Résumé: Les enfants comme répondants dans les enquêtes -Développement cognitiv et qualité des réponses. Quoique les enfants ne sont plus une population négligé des statistiques officièlles et des enquêtes, des études méethodologiques sur des enquêtes d'enfants sont rares. Les chercheirs doivent se baser sur les connaisances ad hoc venant des domaines aussi divers que la psychiatrie enfantine et les test d'éducation, ou extrapoler à partir de la connaisance méthodologique associée aux enquêtes auprès d'adultes. Dans cet article, les auteurs passant en revu la littérature scientifique disponible sur les enfants comme répondants, et présentent les résultats préliminaires d'une analyse secondaire de l'influence du développement cognitif sur la qualité des réponses. Enfin, il y a des recommandations concernants les enquêtes des enfants. Enfants, Développement cognitif, Qualité des données, Questionnaires, Entretiens.Abstract. Although children are no longer a neglected minority in official statistics and surveys, methodological knowledge on how to survey children is still scarce. Researchers have to rely mainly on ad-hoc knowledge from such diverse fields as child psychiatry and educational testing, or extrapolate from methodological knowledge on how to survey adults. In this article we review the available literature on children as respondents, and present the first results of a secondary analysis on the influence of cognitive development on response quality. We finish with recommendations for surveying children. Child, Cognitive growth, Data quality, Questionnaires, Interview.

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There is an ongoing debate in the survey research literature about whether and when probability and nonprobability sample surveys produce accurate estimates of a larger population. Statistical theory provides a justification for confidence in probability sampling as a function of the survey design, whereas inferences based on nonprobability sampling are entirely dependent on models for validity. This article reviews the current debate about probability and nonprobability sample surveys. We describe the conditions under which nonprobability sample surveys may provide accurate results in theory and discuss empirical evidence on which types of samples produce the highest accuracy in practice. From these theoretical and empirical considerations, we derive best-practice recommendations and outline paths for future research.

Surveys increasingly use mixed mode data collection (e.g., combining face-to-face and web) because this controls costs and helps to maintain good response rates. However, a combination of different survey modes in one study, be it cross-sectional or longitudinal, can lead to different kinds of measurement errors. For example, respondents in a face-to-face survey or a web survey may interpret the same question differently, and might give a different answer, just because of the way the question is presented. This effect of survey mode on the question-answer process is called measurement mode effect. This study develops methodological and statistical tools to identify the existence and size of mode effects in a mixed mode survey. In addition, it assesses the size and importance of mode effects in measurement instruments using a specific mixed mode panel survey (Netherlands Kinship Panel Study). Most measurement instruments in the NKPS are multi-item scales, therefore confirmatory factor analysis (CFA) will be used as the main analysis tool, using propensity score methods to correct for selection effects. The results show that the NKPS scales by and large have measurement equivalence, but in most cases only partial measurement equivalence. Controlling for respondent differences on demographic variables, and on scale scores from the previous uni-mode measurement occasion, tends to improve measurement equivalence, but not for all scales. The discussion ends with a review of the implications of our results for analyses employing these scales.

Computer assisted telephone interviewing, and to a lesser degree, computer assisted face-to-face interviewing, are by now widely used in survey research. Recently, self-administered forms of computer-assisted data collection, such as web surveys, have become extremely popular. Advocates of computer assisted interviewing (CAI) claim that its main advantages are improved data quality and lower costs. This paper summarizes what is currently known about computer assisted data collection methods. The emphasis is on data quality and the influence of technology on the respondent.

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