Methoden

methoden@mailman.uni-konstanz.de

5 participants
1902 discussions

CfP ESRA 2017 - Deviations and Fraud in Surveys - the Impact of Motivation and Incentives
by Katrin Auspurg 17 Nov '16

17 Nov '16

We invite submissions to a session of the ESRA 2017 conference: *** Deviations and Fraud in Surveys - the Impact of Motivation and Incentives *** See below for more information on the session. The conference will take place in Lisbon, Portugal, July 17-21, 2017. For more information or to submit a paper, see: http://www.europeansurveyresearch.org/conference Please submit by December 4, 2016. Thank you very much for your attention, Katrin Auspurg, Thomas Hinz, Natalja Menold and Peter Winker (Organizers) *** Deviations and Fraud in Surveys – the Impact of Motivation and Incentives *** Keywords: Data Manipulation, Data Quality, Survey Errors, Motivation, Interviewer Effects Abstract: Credibility of social science was repeatedly jeopardized by recent and spectacular cases of deviant behavior in conducting surveys or fraud in presenting survey based research results. Several times researchers published path-breaking results that turned out to be 'too good to be true.' Because the incentive system in science commonly rewards originality higher than accurateness, most probably, the detected cases of making up data or trimming results are only the tip of the iceberg. What makes the situation in survey research even more complex is the fact that several actors are involved who have manifold incentives to manipulate data. These include the researchers, survey institutes, survey supervisors, interviewers and respondents. Contributions to the session will discuss the motivation, prevalence and implications of misbehavior of actors in survey research. Of interest are theoretical approaches and empirical studies on the motivation, detection and prevention of data manipulations. Strategies to detect fraud deserve specific attention, but we also welcome empirical work on causal mechanisms: Which conditions most likely trigger fraud? Which interventions could accordingly work? Some examples along the survey process highlight possible topics for the session: (1) Respondents often share an interest with the interviewers to save time by taking inaccurate short cuts in the questionnaires. Additionally, they are prone to provide false answers, for instance, if questions are sensitive. Both kinds of behavior yield inaccurate measurements. (2) Interviewers often may have a high discretion on many decisions in the process of conducting a survey (e.g. when selecting households in a random walk sample, by shortening the interview time through steering the respondents to filter options in questionnaires, or making up interviews (partly) from the scratch). The motivation for deviant behavior can be influenced by factors such as task difficulty, interviewers' ability, and experience, but also by the quality of questionnaires and instructions and other administrative characteristics of the survey. (3) Survey institutes often operate commercially under high cost and time pressure. In order to fulfill their contractual obligations to their clients they might have incentives to change, for instance, complex screening procedures without documenting, to manipulate statistics on non-response or even produce (near) duplicates to satisfy quota. (4) Finally, researchers in survey research can engage in questionable practices as well when they select cases and statistical models just in purpose to get most sensational results.

1 0

Stellenausschreibung: Professur für Quantitative Lebensverlaufssoziologie; DZHW
by Tobias Wolbring 16 Nov '16

16 Nov '16

Liebe Kolleginnen und Kollegen, anbei eine Stellenausschreibung für eine Professur für quantitative Lebensverlaufssoziologie am DZHW in Hannover. Beste Grüße Tobias Wolbring -- Prof. Dr. Tobias Wolbring Assistant Professor of Sociology with a specialization in Longitudinal Data Analysis Department of Sociology University of Mannheim A5, 6 D-68131 Mannheim Office: +49 621 181 1974 wolbring(a)uni-mannheim.de http://wolbring.uni-mannheim.de/

1 0

Stellenausschreibung infas Bonn - StatistikerIn
by Prof. Dr. Stefanie Eifler 16 Nov '16

16 Nov '16

Liebe Kollegen und Kolleginnen, anbei erhalten Sie eine Stellenausschreibung des infas Instituts in Bonn für eine/n Mitarbeiter/in im Bereich Statistik, die für Sie von Interesse sein könnte. Mit besten Grüßen, Stefanie Eifler

