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Open access

Joanne Pascale, Angela Fertig and Kathleen Call

Abstract

This study randomized a sample of households covered by one large health plan to two different surveys on health insurance coverage and matched person-level survey reports to enrollment records. The goal was to compare accuracy of coverage type and uninsured estimates produced by the health insurance modules from two major federal surveys – the redesigned Current Population Survey Annual Social and Economic Supplement (CPS) and the American Community Survey (ACS) – after implementation of the Affordable Care Act. The sample was stratified by coverage type, including two types of public coverage (Medicaid and a state-sponsored program) and three types of private coverage (employer-sponsored, non-group, and marketplace plans). Consistent with previous studies, accurate reporting of private coverage is higher than public coverage. Generally, misreporting the wrong type of coverage is more likely than incorrectly reporting no coverage; the CPS module overestimated the uninsured by 1.9 and the ACS module by 3.5 percentage points. Other differences in accuracy metrics between the CPS and ACS are relatively small, suggesting that reporting accuracy should not be a factor in decisions about which source of survey data to use. Results consistently indicate that the Medicaid undercount has been substantially reduced with the redesigned CPS.

Open access

Bogna Zawieja, Sylwia Lewandowska, Tomasz Mikulski and Wiesław Pilarczyk

Summary

An analysis is made of results from early stages of testing of promising hybrids. The data consist of single-replicate trials performed by Norddeutsche Pflanzenzucht in 6 locations (5 in Poland and one in Germany). In total 165 hybrids were tested with 3 standard varieties. The subject of the analysis was the seed yield. Three measures of stability were used. The yield of tested hybrids is expressed as percentage of that of standard varieties. Wricke’s ecovalence expressed as a contribution to G x E interaction was used as a measure of stability. Additional characterization of the tested hybrids was performed by regressing hybrid yield on the mean yields of the experiment, as described by Finlay and Wilkinson and by Eberhart and Russel. The methods applied enabled selection of the most promising hybrids for further yield testing.

Open access

Moawia Alghalith

Summary

We develop a simple method that completely eliminates the specification error and spurious relationships in regression. Furthermore, we introduce a stronger test of causality. We apply our method to oil prices.

Open access

Jacek Białek

Abstract

As is known, all geo-logarithmic indices enjoy the axiomatic properties of being proportional, commensurable and homogeneous, together with their cofactors (Martini 1992a). Geologarithmic price indices satisfying the axioms of monotonicity, basis reversibility and factor reversibility have been investigated by Marco Fattore (2010), who has shown that the superlative Fisher price index does not belong to this family of indices. In this article, we discuss geo-logarithmic price indices with reference to the Laspeyres-Paasche bounding test and we propose a modification of the considered index family that satisfies this test. We also modify the structure of geo-logarithmic indices by using an additional parameter and, following the economic approach, we list superlative price index formulas that are members of the considered price index family. We obtain a special subfamily that approximates superlative price indices and includes the Fisher, Walsh and Sato-Vartia price indices.

Open access

James Chipperfield, John Newman, Gwenda Thompson, Yue Ma and Yan-Xia Lin

Abstract

Many statistical agencies face the challenge of maintaining the confidentiality of respondents while providing as much analytical value as possible from their data. Datasets relating to businesses present particular difficulties because they are likely to contain information about large enterprises that dominate industries and may be more easily identified. Agencies therefore tend to take a cautious approach to releasing business data (e.g., trusted access, remote access and synthetic data). The Australian Bureau of Statistics has developed a remote server, called TableBuilder, which has the capability to allow users to specify and request tables created from business microdata. The tables are confidentialised automatically by perturbing cell values, and the results are returned quickly to the users. The perturbation method is designed to protect against attacks, which are attempts to undo the confidentialisation, such as the well-known differencing attack. This paper considers the risk and utility trade-off when releasing three Australian Bureau of Statistics business collections via its TableBuilder product.

