Search

Multimode data collection has emerged as a common approach for conducting household surveys in the United States. A number of different data collection schemes have been investigated, with an emphasis on collecting as many respondents by the Web prior to going to paper data collection to reduce costs. Despite this, little research has been conducted on the approaches to weighting data from multimode surveys. The typical approach assumes that all respondents should be treated the same regardless of mode even though it is well known that the response patterns by mode vary substantially. We examine an adaptive mode adjustment to address these differences and propose an imbalance measure to help determine the adjustment factor using ideas from responsive design. We then compare the effects of the alternative weighting method in two recent sequential mixed-mode surveys and show it appears to reduce bias while only slightly increasing variances of the estimates. [ABSTRACT FROM AUTHOR]

We discuss a model for long memory and persistence in time series that amounts to harmonically weighting short memory processes, ∑jxt−j/(j+1). A non‐standard rate of convergence is required to establish a Gaussian functional central limit theorem. Theoretically, the harmonically weighted (HW) process displays less persistence and weaker memory than the classical competitor, fractional integration (FI) of order d. Still, we establish that a test rejects the null hypothesis of d = 0 if the process is HW. Similarly, a bias approximation shows that estimators of d will fail to distinguish between HW and FI given realistic sample sizes. The difficulties to disentangle HW and FI are illustrated experimentally and with USA inflation data. [ABSTRACT FROM AUTHOR]

Dual-frame telephone surveys that sample from both landline and cell-phone frames have become common because the US population is increasingly abandoning landline phones. Designing a dual-frame telephone survey requires a decision on the sample allocation, and ultimately the allocation of respondents, from each of the two frames. The allocation of the sample to the two frames influences the unequal weighting effect (UWE), and consequently, the precision of estimates calculated from the survey data. The sample allocation also influences cost, since obtaining cell-phone respondents is often more expensive than obtaining landline respondents. In this paper, we present results that designers of dual-frame studies can use to determine an allocation of responders that optimizes the precision of the survey estimates for a given cost. [ABSTRACT FROM AUTHOR]

Given the theoretical promise of these auxiliary data for overcoming the challenge of nonresponse, survey researchers have shown an increased interest in collecting paradata, data from screening interviews, and other contextual information. However, very few studies have systematically assessed the use of these data for post-survey nonresponse adjustments. Those studies that do exist generally do not identify auxiliary variables that correlate with response propensity and key survey variables, a necessary condition for auxiliary data to be effective tools for reducing nonresponse bias. Using the National Survey of Family Growth (NSFG), this paper leverages a large set of auxiliary variables available for the full NSFG sample to assess their potential as independent tools for post-survey nonresponse adjustments. We begin by using this auxiliary information to predict response propensity (RP) for each person in the full sample. We then display descriptive estimates for a variety of attitudes and behaviors measured in the NSFG, using post-stratification weighting adjustments as well as RP adjustments followed by post-stratification. The results show that accounting for RP in the weighting adjustment often produces noteworthy differences in the estimates, thus supporting the collection of these types of auxiliary variables in practice. These results also suggest that standard post-stratification adjustments may not be entirely effective at removing nonresponse bias from all survey estimates, and that some subgroup analyses may be especially subject to bias when adjusting survey estimates using post-stratification alone. [ABSTRACT FROM AUTHOR]

Abstract: The purpose of this study was to examine the average treatment effect of preschool special education services on children''s kindergarten academic skills. Using data from a nationally representative sample of United States children who participated in the Early Childhood Longitudinal Study—Birth Cohort, we examined the effectiveness of preschool special education services by comparing reading and math outcomes for children who received special education services at preschool-age to a propensity-score-weighted sample of children who did not receive these services. Results indicated that the receipt of these special education services had a statistically significant moderate negative effect on children''s kindergarten skills in both reading (d =−0.21) and mathematics (d =−0.29). These findings have implications for the implementation and evaluation of services for young children experiencing developmental delays or disabilities. [Copyright &y& Elsevier]

Abstract: This study estimates trip demand and economic benefits for visitors to recreation sites when past season trip information is elicited from travelers intercepted on-site. We use a weighting function for past season counts that is different from, but nests, the standard on-site correction appropriate for current season counts. We find that for our sample of lake visitors relatively stronger preference or “avidity” for the interview site carries over across seasons. We further show that the appropriate weighting of past trip counts is critical in deriving meaningful estimates of travel demand and economic benefits. [Copyright &y& Elsevier]

This study determined the percentages of individuals who report adverse effects from exposure to fragranced products in the U.S. population and in subpopulations of those with asthma or chemical sensitivity. Data were collected through telephone interviews from two geographically weighted, random samples of the continental U.S. in two surveys during 2002-2003 and 2005-2006 (1,057 and 1,058 cases, respectively). Respondents were asked if they find being next to someone wearing a scented product irritating or appealing; if they have headaches, breathing difficulties, or other problems when exposed to air fresheners or deodorizers; and if they are irritated by the scent from laundry products, fabric softeners, or dryer sheets that are vented outside. Results aggregated from both surveys found that 30.5% of the general population reported scented products on others irritating, 19% reported adverse health effects from air fresheners, and 10.9% reported irritation by scented laundry products vented outside. This study reveals that a considerable percentage of the U.S. population reports adverse health effects or irritation from fragranced products, with higher percentages among those with asthma and chemical sensitivity. [ABSTRACT FROM AUTHOR]

The method of inverse probability weighting (henceforth, weighting) can be used to adjust for measured confounding and selection bias under the four assumptions of consistency, exchangeability, positivity, and no misspecification of the model used to estimate weights. In recent years, several published estimates of the effect of time-varying exposures have been based on weighted estimation of the parameters of marginal structural models because, unlike standard statistical methods, weighting can appropriately adjust for measured time-varying confounders affected by prior exposure. As an example, the authors describe the last three assumptions using the change in viral load due to initiation of antiretroviral therapy among 918 human immunodeficiency virus-infected US men and women followed for a median of 5.8 years between 1996 and 2005. The authors describe possible tradeoffs that an epidemiologist may encounter when attempting to make inferences. For instance, a tradeoff between bias and precision is illustrated as a function of the extent to which confounding is controlled. Weight truncation is presented as an informal and easily implemented method to deal with these tradeoffs. Inverse probability weighting provides a powerful methodological tool that may uncover causal effects of exposures that are otherwise obscured. However, as with all methods, diagnostics and sensitivity analyses are essential for proper use. [ABSTRACT FROM AUTHOR]