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Declining response rates worldwide have stimulated interest in understanding what may be influencing this decline and how it varies across countries and survey populations. In this paper, we describe the development and validation of a short 9-item survey attitude scale that measures three important constructs, thought by many scholars to be related to decisions to participate in surveys, that is, survey enjoyment, survey value, and survey burden. The survey attitude scale is based on a literature review of earlier work by multiple authors. Our overarching goal with this study is to develop and validate a concise and effective measure of how individuals feel about responding to surveys that can be implemented in surveys and panels to understand the willingness to participate in surveys and improve survey effectiveness. The research questions relate to factor structure, measurement equivalence, reliability, and predictive validity of the survey attitude scale. The data came from three probability-based panels: the German GESIS and PPSM panels and the Dutch LISS panel. The survey attitude scale proved to have a replicable three-dimensional factor structure (survey enjoyment, survey value, and survey burden). Partial scalar measurement equivalence was established across three panels that employed two languages (German and Dutch) and three measurement modes (web, telephone, and paper mail). For all three dimensions of the survey attitude scale, the reliability of the corresponding subscales (enjoyment, value, and burden) was satisfactory. Furthermore, the scales correlated with survey response in the expected directions, indicating predictive validity., ZIS - The Collection of Items and Scales for the Social Sciences

Declining response rates worldwide have stimulated interest in understanding what may be influencing this decline and how it varies across countries and survey populations. In this paper, we describe the development and validation of a short 9-item survey attitude scale that measures three important constructs, thought by many scholars to be related to decisions to participate in surveys, that is, survey enjoyment, survey value, and survey burden. The survey attitude scale is based on a literature review of earlier work by multiple authors. Our overarching goal with this study is to develop and validate a concise and effective measure of how individuals feel about responding to surveys that can be implemented in surveys and panels to understand the willingness to participate in surveys and improve survey effectiveness. The research questions relate to factor structure, measurement equivalence, reliability, and predictive validity of the survey attitude scale.The data came from three probability-based panels: the German GESIS and PPSM panels and the Dutch LISS panel. The survey attitude scale proved to have a replicable three-dimensional factor structure (survey enjoyment, survey value, and survey burden). Partial scalar measurement equivalence was established across three panels that employed two languages (German and Dutch) and three measurement modes (web, telephone, and paper mail). For all three dimensions of the survey attitude scale, the reliability of the corresponding subscales (enjoyment, value, and burden) was satisfactory. Furthermore, the scales correlated with survey response in the expected directions, indicating predictive validity.

With the decrease of landline phones in the last decade, telephone survey methodologists face a new challenge to overcome coverage bias. In this study we investigate coverage error for telephone surveys in Europe over time and compare two situations: classical surveys that rely on landline only with surveys that also include mobile phones. We analyzed Eurobarometer data, which are collected by means of face-to-face interviews and contain information on ownership of landline and mobile phones. We show that for the period 2000-2009, time has a significant effect on both mobile phone penetration and coverage bias. In addition, the countries’ development significantly affects the pace of these changes.

In experimental research, it is not uncommon to assign clusters to conditions.When analysing the data of such cluster-randomized trials, a multilevel analysis should be applied in order to take into account the dependency of firstlevel units (i.e., subjects) within a second-level unit (i.e., a cluster). Moreover, the multilevel analysis can handle covariates on both levels. If a first-level covariate is involved, usually the within-cluster effect of this covariate will be estimated, implicitly assuming the contextual effect to be equal. However, this assumption may be violated. The focus of the present simulation study is the effects of ignoring the inequality of the within-cluster and contextual covariate effects on parameter and standard error estimates of the treatment effect, which is the parameter of main interest in experimental research. We found that ignoring the inequality of the within-cluster and contextual effects does not affect the estimation of the treatment effect or its standard errors. However, estimates of the variance components, as well as standard errors of the constant, were found to be biased.

Objective: This study investigates the clustering of a broad range of health-compromising and delinquent behaviors. We examine whether these behaviors belong to a single but broad cluster, 'risk-taking behavior', and whether the nature and degree of clustering in adolescents differs from that in adults. Method: A representative sample (N = 4395) of the Dutch population aged 12 to 40 (overall response rate 67%), was asked about various health-compromising behaviors, such as alcohol consumption, smoking, illegal drug use, unsafe sexual behavior, physical inactivity, poor nutrition (such as skipping breakfast and not eating fruit and vegetables), poor sleep behavior, unlawful traffic behavior, and delinquent and aggressive behavior. Data were collected from fall 2005 to spring 2006 using internet questionnaires and face-to-face computer-assisted interviews. Results: No single broad cluster was found. Instead, there were several separate but interrelated clusters. The contents of these clusters differed between age groups. For young adolescents (12-15) two clusters were identified: Alcohol and Delinquency. For older adolescents (16-18) and adults (19-40) three clusters were identified: Alcohol, Delinquency and Health. Conclusion: The findings of this study support a more integrated approach to promoting healthier lifestyles, and suggest that the behavior targets of integrated prevention programs should be different for adolescents and adults. © 2009 Elsevier Inc. All rights reserved.

The construct representation of the cross-informant model of the Child Behavior Checklist (CBCL) and the Teacher Report Form (TRF) was evaluated using confirmatory factor analysis. Samples were collected in seven different countries. The results are based on 13,226 parent ratings and 8893 teacher ratings. The adequacy of fit for the cross-informant model was established on the basis of three approaches: conventional rules of fit, simulation, and comparison with other models. The results indicated that the cross-informant model fits these data poorly. These results were consistent across countries, informants, and both clinical and population samples. Since inadequate empirical support for the cross-informant syndromes and their differentiation was found, the construct validity of these syndrome dimensions is questioned.

What are the conditions that will allow for appropriate comparisons among groups" Should the concept of comparative validity be added to the lexicon of the psychometrician"