Open access

Delwyn G. Cooke, Leonard F. Blackwell and Simon Brown

Summary

It has been suggested that it is possible to monitor the menstrual cycle by measuring the concentration of urinary reproductive steroids. This neglects the variation in void volume and in urine production rate. In neither case has any systematic analysis been reported previously. Overnight urine samples were collected each day for one complete cycle by 24 women and the void volumes and intervoid times were recorded. The void volume and urine production rate were approximately lognormally distributed and the intervoid time was approximately normally distributed. Using these distributions we consider the implications of the variation in void volume and urine production rate for the comparison of the concentrations of a urinary analyte in two samples.

Open access

Iwona Mejza, Katarzyna Ambroży-Deręgowska, Jan Bocianowski, Józef Błażewicz, Marek Liszewski, Kamila Nowosad and Dariusz Zalewski

Summary

The main purpose of this study was the model fitting of data deriving from a three-year experiment with barley malt. Two linear models were considered: a fixed linear model with fixed effects of years and other factors, and a mixed linear model with random effects of years and fixed effects of other factors. Two cultivars of brewing barley, Sebastian and Mauritia, six methods of nitrogen fertilization and four germination times were analyzed. Three quantitative traits were observed: practical extractivity of the malt, malting productivity, and a quality coefficient Q. The starting point for the statistical analyses was the available experimental material, which consisted of barley grain samples destined for malting. The analyses were performed over a series of years with respect to fixed or random effects of years. Due to the strong differentiation of the years of the study and some significant interactions of factors with years, annual analyses were also carried out.

Open access

Dariusz Kayzer

Summary

Results of ecological studies that involve the use of multivariate analysis of variance techniques for testing various hypotheses, interesting from the point of view of comparing the linear functions of parameters, were considered. For testing the most interesting hypotheses on a variety of interaction effects and on contrasts of class means, the application of a multivariate test statistic is recommended. Canonical variate analysis is used for graphical presentation of the results of multidimensional experiments. In this paper it is shown how a generalized form of canonical variate analysis can be useful to reveal which parametric functions of a multivariate analysis of variance model are responsible for rejecting the linear hypothesis. As an example, an analysis was made of an ecological study of trace element accumulation in plants of Italian ryegrass as a method of biomonitoring of air pollution.

Open access

Jennifer Dykema, Dana Garbarski, Ian F. Wall and Dorothy Farrar Edwards

Abstract

While scales measuring subjective constructs historically rely on agree-disagree (AD) questions, recent research demonstrates that construct-specific (CS) questions clarify underlying response dimensions that AD questions leave implicit and CS questions often yield higher measures of data quality. Given acknowledged issues with AD questions and certain established advantages of CS items, the evidence for the superiority of CS questions is more mixed than one might expect. We build on previous investigations by using cognitive interviewing to deepen understanding of AD and CS response processing and potential sources of measurement error. We randomized 64 participants to receive an AD or CS version of a scale measuring trust in medical researchers. We examine several indicators of data quality and cognitive response processing including: reliability, concurrent validity, recency, response latencies, and indicators of response processing difficulties (e.g., uncodable answers). Overall, results indicate reliability is higher for the AD scale, neither scale is more valid, and the CS scale is more susceptible to recency effects for certain questions. Results for response latencies and behavioral indicators provide evidence that the CS questions promote deeper processing. Qualitative analysis reveals five sources of difficulties with response processing that shed light on under-examined reasons why AD and CS questions can produce different results, with CS not always yielding higher measures of data quality than AD.

Open access

Piotr Sulewski

Summary

In the statistical literature there are proposed many test measures to determine the independence of two qualitative variables in contingency tables, in particular in two-way contingency tables larger than 2×2. For statistical analysis, three of the so-called “chi-squared tests”—the T 3 test, BP test and |χ| test—were selected. These tests were compared with a logarithmic minimum test, which is the author’s proposal. Critical values for the tests were determined with the Monte Carlo method. To compare the tests, an appropriate measure of untruthfulness of H 0 was used and the power of the tests was calculated.