1 0

PostDoc Stelle TU Berlin
by Isabell Stamm 15 Nov '16

15 Nov '16

Liebe Kolleginnen und Kollegen, untenstehend eine Stellenausschreibung für eine PostDoc Stelle (4,5 Jahre) am Institut für Soziologie an der TU Berlin mit der Bitte um Weiterleitung an potentielle Kandidaten/Kandidatinnen. Herzlichen Dank. Isabell Stamm ************ Bei der Technischen Universität Berlin, Fakultät VI - Institut für Soziologie/ FG Organisationssoziologie ist folgende Stelle zu besetzen: Wiss. Mitarbeiter/in - PostDoc - Entgeltgruppe 13 TV-L Berliner Hochschulen unter dem Vorbehalt der Mittelbewilligung - Teilzeitbeschäftigung ist ggf. möglich Kennziffer: VI-580/16 (besetzbar ab 01.03.2017 / befristet bis 31.08.2021 / Bewerbungsfristende 02.12.2016) Am Institut für Soziologie beginnt die Forschungsgruppe Entrepreneurial Group Dynamics, die im Freigeist-Programm der VolkswagenStiftung gefördert wird (www.entrepreneurialgroups.org). Ein Teilprojekt baut mittels Crowdsourcing einen Mehrebenen-Datensatz auf, der es erlaubt, die sich veränderten Konstellationen von unternehmerischen Gruppen über einen langen Zeitraum hinweg zu verfolgen. Für die Leitung dieses Teilprojektes suchen wir eine/n motivierte/n und engagierte/n Mitarbeiter/in. Aufgabenbeschreibung: Die idealen Bewerber streben mit Leidenschaft und ausgezeichneten Fähigkeiten danach, die Methoden und methodologischen Implikationen der Organisations- und Wirtschaftssoziologie weiter zu entwickeln. Sie interessieren sich insbesondere dafür die Anwendung von Crowdsourcing als Forschungsmethode. Der/die Bewerber/in soll mittels Crowdsourcing einen quantitativen Datensatz zur Erfassung von Dynamiken in unternehmerischen Gruppen entwickeln. Dies beinhaltet die Auswahl und das Testen geeigneter Datenquellen, die im Zuge einer Dokumentenanalyse nutzbar gemacht werden können (z.B. Zeitungsartikel, Branchenbücher, Unternehmensregistereinträge, Websites); das Erstellen eines Handbuches, das die Schritte der Datenerfassung im Rahmen des Crowdsourcing dokumentiert; Koordination der Entwicklung einer Crowdsourcing-Plattform mit externen Partnern; sowie Ausschreibung und Leitung der Datenerfassung mittels Crowdsourcing; Validieren der entstehenden Datenbank und selbständige Auswertung der Daten mittels fortgeschrittenen quantitativen Methoden. Der/die Bewerber/in wird den Forschungsprozess und die erzielten Ergebnisse durch wissenschaftliche Präsentations- und Publikationstätigkeit sowie Öffentlichkeitsarbeit kommunizieren. Wir bieten: Individueller Personalentwicklungsplan, der Karriereziele innerhalb und außerhalb der Wissenschaft unter-stützt. Möglichkeit zu eigenständigen wissenschaftlichen Publikationen und eventuell zur Habilitation. Möglichkeit an einem mehrwöchigen Austausch mit der DUKE University teilzunehmen. Erwartete Qualifikationen: Erfolgreich abgeschlossenes wissenschaftliches Hochschulstudium (Diplom, Master oder Äquivalent) und abgeschlossene Promotion in den Sozialwissenschaften oder einer angrenzenden Disziplin mit einem Schwerpunkt in Methoden der empirischen Sozialforschung. Sie können sehr gute Fähigkeiten in der Erhebung, Aufbereitung und Auswertung standardisierter Daten nachweisen, insbesondere prozessproduzierter Daten (z.B. öffentliche Registerdaten, Unternehmensdaten) und in digitalen Methoden. Sie haben Erfahrung in dem Aufbau und im Umgang mit Mehr-Ebenen-Datensätzen und Paneldatensätzen und verfügen über sehr gute Kenntnisse in multivariater Statistik (z.B. Mehrebenenanalyse, Sequenzanalyse und Netzwerkanalysen). Sie arbeiten wissenschaftlich selbständig, sind versiert in statistischen Analyseprogrammen (z.B. STATA, R, SPSS), idealerweise haben Sie Kennnisse in CMS. Sehr gute Kenntnisse in Englisch und Deutsch sind wünschenswert. Wir suchen einen Teamplayer mit Bereitschaft zu kollegialem Austausch. Ihre Bewerbung richten Sie unter Angabe der Kennziffer mit den üblichen Unterlagen (insb. Motivationsschreiben, Lebenslauf inklusive Literaturliste, Forschungsprofil, Zeugnisse) bitte vorzugsweise per E-Mail (in einem PDF-Dokument) an silke.kirchhof(a)tu-berlin.de an die Technische Universität Berlin - Der Präsident - Fakultät VI, Institut für Soziologie, Frau Dr. Stamm, Sekr. FH 9-1, Frauenhofer Str. 33-36, 10578 Berlin. __________________________ Dr. Isabell Stamm Technical University Berlin Department for Sociology Research Group Leader Entrepreneurial Group Dynamics Frauenhofer Str. 33-36 10587 Berlin Tel. +49 30 314 75679 http://www.soz.tu-berlin.de/menue/institut_fuer_soziologie/parameter/en/ http://www.isabellstamm.de <http://www.isabellstamm.de/>

