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Measurement invariance is necessary before any substantive cross-national comparisons can be made. The statistical workhorse for conducting measurement invariance analyses is the multigroup confirmatory factor analysis model. This model works well if a few items exhibit clearly differential item functioning, but it is not able to capture, model, and control for measurement bias that affects all items, i.e., this model cannot account for common method variance. The presence of common method variance in cross-national data leads to poorly fitting models which in turn often results in biased, if not incorrect, results. We introduce a procedure to analyze and control for common method variance in one's data, based on a series of factor analysis models with a random intercept. The modeling framework yields constructs and factor scores free of method effects. We use marker variables to support the validity of the interpretation of the random intercept as method factor. An empirical application dealing with material values in Spain, the UK, and Brazil is provided. We compare results with those obtained for the standard multigroup confirmatory factor analysis model., Author(s): Jan-Benedict E.M. Steenkamp [sup.1] , Alberto Maydeu-Olivares [sup.2] Author Affiliations: (1) grid.10698.36, 0000000122483208, University of North Carolina at Chapel Hill, , Campus Box 3490, McColl Building, 27599, Chapel Hill, [...]

This paper develops a two-stage statistical analysis to identify and assess the effect of a sample bias associated with an individual's household role. Survey responses to questions about the respondent's role in household finances and a sampling design in which some households have all members take the survey enable the estimation of distributions for each individual's share of household responsibility. The methodology is applied to the 2017 Survey of Consumer Payment Choice. The distribution of responsibility shares among survey respondents suggests that the sampling procedure favors household members with higher levels of responsibility. A bootstrap analysis reveals that population mean estimates of monthly payment instrument use that do not account for this type of sample misrepresentation are likely biased for instruments often used to make household purchases. For checks and electronic payments, analysis suggests it is likely that unadjusted estimates overstate true values by 10 percent to 20 percent. JEL classification: C11, C83, D12 Key words: survey error, Bayesian interference, Survey of Consumer Payment Choice, bootstrap, household economics, Working Paper 2021-9 February 2021 1 Introduction An increasingly important aspect of survey-based inference involves recognizing and adjusting for discrepancies between respondents and the target population. For one, a general [...]

Introduction Many nonpublic well water users are unknowingly consuming water contaminated with industrial solvents, pesticides, or other contaminants at levels that are unsafe. In a study conducted by the U.S. [...], Background: Many nonpublic water well users unknowingly consume contaminated groundwater containing unsafe levels of pollutants. This has important implications for more than 13 million households in the United States that rely upon nonpublic water wells for drinking, cooking, and other household uses. Although public water quality is regulated through the Safe Drinking Water Act, there are no drinking water standards for nonpublic water well quality in Kansas, nor is there an adequate public health infrastructure in place to prevent or address potential exposures to contamination. OBJECTIVES: This project was conducted to identify promising action steps that would protect Kansans relying on nonpublic water wells for drinking, cooking, and other household purposes. METHODS: The project team consisted of public health, environmental health, and legal professionals with experience working on groundwater quality issues impacting nonpublic water wells in Kansas. From 2015 through 2018, the team established and convened an advisory group; reviewed relevant state statutes and regulations, all Kansas county environmental codes, and a representative sample of 23 city water well codes; conducted an extensive review of academic literature to identify best practices; conducted dozens of key informant interviews; proposed recommendations; engaged dozens of stakeholders through a survey of these proposed recommendations; and conducted interactive webinars to identify which organizations need to lead each of the recommendations. Discussion: The project team developed 18 recommendations. The recommendations are organized by survey respondents' perceptions of potential public health impact. There are very few standard practices in Kansas that ensure safe water for nonpublic household water wells. Although not all of the 18 recommendations may be applicable to other communities and states, many likely would be useful for governmental agencies, academic institutions, nonprofit organizations, and others to consider. These recommendations offer more protections for nonpublic household water well users than any resource we have found.