Power analysis for clustered non-continuous responses in multicenter trials

Power analysis for multi-center randomized control trials is quite difficult to perform for non-continuous responses when site differences are modeled by random effects using the generalized linear mixed-effects model (GLMM). First, it is not possible to construct power functions analytically, because of the extreme complexity of the sampling distribution of parameter estimates. Second, Monte Carlo (MC) simulation, a popular option for estimating power for complex models, does not work within the current context because of a lack of methods and software packages that would provide reliable estimates for fitting such GLMMs. For example, even statistical packages from software giants like SAS do not provide reliable estimates at the time of writing. Another major limitation of MC simulation is the lengthy running time, especially for complex models such as GLMM, especially when estimating power for multiple scenarios of interest. We present a new approach to address such limitations. The proposed approach defines a marginal model to approximate the GLMM and estimates power without relying on MC simulation. The approach is illustrated with both real and simulated data, with the simulation study demonstrating good performance of the method.     

Investigating impacts of complex sampling on latent growth curve modelling

We investigate the impacts of complex sampling on point and standard error estimates in latent growth curve modelling of survey data. Methodological issues are illustrated with empirical evidence from the analysis of longitudinal data on life satisfaction trajectories using data from the British Household Panel Survey, a national representative survey in Great Britain. A multi-process second-order latent growth curve model with conditional linear growth is used to study variation in the two perceived life satisfaction latent factors considered. The benefits of accounting for the complex survey design are considered, including obtaining unbiased both point and standard error estimates, and therefore correctly specified confidence intervals and statistical tests. We conclude that, even for the rather elaborated longitudinal data models that were considered, estimation procedures are affected by variance-inflating impacts of complex sampling.     

Methods to assess measurement error in questionnaires of sedentary behavior

Sedentary behavior has already been associated with mortality, cardiovascular disease, and cancer. Questionnaires are an affordable tool for measuring sedentary behavior in large epidemiological studies. Here, we introduce and evaluate two statistical methods for quantifying measurement error in questionnaires. Accurate estimates are needed for assessing questionnaire quality. The two methods would be applied to validation studies that measure a sedentary behavior by both questionnaire and accelerometer on multiple days. The first method fits a reduced model by assuming the accelerometer is without error, while the second method fits a more complete model that allows both measures to have error. Because accelerometers tend to be highly accurate, we show that ignoring the accelerometer's measurement error, can result in more accurate estimates of measurement error in some scenarios. In this article, we derive asymptotic approximations for the mean-squared error of the estimated parameters from both methods, evaluate their dependence on study design and behavior characteristics, and offer an R package so investigators can make an informed choice between the two methods. We demonstrate the difference between the two methods in a recent validation study comparing previous day recalls to an accelerometer-based ActivPal.     

Some maximum-indifference estimators for the slope of a univariate linear model

As known, the least-squares estimator of the slope of a univariate linear model sets to zero the covariance between the regression residuals and the values of the explanatory variable. To prevent the estimation process from being influenced by outliers, which can be theoretically modelled by a heavy-tailed distribution for the error term, one can substitute covariance with some robust measures of association, for example Kendall's tau in the popular Theil–Sen estimator. In a scarcely known Italian paper, Cifarelli [(1978), ‘La Stima del Coefficiente di Regressione Mediante l'Indice di Cograduazione di Gini’, Rivista di matematica per le scienze economiche e sociali, 1, 7–38. A translation into English is available at http://arxiv.org/abs/1411.4809 and will appear in Decisions in Economics and Finance] shows that a gain of efficiency can be obtained by using Gini's cograduation index instead of Kendall's tau. This paper introduces a new estimator, derived from another association measure recently proposed. Such a measure is strongly related to Gini's cograduation index, as they are both built to vanish in the general framework of indifference. The newly proposed estimator is shown to be unbiased and asymptotically normally distributed. Moreover, all considered estimators are compared via their asymptotic relative efficiency and a small simulation study. Finally, some indications about the performance of the considered estimators in the presence of contaminated normal data are provided.     