1 0

Fw: [aimsl] Call - "BMS" Editor / Rédacteur en chef
by Peter Ohly 10 Nov '16

10 Nov '16

> Gesendet: Donnerstag, 10. November 2016 um 11:43 Uhr > Von: "VAN METER Karl" <karl.vanmeter(a)ens.fr> > An: bms-rc33(a)services.cnrs.fr, jourdan(a)ens.fr, aimsl(a)services.cnrs.fr > Betreff: [aimsl] Call - "BMS" Editor / Rédacteur en chef > > > > Call - "BMS" Editor / Rédacteur en chef > > The "Bulletin de Méthodoligie Sociologique / Bulletin of Sociological > Methodology" or "BMS", a bilingual English-French quarterly scientific > journal, published jointly by the AIMS (Association Internationale de > Méthodologie Sociologique) and Sage Publications in London, is looking > for a new Editor to begin working within six months. This is a > non-salaried position and although the capacity to work in both English > and French is desirable, it is not a requirement. Interested candidates > should carefully look over the "BMS" Web site at Sage > (http://bms.sagepub.com/) before applying by sending us an email and a > curriculum vita at bms-aims(a)orange.fr. > > ----- > > Le "Bulletin de Méthodologie Sociologique / Bulletin of Sociological > Methodology" ou "BMS", une revue scientifique trimestrielle bilingue > anglais-français, publiée conjointement par l'AIMS (Association > Internationale de Méthodologie Sociologique) et Sage Publications à > Londres, est à la recherche d'un nouveau rédacteur en chef pour > commencer à travailler dans les six mois. Ceci est une position > non-salariée et bien que la capacité à travailler en anglais et en > français soit souhaitable, ce n'est pas une exigence. Les candidats > potentiels doivent regarder attentivement le site Web du "BMS" à Sage > (http://bms.sagepub.com/) avant de proposer leur candidature en nous > envoyant un courriel avec un curriculum vitae à bms-aims(a)orange.fr. > > >> Consider submitting your methodologically interesting articles to the > >> BMS << > > ******************************************************************************* > * > * Karl M. van Meter BMS, Bulletin de Methodologie > Sociologique > * karl.vanmeter(a)ens.fr (Bulletin of Sociological Methodology) > * tel 33 (0)1 43 25 26 57 Web http://bms.sagepub.com > * Blog http://karlvanmeter.wordpress.com/ > * Ecole normale supérieure distribution list > bms-rc33(a)services.cnrs.fr > * 48 boulevard Jourdan free distribution list > aimsl(a)services.cnrs.fr > * 75014 Paris, France > * RC33, Research Committee Logic & > * BMS-AIMS Methodology of the International > * 45 rue Linné Sociological Association (ISA) > * 75005 Paris, France http://www.rc33.org/ > * > * http://ens.academia.edu/KarlMvanMeter > ******************************************************************************* > >

