through varying trajectories of heart disease mortality.     

Association Between Lifting Weights and Metabolic Syndrome among U.S. Adults: 1999-2004 National Health and Nutrition Examination Survey

ABSTRACT: Magyari, PM and Churilla, JR. Association between lifting weights and metabolic syndrome among U.S. adults: 1999-2004 National Health and Nutrition Examination Survey. J Strength Cond Res 26(11): 3113-3117, 2012-The purpose of this cross-sectional study was to determine the proportion of U.S. adults who participate in the resistance exercise modality of lifting weights (LWs) by demographic characteristics and to investigate the impact of LWs on the prevalence and risk of metabolic syndrome (MetS) in a national representative sample of U.S. adults. The sample (n = 5,618) in this cross-sectional study included adults aged ≥20 years who participated in the 1999-2004 National Health and Nutrition Examination Survey. Approximately twice as many men (11.2%; 95% confidence interval [CI] 9.5, 13.1) reported LWs as women did (6.3%; 95% CI 5.2, 7.6) with non-Hispanic Whites (9.6%; 95% CI 8.1, 11.4) reporting the highest levels and Mexican Americans reporting the lowest levels (5.6%; 95% CI 4.4, 7.2) of engaging in LWs. Additionally, higher levels of socioeconomic status were associated with greater levels of self-reported LWs. MetS prevalence was found to be significantly lower among U.S. adults reporting LWs (24.6%; 95% CI 19.3, 30.9) compared with adults not reporting LWs (37.3%; 95% CI 35.5, 39.2) with associated risk reductions of 58% (p < 0.001) and 37% (p < 0.01) in the unadjusted model and model adjusted for demographic variables, respectively. These findings suggest that LWs may play a role in reducing the prevalence and risk of MetS among U.S. adults. Therefore, exercise professionals should strongly encourage the activity of LWs among adults of all ages to promote metabolic health and focus programs designed to increase the adoption of LWs among the subgroups who report the lowest levels of LWs.     

Logistic regression analysis of two-phase studies using generalized method of moments

Two-phase designs can reduce the cost of epidemiological studies by limiting the ascertainment of expensive covariates or/and exposures to an efficiently selected subset (phase-II) of a larger (phase-I) study. Efficient analysis of the resulting data set combining disparate information from phase-I and phase-II, however, can be complex. Most of the existing methods, including semiparametric maximum-likelihood estimator, require the information in phase-I to be summarized into a fixed number of strata. In this paper, we describe a novel method for the analysis of two-phase studies where information from phase-I is summarized by parameters associated with a reduced logistic regression model of the disease outcome on available covariates. We then setup estimating equations for parameters associated with the desired extended logistic regression model, based on information on the reduced model parameters from phase-I and complete data available at phase-II after accounting for nonrandom sampling design. We use generalized method of moments to solve overly identified estimating equations and develop the resulting asymptotic theory for the proposed estimator. Simulation studies show that the use of reduced parametric models, as opposed to summarizing data into strata, can lead to more efficient utilization of phase-I data. An application of the proposed method is illustrated using the data from the U.S. National Wilms Tumor Study.     

Random effects logistic regression analysis with auxiliary covariates

We study a semiparametric estimation method for the random effects logistic regression when there is auxiliary covariate information about the main exposure variable. We extend the semiparametric estimator of Pepe and Fleming (1991, Journal of the American Statistical Association 86, 108-113) to the random effects model using the best linear unbiased prediction approach of Henderson (1975, Biometrics 31, 423-448). The method can be used to handle the missing covariate or mismeasured covariate data problems in a variety of real applications. Simulation study results show that the proposed method outperforms the existing methods. We analyzed a data set from the Collaborative Perinatal Project using the proposed method and found that the use of DDT increases the risk of preterm births among U.S. children.     

Two auxiliary variates in ratio method of estimation

A ratio type estimator using two auxiliary variates has been proposed and conditions are obtained to choose between proposed estimator and OLKIN'S (1958) estimator using two auxiliary variates.     

Estimating mean cost using auxiliary covariates

We study the estimation of mean medical cost when censoring is dependent and a large amount of auxiliary information is present. Under missing at random assumption, we propose semiparametric working models to obtain low-dimensional summarized scores. An estimator for the mean total cost can be derived nonparametrically conditional on the summarized scores. We show that when either the two working models for cost-survival process or the model for censoring distribution is correct, the estimator is consistent and asymptotically normal. Small-sample performance of the proposed method is evaluated via simulation studies. Finally, our approach is applied to analyze a real data set in health economics.     

Using calibration weighting to adjust for nonresponse under a plausible model

When we estimate the population total for a survey variableor variables, calibration forces the weighted estimates of certaincovariates to match known or alternatively estimated populationtotals called benchmarks. Calibration can be used to correctfor sample-survey nonresponse, or for coverage error resultingfrom frame undercoverage or unit duplication. The quasi-randomizationtheory supporting its use in nonresponse adjustment treats responseas an additional phase of random sampling. The functional formof a quasi-random response model is assumed to be known, itsparameter values estimated implicitly through the creation ofcalibration weights. Unfortunately, calibration depends uponknown benchmark totals while the covariates in a plausible modelfor survey response may not be the benchmark covariates. Moreover,it may be prudent to keep the number of covariates in a responsemodel small. We use calibration to adjust for nonresponse whenthe benchmark model and covariates may differ, provided thenumber of the former is at least as great as that of the latter.We discuss the estimation of a total for a vector of surveyvariables that do not include the benchmark covariates, butthat may include some of the model covariates. We show how tomeasure both the additional asymptotic variance due to the nonresponsein a calibration-weighted estimator and the full asymptoticvariance of the estimator itself. All variances are determinedwith respect to the randomization mechanism used to select thesample, the response model generating the subset of sample respondents,or both. Data from the U.S. National Agricultural StatisticalService's 2002 Census of Agriculture and simulations are usedto illustrate alternative adjustments for nonresponse. The paperconcludes with some remarks about adjustment for coverage error.     