“It has given me life.” Latinas and the U-Visa: A Qualitative Study

Women, particularly undocumented women, are at an increased risk for gender-based violence including intimate partner violence (IPV). Women’s lack of legal immigration status is often used as a tool of dominance and control of undocumented women. The Victim of Trafficking and Violence Prevention Act 2000 created the U-Visa that provides undocumented IPV victims with lawful immigration status if they are willing to assist authorities in investigating crimes. The objective of this study is to better understand the benefits of obtaining the U-Visa from the perspectives of Latina U-Visa recipients who are survivors of IPV. In this community-based qualitative research study involving IPV survivors, community leaders, service providers and academics, we collected qualitative data through interviews with 20 participants including 15 survivors of IPV who were U-Visa recipients. Interviews were digitally-recorded, transcribed and translated, and analyzed using a qualitative software to develop key themes. Women received a $20 gift card as a token of appreciation for their participation in this study. Findings highlight key benefits such as improved mental health, renewed confidence and self-esteem, self-confidence, less perceived exploitation, access to better jobs and housing, freedom to travel, and improved economic and social well-being for visa recipients and their families. Obtaining the U-Visa was a transformative and life-changing experience for Latina survivors of IPV. Social policies such as TVPA help support vulnerable women who are victims of IPV.     

Cell Phone Survey Feasibility in The U.S.: Sampling and Calling Cell Numbers Versus Landline Numbers

In 2004, we conducted a nationwide dual frame survey of landlineand cell phone numbers to evaluate the feasibility of includingcell phone numbers in a random digit dial telephone survey.Households with both landline and cell phones were eligiblefor selection in both samples. This article describes our designand data collection methods; compares the results from the twosamples (with an emphasis on operational characteristics); andpresents the outcomes of two experimental manipulations designedto improve the cell phone response rate.     

Sampling Telephone Numbers and Adults, Interview Length, and Weighting in The California Health Interview Survey Cell Phone Pilot Study

This article describes several features included in a CaliforniaHealth Interview Survey cell phone pilot study that differ fromearlier cell phone surveys conducted in the United States. Onedifference is that the study used a screening design and onlyadults living in cell-only households were interviewed. Mostof the previous studies used dual frame designs. Another differencewas the development and implementation of a within-householdadult sampling procedure to cover adults when cell phones wereshared in the household. The study was also intended to determineif conducting a cell phone interview of the same scope and lengthas a regular telephone interview was feasible. Most previoussurveys were focused on cell phone topics and were shorter thanthe comparable landline surveys. We then explore some interestingproblems that arise in weighting a cell phone survey using ascreening design. We conclude with a discussion of planninga new cell phone survey in 2007 that incorporates findings fromthis study.     

Domestic violence screening and service acceptance among adult victims in a dependency court setting

Many child welfare systems are unable to effectively identify and address co-occurring domestic violence and child maltreatment. In response, the Dependency Court Intervention Program for Family Violence implemented a protocol to identify indicators of domestic violence in families involved with child protection proceedings. This article highlights data that demonstrate the ability of an outreach and screening process to identify adult victims of domestic violence in dependency court and to offer them appropriate intervention services.     

Protective and risk influences of drug use among a multiethnic sample of adolescent boys

A measurement model was analyzed to demonstrate a differential distribution and cumulative exposure to psychosocial risk and protective influences of adolescent drug use among ethnically-diverse adolescent samples. The sample included U.S.-born (US) Latino (N = 837), foreign-born (FB) Latino (N = 447), White (N = 632), and African American (N = 618) adolescent boys. Psychological Distress, Peer Drug Use, and Adolescent Drug Use were significantly positively correlated with Peer Drug Use and Adolescent Drug Use. In contrast, Family, School, law abidance, and guilt were significantly negatively correlated with Peer Drug Use and Adolescent Drug Use. Multiple group analyses indicated significant similarities and differences among US and FB Latinos, and Whites. Implications for early prevention, multi-level interventions, and suggestions for future research are discussed.