ALLBUS-Bibliographie 25. Fassung, Stand - SSOAR

758 ALLBUS-Bibliographie (25. Fassung)
response on these open-ended questions has to be considered before substantive analyses
can start. About 20% of the respondents answered 'Don't know' or did not answer.
Such a considerable amount of non-response might have effects on data quality
and, hence, on the interpretation of the data. We assume that those non-respondents
would have problems with the self-placement on the left-right scale. We further assume
that demographic and indicators on political interest, participation, and knowledge
influence the non-response behavior. We will present the basic results of our
investigation of item non-response on the questions about associations with left/right
and discuss quality problems related to the validity of the left-right scale itself.".
Aufgenommen: 25. Fassung, März 2011
Schorlemmer, Georg Freiherr von, (1996). Die netzwerkbezogene Kettenmigration
unter besonderer Berücksichtigung der migrationsfunktionalen Aspekte von Unterstützungsleistungen
in sozialen Netzwerken. Dissertation: Freie Universität Berlin.
Abstract: (dkr) Es liegt kein Belegexemplar vor
Aufgenommen: 15. Fassung, Oktober 1998
Schott, Ute, (1994). Berufliche Selbstständigkeit. Eine Alternative für Frauen zur
abhängigen Erwerbstätigkeit. Magisterarbeit: Universität Heidelberg.
Abstract: ALLBUS 1980 - 1988
Schraepler, Joerg-Peter und Wagner, Gert G., (2003). Identification, Characteristics
and Impact of Faked Interviews in Surveys - An analysis by means of genuine fakes
in the raw data of SOEP. DIW-Berlin: Berlin.
Abstract: "To the best of our knowledge, most of the few methodological studies
which analyze the impact of faked interviews on survey results are based on "artificial
fakes" generated by project students in a "laboratory environment". In contrast,
panel data provide a unique opportunity to identify data which are actually faked by
interviewers. By comparing data of two waves, unequivocal fakes are easily identifiable.
However, in most surveys there is no second wave because they have a pure
cross-sectional nature. In search of a method which does not need two waves of data
we test an unconventional benchmark called Benford's Law, which is used by several
accountants to discover frauds. Our preliminary results let us conclude that Benford´s
Law might be not an efficient method for detecting faked data, but it might be a new
instrument for quality control of the interviewing process. The raw data of the Ger-