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  • 1
    Monograph available for loan
    Monograph available for loan
    College Station, Tex. : Stata Press
    Call number: PIK M 311-12-0285
    Description / Table of Contents: Contents: 1 The first time ; 2 Working with do-files ; 3 The grammar of Stata ; 4 General comments on the statistical commands ; 5 Creating and changing variables ; 6 Creating and changing graphs ; 7 Describing and comparing distributions ; 8 Statistical inference ; 9 Introduction to linear regression ; 10 Regression models for categorical dependent variables ; 11 Reading and writing data ; 12 Do-files for advanced users and user-written programs ; 13 Around Stata
    Type of Medium: Monograph available for loan
    Pages: XXVI, 497 S. : graph. Darst.
    Edition: 3. ed.
    ISBN: 9781597181105
    Location: A 18 - must be ordered
    Branch Library: PIK Library
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  • 2
    Call number: IASS 16.90149
    Description / Table of Contents: Dieses Buch ist die bislang einzige deutschsprachige Einführung in das Statistikprogramm Stata und zugleich das einzige Buch über Stata, das auch Anfängern eine ausreichende Erklärung der Datenanalysetechnik liefert. Dabei handelt es sich um kein reines Befehls-Handbuch, vielmehr werden alle Schritte einer Datenanalyse an praktischen Beispielen vorgeführt und erläutert. Diese Beispiele beziehen sich auf Themen der öffentlichen Diskussion oder der direkten Umgebung der meisten Leser. Dies erlaubt den Verzicht auf wissenschaftliche Theorien zur Begründung der Analysebeispiele und erleichtert eine interdisziplinäre Anwendung. Die Neuauflage enthält nicht nur Anpassungen an die neueste Stata Programmversion (Version 12) sondern auch ein komplett neues Kapitel zur Inferenzstatistik und der Analyse von Survey Daten. Des Weiteren werden neue Entwicklungen zur grafischen Darstellung von Regressionsergebnissen berücksichtigt.
    Type of Medium: Monograph available for loan
    Pages: IX, 467 S. , Ill., graph. Darst. , 24 cm
    Edition: 4., aktualisierte und überarb. Aufl.
    ISBN: 3486709216 (Pb.) , 9783486709216 (Pb.)
    Language: German
    Branch Library: RIFS Library
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  • 3
    Publication Date: 2019-08-21
    Electronic ISSN: 1932-6203
    Topics: Medicine , Natural Sciences in General
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  • 4
    Publication Date: 2021-08-31
    Description: The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic is posing a global public health burden. These consequences have been shown to increase the risk of mental distress, but the underlying protective and risk factors for mental distress and trends over different waves of the pandemic are largely unknown. Furthermore, it is largely unknown how mental distress is associated with individual protective behavior. Three quota samples, weighted to represent the population forming the German COVID-19 Snapshot Monitoring study (24 March and 26 May 2020, and 9 March 2021 with 〉900 subjects each), were used to describe the course of mental distress and resilience, to identify risk and protective factors during the pandemic, and to investigate their associations with individual protective behaviors. Mental distress increased slightly during the pandemic. Usage of cognitive reappraisal strategies, maintenance of a daily structure, and usage of alternative social interactions decreased. Self-reported resilience, cognitive reappraisal strategies, and maintaining a daily structure were the most important protective factors in all three samples. Adherence to individual protective behaviors (e.g., physical distancing) was negatively associated with mental distress and positively associated with frequency of information intake, maintenance of a daily structure, and cognitive reappraisal. Maintaining a daily structure, training of cognitive reappraisal strategies, and information provision may be targets to prevent mental distress while assuring a high degree of individual protective behaviors during the COVID-19 pandemic. Effects of the respective interventions have to be confirmed in further studies.
    Print ISSN: 1661-7827
    Electronic ISSN: 1660-4601
    Topics: Energy, Environment Protection, Nuclear Power Engineering , Medicine
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  • 5
    Publication Date: 2019-03-07
    Description: The long-standing approach of using probability samples in social science research has come under pressure through eroding survey response rates, advanced methodology, and easier access to large amounts of data. These factors, along with an increased awareness of the pitfalls of the nonequivalent comparison group design for the estimation of causal effects, have moved the attention of applied researchers away from issues of sampling and toward issues of identification. This article discusses the usability of samples with unknown selection probabilities for various research questions. In doing so, we review assumptions necessary for descriptive and causal inference and discuss research strategies developed to overcome sampling limitations.
    Print ISSN: 2326-8298
    Electronic ISSN: 2326-831X
    Topics: Mathematics
    Published by Annual Reviews
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  • 6
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    Taylor & Francis | Handbook of Computational Social Science, Vol 1 | Routledge
    Publication Date: 2024-03-29
    Description: "The Handbook of Computational Social Science is a comprehensive reference source for scholars across multiple disciplines. It outlines key debates in the field, showcasing novel statistical modeling and machine learning methods, and draws from specific case studies to demonstrate the opportunities and challenges in CSS approaches. The Handbook is divided into two volumes written by outstanding, internationally renowned scholars in the field. This first volume focuses on the scope of computational social science, ethics, and case studies. It covers a range of key issues, including open science, formal modeling, and the social and behavioral sciences. This volume explores major debates, introduces digital trace data, reviews the changing survey landscape, and presents novel examples of computational social science research on sensing social interaction, social robots, bots, sentiment, manipulation, and extremism in social media. The volume not only makes major contributions to the consolidation of this growing research field, but also encourages growth into new directions. With its broad coverage of perspectives (theoretical, methodological, computational), international scope, and interdisciplinary approach, this important resource is integral reading for advanced undergraduates, postgraduates and researchers engaging with computational methods across the social sciences, as well as those within the scientific and engineering sectors."
    Keywords: AI, big data, data analysis, data archives, data ownership, data science, digital trace, ethical standards, ethics, human-robot interaction, information technology, machine learning, open data, politics, policy, quantitative, replication, social, social media, socio-robots, survey data, survey design, survey methodology, unstructured data ; bic Book Industry Communication::J Society & social sciences::JM Psychology ; bic Book Industry Communication::J Society & social sciences::JM Psychology::JMB Psychological methodology ; thema EDItEUR::J Society and Social Sciences::JM Psychology ; thema EDItEUR::J Society and Social Sciences::JM Psychology::JMB Psychological methodology
    Language: English
    Format: image/jpeg
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