The effects of measurement error in cross cultural research

"In survey research many decisions are made in order to design an instrument for data collection. These choices have to do with the formulation of the question, the response categories, the instruction, the sample, the mode of data collection, etc. Each of these choices can lead to different errors (Sudman and Bradburn, 1974; Belson, 1981; Schuman and Presser, 1981; Dijkstra and Van der Zouwen, 1982; Andrews, 1984; Molenaar, 1986; Billiet et al., 1986; Groves, 1989; Alwin and Krosnick, 1991, and Scherpenzeel and Saris, 1997) and consequently to incomparability of results with respect to estimates of correlations and effect parameters across studies and also across countries. It is common knowledge that cross-cultural comparison can only be made if the measurement procedures are completely the same. In this study, we want to argue that this requirement is not enough. We will show that the results can also differ if the same procedures have been used because of differences in measurement errors in the different countries. We therefore propose a procedure to correct for measurement error, in order to make comparisons across countries with respect to correlations and regression coefficients. To correct for measurement error, we have chosen an approach that can be used by every researcher involved in social science research. This in particular is why we advocate this approach, even though, from a methodological point of view, more suitable approaches are available. We avoid using these methods because one purpose of this project is that we want to demonstrate a procedure for the correction of measurement error which can be used in any study, once prior methodological research is done. We begin with a discussion of the problems connected with measurement error in comparative survey research and then we describe the solution we have chosen for these problems. All examples given are based on the satisfaction studies done in the context of a methodological, comparative research project involving 13 language areas." (author's abstract

A decision theoretical analysis of decisions of the Dutch government in exile during World War II

Das Papier beschreibt eine entscheidungstheoretische Analyse von Entscheidungen der niederländischen Exilregierung in London in den Jahren 1940 und 1941 in bezug auf die Verlegung des Regierungssitzes nach Holländisch-Ostindien. Zusammen mit einem von den Autoren entwickelten textanalytischen Verfahren, führt der entscheidungstheoretische Ansatz zu sehr nützlichen Einsichten in die entsprechenden Dokumente: Der Entscheidungsprozeß und das Muster der Einflußnahme verschiedener Regierungsberater konnten entdeckt werden. Die Entscheidungsgrundlagen, die die Wahl der verschiedenen Alternativen begründeten, konnten vollständig vorausgesagt werden, wobei dies auf der Qualität der Wert- und Wahrscheinlichkeitsaussagen basierte. (KW)'This paper describes a decision theoretical analysis of decisions of the Dutch government in exile in London in 1940/41 with respect to the transference of the seat of the government to the Dutch East-Indies. Combined with a text-analysis procedure developed by the authors, the decision theoretical approach to the related documents produced very useful insights: the decision process and the influence-pattern of the different governmental advisers could be detected and the decision rules which explain the choices could be perfectly predicted, based on the quality of the value- and probability statements.' (author's abstract

Moderating Effects of Management Control Systems and Innovation on Performance. Simple Methods for Correcting the Effects of Measurement Error for Interaction Effects in Small Samples

In the accounting literature, interaction or moderating effects are usually assessed by means of OLS regression and summated rating scales are constructed to reduce measurement error bias. Structural equation models and two-stage least squares regression could be used to completely eliminate this bias, but large samples are needed. Partial Least Squares are appropriate for small samples but do not correct measurement error bias. In this article, disattenuated regression is discussed as a small sample alternative and is illustrated on data of Bisbe and Otley (in press) that examine the interaction effect of innovation and style of use of budgets on performance. Sizeable differences emerge between OLS and disattenuated regression.measurement error; interaction effects; disattenuation; small samples; moderated regression; reliability; Chronbach’s alpha