Empirical Bayes small area prediction under a zero-inflated lognormal model with correlated random area effects

Many variables of interest in agricultural or economical surveys have skewed distributions and can equal zero. Our data are measures of sheet and rill erosion called Revised Universal Soil Loss Equation - 2 (RUSLE2). Small area estimates of mean RUSLE2 erosion are of interest. We use a zero-inflated lognormal mixed effects model for small area estimation. The model combines a unit-level lognormal model for the positive RUSLE2 responses with a unit-level logistic mixed effects model for the binary indicator that the response is nonzero. In the Conservation Effects Assessment Project (CEAP) data, counties with a higher probability of nonzero responses also tend to have a higher mean among the positive RUSLE2 values. We capture this property of the data through an assumption that the pair of random effects for a county are correlated. We develop empirical Bayes (EB) small area predictors and a bootstrap estimator of the mean squared error (MSE). In simulations, the proposed predictor is superior to simpler alternatives. We then apply the method to construct EB predictors of mean RUSLE2 erosion for South Dakota counties. To obtain auxiliary variables for the population of cropland in South Dakota, we integrate a satellite-derived land cover map with a geographic database of soil properties. We provide an R Shiny application called viscover (available at https://lyux.shinyapps.io/viscover/ ) to visualize the overlay operations required to construct the covariates. On the basis of bootstrap estimates of the mean square error, we conclude that the EB predictors of mean RUSLE2 erosion are superior to direct estimators.     

Trends in Waist Circumference among U.S. Adults

Objective: Waist circumference has been proposed as a measure of obesity or as an adjunct to other anthropometric measures to determine obesity. Our objective was to examine temporal trends in waist circumference among adults in the U.S. Research Methods and Procedures: We used data from 15, 454 participants ≥20 years old in National Health and Nutrition Examination Survey (NHANES) III (1988 to 1994) and 4024 participants ≥20 years old from National Health and Nutrition Examination Survey 1999 to 2000. Results: The unadjusted waist circumference increased from 95.3 (age‐adjusted, 96.0 cm) to 98.6 (age‐adjusted, 98.9 cm) cm among men and from 88.7 (age‐adjusted 88.9 cm) to 92.2 (age‐adjusted 92.1 cm) cm among women. The percentiles from the two surveys suggest that much of the waist circumference distribution has shifted. Statistically significant increases occurred among all age groups and racial or ethnic groups except men 30 to 59 years old, women 40 to 59 and ≥70 years old, and women who were Mexican American or of “other” race or ethnicity. Discussion: These results demonstrate the rapid increase in obesity, especially abdominal obesity, among U.S. adults. Unless measures are taken to slow the increase in or reverse the course of the obesity epidemic, the burden of obesity‐associated morbidity and mortality in the U.S. can be expected to increase substantially in future years.     

A computational model of the error detector of human visual accommodation

A mathematical model is proposed for the error detector of the human visual accommodative system. The model supposes that the accommodative error detector derives both the direction and the magnitude of the accommodative error from naturally-occuring oscillations of the lens and their effects on retinal-image contrast. Differential operators take the first derivatives of two time varying functions: lens power and retinal-image contrast. Directional information is obtained by comparing the signs of these two derivatives and magnitude information is obtained by comparing their amplitudes.Research conducted at the School of Optometry, University of California, BerkeleySupported by National Eye Institute grant EYO-3532-04(C.S.) and National Institutes of Health core grant # 1-445420-32011     

Causal inference with outcomes truncated by death in multiarm studies

It is challenging to evaluate causal effects when the outcomes of interest suffer from truncation-by-death in many clinical studies; that is, outcomes cannot be observed if patients die before the time of measurement. To address this problem, it is common to consider average treatment effects by principal stratification, for which, the identifiability results and estimation methods with a binary treatment have been established in previous literature. However, in multiarm studies with more than two treatment options, estimation of causal effects becomes more complicated and requires additional techniques. In this article, we consider identification, estimation, and bounds of causal effects with multivalued ordinal treatments and the outcomes subject to truncation-by-death. We define causal parameters of interest in this setting and show that they are identifiable either using some auxiliary variable or based on linear model assumption. We then propose a semiparametric method for estimating the causal parameters and derive their asymptotic results. When the identification conditions are invalid, we derive sharp bounds of the causal effects by use of covariates adjustment. Simulation studies show good performance of the proposed estimator. We use the estimator to analyze the effects of a four-level chronic toxin on fetal developmental outcomes such as birth weight in rats and mice, with data from a developmental toxicity trial conducted by the National Toxicology Program. Data analyses demonstrate that a high dose of the toxin significantly reduces the weights of pups.     

On Two Auxiliary Variates in Ratio Method of Estimation

A ratio type estimator using two auxiliary variates is suggested which is found to be more practicable than that of AGARWAL'S (1980) estimator.     

Gingival and Periodontal Parameters in a Population of Healthy Adults, 22–90 Years of Age1

There are little data concerning the periodontal status of aging individuals free of systemic disease and medication utilization. In the present study 55 healthy male and female, non-medicated adults between the ages of 22 and 90 were evaluated by comparing gingival and periodontal parameters. The results indicate greater proportions of sites with dental plaque, calculus, gingival bleeding and recession, and attachment loss in the oldest age group. The progression of these changes from young to middle to old age was not uniform. Attachment loss showed the most significant age-related changes. Results from this small, cross-sectional study of healthy individuals are generally comparable to findings reported from the NIDR 1985 National Survey of Oral Health in U.S. Adults.