1 0

ESRA 2017 CfP: Quantitative Spatial Analysis of Micro and Macro Data
by Henning Best 09 Nov '16

09 Nov '16

*** Apologies for cross-posting *** Dear all, The 7th Conference of the European Survey Research Association (ESRA) will take place from July 17 to 21 2017 in Lisbon, Portugal. We invite paper proposals for our session "Quantitative Spatial Analysis of Micro and Macro Data: Methodological Challenges and Solutions". The session intends to bring together methodological experiences made when working with spatial data in quantitative empirical social research. On the one hand, spatial data offers the opportunity to investigate the relationship between regional characteristics on the macro level. On the other hand, spatial data can be used to enrich survey data with structural information on a certain regional level, either to control for context effects or to explicitly analyse these effects and their interplay with mechanisms on the individual level. By using GIS, addresses of survey participants can be linked with objective measures of their neighbourhood (e.g. pollution data) or proximity to institutions (e.g. of educational institutions or workplaces). Thus, these data allow investigating the relevance of infrastructure distances for social action as well as processes of spatial spillovers and diffusion. In doing so, several methodological questions arise: What kind of regional level is adequate to what kind of question (MAUP)? And how can we handle social action at boarders of administrative units? To derive closer estimates of real individual distances and potential spaces of action a possible solution could be to weight the importance of neighbouring regions by information on actual traveling times with different means of transport. What are the challenges and limitations of these approaches and how can it be done reliably? Furthermore, innovative statistical methods are necessary to adequately analyse spatial data. Various regression models (e.g. SAR, SARAR, SLX, Durbin and others) address the spatial dependence in different ways and offer alternative approaches to identify different types of spatial spillovers or spatial interdependences, in cross-sectional and longitudinal data. Which types of models are adequate for which type of questions? Which models can be used to simultaneously analyse individual and aggregate data? In sum, in this session we are especially interested in methodological and applied studies dealing with topics of: 1. Choice of adequate regional level and handling of borders when using administrative data 2. Connection of individual data and spatially aggregate as well as infrastructural data 3. Spatial analysis of time-series and cross-sectional data 4. Modelling spatial relationships (e.g. commuting flows, distances, traveling times, social interactions) 5. Modelling spatial interaction, spillover or diffusion processes 6. Further challenges and solutions when using georeferenced data Henning Best (TU Kaiserslautern) Corinna Kleinert (Leibniz Institute for Educational Trajectories) Tobias Ruettenauer (TU Kaiserslautern) Michaela Sixt (Leibniz Institute for Educational Trajectories)

1 0

Frühjahrstagung "Familie und Gesundheit" (20.-21.02.2017)
by O. Arránz Becker 08 Nov '16

08 Nov '16

Liebe Kolleginnen und Kollegen, anbei sende ich Ihnen einen Call für die gemeinsame Frühjahrstagung der DGS-Sektionen Familiensoziologie und Medizin- und Gesundheitssoziologie zum Thema "Familie und Gesundheit", die am 20./21. Februar 2017 stattfindet (Einsendefrist: 30.11.2016) mit der Bitte um Verbreitung und Weiterleitung an interessierte Personen. -- Beste Grüße Oliver Arránz Becker _________________________________________ Prof. Dr. O. Arránz Becker Professor of Quantitative Methods in the Social Sciences Martin-Luther University Halle-Wittenberg Institute of Sociology D-06099 Halle (Saale) Germany Visitor address: Geistes- und Sozialwissenschaftliches Zentrum (Steintor-Campus) Emil-Abderhalden-Straße 26-27 (Raum E.54.0) phone: +49 - (0)345 - 55 24260 fax: +49 - (0)345 - 55 27150 e-mail: oliver.arranz-becker(a)soziologie.uni-halle.de

1 0

Frühjahrstagung 2017 der DGS Sektion Methoden der empirischen Sozialforschung
by Prof. Dr. Stefanie Eifler 08 Nov '16

08 Nov '16

Liebe Kollegen und Kolleginnen, anbei erhalten Sie den CfP für die kommende Frühjahrstagung der DGS-Sektion Methoden der empirischen Sozialforschung, zu der ich hiermit herzlich einlade. Die Tagung wird sich dem Thema "Measurement Error" widmen und wird am 28. und 29. April 2017 an der Universität Mannheim stattfinden. Die lokale Organisation übernehmen Natalja Menold, Silke Schneider, Beatrice Rammstedt und Cornelia Zuell. Wir freuen uns auf Ihre Vortragsangebote! Vielen Dank und mit besten Grüßen, Stefanie Eifler

1 0

ESRA 2017 Call for Papers: Researching Sensitive Topics: Improving Theory and Survey
by Trappmann Mark 07 Nov '16

07 Nov '16

Liebe Kolleginnen und Kollegen, anbei ein weiterer Call for Papers für eine Session bei der ESRA im kommenden Juli (17.-21.7.) in Lissabon. Wir freuen uns auf Ihre Einreichungen. Mit freundlichen Grüßen Ivar Krumpal, Ben Jann, Mark Trappmann, Researching Sensitive Topics: Improving Theory and Survey Design Convenor Dr Ivar Krumpal (University of Leipzig) Coordinator 1 Professor Ben Jann (University of Bern) Coordinator 2 Professor Mark Trappmann (IAB Nürnberg) Social desirability bias is a problem in surveys collecting data on private issues, deviant behavior or unsocial opinions (e.g. sex, health, income, illicit drug use, tax evasion or xenophobia) as soon as the respondents' true scores differ from social norms. Asking sensitive questions poses a dilemma to survey participants. On the one hand, politeness norms may oblige the respondent to be helpful and cooperative and self-report the sensitive personal information truthfully. On the other hand, the respondent may not trust in his or her data protection and may fear negative consequences from self-reporting norm-violating behavior or opinions. Cumulative empirical evidence shows that in the context of surveying sensitive issues respondents often engage in self-protective behavior, i.e. they either give socially desirable answers or they refuse to answer at all. Such systematic misreporting or nonresponse leads to biased estimates and poor data quality of the entire survey study. Specific data collection approaches were proposed to increase respondents' cooperation and improve validity of self-reports in sensitive surveys. This session is about deepening our knowledge of the data generation process and advancing the theoretical basis of the ongoing debate about establishing best practices and designs for surveying sensitive topics. We invite submissions that deal with these problems and/or present potential solutions. In particular, we are interested in studies that (1) reason about the psychological processes and social interactions between the actors that are involved in the collection of the sensitive data; (2) present current empirical research focusing on 'question-and-answer' based (e.g. randomized response techniques, factorial surveys), non-reactive (e.g. record linkage approaches, field experiments or administrative data usage) or mixed methods of data collection (e.g. big data analyses in combination with classical survey approaches) focusing on the problem of social desirability; (3) deal with statistical procedures to analyze data generated with special data collection methods; (4) explore the possibilities and limits of integrating new and innovative data collection approaches for sensitive issues in well-established, large-scale population surveys taking into account problems of research ethics and data protection. In order to submit an abstract you need to log in to your ESRA account or create a new one at http://www.europeansurveyresearch.org/conference and then select our session which is listed in alphabetical order under "survey methodological research" -> "Researching Sensitive Topics: Improving Theory and Survey Design". The closing date for the submission of abstracts is 4th December 2016. Prof. Dr. Mark Trappmann Institut für Arbeitsmarkt- und Berufsforschung (IAB) Forschungsbereich E3: Panel "Arbeitsmarkt und soziale Sicherung" Regensburger Str. 104 90478 Nürnberg Tel. 0911-179-3096 und Otto-Friedrich-Universität Bamberg Fakultät für Sozial- und Wirtschaftswissenschaften Lehrstuhl für Soziologie, insbes. Survey-Methodologie 96045 Bamberg

1 0

ESRA 2017: CfP 'Proper and robust multiple imputation of complex data'
by Martin Spiess 07 Nov '16

07 Nov '16

Call for Papers Session: `Proper and robust multiple imputation of complex data' Organizer: Kristian Kleinke, Martin Spiess & Jost Reinecke Dear Colleagues, we would like to draw your attention to the call for papers for our session 'Proper and robust multiple imputation of complex data' at the 7th Conference of the European Survey Research Association, 17th-21st July 2017 in Lisbon, Portugal. ********************************************************** Summary: Allison (2001) states that the best solution to the missing data problem is prevention. This is especially true for complex data sets like multilevel data. Here, missingness may occur at various levels: in the outcome variable(s), in level-1 predictors, level-2 predictors, or even higher levels, and finally even in the group identifier(s). Many researchers still handle missingness (e.g. in multilevel data in level-1 and level-2 predictors) by excluding the incomplete cases from the analysis – a wasteful practice, which may lead to biased inferences. On the other hand, also none of the currently existing multiple imputation solutions for complex data can be described as optimal, as they either rely rather heavily upon strong distributional assumptions, often including homoscedasticity, which are frequently violated in “real life” situations. On the other hand, non- or semiparametric imputations methods often lack justification. Recent papers that contrast and review various strategies to impute complex or multilevel data are Drechsler (2015) and Enders, Mistler and Keller (2016). Shortcomings of some imputation techniques or consequences of misspecifications even in simple data sets are considered, e.g. in de Jong, van Buuren and Spiess (2016) or He and Raghunathan (2009). All in all, missing data in complex data structures is a field where a lot of research still has to be done. Feasible and robust software solutions need to be developed that work, even when empirical data do not exactly follow the convenient statistical distributions assumed by the respective procedures. We invite colleagues to present their research on multiple imputation solutions for complex data structures (e.g. clustered data, longitudinal data, panel data, cohort-sequential designs, etc.). We especially encourage proposals for robust procedures for “non-normal” missing data problems, i.e. when convenient distributional assumptions of standard MI procedures (normality, homoscedasticity) are violated. Also simulations that evaluate/compare different MI procedures regarding their robustness against violated assumptions are highly welcome. References Allison, P. D. (2001). Missing data. Thousand Oaks: Sage. de Jong, R., van Buuren, S. & Spiess, M. (2016) Multiple Imputation of Predictor Variables Using Generalized Additive Models. Communications in Statistics – Simulation and Computation, 45(3), 968–985. Drechsler, J. (2015). Multiple Imputation of Multilevel Missing Data – Rigor Versus Simplicity. Journal of Educational and Behavioral Statistics, 40(1), 69–95. Enders, C. K., Mistler, S. A., & Keller, B. T. (2016). Multilevel multiple imputation: A review and evaluation of joint modeling and chained equations imputation. Psychological Methods, 21(2), 222–240. He, Y. & Raghunathan, T. (2009). On the Performance of Sequential Regression Multiple Imputation Methods with Non Normal Error Distributions. Communications in Statistics – Simulation and Computation, 38(4), 856–883. *********************************************************** To submit an abstract, please visit the conference website at http://www.europeansurveyresearch.org/conference, sign up/log in and follow the instructions. You can select this session from the list of sessions provided in the submission form. [Proposals must be submitted online by 4th December 2016.] If you have any question, please feel free to contact us: Kristian Kleinke (kristian.kleinke(a)fernuni-hagen.de) Martin Spiess (martin.spiess(a)uni-hamburg.de) -- Prof. Dr. Martin Spiess Psychological Methods and Statistics Institute of Psychology Universitaet Hamburg Von-Melle-Park 5 20146 Hamburg Germany Tel. + 49 40 - 42838 5351 Fax. + 49 40 - 42838 6555 https://www.psy.uni-hamburg.de/arbeitsbereiche/psychologische-methoden-und-…

1 0

Jump to page:

2025

2024

2023

2022

2021

2020

2019

2018

2017

2016

2015

2014

2013

2012

2011

2010

2009

2008

2007

2006

2005

2004

Methoden